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Archive for the ‘Cancer Informatics’ Category

Hematological Malignancy Diagnostics

Author and Curator: Larry H. Bernstein, MD, FCAP

 

2.4.3 Diagnostics

2.4.3.1 Computer-aided diagnostics

Back-to-Front Design

Robert Didner
Bell Laboratories

Decision-making in the clinical setting
Didner, R  Mar 1999  Amer Clin Lab

Mr. Didner is an Independent Consultant in Systems Analysis, Information Architecture (Informatics) Operations Research, and Human Factors Engineering (Cognitive Psychology),  Decision Information Designs, 29 Skyline Dr., Morristown, NJ07960, U.S.A.; tel.: 973-455-0489; fax/e-mail: bdidner@hotmail.com

A common problem in the medical profession is the level of effort dedicated to administration and paperwork necessitated by various agencies, which contributes to the high cost of medical care. Costs would be reduced and accuracy improved if the clinical data could be captured directly at the point they are generated in a form suitable for transmission to insurers or machine transformable into other formats. Such a capability could also be used to improve the form and the structure of information presented to physicians and support a more comprehensive database linking clinical protocols to outcomes, with the prospect of improving clinical outcomes. Although the problem centers on the physician’s process of determining the diagnosis and treatment of patients and the timely and accurate recording of that process in the medical system, it substantially involves the pathologist and laboratorian, who interact significantly throughout the in-formation-gathering process. Each of the currently predominant ways of collecting information from diagnostic protocols has drawbacks. Using blank paper to collect free-form notes from the physician is not amenable to computerization; such free-form data are also poorly formulated, formatted, and organized for the clinical decision-making they support. The alternative of preprinted forms listing the possible tests, results, and other in-formation gathered during the diagnostic process facilitates the desired computerization, but the fixed sequence of tests and questions they present impede the physician from using an optimal decision-making sequence. This follows because:

  • People tend to make decisions and consider information in a step-by-step manner in which intermediate decisions are intermixed with data acquisition steps.
  • The sequence in which components of decisions are made may alter the decision outcome.
  • People tend to consider information in the sequence it is requested or displayed.
  • Since there is a separate optimum sequence of tests and questions for each cluster of history and presenting symptoms, there is no one sequence of tests and questions that can be optimal for all presenting clusters.
  • As additional data and test results are acquired, the optimal sequence of further testing and data acquisition changes, depending on the already acquired information.

Therefore, promoting an arbitrary sequence of information requests with preprinted forms may detract from outcomes by contributing to a non-optimal decision-making sequence. Unlike the decisions resulting from theoretical or normative processes, decisions made by humans are path dependent; that is, the out-come of a decision process may be different if the same components are considered in a different sequence.

Proposed solution

This paper proposes a general approach to gathering data at their source in computer-based form so as to improve the expected outcomes. Such a means must be interactive and dynamic, so that at any point in the clinical process the patient’s presenting symptoms, history, and the data already collected are used to determine the next data or tests requested. That de-termination must derive from a decision-making strategy designed to produce outcomes with the greatest value and supported by appropriate data collection and display techniques. The strategy must be based on the knowledge of the possible outcomes at any given stage of testing and information gathering, coupled with a metric, or hierarchy of values for assessing the relative desirability of the possible outcomes.

A value hierarchy

  • The numbered list below illustrates a value hierarchy. In any particular instance, the higher-numbered values should only be considered once the lower- numbered values have been satisfied. Thus, a diagnostic sequence that is very time or cost efficient should only be considered if it does not increase the likelihood (relative to some other diagnostic sequence) that a life-threatening disorder may be missed, or that one of the diagnostic procedures may cause discomfort.
  • Minimize the likelihood that a treatable, life-threatening disorder is not treated.
  • Minimize the likelihood that a treatable, discomfort-causing disorder is not treated.
  • Minimize the likelihood that a risky procedure(treatment or diagnostic procedure) is inappropriately administered.
  • Minimize the likelihood that a discomfort-causing procedure is inappropriately administered.
  • Minimize the likelihood that a costly procedure is inappropriately administered.
  • Minimize the time of diagnosing and treating thepatient.8.Minimize the cost of diagnosing and treating the patient.

The above hierarchy is relative, not absolute; for many patients, a little bit of testing discomfort may be worth a lot of time. There are also some factors and graduations intentionally left out for expository simplicity (e.g., acute versus chronic disorders).This value hierarchy is based on a hypothetical patient. Clearly, the hierarchy of a health insurance carrier might be different, as might that of another patient (e.g., a geriatric patient). If the approach outlined herein were to be followed, a value hierarchy agreed to by a majority of stakeholders should be adopted.

Efficiency

Once the higher values are satisfied, the time and cost of diagnosis and treatment should be minimized. One way to do so would be to optimize the sequence in which tests are performed, so as to minimize the number, cost, and time of tests that need to be per-formed to reach a definitive decision regarding treatment. Such an optimum sequence could be constructed using Claude Shannon’s information theory.

According to this theory, the best next question to ask under any given situation (assuming the question has two possible outcomes) is that question that divides the possible outcomes into two equally likely sets. In the real world, all tests or questions are not equally valuable, costly, or time consuming; therefore, value(risk factors), cost, and time should be used as weighting factors to optimize the test sequence, but this is a complicating detail at this point.

A value scale

For dynamic computation of outcome values, the hierarchy could be converted into a weighted value scale so differing outcomes at more than one level of the hierarchy could be readily compared. An example of such a weighted value scale is Quality Adjusted Life Years (QALY).

Although QALY does not incorporate all of the factors in this example, it is a good conceptual starting place.

The display, request, decision-making relationship

For each clinical determination, the pertinent information should be gathered, organized, formatted, and formulated in a way that facilitates the accuracy, reliability, and efficiency with which that determination is made. A physician treating a patient with high cholesterol and blood pressure (BP), for example, may need to know whether or not the patient’s cholesterol and BP respond to weight changes to determine an appropriate treatment (e.g., weight control versus medication). This requires searching records for BP, certain blood chemicals (e.g., HDLs, LDLs, triglycerides, etc.), and weight from several

sources, then attempting to track them against each other over time. Manually reorganizing this clinical information each time it is used is extremely inefficient. More important, the current organization and formatting defies principles of human factors for optimally displaying information to enhance human information-processing characteristics, particularly for decision support.

While a discussion of human factors and cognitive psychology principles is beyond the scope of this paper, following are a few of the system design principles of concern:

  • Minimize the load on short-term memory.
  • Provide information pertinent to a given decision or component of a decision in a compact, contiguous space.
  • Take advantage of basic human perceptual and pat-tern recognition facilities.
  • Design the form of an information display to com-plement the decision-making task it supports.

F i g u re 1 shows fictitious, quasi-random data from a hypothetical patient with moderately elevated cholesterol. This one-page display pulls together all the pertinent data from six years of blood tests and related clinical measurements. At a glance, the physician’s innate pattern recognition, color, and shape perception facilities recognize the patient’s steadily increasing weight, cholesterol, BP, and triglycerides as well as the declining high-density lipoproteins. It would have taken considerably more time and effort to grasp this information from the raw data collection and blood test reports as they are currently presented in independent, tabular time slices.

Design the formulation of an information display to complement the decision-making task.

The physician may wish to know only the relationship between weight and cardiac risk factors rather than whether these measures are increasing or decreasing, or are within acceptable or marginal ranges. If so, Table 1 shows the correlations between weight and the other factors in a much more direct and simple way using the same data as in Figure 1. One can readily see the same conclusions about relations that were drawn from Figure 1.This type of abstract, symbolic display of derived information also makes it easier to spot relationships when the individual variables are bouncing up and down, unlike the more or less steady rise of most values in Figure 1. This increase in precision of relationship information is gained at the expense of other types of information (e.g., trends). To display information in an optimum form then, the system designer must know what the information demands of the task are at the point in the task when the display is to be used.

Present the sequence of information display clusters to complement an optimum decision-making strategy.

Just as a fixed sequence of gathering clinical, diagnostic information may lead to a far from optimum outcome, there exists an optimum sequence of testing, considering information, and gathering data that will lead to an optimum outcome (as defined by the value hierarchy) with a minimum of time and expense. The task of the information system designer, then, is to provide or request the right information, in the best form, at each stage of the procedure. For ex-ample, Figure 1 is suitable for the diagnostic phase since it shows the current state of the risk factors and their trends. Table 1, on the other hand, might be more appropriate in determining treatment, where there may be a choice of first trying a strict dietary treatment, or going straight to a combination of diet plus medication. The fact that Figure 1 and Table 1 have somewhat redundant information is not a problem, since they are intended to optimally provide information for different decision-making tasks. The critical need, at this point, is for a model of how to determine what information should be requested, what tests to order, what information to request and display, and in what form at each step of the decision-making process. Commitment to a collaborative relationship between physicians and laboratorians and other information providers would be an essential requirement for such an undertaking. The ideal diagnostic data-collection instrument is a flexible, computer-based device, such as a notebook computer or Personal Digital Assistant (PDA) sized device.

Barriers to interactive, computer-driven data collection at the source

As with any major change, it may be difficult to induce many physicians to change their behavior by interacting directly with a computer instead of with paper and pen. Unlike office workers, who have had to make this transition over the past three decades, most physicians’ livelihoods will not depend on converting to computer interaction. Therefore, the transition must be made attractive and the changes less onerous. Some suggestions follow:

  1. Make the data collection a natural part of the clinical process.
  2. Ensure that the user interface is extremely friendly, easy to learn, and easy to use.
  3. Use a small, portable device.
  4. Use the same device for collection and display of existing information (e.g., test results and his-tory).
  5. Minimize the need for free-form written data entry (use check boxes, forms, etc.).
  6. Allow the entry of notes in pen-based free-form (with the option of automated conversion of numeric data to machine-manipulable form).
  7. Give the physicians a more direct benefit for collecting data, not just a means of helping a clerk at an HMO second-guess the physician’s judgment.
  8. Improve administrative efficiency in the office.
  9. Make the data collection complement the clinical decision-making process.
  10. Improve information displays, leading to better outcomes.
  11. Make better use of the physician’s time and mental effort.

Conclusion

The medical profession is facing a crisis of information. Gathering information is costing a typical practice more and more while fees are being restricted by third parties, and the process of gathering this in-formation may be detrimental to current outcomes. Gathered properly, in machine-manipulable form, these data could be reformatted so as to greatly improve their value immediately in the clinical setting by leading to decisions with better outcomes and, in the long run, by contributing to a clinical data warehouse that could greatly improve medical knowledge. The challenge is to create a mechanism for data collection that facilitates, hastens, and improves the outcomes of clinical activity while minimizing the inconvenience and resistance to change on the part of clinical practitioners. This paper is intended to provide a high-level overview of how this may be accomplished, and start a dialogue along these lines.

References

  1. Tversky A. Elimination by aspects: a theory of choice. Psych Rev 1972; 79:281–99.
  2. Didner RS. Back-to-front design: a guns and butter approach. Ergonomics 1982; 25(6):2564–5.
  3. Shannon CE. A mathematical theory of communication. Bell System Technical J 1948; 27:379–423 (July), 623–56 (Oct).
  4. Feeny DH, Torrance GW. Incorporating utility-based quality-of-life assessment measures in clinical trials: two examples. Med Care 1989; 27:S190–204.
  5. Smith S, Mosier J. Guidelines for designing user interface soft-ware. ESD-TR-86-278, Aug 1986.
  6. Miller GA. The magical number seven plus or minus two. Psych Rev 1956; 65(2):81–97.
  7. Sternberg S. High-speed scanning in human memory. Science 1966; 153: 652–4.

Table 1

Correlation of weight with other cardiac risk factors

Cholesterol 0.759384
HDL 0.53908
LDL 0.177297
BP-syst. 0.424728
BP-dia. 0.516167
Triglycerides 0.637817

Figure 1  Hypothetical patient data.

(not shown)

Realtime Clinical Expert Support

http://pharmaceuticalintelligence.com/2015/05/10/realtime-clinical-expert-support/

Regression: A richly textured method for comparison and classification of predictor variables

http://pharmaceuticalintelligence.com/2012/08/14/regression-a-richly-textured-method-for-comparison-and-classification-of-predictor-variables/

Converting Hematology Based Data into an Inferential Interpretation

Larry H. Bernstein, Gil David, James Rucinski and Ronald R. Coifman
In Hematology – Science and Practice
Lawrie CH, Ch 22. Pp541-552.
InTech Feb 2012, ISBN 978-953-51-0174-1
https://www.researchgate.net/profile/Larry_Bernstein/publication/221927033_Converting_Hematology_Based_Data_into_an_Inferential_Interpretation/links/0fcfd507f28c14c8a2000000.pdf

A model for Thalassemia Screening using Hematology Measurements

https://www.researchgate.net/profile/Larry_Bernstein/publication/258848064_A_model_for_Thalassemia_Screening_using_Hematology_Measurements/links/0c9605293c3048060b000000.pdf

2.4.3.2 A model for automated screening of thalassemia in hematology (math study).

Kneifati-Hayek J, Fleischman W, Bernstein LH, Riccioli A, Bellevue R.
Lab Hematol. 2007; 13(4):119-23. http://dx.doi.org:/10.1532/LH96.07003.

The results of 398 patient screens were collected. Data from the set were divided into training and validation subsets. The Mentzer ratio was determined through a receiver operating characteristic (ROC) curve on the first subset, and screened for thalassemia using the second subset. HgbA2 levels were used to confirm beta-thalassemia.

RESULTS: We determined the correct decision point of the Mentzer index to be a ratio of 20. Physicians can screen patients using this index before further evaluation for beta-thalassemia (P < .05).

CONCLUSION: The proposed method can be implemented by hospitals and laboratories to flag positive matches for further definitive evaluation, and will enable beta-thalassemia screening of a much larger population at little to no additional cost.

Measurement of granulocyte maturation may improve the early diagnosis of the septic state.

2.4.3.3 Bernstein LH, Rucinski J. Clin Chem Lab Med. 2011 Sep 21;49(12):2089-95.
http://dx.doi.org:/10.1515/CCLM.2011.688.

2.4.3.4 The automated malnutrition assessment.

David G, Bernstein LH, Coifman RR. Nutrition. 2013 Jan; 29(1):113-21.
http://dx.doi.org:/10.1016/j.nut.2012.04.017

2.4.3.5 Molecular Diagnostics

Genomic Analysis of Hematological Malignancies

Acute lymphoblastic leukemia (ALL) is the most common hematologic malignancy that occurs in children. Although more than 90% of children with ALL now survive to adulthood, those with the rarest and high-risk forms of the disease continue to have poor prognoses. Through the Pediatric Cancer Genome Project (PCGP), investigators in the Hematological Malignancies Program are identifying the genetic aberrations that cause these aggressive forms of leukemias. Here we present two studies on the genetic bases of early T-cell precursor ALL and acute megakaryoblastic leukemia.

  • Early T-Cell Precursor ALL Is Characterized by Activating Mutations
  • The CBFA2T3-GLIS2Fusion Gene Defines an Aggressive Subtype of Acute Megakaryoblastic Leukemia in Children

Early T-cell precursor ALL (ETP-ALL), which comprises 15% of all pediatric T-cell leukemias, is an aggressive disease that is typically resistant to contemporary therapies. Children with ETP-ALL have a high rate of relapse and an extremely poor prognosis (i.e., 5-year survival is approximately 20%). The genetic basis of ETP-ALL has remained elusive. Although ETP-ALL is associated with a high burden of DNA copy number aberrations, none are consistently found or suggest a unifying genetic alteration that drives this disease.

Through the efforts of the PCGP, Jinghui Zhang, PhD (Computational Biology), James R. Downing, MD (Pathology), Charles G. Mullighan, MBBS(Hons), MSc, MD (Pathology), and colleagues analyzed the whole-genome sequences of leukemic cells and matched normal DNA from 12 pediatric patients with ETP-ALL. The identified genetic mutations were confirmed in a validation cohort of 52 ETP-ALL specimens and 42 non-ETP T-lineage ALLs (T-ALL).

In the journal Nature, the investigators reported that each ETP-ALL sample carried an average of 1140 sequence mutations and 12 structural variations. Of the structural variations, 51% were breakpoints in genes with well-established roles in hematopoiesis or leukemogenesis (e.g., MLH2,SUZ12, and RUNX1). Eighty-four percent of the structural variations either caused loss of function of the gene in question or resulted in the formation of a fusion gene such as ETV6-INO80D. The ETV6 gene, which encodes a protein that is essential for hematopoiesis, is frequently mutated in leukemia. Among the DNA samples sequenced in this study, ETV6 was altered in 33% of ETP-ALL but only 10% of T-ALL cases.

Next-generation sequencing in hematologic malignancies: what will be the dividends?

Jason D. Merker, Anton Valouev, and Jason Gotlib
Ther Adv Hematol. 2012 Dec; 3(6): 333–339.
http://dx.doi.org:/10.1177/2040620712458948

The application of high-throughput, massively parallel sequencing technologies to hematologic malignancies over the past several years has provided novel insights into disease initiation, progression, and response to therapy. Here, we describe how these new DNA sequencing technologies have been applied to hematolymphoid malignancies. With further improvements in the sequencing and analysis methods as well as integration of the resulting data with clinical information, we expect these technologies will facilitate more precise and tailored treatment for patients with hematologic neoplasms.

Leveraging cancer genome information in hematologic malignancies.

Rampal R1, Levine RL.
J Clin Oncol. 2013 May 20; 31(15):1885-92.
http://dx.doi.org:/10.1200/JCO.2013.48.7447

The use of candidate gene and genome-wide discovery studies in the last several years has led to an expansion of our knowledge of the spectrum of recurrent, somatic disease alleles, which contribute to the pathogenesis of hematologic malignancies. Notably, these studies have also begun to fundamentally change our ability to develop informative prognostic schema that inform outcome and therapeutic response, yielding substantive insights into mechanisms of hematopoietic transformation in different tissue compartments. Although these studies have already had important biologic and translational impact, significant challenges remain in systematically applying these findings to clinical decision making and in implementing new technologies for genetic analysis into clinical practice to inform real-time decision making. Here, we review recent major genetic advances in myeloid and lymphoid malignancies, the impact of these findings on prognostic models, our understanding of disease initiation and evolution, and the implication of genomic discoveries on clinical decision making. Finally, we discuss general concepts in genetic modeling and the current state-of-the-art technology used in genetic investigation.

p53 mutations are associated with resistance to chemotherapy and short survival in hematologic malignancies

E Wattel, C Preudhomme, B Hecquet, M Vanrumbeke, et AL.
Blood, (Nov 1), 1994; 84(9): pp 3148-3157
http://www.bloodjournal.org/content/bloodjournal/84/9/3148.full.pdf

We analyzed the prognostic value of p53 mutations for response to chemotherapy and survival in acute myeloid leukemia (AML), myelodysplastic syndrome (MDS), and chronic lymphocytic leukemia (CLL). Mutations were detected by single-stranded conformation polymorphism (SSCP) analysis of exons 4 to 10 of the P53 gene, and confirmed by direct sequencing. A p53 mutation was found in 16 of 107 (15%) AML, 20 of 182 (11%) MDS, and 9 of 81 (11%) CLL tested. In AML, three of nine (33%) mutated cases and 66 of 81 (81%) nonmutated cases treated with intensive chemotherapy achieved complete remission (CR) (P = .005) and none of five mutated cases and three of six nonmutated cases treated by low-dose Ara C achieved CR or partial remission (PR) (P = .06). Median actuarial survival was 2.5 months in mutated cases, and 15 months in nonmutated cases (P < lo-‘). In the MDS patients who received chemotherapy (intensive chemotherapy or low-dose Ara C), 1 of 13 (8%) mutated cases and 23 of 38 (60%) nonmutated cases achieved CR or PR (P = .004), and median actuarial survival was 2.5 and 13.5 months, respectively (P C lo-’). In all MDS cases (treated and untreated), the survival difference between mutated cases and nonmutated cases was also highly significant. In CLL, 1 of 8 (12.5%) mutated cases treated by chemotherapy (chlorambucil andlor CHOP andlor fludarabine) responded, as compared with 29 of 36 (80%) nonmutated cases (P = .02). In all CLL cases, survival from p53 analysis was significantly shorter in mutated cases (median 7 months) than in nonmutated cases (median not reached) (P < IO-’). In 35 of the 45 mutated cases of AML, MDS, and CLL, cytogenetic analysis or SSCP and sequence findings showed loss of the nonmutated P53 allele. Our findings show that p53 mutations are a strong prognostic indicator of response to chemotherapy and survival in AML, MDS, and CLL. The usual association of p53 mutations to loss of the nonmutated P53 allele, in those disorders, ie, to absence of normal p53 in tumor cells, suggests that p53 mutations could induce drug resistance, at least in part, by interfering with normal apoptotic pathways in tumor cells.

Genomic approaches to hematologic malignancies

Benjamin L. Ebert and Todd R. Golub
Blood. 2004; 104:923-932
https://www.broadinstitute.org/mpr/publications/projects/genomics/Review%20Genomics%20of%20Heme%20Malig,%20Blood%202004.pdf

In the past several years, experiments using DNA microarrays have contributed to an increasingly refined molecular taxonomy of hematologic malignancies. In addition to the characterization of molecular profiles for known diagnostic classifications, studies have defined patterns of gene expression corresponding to specific molecular abnormalities, oncologic phenotypes, and clinical outcomes. Furthermore, novel subclasses with distinct molecular profiles and clinical behaviors have been identified. In some cases, specific cellular pathways have been highlighted that can be therapeutically targeted. The findings of microarray studies are beginning to enter clinical practice as novel diagnostic tests, and clinical trials are ongoing in which therapeutic agents are being used to target pathways that were identified by gene expression profiling. While the technology of DNA microarrays is becoming well established, genome-wide surveys of gene expression generate large data sets that can easily lead to spurious conclusions. Many challenges remain in the statistical interpretation of gene expression data and the biologic validation of findings. As data accumulate and analyses become more sophisticated, genomic technologies offer the potential to generate increasingly sophisticated insights into the complex molecular circuitry of hematologic malignancies. This review summarizes the current state of discovery and addresses key areas for future research.

2.4.3.6 Flow cytometry

Introduction to Flow Cytometry: Blood Cell Identification

Dana L. Van Laeys
https://www.labce.com/flow_cytometry.aspx

No other laboratory method provides as rapid and detailed analysis of cellular populations as flow cytometry, making it a valuable tool for diagnosis and management of several hematologic and immunologic diseases. Understanding this relevant methodology is important for any medical laboratory scientist.

Whether you have no previous experience with flow cytometry or just need a refresher, this course will help you to understand the basic principles, with the help of video tutorials and interactive case studies.

Basic principles include:

  1. Immunophenotypic features of various types of hematologic cells
  2. Labeling cellular elements with fluorochromes
  3. Blood cell identification, specifically B and T lymphocyte identification and analysis
  4. Cell sorting to isolate select cell population for further analysis
  5. Analyzing and interpreting result reports and printouts

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Genetic Testing for Hereditary Cancer Risk @Stanford

Reporter: Aviva Lev-Ari, PhD, RN

 

 

Genetic Testing for Hereditary Cancer Risk

With James Ford, MD – 50 Min.

VIEW VIDEO

https://cancer.stanford.edu/media/video/genetic_testing.html

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New Trends in Personalized Medicine Delivery: HMO partner with Cancer Genetic Diagnostics – Harvard Pilgrim for Access to Cancer Dx Services

Reporter: Aviva Lev-Ari, PhD, RN

 

 

Cancer Genetics Inks Agreement with Harvard Pilgrim for Access to Cancer Dx Services

NEW YORK (GenomeWeb) – Cancer Genetics today announced that it has signed an agreement with Harvard Pilgrim Healthcare to provide its cancer diagnostic services.

Harvard Pilgrim’s provider network includes more than 135 hospitals and 28,000 doctors covering more than one million people in Massachusetts, Connecticut, and Maine. Cancer Genetics provides molecular testing services for hematological, urogenital, and HPV-associated cancers.

SOURCE

https://www.genomeweb.com/business-news/cancer-genetics-inks-agreement-harvard-pilgrim-access-cancer-dx-services

Cancer Genetics, ACPN Reach Agreement for Access to Cancer Dx Services

NEW YORK (GenomeWeb) – Cancer Genetics today said that it has reached a deal with America’s Choice Provider Network to provide its 19 million members in the US access to Cancer Genetics’ cancer diagnostic services.

ACPN is an independent network of healthcare providers in the US that offers out-of-network solutions for more than 1,100 payors. Cancer Genetics Director of Reimbursement and Clinical Revenue Cycle Management Randy Goodman said that the deal allows his firm to deliver services to a larger number of patients who access ACPN’s provider network through their coverage with insurers such as Humana, Cigna, and Oxford Health Plan.

The company added that participation in provider networks such as ACPN is an integral element of its access and reimbursement strategy, which also includes partnerships and collaborations with cooperative oncology study groups, targeted relationships with payors, and health economic and validation studies with medical institutions.

SOURCE

https://www.genomeweb.com/business-news/cancer-genetics-acpn-reach-agreement-access-cancer-dx-services

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Therapeutic Implications for Targeted Therapy from the Resurgence of Warburg ‘Hypothesis’

Writer and Curator: Larry H. Bernstein, MD, FCAP 

(Note that each portion of the discussion is followed by a reference)

It is now a time to pause after almost a century of a biological scientific discoveries that have transformed the practice of medicine and impacted the lives of several generations of young minds determined to probe the limits of our knowledge.  In the century that we have entered into the scientific framework of medicine has brought together a difficult to grasp evolution of the emergence of human existence from wars, famine, droughts, storms, infectious diseases, and insect born pestilence with betterment of human lives, only unevenly divided among societal classes that have existed since time immemorial. In this short time span there have emerged several generations of physicians who have benefited from a far better medical education that their forebears could have known. In this expansive volume on cancer, we follow an incomplete and continuing challenge to understand cancer, a disease that has become associated with longer life spans in developed nations.

While there are significant improvements in the diagnosis and treatment of cancers, there is still a personal as well as locality factor in the occurrence of this group of diseases, which has been viewed incorrectly as a “dedifferentiation” of mature tissue types and the emergence of a cell phenotype that is dependent on glucose, reverts to a cancer “stem cell type” (loss of stemness), loses cell to cell adhesion, loses orderly maturation, and metastasizes to distant sites. At the same time, physician and nurses are stressed in the care of patients by balancing their daily lives and maintaining a perspective.

The conceptual challenge of cancer diagnosis and management has seemed insurmountable, but owes much to the post World War I activities of Otto Heinrich Warburg. It was Warburg who made the observation that cancer cells metabolize glucose by fermentation in much the way Pasteur 60 years earlier observed fermentation of yeast cells. This metabolic phenomenon occurs even in the presence of an oxygen supply, which would provide a huge deficit in ATP production compared with respiration. The cancer cell is “addicted to glucose” and produced lactic acid. Warburg was awarded the Nobel Prize in Medicine for this work in 1931.

In the last 15 years there has been a resurgence of work on the Warburg effect that sheds much new light on the process that was not previously possible, with significant therapeutic implications.  In the first place, the metabolic mechanism for the Warburg effect was incomplete even at the beginning of the 21st century.  This has been partly rectified with the enlightening elucidation of genome modifications, cellular metabolic regulation, and signaling pathways.

The following developments have become central to furthering our understanding of malignant transformation.

  1. There is usually an identifiable risk factor, such as, H. pylori, or of a chronic inflammatory state, as in the case of Barrett’s esophagus.
  2. There are certain changes in glucose metabolism that have been unquestionably been found in the evolution of this disease. The changes are associated with major changes in metabolic pathways, miRN signaling, and the metabolism geared to synthesis of cells with an impairment of the cell death cycle. In these changes, mitochondrial function is central to both the impaired respiration and the autophagy geared to the synthesis of cancer cells.

The emergence of this cell prototype is characterized by the following, again related to the Warburg effect:

  1. Cancer cells oxidize a decreased fraction of the pyruvate generated from glycolysis
  2. The mitochondrial pyruvate carrier (MPC), composed of the products of the MPC1 and MPC2 genes, modulates fractional pyruvate oxidation. MPC1 is deleted or underexpressed in multiple cancers and correlates with poor prognosis.
  3. Cancer cells tend to express a partially inhibited splice variant of pyruvate kinase (PK-M2), leading to decreased pyruvate production.
  4. The two proteins that mediate pyruvate conversion to lactate and its export, M-type lactate dehydrogenase and the monocarboxylate transporter MCT-4, are commonly upregulated in cancer cells leading to decreased pyruvate oxidation.
  5. The enzymatic step following mitochondrial entry is the conversion of pyruvate to acetyl-CoA by the pyruvate dehydrogenase (PDH) complex. Cancer cells frequently exhibit increased expression of the PDH kinase PDK1, which phosphorylates and inactivates PDH. This PDH regulatory mechanism is required for oncogene induced transformation and reversed in oncogene-induced senescence.
  6. The PDK inhibitor dichloroacetate has shown some clinical efficacy, which correlates with increased pyruvate oxidation. One of the simplest mechanisms to explain decreased mitochondrial pyruvate oxidation in cancer cells, a loss of mitochondrial pyruvate import, has been observed repeatedly over the past 40 years. This process has been impossible to study at a molecular level until recently, however, as the identities of the protein(s) that mediate mitochondrial pyruvate uptake were unknown.
  7. The mitochondrial pyruvate carrier (MPC) as a multimeric complex that is necessary for efficient mitochondrial pyruvate uptake. The MPC contains two distinct proteins, MPC1 and MPC2; the absence of either leads to a loss of mitochondrial pyruvate uptake and utilization in yeast, flies, and mammalian cells.

A Role for the Mitochondrial Pyruvate Carrier as a Repressor of the Warburg Effect and Colon Cancer Cell Growth

John C. Schell, Kristofor A. Olson, Lei Jiang, Amy J. Hawkins, et al.
Molecular Cell Nov 6, 2014; 56: 400–413.
http://dx.doi.org/10.1016/j.molcel.2014.09.026

In addition to the above, the following study has therapeutic importance:

Glycolysis has become a target of anticancer strategies. Glucose deprivation is sufficient to induce growth inhibition and cell death in cancer cells. The increased glucose transport in cancer cells has been attributed primarily to the upregulation of glucose transporter 1 (Glut1),  1 of the more than 10 glucose transporters that are responsible for basal glucose transport in almost all cell types. Glut1 has not been targeted until very recently due to the lack of potent and selective inhibitors.

First, Glut1 antibodies were shown to inhibit cancer cell growth. Other Glut1 inhibitors and glucose transport inhibitors, such as fasentin and phloretin, were also shown to be effective in reducing cancer cell growth. A group of inhibitors of glucose transporters has been recently identified with IC50 values lower than 20mmol/L for inhibiting cancer cell growth. However, no animal or detailed mechanism studies have been reported with these inhibitors.

Recently, a small molecule named STF-31 was identified that selectively targets the von Hippel-Lindau (VHL) deficient kidney cancer cells. STF-31 inhibits VHL deficient cancer cells by inhibiting Glut1. It was further shown that daily intraperitoneal injection of a soluble analogue of STF-31 effectively reduced the growth of tumors of VHL-deficient cancer cells grafted on nude mice. On the other hand, STF-31 appears to be an inhibitor with a narrow cell target spectrum.

These investigators recently reported the identification of a group of novel small compounds that inhibit basal glucose transport and reduce cancer cell growth by a glucose deprivation–like mechanism. These compounds target Glut1 and are efficacious in vivo as anticancer agents. A novel representative compound WZB117 not only inhibited cell growth in cancer cell lines but also inhibited cancer growth in a nude mouse model. Daily intraperitoneal injection of WZB117 resulted in a more than 70% reduction in the size of human lung cancer of A549 cell origin. Mechanism studies showed that WZB117 inhibited glucose transport in human red blood cells (RBC), which express Glut1 as their sole glucose transporter. Cancer cell treatment with WZB117 led to decreases in levels of Glut1 protein, intracellular ATP, and glycolytic enzymes. All these changes were followed by increase in ATP sensing enzyme AMP-activated protein kinase (AMPK) and declines in cyclin E2 as well as phosphorylated retinoblastoma, resulting in cell-cycle arrest, senescence, and necrosis. Addition of extracellular ATP rescued compound-treated cancer cells, suggesting that the reduction of intracellular ATP plays an important role in the anticancer mechanism of the molecule.

A Small-Molecule Inhibitor of Glucose Transporter 1 Downregulates Glycolysis, Induces Cell-Cycle Arrest, and Inhibits Cancer Cell Growth In Vitro and In Vivo

Yi Liu, Yanyan Cao, Weihe Zhang, Stephen Bergmeier, et al.
Mol Cancer Ther Aug 2012; 11(8): 1672–82
http://dx.doi.org://10.1158/1535-7163.MCT-12-0131

Alterations in cellular metabolism are among the most consistent hallmarks of cancer. These investigators have studied the relationship between increased aerobic lactate production and mitochondrial physiology in tumor cells. To diminish the ability of malignant cells to metabolize pyruvate to lactate, M-type lactate dehydrogenase levels were knocked down by means of LDH-A short hairpin RNAs. Reduction in LDH-A activity resulted in stimulation of mitochondrial respiration and decrease of mitochondrial membrane potential. It also compromised the ability of these tumor cells to proliferate under hypoxia. The tumorigenicity of the LDH-A-deficient cells was severely diminished, and this phenotype was reversed by complementation with the human ortholog LDH-A protein. These results demonstrate that LDH-A plays a key role in tumor maintenance.

The results are consistent with a functional connection between alterations in glucose metabolism and mitochondrial physiology in cancer. The data also reflect that the dependency of tumor cells on glucose metabolism is a liability for these cells under limited-oxygen conditions. Interfering with LDH-A activity as a means of blocking pyruvate to lactate conversion could be exploited therapeutically. Because individuals with complete deficiency of LDH-A do not show any symptoms under ordinary circumstances, the genetic data suggest that inhibition of LDH-A activity may represent a relatively nontoxic approach to interfere with tumor growth.

Attenuation of LDH-A expression uncovers a link between glycolysis, mitochondrial physiology, and tumor maintenance

Valeria R. Fantin Julie St-Pierre and Philip Leder
Cancer Cell Jun 2006; 9: 425–434.
http://dx.doi.org:/10.1016/j.ccr.2006.04.02

The widespread clinical use of positron-emission tomography (PET) for the detection of aerobic glycolysis in tumors and recent findings have rekindled interest in Warburg’s theory. Studies on the physiological changes in malignant conversion provided a metabolic signature for the different stages of tumorigenesis; during tumorigenesis, an increase in glucose uptake and lactate production have been detected. The fully transformed state is most dependent on aerobic glycolysis and least dependent on the mitochondrial machinery for ATP synthesis.

Tumors ferment glucose to lactate even in the presence of oxygen (aerobic glycolysis; Warburg effect). The pentose phosphate pathway (PPP) allows glucose conversion to ribose for nucleic acid synthesis and glucose degradation to lactate. The nonoxidative part of the PPP is controlled by transketolase enzyme reactions. We have detected upregulation of a mutated transketolase transcript (TKTL1) in human malignancies, whereas transketolase (TKT) and transketolase-like-2 (TKTL2) transcripts were not upregulated. Strong TKTL1 protein expression was correlated to invasive colon and urothelial tumors and to poor patients outcome. TKTL1 encodes a transketolase with unusual enzymatic properties, which are likely to be caused by the internal deletion of conserved residues. We propose that TKTL1 upregulation in tumors leads to enhanced, oxygen-independent glucose usage and a lactate based matrix degradation. As inhibition of transketolase enzyme reactions suppresses tumor growth and metastasis, TKTL1 could be the relevant target for novel anti-transketolase cancer therapies. We suggest an individualized cancer therapy based on the determination of metabolic changes in tumors that might enable the targeted inhibition of invasion and metastasis.

Other important links between cancer-causing genes and glucose metabolism have been already identified. Activation of the oncogenic kinase Akt has been shown to stimulate glucose uptake and metabolism in cancer cells and renders these cells susceptible to death in response to glucose withdrawal. Such tumor cells have been shown to be dependent on glucose because the ability to induce fatty acid oxidation in response to glucose deprivation is impaired by activated Akt. In addition, AMP-activated protein kinase (AMPK) has been identified as a link between glucose metabolism and the cell cycle, thereby implicating p53 as an essential component of metabolic cell-cycle control.

Expression of transketolase TKTL1 predicts colon and urothelial cancer patient survival: Warburg effect reinterpreted

S Langbein, M Zerilli, A zur Hausen, W Staiger, et al.
British Journal of Cancer (2006) 94, 578–585.
http://dx.doi.org:/10.1038/sj.bjc.6602962

The unique metabolic profile of cancer (aerobic glycolysis) might confer apoptosis resistance and be therapeutically targeted. Compared to normal cells, several human cancers have high mitochondrial membrane potential (DJm) and low expression of the K+ channel Kv1.5, both contributing toapoptosis resistance. Dichloroacetate (DCA) inhibits mitochondrial pyruvate dehydrogenase kinase (PDK), shifts metabolism from glycolysis to glucose oxidation, decreases DJm, increases mitochondrial H2O2, and activates Kv channels in all cancer, but not normal, cells; DCA upregulates Kv1.5 by an NFAT1-dependent mechanism. DCA induces apoptosis, decreases proliferation, and inhibits tumor growth, without apparent toxicity. Molecular inhibition of PDK2 by siRNA mimics DCA. The mitochondria-NFAT-Kv axis and PDK are important therapeutic targets in cancer; the orally available DCA is a promising selective anticancer agent.

Cancer progression and its resistance to treatment depend, at least in part, on suppression of apoptosis. Although mitochondria are recognized as regulators of apoptosis, their importance as targets for cancer therapy has not been adequately explored or clinically exploited. In 1930, Warburg suggested that mitochondrial dysfunction in cancer results in a characteristic metabolic phenotype, that is, aerobic glycolysis (Warburg, 1930). Positron emission tomography (PET) imaging has now confirmed that most malignant tumors have increased glucose uptake and metabolism. This bioenergetic feature is a good marker of cancer but has not been therapeutically pursued..

The small molecule DCA is a metabolic modulator that has been used in humans for decades in the treatment of lactic acidosis and inherited mitochondrial diseases. Without affecting normal cells, DCA reverses the metabolic electrical remodeling that we describe in several cancer lines (hyperpolarized mitochondria, activated NFAT1, downregulated Kv1.5), inducing apoptosis and decreasing tumor growth. DCA in the drinking water at clinically relevant doses for up to 3 months prevents and reverses tumor growth in vivo, without apparent toxicity and without affecting hemoglobin, transaminases, or creatinine levels. The ease of delivery, selectivity, and effectiveness  make DCA an attractive candidate for proapoptotic cancer therapy which can be rapidly translated into phase II–III clinical trials.

A Mitochondria-K+ Channel Axis Is Suppressed in Cancer and Its Normalization Promotes Apoptosis and Inhibits Cancer Growth

Sebastien Bonnet, Stephen L. Archer, Joan Allalunis-Turner, et al.

Cancer Cell Jan 2007; 11: 37–51.
http://dx.doi.org:/10.1016/j.ccr.2006.10.020

Tumor cells, just as other living cells, possess the potential for proliferation, differentiation, cell cycle arrest, and apoptosis. There is a specific metabolic phenotype associated with each of these conditions, characterized by the production of both energy and special substrates necessary for the cells to function in that particular state. Unlike that of normal living cells, the metabolic phenotype of tumor cells supports the proliferative state. Aim: To present the metabolic hypothesis that (1) cell transformation and tumor growth are associated with the activation of metabolic enzymes that increase glucose carbon utilization for nucleic acid synthesis, while enzymes of the lipid and amino acid synthesis pathways are activated in tumor growth inhibition, and (2) phosphorylation and allosteric and transcriptional regulation of intermediary metabolic enzymes and their substrate availability together mediate and sustain cell transformation from one condition to another. Conclusion: Evidence is presented that demonstrates opposite changes in metabolic phenotypes induced by TGF-β, a cell transforming agent, and tumor growth-inhibiting phytochemicals such as genistein and Avemar, or novel synthetic antileukemic drugs such as STI571 (Gleevec).  Intermediary metabolic enzymes that mediate the growth signaling pathways and promote malignant cell transformation may serve as high efficacy nongenetic novel targets for cancer therapies.

A Metabolic Hypothesis of Cell Growth and Death in Pancreatic Cancer

Laszlo G. Boros, Wai-Nang Paul Lee, and Vay Liang W. Go
Pancreas 2002; 24(1):26–33

Clear cell renal cell carcinoma (ccRCC) is the most common pathological subtype of kidney cancer. Here, we integrated an unbiased genome-wide RNA interference screen for ccRCC survival regulators with an analysis of recurrently overexpressed genes in ccRCC to identify new therapeutic targets in this disease. One of the most potent survival regulators, the monocarboxylate transporter MCT4 (SLC16A3), impaired ccRCC viability in all eight ccRCC lines tested and was the seventh most overexpressed gene in a meta-analysis of five ccRCC expression datasets.

MCT4 silencing impaired secretion of lactate generated through glycolysis and induced cell cycle arrest and apoptosis. Silencing MCT4 resulted in intracellular acidosis, and reduction in intracellular ATP production together with partial reversion of the Warburg effect in ccRCC cell lines. Intra-tumoral heterogeneity in the intensity of MCT4 protein expression was observed in primary ccRCCs.

MCT4 protein expression analysis based on the highest intensity of expression in primary ccRCCs was associated with poorer relapse-free survival, whereas modal intensity correlated with Fuhrman nuclear grade. Consistent with the potential selection of subclones enriched for MCT4 expression during disease progression, MCT4 expression was greater at sites of metastatic disease. These data suggest that MCT4 may serve as a novel metabolic target to reverse the Warburg effect and limit disease progression in ccRCC.

Clear cell carcinoma (ccRCC) is the commonest subtype of renal cell carcinoma, accounting for 80% of cases. These tumors are highly resistant to cytotoxic chemotherapy and until recently, systemic treatment options for advanced ccRCC were limited to cytokine based therapies, such as interleukin-2 and interferon-α. Recently, anti-angiogenic drugs and mTOR inhibitors, all targeting the HIF–VEGF axis which is activated in up to 91% of ccRCCs through loss of the VHL tumor suppressor gene [1], have been shown to be effective in metastatic ccRCC [2–5]. Although these drugs increase overall survival to more than 2 years [6], resistance invariably occurs, making the identification of new molecular targets a major clinical need to improve outcomes in patients with metastatic ccRCC.

Genome-wide RNA interference analysis of renal carcinoma survival regulators identifies MCT4 as a Warburg effect metabolic target

Marco Gerlinger, Claudio R Santos, Bradley Spencer-Dene, et al.
J Pathol 2012; 227: 146–156
http://dx.doi.org:/10.1002/path.4006

Hypoxia-inducible factor 1 (HIF-1) plays a key role in the reprogramming of cancer metabolism by activating transcription of genes encoding glucose transporters and glycolytic enzymes, which take up glucose and convert it to lactate; pyruvate dehydrogenase kinase 1, which shunts pyruvate away from the mitochondria; and BNIP3, which triggers selective mitochondrial autophagy. The shift from oxidative to glycolytic metabolism allows maintenance of redox homeostasis and cell survival under conditions of prolonged hypoxia. Many metabolic abnormalities in cancer cells increase HIF-1 activity. As a result, a feed-forward mechanism can be activated that drives HIF-1 activation and may promote tumor progression.

Metastatic cancer is characterized by reprogramming of cellular metabolism leading to increased uptake of glucose for use as both an anabolic and a catabolic substrate. Increased glucose uptake is such a reliable feature that it is utilized clinically to detect metastases by positron emission tomography using 18F-fluorodeoxyglucose (FDG-PET) with a sensitivity of >90% [1]. As with all aspects of cancer biology, the details of metabolic reprogramming differ widely among individual tumors. However, the role of specific signaling pathways and transcription factors in this process is now understood in considerable detail. This review will focus on the involvement of hypoxia-inducible factor 1 (HIF-1) in both mediating metabolic reprogramming and responding to metabolic alterations. The placement of HIF-1 both upstream and downstream of cancer metabolism results in a feed-forward mechanism that may play a major role in the development of the invasive, metastatic, and lethal cancer phenotype.

O2 concentrations are significantly reduced in many human cancers compared with the surrounding normal tissue. The median PO2 in breast cancers is 10 mmHg, as compared with65 mmHg in normal breast tissue. Reduced O2 availability induces HIF-1, which regulates the transcription of hundreds of genes that encode proteins involved in every aspect of cancer biology, including: cell immortalization and stem cell maintenance; genetic instability; glucose and energy metabolism; vascularization; autocrine growth factor signaling; invasion and metastasis; immune evasion; and resistance to chemotherapy and radiation therapy.

HIF-1 is a transcription factor that consists of an O2 regulated HIF-1a and a constitutively expressed HIF-1b subunit. In well-oxygenated cells, HIF-1a is hydroxylated on proline residue 402 (Pro-402) and/or Pro-564 by prolyl hydroxylase domain protein 2 (PHD2), which uses O2 and a-ketoglutarate as substrates in a reaction that generates CO2 and succinate as byproducts. Prolylhydroxylated HIF-1a is bound by the von Hippel–Lindau tumor suppressor protein (VHL), which recruits an E3-ubiquitin ligase that targets HIF-1a for proteasomal degradation (Figure 1a). Asparagine 803 in the transactivation domain is hydroxylated in well-oxygenated cells by factor inhibiting HIF-1 (FIH-1), which blocks the binding of the coactivators p300 and CBP. Under hypoxic conditions, the prolyl and asparaginyl hydroxylation reactions are inhibited by substrate (O2) deprivation and/or the mitochondrial generation of reactive oxygen species (ROS), which may oxidize Fe(II) present in the catalytic center of the hydroxylases.

The finding that acute changes in PO2 increase mitochondrial ROS production suggests that cellular respiration is optimized at physiological PO2 to limit ROS generation and that any deviation in PO2 – up or down – results in increased ROS generation. If hypoxia persists, induction of HIF-1 leads to adaptive mechanisms to reduce ROS and re-establish homeostasis, as described below. Prolyl and asparaginyl hydroxylation provide a molecular mechanism by which changes in cellular oxygenation can be transduced to the nucleus as changes in HIF-1 activity.

HIF-1: upstream and downstream of cancer metabolism

Gregg L Semenza
Current Opinion in Genetics & Development 2010, 20:51–56

This review comes from a themed issue on Genetic and cellular mechanisms of oncogenesis Edited by Tony Hunter and Richard Marais

http://dx.doi.org:/10.1016/j.gde.2009.10.009

Hypoxia-inducible factor 1 (HIF-1) regulates the transcription of many genes involved in key aspects of cancer biology, including immortalization, maintenance of stem cell pools, cellular dedifferentiation, genetic instability, vascularization, metabolic reprogramming, autocrine growth factor signaling, invasion/metastasis, and treatment failure. In animal models, HIF-1 overexpression is associated with increased tumor growth, vascularization, and metastasis, whereas HIF-1 loss-of-function has the opposite effect, thus validating HIF-1 as a target. In further support of this conclusion, immunohistochemical detection of HIF-1a overexpression in biopsy sections is a prognostic factor in many cancers. A growing number of novel anticancer agents have been shown to inhibit HIF-1 through a  variety of molecular mechanisms. Determining which combination of drugs to administer to any given patient remains a major obstacle to improving cancer treatment outcomes.

Intratumoral hypoxia The majority of locally advanced solid tumors contain regions of reduced oxygen availability. Intratumoral hypoxia results when cells are located too far from a functional blood vessel for diffusion of adequate amounts of O2 as a result of rapid cancer cell proliferation and the formation of blood vessels that are structurally and functionally abnormal. In the most extreme case, O2 concentrations are below those required for survival, resulting in cell death and establishing a selection for cancer cells in which apoptotic pathways are inactivated, anti-apoptotic pathways are activated, or invasion/metastasis pathways that promote escape from the hypoxic microenvironment are activated. This hypoxic adaptation may arise by alterations in gene expression or by mutations in the genome or both and is associated with reduced patient survival.

Hypoxia-inducible factor 1 (HIF-1) The expression of hundreds of genes is altered in each cell exposed to hypoxia. Many of these genes are regulated by HIF-1. HIF-1 is a heterodimer formed by the association of an O2-regulated HIF1a subunit with a constitutively expressed HIF-1b subunit. The structurally and functionally related HIF-2a protein also dimerizes with HIF-1b and regulates an overlapping battery of target genes. Under nonhypoxic conditions, HIF-1a (as well as HIF-2a) is subject to O2-dependent prolyl hydroxylation and this modification is required for binding of the von Hippel–Lindau tumor suppressor protein (VHL), which also binds to Elongin C and thereby recruits a ubiquitin ligase complex that targets HIF-1a for ubiquitination and proteasomal degradation. Under hypoxic conditions, the rate of hydroxylation and ubiquitination declines, resulting in accumulation of HIF-1a. Immunohistochemical analysis of tumor biopsies has revealed high levels of HIF-1a in hypoxic but viable tumor cells surrounding areas of necrosis.

Genetic alterations in cancer cells increase HIF-1 activity In the majority of clear-cell renal carcinomas, VHL function is lost, resulting in constitutive activation of HIF-1. After re-introduction of functional VHL, renal carcinoma cell lines are no longer tumorigenic, but can be made tumorigenic by expression of HIF2a in which the prolyl residues that are subject to hydroxylation have been mutated. In addition to VHL loss-of-function, many other genetic alterations that inactivate tumor suppressors

Evaluation of HIF-1 inhibitors as anticancer agents

Gregg L. Semenza
Drug Discovery Today Oct 2007; 12(19/20).
http://dx.doi.org:/10.1016/j.drudis.2007.08.006

Hypoxia-inducible factor-1 (HIF-1), which is present at high levels in human tumors, plays crucial roles in tumor promotion by upregulating its target genes, which are involved in anaerobic energy metabolism, angiogenesis, cell survival, cell invasion, and drug resistance. Therefore, it is apparent that the inhibition of HIF-1 activity may be a strategy for treating cancer. Recently, many efforts to develop new HIF-1-targeting agents have been made by both academic and pharmaceutical industry laboratories. The future success of these efforts will be a new class of HIF-1-targeting anticancer agents, which would improve the prognoses of many cancer patients. This review focuses on the potential of HIF-1 as a target molecule for anticancer therapy, and on possible strategies to inhibit HIF-1 activity. In addition, we introduce YC-1 as a new anti-HIF-1, anticancer agent. Although YC-1 was originally developed as a potential therapeutic agent for thrombosis and hypertension, recent studies demonstrated that YC-1 suppressed HIF-1 activity and vascular endothelial growth factor expression in cancer cells. Moreover, it halted tumor growth in immunodeficient mice without serious toxicity during the treatment period. Thus, we propose that YC-1 is a good lead compound for the development of new anti-HIF-1, anticancer agents.

Although many anticancer regimens have been introduced to date, their survival benefits are negligible, which is the reason that a more innovative treatment is required. Basically, the identification of the specific molecular features of tumor promotion has allowed for rational drug discovery in cancer treatment, and drugs have been screened based upon the modulation of specific molecular targets in tumor cells. Target-based drugs should satisfy the following two conditions.

First, they must act by a described mechanism.

Second, they must reduce tumor growth in vivo, associated with this mechanism.

Many key factors have been found to be involved in the multiple steps of cell growth signal-transduction pathways. Targeting these factors offers a strategy for preventing tumor growth; for example, competitors or antibodies blocking ligand–receptor interaction, and receptor tyrosine kinase inhibitors, downstream pathway inhibitors (i.e., RAS farnesyl transferase inhibitors, mitogen-activated protein kinase and mTOR inhibitors), and cell-cycle arresters (i.e., cyclin-dependent kinase inhibitors) could all be used to inhibit tumor growth.

In addition to the intracellular events, tumor environmental factors should be considered to treat solid tumors. Of these, hypoxia is an important cancer-aggravating factor because it contributes to the progression of a more malignant phenotype, and to the acquisition of resistance to radiotherapy and chemotherapy. Thus, transcription factors that regulate these hypoxic events are good targets for anticancer therapy and in particular HIF-1 is one of most compelling targets. In this paper, we introduce the roles of HIF-1 in tumor promotion and provide a summary of new anticancer strategies designed to inhibit HIF-1 activity.

New anticancer strategies targeting HIF-1

Eun-Jin Yeo, Yang-Sook Chun, Jong-Wan Park
Biochemical Pharmacology 68 (2004) 1061–1069
http://dx.doi.org:/10.1016/j.bcp.2004.02.040

Classical work in tumor cell metabolism focused on bioenergetics, particularly enhanced glycolysis and suppressed oxidative phosphorylation (the ‘Warburg effect’). But the biosynthetic activities required to create daughter cells are equally important for tumor growth, and recent studies are now bringing these pathways into focus. In this review, we discuss how tumor cells achieve high rates of nucleotide and fatty acid synthesis, how oncogenes and tumor suppressors influence these activities, and how glutamine metabolism enables macromolecular synthesis in proliferating cells.

Otto Warburg’s demonstration that tumor cells rapidly use glucose and convert the majority of it to lactate is still the most fundamental and enduring observation in tumor metabolism. His work, which ushered in an era of study on tumor metabolism focused on the relationship between glycolysis and cellular bioenergetics, has been revisited and expanded by generations of tumor biologists. It is now accepted that a high rate of glucose metabolism, exploited clinically by 18FDGPET scanning, is a metabolic hallmark of rapidly dividing cells, correlates closely with transformation, and accounts for a significant percentage of ATP generated during cell proliferation. A ‘metabolic transformation’ is required for tumorigenesis. Research over the past few years has reinforced this idea, revealing the conservation of metabolic activities among diverse tumor types, and proving that oncogenic mutations can promote metabolic autonomy by driving nutrient uptake to levels that often exceed those required for cell growth and proliferation.

In order to engage in replicative division, a cell must duplicate its genome, proteins, and lipids and assemble the components into daughter cells; in short, it must become a factory for macromolecular biosynthesis. These activities require that cells take up extracellular nutrients like glucose and glutamine and allocate them into metabolic pathways that convert them into biosynthetic precursors (Figure 1). Tumor cells can achieve this phenotype through changes in the expression of enzymes that determine metabolic flux rates, including nutrient transporters and enzymes [8– 10]. Current studies in tumor metabolism are revealing novel mechanisms for metabolic control, establishing which enzyme isoforms facilitate the tumor metabolic phenotype, and suggesting new targets for cancer therapy.

The ongoing challenge in tumor cell metabolism is to understand how individual pathways fit together into the global metabolic phenotype of cell growth. Here we discuss two biosynthetic activities required by proliferating tumor cells: production of ribose-5 phosphate for nucleotide biosynthesis and production of fatty acids for lipid biosynthesis. Nucleotide and lipid biosynthesis share three important characteristics.

  • First, both use glucose as a carbon source.
  • Second, both consume TCA cycle intermediates, imposing the need for a mechanism to replenish the cycle.
  • Third, both require reductive power in the form of NADPH.

In this Essay, we discuss the possible drivers, advantages, and potential liabilities of the altered metabolism of cancer cells (Figure 1, not shown). Although our emphasis on the Warburg effect reflects the focus of the field, we would also like to encourage a broader approach to the study of cancer metabolism that takes into account the contributions of all interconnected small molecule pathways of the cell.

The Tumor Microenvironment Selects for Altered Metabolism One compelling idea to explain the Warburg effect is that the altered metabolism of cancer cells confers a selective advantage for survival and proliferation in the unique tumor microenvironment. As the early tumor expands, it outgrows the diffusion limits of its local blood supply, leading to hypoxia and stabilization of the hypoxia-inducible transcription factor, HIF. HIF initiates a transcriptional program that provides multiple solutions to hypoxic stress (reviewed in Kaelin and Ratcliffe, 2008). Because a decreased dependence on aerobic respiration becomes advantageous, cell metabolism is shifted toward glycolysis by the increased expression of glycolytic enzymes, glucose transporters, and inhibitors of mitochondrial metabolism. In addition, HIF stimulates angiogenesis (the formation of new blood vessels) by upregulating several factors, including most prominently vascular endothelial growth factor (VEGF).

Blood vessels recruited to the tumor microenvironment, however, are disorganized, may not deliver blood effectively, and therefore do not completely alleviate hypoxia (reviewed in Gatenby and Gillies, 2004). The oxygen levels within a tumor vary both spatially and temporally, and the resulting rounds of fluctuating oxygen levels potentially select for tumors that constitutively upregulate glycolysis. Interestingly, with the possible exception of tumors that have lost the von Hippel-Lindau protein (VHL), which normally mediates degradation of HIF, HIF is still coupled to oxygen levels, as evident from the heterogeneity of HIF expression within the tumor microenvironment. Therefore, the Warburg effect—that is, an uncoupling of glycolysis from oxygen levels—cannot be explained solely by upregulation of HIF. Other molecular mechanisms are likely to be important, such as the metabolic changes induced by oncogene activation and tumor suppressor loss.

Oncogene Activation Drives Changes in Metabolism Not only may the tumor microenvironment select for a deranged metabolism, but oncogene status can also drive metabolic changes. Since Warburg’s time, the biochemical study of cancer metabolism has been overshadowed by efforts to identify the mutations that contribute to cancer initiation and progression. Recent work, however, has demonstrated that the key components of the Warburg effect—

  • increased glucose consumption,
  • decreased oxidative phosphorylation, and
  • accompanying lactate production—
  • are also distinguishing features of oncogene activation.

The signaling molecule Ras, a powerful oncogene when mutated, promotes glycolysis (reviewed in Dang and Semenza, 1999; Ramanathan et al., 2005). Akt kinase, a well-characterized downstream effector of insulin signaling, reprises its role in glucose uptake and utilization in the cancer setting (reviewed in Manning and Cantley, 2007), whereas the Myc transcription factor upregulates the expression of various metabolic genes (reviewed in Gordan et al., 2007). The most parsimonious route to tumorigenesis may be activation of key oncogenic nodes that execute a proliferative program, of which metabolism may be one important arm. Moreover, regulation of metabolism is not exclusive to oncogenes.

Cancer Cell Metabolism: Warburg & Beyond

Hsu PP & Sabatini DM
Cell  Sep 5, 2008; 134, 703-705
http://dx.doi.org:/10.1016/j.cell.2008.08.021

Tumor cells respond to growth signals by the activation of protein kinases, altered gene expression and significant modifications in substrate flow and redistribution among biosynthetic pathways. This results in a proliferating phenotype with altered cellular function. These transformed cells exhibit unique anabolic characteristics, which includes increased and preferential utilization of glucose through the non-oxidative steps of the pentose cycle for nucleic acid synthesis but limited de novo fatty  acid   synthesis   and   TCA   cycle   glucose   oxidation. This  primarily nonoxidative anabolic profile reflects an undifferentiated highly proliferative aneuploid cell phenotype and serves as a reliable metabolic biomarker to determine cell proliferation rate and the level of cell transformation/differentiation in response to drug treatment.

Novel drugs effective in particular cancers exert their anti-proliferative effects by inducing significant reversions of a few specific non-oxidative anabolic pathways. Here we present evidence that cell transformation of various mechanisms is sustained by a unique disproportional substrate distribution between the two branches of the pentose cycle for nucleic acid synthesis, glycolysis and the TCA cycle for fatty acid synthesis and glucose oxidation. This can be demonstrated by the broad labeling and unique specificity of [1,2-13C2]glucose to trace a large number of metabolites in the metabolome. Stable isotope-based dynamic metabolic profiles (SIDMAP) serve the drug discovery process by providing a powerful new tool that integrates the metabolome into a functional genomics approach to developing new drugs. It can be used in screening kinases and their metabolic targets, which can therefore be more efficiently characterized, speeding up and improving drug testing, approval and labeling processes by saving trial and error type study costs in drug testing.

Metabolic Biomarker and Kinase Drug Target Discovery in Cancer Using Stable Isotope-Based Dynamic Metabolic Profiling (SIDMAP)

László G. Boros, Daniel J. Brackett and George G. Harrigan
Current Cancer Drug Targets, 2003, 3, 447-455 447

Pyruvate constitutes a critical branch point in cellular carbon metabolism. We have identified two proteins, Mpc1 and Mpc2, as essential for mitochondrial pyruvate transport in yeast, Drosophila, and humans. Mpc1 and Mpc2 associate to form an ~150 kilodalton complex in the inner mitochondrial membrane. Yeast and Drosophila mutants lacking MPC1 display impaired pyruvate metabolism, with an accumulation of upstream metabolites and a depletion of tricarboxylic acid cycle intermediates. Loss of yeast Mpc1 results in defective mitochondrial pyruvate uptake, while silencing of MPC1 or MPC2 in mammalian cells impairs pyruvate oxidation. A point mutation in MPC1 provides resistance to a known inhibitor of the mitochondrial pyruvate carrier. Human genetic studies of three families with children suffering from lactic acidosis and hyperpyruvatemia revealed a causal locus that mapped to MPC1, changing single amino acids that are conserved throughout eukaryotes. These data demonstrate that Mpc1 and Mpc2 form an essential part of the mitochondrial pyruvate carrier.

A Mitochondrial Pyruvate Carrier Required for Pyruvate Uptake in Yeast, Drosophila , and Humans

Daniel K. Bricker, Eric B. Taylor, John C. Schell, Thomas Orsak, et al.
Science Express 24 May 2012
http://dx.doi.org:/10.1126/science.1218099

Adenosine deaminase acting on RNA (ADAR) enzymes convert adenosine (A) to inosine (I) in double-stranded (ds) RNAs. Since Inosine is read as Guanosine, the biological consequence of ADAR enzyme activity is an A/G conversion within RNA molecules. A-to-I editing events can occur on both coding and non-coding RNAs, including microRNAs (miRNAs), which are small regulatory RNAs of ~20–23 nucleotides that regulate several cell processes by annealing to target mRNAs and inhibiting their translation. Both miRNA precursors and mature miRNAs undergo A-to-I RNA editing, affecting the miRNA maturation process and activity. ADARs can also edit 3′ UTR of mRNAs, further increasing the interplay between mRNA targets and miRNAs. In this review, we provide a general overview of the ADAR enzymes and their mechanisms of action as well as miRNA processing and function. We then review the more recent findings about the impact of ADAR-mediated activity on the miRNA pathway in terms of biogenesis, target recognition, and gene expression regulation.

Review ADAR Enzyme and miRNA Story: A Nucleotide that Can Make the Difference 

Sara Tomaselli, Barbara Bonamassa, Anna Alisi, Valerio Nobili, Franco Locatelli and Angela Gallo
Int. J. Mol. Sci. 19 Nov 2013; 14, 22796-22816 http://dx.doi.org:/10.3390/ijms141122796

The fermented wheat germ extract (FWGE) nutraceutical (Avemar™), manufactured under “good manufacturing practice” conditions and, fulfilling the self-affirmed “generally recognized as safe” status in the United States, has been approved as a “dietary food for special medical purposes for cancer patients” in Europe. In this paper, we report the adjuvant use of this nutraceutical in the treatment of high-risk skin melanoma patients. Methods: In a randomized, pilot, phase II clinical trial, the efficacy of dacarbazine (DTIC)-based adjuvant chemotherapy on survival parameters of melanoma patients was compared to that of the same treatment supplemented with a 1-year long administration of FWGE. Results: At the end of an additional 7-year-long follow-up period, log-rank analyses (Kaplan-Meier estimates) showed significant differences in both progression-free (PFS) and overall survival (OS) in favor of the FWGE group. Mean PFS: 55.8 months (FWGE group) versus 29.9 months (control group), p  0.0137. Mean OS: 66.2 months (FWGE group) versus 44.7 months (control group), p < 0.0298. Conclusions: The inclusion of Avemar into the adjuvant protocols of high-risk skin melanoma patients is highly recommended.

Adjuvant Fermented Wheat Germ Extract (Avemar™) Nutraceutical Improves Survival of High-Risk Skin Melanoma Patients: A Randomized, Pilot, Phase II Clinical Study with a 7-Year Follow-Up

LV Demidov, LV Manziuk, GY Kharkevitch, NA Pirogova, and EV Artamonova
Cancer Biotherapy & Radiopharmaceuticals 2008; 23(4)
http://dx.doi.org:/10.1089/cbr.2008.0486

Cancer cells possess unique metabolic signatures compared to normal cells, including shifts in aerobic glycolysis, glutaminolysis, and de novo biosynthesis of macromolecules. Targeting these changes with agents (drugs and dietary components) has been employed as strategies to reduce the complications associated with tumorigenesis. This paper highlights the ability of several food components to suppress tumor-specific metabolic pathways, including increased expression of glucose transporters, oncogenic tyrosine kinase, tumor-specific M2-type pyruvate kinase, and fatty acid synthase, and the detection of such effects using various metabonomic technologies, including liquid chromatography/mass spectrometry (LC/MS) and stable isotope-labeled MS. Stable isotope-mediated tracing technologies offer exciting opportunities for defining specific target(s) for food components. Exposures, especially during the early transition phase from normal to cancer, are critical for the translation of knowledge about food components into effective prevention strategies. Although appropriate dietary exposures needed to alter cellular metabolism remain inconsistent and/or ill-defined, validated metabonomic biomarkers for dietary components hold promise for establishing effective strategies for cancer prevention.

Bioactive Food Components and Cancer-Specific Metabonomic Profiles

Young S. Kim and John A. Milner
Journal of Biomedicine and Biotechnology 2011, Art ID 721213, 9 pages
http://dx.doi.org:/10.1155/2011/721213

This reviewer poses the following observation.  The importance of the pyridine nucleotide reduced/oxidized ratio has not been alluded to here, but the importance cannot be understated. It has relevance to the metabolic functions of anabolism and catabolism of the visceral organs.  The importance of this has ties to the pentose monophosphate pathway. The importance of the pyridine nucleotide transhydrogenase reaction remains largely unexplored.  In reference to the NAD-redox state, the observation was made by Nathan O. Kaplan that the organs may be viewed with respect to their primary functions in anabolic or high energy catabolic activities. Thus we find that the endocrine organs are largely tied to anabolic functioning, and to NADP, whereas cardiac and skeletal muscle are highly dependent on NAD. The consequence of this observed phenomenon appears to be related to a difference in the susceptibility to malignant transformation.  In the case of the gastrointestinal tract, the rate of turnover of the epithelium is very high. However, with the exception of the liver, there is no major activity other than cell turnover. In the case of the liver, there is a major commitment to synthesis of lipids, storage of fuel, and synthesis of proteins, which is largely anabolic, but there is also a major activity in detoxification, which is not.  In addition, the liver has a double circulation. As a result, a Zahn infarct is uncommon.  Now we might also consider the heart.  The heart is a muscle syncytium with a high need for oxygen.  Cutting of the oxygen supply makes the myocytes vulnerable to ischemic insult and abberant rhythm abnormalities.  In addition, the cardiomyocyte can take up lactic acid from the circulation for fuel, which is tied to the utilization of lactate from vigorous skeletal muscle activity.  The skeletal muscle is tied to glycolysis in normal function, which has a poor generation of ATP, so that the recycling of excess lactic acid is required by cardiac muscle and hepatocytes.  This has not been a part of the discussion, but this reviewer considers it important to remember in considering the organ-specific tendencies to malignant transformation.

Comment (Aurelian Udristioiu):

Otto Warburg observed that many cancers lose their capacity for mitochondrial respiration, limiting ATP production to anaerobic glycolytic pathways. The phenomenon is particularly prevalent in aggressive malignancies, most of which are also hypoxic [1].
Hypoxia induces a stochastic imbalance between the numbers of reduced mitochondrial species vs. available oxygen, resulting in increased reactive oxygen species (ROS) whose toxicity can lead to apoptotic cell death.
Mechanism involves inhibition of glycolytic ATP production via a Randle-like cycle while increased uncoupling renders cancers unable to produce compensatory ATP from respiration-.generation in the presence of intact tricarboxylic acid (TCA) enzyme.
One mitochondrial adaptation to increased ROS is over-expression of the uncoupling protein 2 (UCP2) that has been reported in multiple human cancer cell lines [2-3]. Increased UCP2 expression was also associated with reduced ATP production in malignant oxyphilic mouse leukemia and human lymphoma cell lines [4].
Hypoxia reduces the ability of cells to maintain their energy levels, because less ATP is obtained from glycolysis than from oxidative phosphorylation. Cells adapt to hypoxia by activating the expression of mutant genes in glycolysis.
-Severe hypoxia causes a high mutation rate, resulting in point mutations that may be explained by reduced DNA mismatch repairing activity.
The most direct induction of apoptosis caused by hypoxia is determined by the inhibition of the electron carrier chain from the inner membrane of the mitochondria. The lack of oxygen inhibits the transport of protons and thereby causes a decrease in membrane potential. Cell survival under conditions of mild hypoxia is mediated by phosphoinositide-3 kinase (PIK3) using severe hypoxia or anoxia, and then cells initiate a cascade of events that lead to apoptosis [5].
After DNA damage, a very important regulator of apoptosis is the p53 protein. This tumor suppressor gene has mutations in over 60% of human tumors and acts as a suppressor of cell division. The growth-suppressive effects of p53 are considered to be mediated through the transcriptional trans-activation activity of the protein. In addition to the maturational state of the clonal tumor, the prognosis of patients with CLL is dependent of genetic changes within the neoplastic cell population.

1.Warburg O. On the origin of cancer cells. Science 1956; 123 (3191):309-314
PubMed Abstract ; Publisher Full Text

2.Giardina TM, Steer JH, Lo SZ, Joyce DA. Uncoupling protein-2 accumulates rapidly in the inner mitochondrial membrane during mitochondrial reactive oxygen stress in macrophages. Biochim Biophys Acta 2008, 1777(2):118-129. PubMed Abstract | Publisher Full Text

3. Horimoto M, Resnick MB, Konkin TA, Routhier J, Wands JR, Baffy G. Expression of uncoupling protein-2 in human colon cancer. Clin Cancer Res 2004; 10 (18 Pt1):6203-6207. PubMed Abstract | Publisher Full Text

4. Randle PJ, England PJ, Denton RM. Control of the tricarboxylate cycle and it interactions with glycolysis during acetate utilization in rat heart. Biochem J 1970; 117(4):677-695. PubMed Abstract | PubMed Central Full Text

5. Gillies RJ, Robey I, Gatenby RA. Causes and consequences of increased glucose metabolism of cancers. J Nucl Med 2008; 49(Suppl 2):24S-42S. PubMed Abstract | Publisher Full Text

Shortened version of Comment –

Hypoxia induces a stochastic imbalance between the numbers of reduced mitochondrial species vs. available oxygen, resulting in increased reactive oxygen species (ROS) whose toxicity can lead to apoptotic cell death.
Mechanism involves inhibition of glycolytic ATP production via a Randle-like cycle while increased uncoupling renders cancers unable to produce compensatory ATP from respiration-.generation in the presence of intact tricarboxylic acid (TCA) enzyme.
One mitochondrial adaptation to increased ROS is over-expression of the uncoupling protein 2 (UCP2) that has been reported in multiple human cancer cell lines. Increased UCP2 expression was also associated with reduced ATP production in malignant oxyphilic mouse leukemia and human lymphoma cell lines.
Severe hypoxia causes a high mutation rate, resulting in point mutations that may be explained by reduced DNA mismatch repairing activity.

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Endometrial Cancer: Mutations, Molecular Types and Immune Responses Evoked by Mutation-prone Endometrial, Ovarian Cancer Subtypes

Curator: Aviva Lev-Ari, PhD, RN

 

This Open Access Online Scientific Journal represents a repository of curated scientific literature on the following types of cancer of relevance to the subject matter of this article. See below the FRONTIER of Research on:

Breast Cancer

http://pharmaceuticalintelligence.com/?s=Breast+Cancer

Ovarian Cancer

http://pharmaceuticalintelligence.com/?s=Ovarian+Cancer

Genomics of Endometriosis

http://pharmaceuticalintelligence.com/?s=Endometriosis+

Reproductive Genomics

http://pharmaceuticalintelligence.com/?s=Reproductive+Genomics

Genomic Endocrinology

http://pharmaceuticalintelligence.com/?s=Endocrinology+Genomic

 

Endometrial Cancer: Mutations, Molecular Types and Immune Responses Evoked by Mutation-prone Endometrial, Ovarian Cancer Subtypes – New Findings

 

CONCLUSIONS

  • the team saw an apparent jump in PD-1 representation in the lymphocytes that were infiltrating neighboring tumors in the BRCA1/2-mutated tumors relative to the other ovarian cancers, though staining for the immune checkpoint contributors within tumors themselves appeared similar regardless of the subtype considered.
  • Strickland and his colleagues reasoned that such a feature may partly explain the relatively high progression-free survival and overall survival rates reported in BRCA1/2-mutated ovarian cancers, though they are continuing to study the relationship between BRCA mutations and tumor features.
  • Memorial Sloan Kettering medical oncologist Alexandra Snyder Charen discussed potential implications of the endometrial and ovarian cancer studies, noting that distinct mutation signatures in different tumor types could also affect immune response.
  • While she expressed enthusiasm about potential treatment clues provided by more-or-less mutated endometrial and ovarian cancers, Snyder Charen noted that additional research is needed on additional forms of the disease, since the work described was done using primary tumors.

 

Recurrent somatic mutations in chromatin-remodeling and ubiquitin ligase complex genes in serous endometrial tumors

http://pharmaceuticalintelligence.com/2012/11/19/recurrent-somatic-mutations-in-chromatin-remodeling-and-ubiquitin-ligase-complex-genes-in-serous-endometrial-tumors/

Testing for Multiple Genetic Mutations via NGS for Patients: Very Strong Family History of Breast & Ovarian Cancer, Diagnosed at Young Ages, & Negative on BRCA Test

http://pharmaceuticalintelligence.com/2013/05/20/testing-for-multiple-genetic-mutations-via-ngs-for-patients-very-strong-family-history-of-breast-ovarian-cancer-diagnosed-at-young-ages-negative-on-brca-test/

TCGA Analysis Uncovers Four Molecular Subtypes for Endometrial Cancer

For tumors from the high-risk serous subtype, meanwhile, they saw genetic and genomic features that resemble those found in serous ovarian cancer and basal-like breast cancer, albeit with more frequent mutations to genes such as PIK3CA, FBXW7, PPP2R1A, and ARID1A.

These and other molecular features identified in the current study could have prognostic and treatment implications, they noted. For instance, survival patterns in the POLE subtype seem to be favorable, despite the rampant mutations present in the genomes of those tumors.

In contrast, individuals with serous or serous-like tumors appear to do much worse, Levine noted.

That, in turn, suggests that there could be a benefit to offering more aggressive treatment to individuals with endometrioid cases falling in the new serous-like category, which is characterized by a higher-than-usual burden of copy number changes coupled with frequent mutations in the TP53 gene, a common cancer culprit.

“Clinicians should carefully consider treating copy-number-altered endometrioid patients with chemotherapy rather than adjuvant radiation,” Levine and his co-authors wrote, “and formally test such hypotheses in prospective clinical trials.”

For their part, researchers involved in the current study recently completed the accrual process for a clinical trial that will involve a little more than 300 endometrial cancer patients being treated with various chemotherapy regimens.

By prospectively collecting and tumors and determining their molecular subtypes, Levine said, it should be possible to track outcomes in relation to the four subtypes identified in the current study and, eventually, to get a better sense of treatment response and survival patterns in each group.

https://www.genomeweb.com/clinical-genomics/tcga-analysis-uncovers-four-molecular-subtypes-endometrial-cancer

 

Immune Responses Evoked by Mutation-prone Endometrial, Ovarian Cancer Subtypes

researchers from Brigham and Women’s Hospital, Harvard Medical School, and the Dana-Farber Cancer Institute characterized tumor-infiltrating immune cell activity and immune checkpoint contributor expression in dozens of archival endometrial tumors samples from mutation-heavy polymerase epsilon (POLE) mutations and microsatellite instability subtypes, comparing them with patterns in more mutation-light microsatellite stable tumors.

The results suggest endometrial cancers from subtypes prone to more widespread mutation also trigger stronger immune responses that might be further enhanced by drugs that inhibit cancer cells’ immune checkpoints, explained Brooke Howitt, a pathologist at the Brigham and Women’s Hospital, who presented the research at ASCO.

Howitt and her colleagues used immunohistochemistry to profile tumor infiltrating lymphocyte and expression of the immune checkpoint players PD-1 and PD-L1 in four POLE-mutated endometrial cancers, 28 endometrial cancers with microsatellite instability, and 32 microsatellite stable endometrial cancers.

Indeed, their results pointed to more pronounced tumor infiltration by CD3+ , CD4+, and CD8+ lymphocytes in the group of POLE-mutated and microsatellite unstable tumors than in the microsatellite stable subtype, consistent with T-cell activity against the mutation-rich tumors.

When they compared the more mutated endometrial cancer subtypes to the microsatellite stable group, the researchers saw signs of enhanced PD-L1 and PD-1 expression in both infiltrating lymphocytes and in the tumors themselves, hinting that the oft-mutated subtypes may respond to immune-targeting PD-1 inhibitor drugs.

Dana-Farber Cancer Institute researcher Kyle Strickland provided evidence for a similar pattern of bolstered immune activity against extensively mutated tumors.

For their part, though, Strickland and his team focused on BRCA1- and/or BRCA2-mutated, high-grade serous ovarian cancers, using immunohistochemistry to see if the high mutational load found in tumors with hampered BRCA-mediated DNA repair activity might also be a flag for the immune system.

There, researchers compared tumor infiltrating lymphocyte patterns in 37 BRCA1/2-mutated tumor samples and in samples from 16 tumors lacking germline or somatic mutations in BRCA1, BRCA2, or related mutations or expression changes — features verified by high-throughput sequencing.

Results from that comparison suggested that all of the ovarian cancers had comparable levels of certain tumor infiltrating lymphocytes, such as the CD3+ or CD20+ lymphocytes.

But compared with the “homologous recombination intact” tumors, the BRCA1/2-mutated ovarian cancers appeared to be marked by higher CD8+ tumor infiltrating lymphocytes and lower CD4+ tumor infiltrating lymphocytes, Strickland explained.

https://www.genomeweb.com/cancer/asco-session-explores-immune-responses-evoked-mutation-prone-endometrial-ovarian-cancer

 

Read Full Post »

Innovation in Cancer Biopharmaceutical Intelligence [11.5]

Writer and Curator: Larry H. Bernstein, MD, FCAP

The content of this article, with several interesting features is as follows:

11.5.1 Carmen Drahl..A Great Organic Chemist and Science Writer

11.5.2 Anthony Melvin Crasto

11.5.3 Amgen files ‘breakthrough’ leukemia drug in the US

11.5.4 Ginseng fights fatigue in cancer patients, Mayo Clinic-led study finds

11.5.5 The 10-Hydroxy-2-Decenoic Acid (10-2-HDA) content in Royal Jelly, is said to possess strong inhibition of malignant cell growth, namely transferable AKR leukemia, TA3 breast malignancy

11.5.6 A Microcapillary Flow Disc (MFD) Reactor for Organic Synthesis

11.5.7 Pauline Lau. Biochemist, Instrumental Analysis, Molecular and Clinical Diagnostics, and Pharmaceuticals

11.5.8  Kinetic and perfusion modeling of hyperpolarized 13C pyruvate and urea in cancer with arbitrary RF flip angles

11.5.9 ZSTK 474

11.5.10 Marrow-Infiltrating Lymphocytes Safely Shrink Multiple Myelomas

Introduction

The following content is a series of discussions that identify innovation in therapeutics and individuals who are leaders in pharmaceutical innovation.

11.5.1 Carmen Drahl. A Great Organic Chemist and Science Writer

Her eyes fit a stellar career path. She is a talent in organic and medicinal chemistry, and an informed reporter.

Extract from Dr. Anthony Melvin Castro,  Organic Chemistry

Carmen Drahl

Carmen Drahl

CARMEN DRAHL

Award-winning science communicator and social media power user based in Washington, DC.

Carmen Drahl is a multimedia science journalist and chemistry communicator based in Washington, DC.

ScienceAlum

ScienceAlum

A social media evangelist, Carmen started her first chemistry blog in 2006. Today, she regularly leverages Twitter, Facebook, and Google Plus Hangouts in her reporting.

Carmen has written about how life may have originated on Earth, explained how new medications get their names, and covered the ongoing issues plaguing the forensic science community. Her video on the food science behind 3D printed cocktail garnishes won the 2014 Folio Eddie Award for Best Association Video.

Until December 2014, Carmen worked at Chemical & Engineering News magazine. Her work has also been featured at Scientific American’s blog network, SiriusXM’s Doctor Radio, and elsewhere.

Carmen holds a Ph.D. in chemistry from Princeton University.

Ph.D. with Erik J. Sorensen.  She was on a team that completed the first total synthesis of abyssomicin C, a molecule found in small quantities in nature that showed hints of promise as a potential antibiotic. I constructed molecular probes from abyssomicin for proteomics studies of its biological activity.

M.A. with George L. McLendon worked toward developing a drug conjugate as a potential treatment for cancer. I synthesized a photosensitizer dye-peptide conjugate for targeting the cell death pathway called apoptosis.

Jacobus Fellowship Recipients - Carmen Drahl - Princeton

Jacobus Fellowship Recipients – Carmen Drahl – Princeton

Jacobus Fellowship Recipients – Carmen Drahl – Princeton

At a reception before the Alumni Day luncheon, President Tilghman (third from left) congratulated the winners of the University’s highest awards for students: (from left) Pyne Prize winners Lester Mackey and Alisha Holland; and Jacobus Fellowship recipients Sarah Pourciau, Egemen Kolemen and Carmen Drahl.

Specialties:

interviewing, science writing, social media, Twitter, Storify, YouTube, public speaking, hosting, video production, iPhone videography, non-linear video editing, blogging (WordPress and Blogger), HTML website coding

Carmen Drahl

By the time I discovered science blogs I knew my career goals were changing. I’d already been lucky enough to audit a science writing course at Princeton taught by Mike Lemonick from TIME, and thought that maybe science writing was a good choice for me. After reading chemistry blogs for a while I realized “Hey, I can do this!” and started my own blog, She Blinded Me with Science, in July 2006. It was the typical grad student blog, a mix of posts about papers I liked and life in the lab.

Carmen Drahl pic1

Carmen Drahl

At C&E News I’ve contributed to its C&ENtral Science blog, which premiered in spring 2008. I’ve experimented with a few different kinds of posts- observations and on-the-street interviews when

I run into something chemistry-related in DC, in-depth posts from meetings, and video demos of iPod apps. One of my favorite things to do is toy with new audio/video/etc technology for the blog.

Meant to treat: tumors with loss-of-function in the tumor suppressor protein PTEN (phosphatase and tensin homolog)- 2nd most inactivated tumor suppressor after p53- cancers where this is often the case include prostate and endometrial

Mode of action: inhibitor of phosphoinositide 3-kinase-beta (PI3K-beta). Several lines of evidence suggest that proliferation in certain PTEN-deficient tumor cell lines is driven primarily by PI3K-beta.

Medicinal chemistry tidbits: The GSK team seemed boxed in because in 3 out of 4 animals used in preclinical testing, promising drug candidates had high clearance. It turned out that a carbonyl group that they thought was critical for interacting with the back pocket of the PI3K-beta enzyme wasn’t so critical after all. When they realized they could replace the carbonyl with a variety of functional groups, GSK2636771 eventually emerged. GSK2636771B (shown)

GSK2636771B-300x224

GSK2636771B-300×224

11.5.2 Anthony Melvin Crasto

Principal Scientist, Process research

Glenmark Generics Ltd.

Anthony Melvin Crasto Ph.D

Worlddrugtracker, Principal scientist, Process research, Glenmark-Generics Ltd & Founder of Several Linkedin Gps

IndiaPharmaceuticals
Glenmark Generics Ltd., Glenmark Pharmaceuticals

Previous
Glenmark Pharmaceuticals, Innovassynth, RPG Life Sciences

Education
Institute of Chemical Technology (UDCT)

December 2005 – Present (9 years 6 months) Mahape, Navimumbai, India,
email  amcrasto@gmail.com

Currently working with GLENMARK GENERICS LTD research centre as Principal Scientist, process research (bulk actives) at Mahape ,Navi Mumbai,and leading a team of scientists in developing APIs for regulated markets, this involves visualization and execution of novel routes, polymorphs, and developing intellectual property to protect the invention. This involves all aspects of synthesis in lab and commercialization on plant , support for DMF filing.

Currently involved in development of several targets for regulated markets. Provide support to US/European marketing team for developing and execution of new projects

Process Development :-

  • Providing guidance and support for process development for challenging of patents in regulated market.
  • Design patent non-infringing scalable synthetic routes/process and scale-up of API’s
  • Bench and Pilot scale synthesis transformations in hands on
  • Optimization of the process, ie,developing industrially feasible process.
  • Preparation of PDR, filing of patent and DMF
  • Lead a group of Scientists and Group Leaders(for docs).

Skill sets:- Technical skills:

Synthesis:

  • Development of novel synthetic routes/process for pharmaceuticals and successful implementation of the technology in pilot plant
  • Conducted various reactions at laboratory and production scales.
  • Synthesized various classes of compounds.
  • Experienced to work under cGMP condition

EX Hoechst Marion Roussel(SANOFI AVENTIS), RPG Life Sciences,Innovassynth, SEARLE,AGREVO,IOC

Glenmark Generics Ltd.

Research Activities Covered in Entire Career

1) Extensive range of chemistry and scale of manufacture from laboratory, scale up laboratory, pilot plant, plant scale including third party activity.

Applied intellectual and synthetic skills to the process development of pharmaceutical drugs/their intermediates, and natural products, neutraceuticals, mettalocenes, speciality chemicals, flavours and fragrances in the laboratory and monitor them during plant trials.

Act as a technology transfer man and provide all data required for transfer from lab to commercialization.

Use of Internet and manual literature search methods to decide on non-infringing route

Write DHR for API before implementation of novel route in the plant and assist for all batches for the DMF purposes, very well versed with IPR issues

Ability to develop novel routes for API,s and draft patents,well versed with polymorphism issues.

Several patents filed in US/EU

Total experience 23+ in industry.

Currently working as principal scientist and leading a team of scientists in developing APIs for regulated markets, this involves novel routes, polymorphs, and developing intellectual property to protect the invention. This involves all aspects of synthesis and commercialization and assist in providing support for DMF filing.

11.5.3 Amgen files ‘breakthrough’ leukemia drug in the US

Daily News | Sept 22, 2014

Selina Mckee

Biotechnology giant Amgen has filed its investigational cancer immunotherapy blinatumomab in the US for the treatment of certain forms of acute lymphoblastic leukaemia (ALL).

Specifically, the Biologic License Application seeks approval to market the drug for patients with Philadelphia-negative (Ph-) relapsed/refractory B-precursor forms of the aggressive blood/bone marrow cancer.

Blinatumomab is the first of Amgen’s BiTE antibody constructs, a novel immunotherapy approach under which antibodies are modified to engage two different targets simultaneously. The drug has already been awarded both ‘Orphan’ and ‘Breakthrough’ status by the Food and Drug Administration, indicating that it could offer a significant advance over available therapies on at least one clinically significant endpoint.

The submission includes data from a Phase II which successfully met its primary endpoint, showing a complete response (no leukaemia cells detectable with microscopy) rate of 43% in patients with relapsed/refractory ALL, including those with resistance to previous treatment approaches.

“Currently, there is no broadly accepted standard treatment regimen for adult patients with relapsed or refractory ALL,” noted Anthony Stein, clinical professor, Haematology/Oncology at City of Hope, adding that “blinatumomab has the potential to significantly advance treatment options for patients living with this difficult-to-treat disease”.

In the US, it is estimated that more than 6,000 cases of ALL will be diagnosed in 2014. In adult patients with relapsed or refractory ALL, median overall survival is just three to five months, further highlighting the urgent need for new treatment options.

Read more at: http://www.pharmatimes.com/Article/14-09-22/Amgen_files_breakthrough_leukaemia_drug_in_the_US.aspx#ixzz3aL5d1ZnJ

Follow us: @PharmaTimes on Twitter

11.5.4 Ginseng fights fatigue in cancer patients, Mayo Clinic-led study finds

By Ralph Turchiano on Aug 5, 2014 •

High doses of the herb American ginseng (Panax quinquefolius) over two months reduced cancer-related fatigue in patients more effectively than a placebo, a Mayo Clinic-led study found. Sixty percent of patients studied had breast cancer. The findings are being presented at the American Society of Clinical Oncology’s annual meeting.

Researchers studied 340 patients who had completed cancer treatment or were being treated for cancer at one of 40 community medical centers. Each day, participants received a placebo or 2,000 milligrams of ginseng administered in capsules containing pure, ground American ginseng root.

“Off-the-shelf ginseng is sometimes processed using ethanol, which can give it estrogen-like properties that may be harmful to breast cancer patients,” says researcher Debra Barton, Ph.D., of the Mayo Clinic Cancer Center.

At four weeks, the pure ginseng provided only a slight improvement in fatigue symptoms. However, at eight weeks, ginseng offered cancer patients significant improvement in general exhaustion — feelings of being “pooped,” “worn out,” “fatigued,” “sluggish,” “run-down,” or “tired” — compared to the placebo group.

11.5.5 The 10-Hydroxy-2-Decenoic Acid (10-2-HDA) content in Royal Jelly, is said to possess strong inhibition of malignant cell growth, namely transferable AKR leukemia, TA3 breast malignancy

Royal Jelly - queen larvae

Royal Jelly – queen larvae

Royal Jelly – queen larvae

Royal jelly is a honey bee secretion that is used in the nutrition of larvae, as well as adult queens.[1] It is secreted from the glands in the hypopharynx of worker bees, and fed to all larvae in the colony, regardless of sex or caste.[2]

When worker bees decide to make a new queen, because the old one is either weakening or dead, they choose several small larvae and feed them with copious amounts of royal jelly in specially constructed queen cells. This type of feeding triggers the development of queen morphology, including the fully developed ovaries needed to lay eggs.[3]

Other Common Names:  Apilak, Gelée Royale, Queen Bee Jelly

Royal Jelly has been called the “Crown Jewel” of the beehive that has become extremely popular since the 1950s as a wonderful source of energy and natural way to increase stamina; perhaps that is the reason why the Queen Bee is so strong and enduring.  It is also thought to be a great nutritional source of enzymes, proteins, sugars and amino acids, but there is no scientific proof to verify the supplement’s efficacy for its use as an overall health tonic.

Royal Jelly is a thick, milky material that is secreted from the hypopharyngea- salivary glands in the heads of the young nurse bees between the sixth and twelfth days of life, and when honey and pollen are combined and refined within the nurse bee, Royal Jelly is naturally created.  While all larvæ in a colony are fed Royal Jelly, it is the only food that is fed to the Queen Bee throughout her life; other adult bees do not consume it at all.  All female eggs may produce a Queen Bee, but this occurs only when – during the whole development of the larvæ – she is cared for and fed by this material – in large quantities.

As a result of this special nutrition, the Queen develops reproductive organs (while the worker bee develops traits that relate only to work, i.e., stronger mandibles, brood food, wax glands and pollen baskets).  The Queen develops in about fifteen days, while the workers require twenty-one; and finally, the Queen endures for several years, while workers survive only a few months. “10-2 HDA,” thought to be the principle active substance in Royal Jelly, makes the Queen Bee fifty percent larger than the other female worker bees and gives her incredible stamina, ovulation ability and longevity, living four to five years longer than worker bees who only live forty or more days.  Perhaps this is the reason why so many positive qualities have been attributed to Royal Jelly as a truly rare gift of nature, but it should be noted that there is no clinical evidence to support the claims.

There is even great controversy as to the constituents included in the supplement.  Most researchers claim that it includes all the B-vitamins and vitamins A, C, D and E; some disagree.  It does contain proteins, sugars, lipids (essential fatty acids), many essential amino acids, collagen, lecithin, enzymes and minerals, in addition to the very valuable 10-2-HDA (10-Hydroxy-2-Decenoic Acid).  It is said that Royal Jelly may be most effective when combined with honey.

The 10-Hydroxy-2-Decenoic Acid (10-2-HDA) content in Royal Jelly, is said to possess strong inhibition of malignant cell growth, namely transferable AKR leukemia, TA3 breast malignancy, etc., and recent studies indicated immuno-regulation and anti-malignancy activities.  It can promote the growth of T-lymphocyte subsets, Interleukin-2 and the generation of tumor necrosis factor.  Much research is being conducted on this valuable active constituent, which has exhibited positive physiological and pharmacological effects including vasodilative and hypotensive activities, antihypercholesterolemic activity and anti-inflammatory functions.

10-2-HDA (10-Hydroxy-2-Decenoic Acid)

10-2-HDA (10-Hydroxy-2-Decenoic Acid)

11.5.6  A Microcapillary Flow Disc (MFD) Reactor for Organic Synthesis
OCT 28, 2014

A Microcapillary Flow Disc (MFD) Reactor for Organic Synthesis,
C.H. Hornung, M.R. Mackley, I.R. Baxendale and S.V. Ley and, Org. Proc. Res. Dev., 2007, 11, 399-405.

http://pubs.acs.org/doi/abs/10.1021/op700015f

This paper reports proof of concept, development, and trials for a novel plastic microcapillary flow disc (MFD) reactor. The MFD was constructed from a flexible, plastic microcapillary film (MCF), comprising parallel capillary channels with diameters in the range of 80−250 μm. MCFs were wound into spirals and heat treated to form solid discs, which were then capable of carrying out continuous flow reactions at elevated temperatures and pressures and with a controlled residence time. Three reaction schemes were conducted in the system, namely the synthesis of oxazoles, the formation of an allyl-ether, and a Diels−Alder reaction. Reaction scales of up to four kilograms per day could be achieved. The potential benefits of the MFD technology are compared against those of other reactor geometries including both conventional lab-scale and other microscale devices.

11.5.7 Pauline Lau. Biochemist, Instrumental Analysis, Molecular and Clinical Diagnostics, and Pharmaceuticals.

She was born on the China-Russian border, near the end of the rail line.  When they came to US her mother saw bagels and said, look – they have round bread.

At the meetings she always took us to the best Chinese restaurant, and said not to ask what’s in the food.  They always brought out a fish fresh from the tank and showed it to us.  When she went to Roche, where she became a legend. she got a house on the lake. They had to remove the roof to put a round banquet table in her house. At a meeting in Mexico, we saw the amazing too good to be true Monarch butterflies filling the trees.  Her photographic skills are suberb.  She’ll live to 100.

Carl Garber just retired and gave me the address.  I just found your photo calender!

Yes, I have been hiding in Taiwan for the past almost 10 years.  I moved from diagnostic to pharma and selling mostly biosimilar products to pharmaceutical emerging countries which has strong market growth comparing to US/EU.

Pauline Lau Group

Pauline Lau Group

Pauline Lau Group

Pauline Lau Group
http://www.gbimonthly.com/v9_2014/v9spreport_2014_2.html

I do not go back to US often now.  We have an office in Taipei.  Here is a recent magazine article about our company.  You will see few of my employees and I in front of our 28th floor office window.

I am rushing out for Singapore and will be meeting there for a few days.

11.5.8  Kinetic and perfusion modeling of hyperpolarized 13C pyruvate and urea in cancer with arbitrary RF flip angles

Naeim Bahrami, Christine Leon Swisher, Cornelius Von Morze, Daniel B. Vigneron, Peder E. Z. Larson
Department of Radiology and Biomedical Imaging, University of California – San Francisco, San Francisco, CA, USA
Quant Imaging MedSurg 2014; 4(1):24-32
http://dx.doi.org:/10.3978/j.issn.2223-4292.2014.02.02

Abstract: The accurate detection and characterization of cancerous tissue is still a major problem for the clinical management of individual cancer patients and for monitoring their response to therapy. MRI with hyperpolarized agents is a promising technique for cancer characterization because it can non-invasively provide a local assessment of the tissue metabolic profile. In this work, we measured the kinetics of hyperpolarized [1-13C] pyruvate and 13C-urea in prostate and liver tumor models using a compressed sensing dynamic MRSI method. A kinetic model fitting method was developed that incorporated arbitrary RF flip angle excitation and measured a pyruvate to lactate conversion rate, Kpl, of 0.050 and 0.052 (1/s) in prostate and liver tumors, respectively, which was significantly higher than Kpl in healthy tissues [Kpl =0.028 (1/s), P<0.001]. Kpl was highly correlated to the total lactate to total pyruvate signal ratio (correlation coefficient =0.95). We additionally characterized the total pyruvate and urea perfusion, as in cancerous tissue there is both existing vasculature and neovascularization as different kinds of lesions surpass the normal blood supply, including small circulation disturbance in some of the abnormal vessels. A significantly higher perfusion of pyruvate (accounting for conversion to lactate and alanine) relative to urea perfusion was seen in cancerous tissues (liver cancer and prostate cancer) compared to healthy tissues (P<0.001), presumably due to high pyruvate uptake in tumors. Keywords: Hyperpolarized carbon-13; metabolic imaging; cancer; perfusion; kinetic modeling; dynamic MRSI

Hyperpolarization is the nuclear spin polarization of a material far beyond thermal equilibrium conditions. The accurate and correct diagnosis and characterization of cancer is still a major problem for the clinical management of every kind of cancer patients, including individual prostate or liver cancer patients, and also in order to monitor their response to therapy (1-3). Magnetic resonance spectroscopic imaging (MRSI) with hyperpolarized 13C labeled substrates is a new method to study any cancers that may be able to simultaneously and noninvasively assess changes in metabolic intermediates from multiple biochemical pathways of interest. Recent studies have shown a large amount of potential applications of hyperpolarized (HP) 13C MRSI for the in vivo monitoring of cellular metabolism and the characterization of disease. The low natural abundance and sensitivity of 13C compared to protons poses a technical challenge using conventional approaches (4,5). Dynamic nuclear polarization (DNP) of 13C labeled pyruvate and subsequent rapid dissolution generates a contrast agent with a four order-of-magnitude sensitivity enhancement that is injected and gives the ability to monitor the spatial distribution of pyruvate and its conversion to lactate, alanine, and bicarbonate. The conversion of pyruvate to lactate catalyzed by the enzyme lactate dehydrogenase is of particular interest, as the kinetics of this process have been shown to be sensitive to the presence and severity of disease in preclinical models (6,7). HP MRSI can also be used to measure perfusion that in cancer can reflect spatially heterogeneous changes to existing vasculature and neovascularization as tumors surpass the normal blood supply, including microcirculatory disturbance in abnormal vessels. Tumor perfusion data in addition to the metabolic data available from spectroscopic imaging of 13C pyruvate would be of important value in exploring the complex relationship between perfusion and metabolism in cancer at both preclinical and clinical research levels (8-11). The primary purpose of this research was to study the dynamics of simultaneously injected HP [1-13C]-pyruvate and 13C-urea to provide improved characterization of cancerous tissues. To achieve rapid, 2 s temporal resolution, whole mouse MRSI we used a 18-fold accelerated compressed sensing acquisition and reconstruction with smaller flip angles for pyruvate and urea compared to lactate and alanine for efficient usage of the hyperpolarized magnetization by preserving the substrate. This flip angle scheme required using a modified kinetic model that accounts for arbitrary RF flip angles (12-15). Data was acquired in mice with prostate and liver cancer and comparisons were made to normal tissues such as kidney and healthy liver of the metabolite concentrations, including Urea, Pyruvate, and Lactate, the conversion constant (Kpl) between pyruvate to lactate, and the conversion constant (Kpa) between pyruvate to alanine. We also created novel parameterizations of the total pyruvate and urea perfusions in order to assess vascular delivery and tissue uptake. A key new feature of our modeling is the ability to detect metabolic conversion, magnetization exchange between compounds, and perfusion when using arbitrary RF flip angles for different compounds.

We observed a strong correlation between Kpl and the total lactate to total pyruvate ratio, as others have also shown. The ratio is a simpler calculation and easier to implement than the kinetic modeling. However, we have determined through simulation that the total lactate to total pyruvate ratio is highly influenced by the delivery time of pyruvate, so care should be taken when using this ratio if variable vascular delivery rates are expected. Both the kinetic modeling and metabolite ratio are highly influenced by the actual RF flip angles, and precise B1 calibration is important for quantitative measurements. Measurement of urea perfusion can be a marker vascular delivery since urea primarily stays in the vasculature. Liver is a very vascular organ and the opened capillary shape of liver vasculature likely caused high urea perfusion in liver. The kidneys are highly vascularized and are also responsible for concentrating urea for removal in the urine. In tumors, the tissue request for blood is high but in a more uncontrolled way because of the abnormality of blood vasculature and circulation inside most tumors. Thus the urea perfusion in tumors is likely more sporadic and random. Urea cannot perfuse well in some parts of tumor particularly in suspected necrotic regions. On the other hand, some parts of tumor have more metabolic activity and, therefore, these parts need more blood and more vessels, and consequently should have more urea perfusion. Our total pyruvate and urea perfusion parameterizations are different from conventional perfusion modeling, and were designed as a simple representation of the total amount of these compounds that are present in the tissue. In particular, the total pyruvate perfusion also includes any pyruvate or metabolic products that remain in the tissue, in addition to those present in the vasculature. The urea perfusion should primarily represent the vasculature delivery since it primarily stays in the vessels, while the total pyruvate perfusion can also be a marker for vascular delivery but also includes tissue uptake. We hypothesize that when the pyruvate perfusion is higher relative to urea perfusion it represents a higher amount of uptake of the pyruvate that is flowing into the tissue.

Conclusions In this study we fit metabolite T1 values, conversion rates, Kpa, and Kpl, and measured novel pyruvate and urea perfusion parameterizations across cancerous and normal tissues from data acquired with a multiband RF excitation, compressed sensing dynamic MRSI pulse sequence. Our modeling allowed for use of arbitrary RF flip angles between metabolites, which in turn allows for efficient usage of the hyperpolarized magnetization. We observed a high correlation between our Kpl fits and the total lactate to pyruvate signal ratio, suggesting either could be used to characterize pyruvate-lactate metabolism. Through the novel pyruvate and urea perfusion parameterizations we were able to quantify the increased uptake of pyruvate in cancerous tissues, which correlated with increased metabolic conversion to lactate. These provided a more complete characterization of cancerous tissue metabolism and perfusion.

11.5.9  ZSTK474

(Dr. Anthony Melvin Castro)

zstk474

zstk474

ZSTK474 is a cell permeable and reversible P13K inhibitor with an IC₅₀ at 6nm. It was identified as part of a screening library, selected for its ability to block tumor cell growth. ZSTK474 has shown strong antitumor activities against human cancer xenographs when administered orally to mice without a significant toxic effect.

Phosphatidylinositol 3-kinase (PI3K) has been implicated in a variety of diseases including cancer. A number of PI3K inhibitors have recently been developed for use in cancer therapy. ZSTK474 is a highly promising antitumor agent targeting PI3K. We previously reported that ZSTK474 showed potent inhibition against four class I PI3K isoforms but not against 140 protein kinases.

However, whether ZSTK474 inhibits DNA-dependent protein kinase (DNA-PK), which is structurally similar to PI3K, remains unknown. To investigate the inhibition of DNA-PK, we developed a new DNA-PK assay method using Kinase-Glo. The inhibition activity of ZSTK474 against DNA-PK was determined, and shown to be far weaker compared with that observed against PI3K. The inhibition selectivity of ZSTK474 for PI3K over DNA-PK was significantly higher than other PI3K inhibitors, namely NVP-BEZ235, PI-103 and LY294002.

PATENT                                                                                                          SUBMITTED GRANTED

Heterocyclic compound and antitumor agent containing the same as active ingredient [US7071189]                                                                                                                                                               2004-06-17   2006-07-04

Treatment of prostate cancer, melanoma or hepatic cancer [US2007244110]                                                                                                                                                                                                   2007-10-18

Heterocyclic compound and antitumor agent containing the same as effective ingredient [US7307077]                                                                                                                                                           2006-11-02   2007-12-11

Immunosuppressive agent and anti-tumor agent comprising heterocyclic compound as active ingredient [us7750001]                                                                                                                                   2008-05-15   2010-07-06

Pyrimidinyl and 1,3,5-triazinyl benzimidazoles and their use in cancer therapy [us2011009405]                                                                                                                                                                       2011-01-13

Substituted pyrimidines and triazines and their use in cancer therapy [us2011053907]                                                                                                                                                                                     2011-03-03

Immunosuppressive agent and anti-tumor agent comprising heterocyclic compound as active ingredient [us2010267700]                                                                                                                             2010-10-21

Amorphous body composed of heterocyclic compound, solid dispersion and pharmaceutical preparation each comprising the same, and process for production of the same [us8227463]                                                                                                                                                                                                                                                                                                                                                                                                                           2010-09-30    2012-07-24

Pyrazolo[1,5-a]pyridines and their use in cancer therapy
[us2010226881]                                                                                                                                                                                                                                                                                                 2010-09-09

Pyrimidinyl and 1,3,5-triazinyl benzimidazole sulfonamides and their use in cancer therapy [us2010249099]                                                                                                                                                   2010-09-30

11.5.10 Marrow-Infiltrating Lymphocytes Safely Shrink Multiple Myelomas

 Medical researchers at the Johns Hopkins Kimmel Cancer Center have published a report that appeared in the journal Science Translational Medicine in which they describe, for the first time, the safe use of a patient’s own immune cells to treat the white blood cell cancer multiple myeloma. There are more than 20,000 new cases of multiple myeloma and more than 10,000 deaths each year in United States. It is the second most common cancer originating in the blood.

The procedure under investigation in this study is called utilizes a specific type of tumor-targeting T cells, known as marrow-infiltrating lymphocytes (MILs). “What we learned in this small trial is that large numbers of activated MILs can selectively target and kill myeloma cells,” says Johns Hopkins immunologist Ivan Borrello, M.D., who led the clinical trial.

According to Borrello, MILs are the foot soldiers of the immune system that attack invading bacteria or viruses. Unfortunately, they are typically inactive and too few in number to have a measurable effect on cancers.

Experiments conducted is Borrello’s laboratory and in the laboratory of competing and collaborating scientists have shown that when myeloma cells are exposed to activated MILs in culture, these cells could not only selectively target the tumor cells, but they could also effectively destroy them.

To move this procedure from the laboratory into the clinic, Borrello and his collaborators enrolled 25 patients with newly diagnosed or relapsed multiple myeloma. Only 22 were able to receive this new treatment, however.

The Hopkins team extracted and purified MILs from the bone marrow of each patient and grew them in the laboratory to increase their numbers. Then they activated the MILs by exposing them to microscopic beads coated with immune activating antibodies. These antibodies bind to specific cell surface proteins on the MILs that induce profound changes in the cells. This induction step wakes the MILs up and readies them to sniff out tumor cells. These laboratory-manipulated MILs were then intravenously injected back into each patient (each of the 22 patients with their own cells). Three days before these injections of expanded MILs, all patients received high doses of chemotherapy and a stem cell transplant, which are standard treatments for multiple myeloma.

One year after receiving the MILs therapy, 13 of the 22 patients had at least a partial response to the therapy (their cancers had shrunk by at least 50 percent) Seven patients experienced at least a 90 percent reduction in tumor cell volume and lived and average of 25.1 months without cancer progression. The remaining 15 patients had an average of 11.8 progression-free months following their MIL therapy. None of the participants experienced serious side effects from the MIL therapy.

According to Borrello, several U.S. cancer centers have conducted similar experimental treatments (adoptive T cell therapy). However, only this Johns Hopkins team has used MILs. Other types of tumor-infiltrating cells can be used for such treatments, but Borrello noted that these cells are usually less plentiful in patients’ tumors and may not grow as well outside the body.

In nonblood-based tumors, such as melanoma, only about half of those patients have T cells in their tumors that can be harvested, and only about one-half of those harvested cells can be grown. “Typically, immune cells from solid tumors, called tumor-infiltrating lymphocytes, can be harvested and grown in only about 25 percent of patients who could potentially be eligible for the therapy. But in our clinical trial, we were able to harvest and grow MILs from all 22 patients,” says Kimberly Noonan, Ph.D., a research associate at the Johns Hopkins Universithttp://www.fiercevaccines.com/special-reports/gvax-pancreasy School of Medicine.

This small trial helped Noonan and her colleagues learn more about which patients may benefit from MILs therapy. As an example, they were able to determine how many of the MILs grown in the lab were specifically targeted to the patient’s tumor and whether they continued to target the tumor after being infused. They also found that patients whose bone marrow before treatment contained a high number of certain immune cells, known as central memory cells, also had better response to MILs therapy. Patients who began treatment with signs of an overactive immune response did not respond as well.

Noonan says the research team has used these data to guide two other ongoing MILs clinical trials. Those studies, she says, are trying to extend anti-tumor response and tumor specificity by combining the MILs transplant with a Johns Hopkins-developed cancer vaccine called GVAX and the myeloma druglenalidomide, which stimulates T cell responses.

These trials also have elucidated new ways to grow the MILs. “In most of these trials, you see that the more cells you get, the better response you get in patients. Learning how to improve cell growth may therefore improve the therapy,” says Noonan.

Kimmel Cancer Center scientists are also developing MILs treatments to address solid tumors such as lung, esophageal and gastric cancers, as well as the pediatric cancers neuroblastoma and Ewing’s sarcoma.

Read Full Post »

Vaccines, Small Peptides, aptamers and Immunotherapy [9]

Writer and Curator: Larry H. Bernstein, MD, FCAP

This contribution has the following structure:

9.1.1 Viruses in carcinogenesis

9.1.2   Simultaneous Humoral and Cellular Immune Response against Cancer–Testis Antigen NY-ESO-1: Definition of Human Histocompatibility Leukocyte Antigen (HLA)-A2–binding Peptide Epitopes

9.1.3 Monoclonal Antibodies in Cancer Therapy

9.1.4 Aptamers

9.1.5 Tumor Suppressors

9.1 Vaccines

9.1.1  Viruses in carcinogenesis

  • HPV-associated cervical cancer
  • HPV-associated head and neck cancer: a virus-related cancer epidemic

The contributions of hepatitis B virus and hepatitis C virus infections to cirrhosis and primary liver cancer worldwide

Risk of pancreatic cancer among individuals with hepatitis C or hepatitis B virus infection: a nationwide study in Sweden.

HIV Infection and Cancer Risk

HIV and cancer of the cervix

Anal cancer: an HIV-associated cancer

The therapeutic potential of CXCR4 antagonists in the treatment of HIV infection, cancer metastasis and rheumatoid arthritis

Types of Cancer: AIDS/HIV related malignancies

Cytokines in cancer pathogenesis and cancer therapy

Dendritic Cells as Therapeutic Vaccines against Cancer

9.1.2   Simultaneous Humoral and Cellular Immune Response against Cancer–Testis Antigen NY-ESO-1: Definition of Human Histocompatibility Leukocyte Antigen (HLA)-A2–binding Peptide Epitopes

9.1.3 Monoclonal antibodies

Monoclonal antibodies in cancer therapy

Monoclonal Antibodies in Cancer Therapy: 25 Years of Progress

9.1.4 Aptamers

Nanocarriers as an emerging platform for cancer therapy

Quantum Dot−Aptamer Conjugates for Synchronous Cancer Imaging, Therapy, and Sensing of Drug Delivery Based on Bi-Fluorescence Resonance Energy Transfer

Oligonucleotide Aptamers: New Tools for Targeted Cancer Therapy

9.1 Vaccines

9.1.1  Viruses in carcinogenesis

HPV-associated cervical cancer

http://www.cancer.net/navigating-cancer-care/prevention-and-healthy-living/hpv-and-cancer

Human papillomavirus (HPV) is a virus that is usually passed on during direct skin-to-skin contact, most commonly sex. In fact, HPV is the most common sexually transmitted disease in the United States. Most men and women are not aware they have an HPV infection because they do not develop any symptoms or health problems. Certain HPV types can cause precancerous lesions (areas of abnormal tissue) or cancer.

More than 40 of the viruses are called “genital type” HPVs. These viruses are spread from person to person when their genitals come into contact, usually during vaginal or anal sex. They can also be passed on through oral sex.

Genital HPV types can infect the genital area of women, including the vulva (outer portion of the vagina), the vagina, and the cervix (the lower, narrow part of a woman’s uterus), as well as the genital area of men, including the penis. In both men and women, genital HPV can infect the anus and some areas of the head and neck.

Nearly all cervical cancers are caused by HPV infection. Strong scientific evidence shows that a lasting HPV infection is required for cervical cancer to begin developing. Whether a woman who is infected with HPV will develop cervical cancer depends on a number of factors, including the type of HPV infection she has. Of the cervical cancers related to HPV, about 70% are caused by two strains, HPV-16 or HPV-18. In women who have HPV, smoking may increase the risk of cervical cancer.

Warts and precancerous lesions can be removed through cryotherapy (freezing); loop electrosurgical excision procedure (LEEP), which uses electric current to remove abnormal tissue; or surgery.

Receiving an HPV vaccine reduces your risk of infection. The U.S. Food and Drug Administration (FDA) approved two vaccines that help prevent HPV infection: Gardasil and Cervarix. It is important to note that the vaccines cannot cure an existing HPV infection.

Purpose of the vaccines. The goal of HPV vaccination is to prevent a lasting HPV infection after a person is exposed to the virus. Gardasil, introduced in 2006, helps prevent infection from the two HPVs known to cause most cervical cancers and precancerous lesions in the cervix. The vaccine also prevents against the two low-risk HPVs known to cause 90% of genital warts. Gardasil is approved for the prevention of cervical, vaginal, and vulvar cancers in girls and women ages nine to 26. It is also approved to prevent anal cancer in women and men and genital warts in men and boys in the same age range. Cervarix, introduced in 2009, is approved for the prevention of cervical cancer in girls and women ages 10 to 25.

Effectiveness and safety of the vaccines. Data show the HPV vaccinations are safe and highly effective in preventing a lasting infection of the HPV types they target. Because it takes many years before a precancerous lesion develops into an invasive cancer, it will likely take several more years before there is evidence that the number of cancer cases in vaccinated individuals has been reduced.

HPV-associated head and neck cancer: a virus-related cancer epidemic
Shanthi Marur, Gypsyamber D’Souza, William H Westra, Arlene A Forastiere
Lancet Oncol 2010; 11: 781–89
http://dx.doi.org:/10.1016/S1470-2045(10)70017-6

A rise in incidence of oropharyngeal squamous cell cancer—specifically of the lingual and palatine tonsils—in white men younger than age 50 years who have no history of alcohol or tobacco use has been recorded over the past decade. This malignant disease is associated with human papillomavirus (HPV) 16 infection. The biology of HPV-positive oropharyngeal cancer is distinct with P53 degradation, retinoblastoma RB pathway inactivation, and P16 upregulation. By contrast, tobacco-related oropharyngeal cancer is characterized by TP53 mutation and downregulation of CDKN2A (encoding P16). The best method to detect virus in tumor is controversial, and both in-situ hybridization and PCR are commonly used; P16 immunohistochemistry could serve as a potential surrogate marker. HPV-positive oropharyngeal cancer seems to be more responsive to chemotherapy and radiation than HPV-negative disease. HPV 16 is a prognostic marker for enhanced overall and disease-free survival, but its use as a predictive marker has not yet been proven. Many questions about the natural history of oral HPV infection remain under investigation. For example, why does the increase in HPV-related oropharyngeal cancer dominate in men? What is the potential of HPV vaccines for primary prevention? Could an accurate method to detect HPV in tumor be developed? Which treatment strategies reduce toxic effects without compromising survival? Our aim with this review is to highlight current understanding of the epidemiology, biology, detection, and management of HPV-related oropharyngeal head and neck squamous cell carcinoma, and to describe unresolved issues.

Cancers of the head and neck arise from mucosa lining the oral cavity, oropharynx, hypopharynx, larynx, sinonasal tract, and nasophaynx. By far the most common histological type is squamous cell carcinoma, and grade can vary from well-differentiated keratinizing to undifferentiated non-keratinizing. An increase in incidence of oropharyngeal squamous cell carcinoma—specifically in the tonsil and tongue base—has been seen in the USA, most notably in individuals aged 40–55 years. Patients with oropharyngeal cancer are mainly white men. Unlike most tobacco-related head and neck tumors, patients with oropharyngeal carcinoma usually do not have a history of tobacco or alcohol use. Instead, their tumors are positive for oncogenic forms of the human papillomavirus (HPV), particularly 16 type. About 60% of oropharyngeal squamous cell cancers in the USA are positive for HPV 16. HPV-associated head and neck squamous cell carcinoma seems to be a distinct clinical entity, and this malignant disease has a better prognosis than HPV-negative tumors, due in part to increased sensitivity of cancers to chemotherapy and radiation therapy. Although HPV is now recognized as a causative agent for a subset of oropharyngeal squamous cell carcinomas, the biology and natural history of oropharyngeal HPV infection and the best clinical management of patients with HPV-related head and neck squamous cell tumors is not well understood.

Head and neck cancer is the sixth most common cancer worldwide, with an estimated annual burden of 563 826 incident cases (including 274 850 oral cavity cancers, 159 363 laryngeal cancers, and 52 100 oropharyngeal cancers) and 301 408 deaths.1 Although HPV has been long known to be an important cause of anogenital cancer, only in recent times has it been recognized as a cause of a subset of head and neck squamous cell carcinomas.2 More than 100 different types of HPV exist,3 and at least 15 types are thought to have oncogenic potential.4 However, most (>90%) HPV-associated head and neck squamous cell cancers are caused by one virus type, HPV 16, the same type that leads to HPV-associated anogenital cancers. The proportion of head and neck squamous cell carcinomas caused by HPV varies widely (figure 1),5–16 largely because of the burden of tobacco-associated disease in this population of tumors. Tobacco, alcohol, poor oral hygiene, and genetics remain important risk factors for head and neck tumors overall, but HPV is now recognized as one of the primary causes of oropharyngeal squamous cell cancers. In the USA, about 40–80% of oropharyngeal cancers are caused by HPV, whereas in Europe the proportion varies from around 90% in Sweden to less than 20% in communities with the highest rates of tobacco use (figure 1).

The incidence of head and neck cancers overall in the USA has fallen in recent years, consistent with the decrease in tobacco use in this region. By contrast, incidence of HPV-associated oropharyngeal cancer seems to be rising, highlighting the increasing importance of this causal association.17–19 In a US study in which data of the Surveillance, Epidemiology, and End Results (SEER) program were used, incidence of oropharyngeal tumors (which are most likely to be HPV-associated) rose by 1·3% for base of tongue cancers and by 0·6% for tonsillar cancers every year between 1973 and 2004. By contrast, incidence of oral cavity cancers (not associated with HPV) declined by 1·9% every year during the same period.17 The age-adjusted incidence of tonsillar cancer increased 3·5-fold in women and 2·6-fold in men between 1970 and 2002.24 Augmented incidence of HPV-associated oropharyngeal cancers represents an emerging viral epidemic of cancer.

Why is increased incidence of HPV-associated oropharyngeal cancer most pronounced in young individuals? This effect could be attributable to changes in sexual norms (i.e., more oral sex partners or oral sex at an earlier age in recent than past generations) combined with fewer tobacco-associated cancers in young cohorts, making the outcomes of HPV-positive cancers more visible. Can the higher rates of HPV-associated oropharyngeal cancers in men compared with women be accounted for solely by differences in sexual behavior, or are biological differences in viral clearance present that could contribute to the higher burden of these cancers in men? HPV prevalence in cervical rather than penile tissue might boost the chances of HPV infection when performing oral sex on a woman, contributing to the higher rate of HPV-associated oropharyngeal cancer in men.

Tobacco use has fallen in past decades, and the corresponding rise in proportion of head and neck cancers that are oropharyngeal in origin has been striking, both in the USA and internationally. SEER data suggest that about 18% of all head and neck carcinomas in the USA were located in the oropharynx in 1973, compared with 31% of such squamous cell tumors in 2004.19 Similarly, in Sweden, the proportion of oropharyngeal cancers caused by HPV has steadily increased, from 23% in the 1970s to 57% in the 1990s, and as high as 93% in 2007.13,25 These data indicate that HPV is now the primary cause of tonsillar malignant disease in North America and Europe.

Findings of initial studies suggest that oral HPV frequency increases with age. Prevalent oral HPV infection is detected in 3–5% of adolescents26–28 and 5–10% of adults.14,29 We do not yet know whether the natural history of oral HPV or risk factors for persistent HPV infection in the oropharynx differ from those known for anogenital HPV infection (table 1). Data suggest oral HPV prevalence is amplified with number of sexual partners and is more typical in men, in HIV-infected individuals, and in current tobacco users.26–28,30,31

In view of the importance of tobacco use in head and neck squamous cell carcinoma, most cases of this malignant disease seen in non-smokers are unsurprisingly HPV-related. However, oral HPV infection is common in smokers and non-smokers and is an important cause of oropharyngeal cancer in both groups. For example, in case series, only 13–16% of individuals with HPV-positive head and neck squamous cell cancer did not smoke or drink alcohol.32,33 Although a higher proportion of individuals with HPV-positive compared with HPV-negative tumors are non-smokers or neither smoke nor drink alcohol, many with HPV-positive disease have a history of alcohol and tobacco use. In fact, 10–30% of HPV-positive head and neck squamous cell carcinomas were recorded in heavy tobacco and alcohol users.32,33 This finding underscores that HPV-associated malignant disease not only arises in people who do not smoke or drink alcohol but also occurs in people with the traditional risk factors of tobacco and alcohol use.

HPV detection may ultimately serve a more comprehensive role than mere prognostication. Detection of HPV is emerging as a valid biomarker for discerning the presence and progress of disease encompassing all aspects of patients’ care, from early cancer detection,41 to more accurate tumor staging (e.g., localization of tumor origin),42,43 to selection of patients most likely to benefit from specific treatments,44 to post-treatment tumor surveillance.45,46 Consequently, there is a pressing need for a method of HPV detection that is highly accurate, reproducible from one diagnostic laboratory to the next, and practical for universal application in the clinical arena. Despite growing calls for routine HPV testing of all oropharyngeal carcinomas, the best method for HPV detection is not established. Various techniques are currently in use, ranging from consensus and type-specific PCR methods, real-time PCR assays to quantify viral load, type-specific DNA in-situ hybridization, detection of serum antibodies directed against HPV epitopes, and immunohistochemical detection of surrogate biomarkers (e.g., P16 protein). Although PCR-based detection of HPV E6 oncogene expression in frozen tissue samples is generally regarded as the gold standard for establishing the presence of HPV, selection of assays for clinical use will ultimately be influenced by concerns relating to sensitivity, specificity, reproducibility, cost, and feasibility. Development of non-fluorescent chromogens has enabled visualization of DNA hybridization by conventional light microscope; furthermore, adaptation of in-situ hybridization to formalin-fixed and paraffin-embedded tissues has made this technique compatible with standard tissue-processing procedures and amenable to retrospective analysis of archival tissue blocks. Most PCR-based methods, on the other hand, need a high level of technical skill and are best used with fresh-frozen samples.

Limitations of any one detection assay can be offset by algorithms that combine the strengths of complementary assays.50 A highly feasible strategy incorporates P16 immunohistochemistry and HPV in-situ hybridization. In view of sensitivity that approaches 100%, P16 immunostaining is a good first-line assay for elimination of HPV-negative cases from any additional analysis. Since specificity is almost 100%, a finding positive for HPV 16 on in-situ hybridization reduces the number of false-positive cases by P16 staining alone. A P16-positive, HPV 16-negative result singles out a subset of tumors that qualifies for rigorous analysis for other (i.e., non-HPV 16) oncogenic virus types.

HPV in-situ hybridisation and P16 immunostaining as a practical diagnostic approach to discernment of HPV status can be applied readily to cytological preparations, including fi ne-needle aspirates from patients with cervical lymph-node metastases.41,52 Further expansion of HPV testing to blood and other body fl uids would advance the role of HPV as a clinically relevant biomarker, but these specimens would need other detection platforms. PCR-based detection of HPV DNA in blood (53) and saliva (54) of patients after treatment of their HPV-positive cancers suggests a future role in tumour surveillance. Detection of serum antibodies to HPV-related epitopes can predict the HPV status of head and neck cancers, and this method has been advocated as a way to project clinical outcomes and guide treatment without the constraints of tissue acquisition.53,55

The increasing prevalence of oropharyngeal cancer in young populations and substantially amplified survival rates with current treatment approaches stands in contrast to survival achieved in older individuals with comorbid disorders associated with tobacco and alcohol history. Several characteristics of patients with head and neck cancer have been linked with favorable prognosis, including non-smoker, minimum exposure to alcohol, good performance status, and no comorbid disorders, all of which are related to HPV-positive tumor status. Findings of retrospective analyses suggest that individuals with HPV-positive oropharyngeal cancer have higher response rates to chemotherapy and radiation and increased survival62–65 compared with those with HPV-negative tumors. Augmented sensitivity to chemotherapy and radiotherapy has been attributed to absence of exposure to tobacco and presence of functional unmutated TP53.63,64,66 Increased survival of patients with HPV-positive cancer is also possibly attributable in part to absence of field cancerization related to tobacco and alcohol exposure.67

Survival outcomes for individuals with HPV 16-positive and P16-positive oropharyngeal tumors were similar. Failure data indicated significantly diminished rates of locoregional failure and second primary tumour in patients with HPV-positive oropharyngeal cancer compared with those with HPV-negative tumors; distant metastases did not differ between the two groups. When survival was assessed after adjustment for tobacco exposure, in individuals who smoked, those with HPV-positive oropharyngeal tumors and fewer than 20 pack-years had 2-year overall survival of 95%, compared with 80% in those with HPV-positive cancers and 20 pack-years or more, and 63% in HPV-negative cancers and 20 pack-years or more. By comparison with people with HPV-positive oropharyngeal tumors who smoked and had fewer than 20 pack-years, the hazard of death was raised for those with HPV-negative tumors and 20 pack-years or more (hazard ratio 4·33) and those with HPV-positive cancers and 20 pack-years or more (1·79). These data indicate clearly that tobacco exposure alters the biology of HPV-positive oropharyngeal tumors and is an important prognostic factor.

An association between HPV-positive, P16-positive oropharyngeal tumors and survival outcomes was reported in another retrospective analysis of a large phase 3 trial of chemoradiation, which included more than 800 patients enrolled from international sites.72 This substudy analysis looked at 195 available tumor samples in patients with an oropharyngeal primary cancer, of which 28% were HPV-positive and 58% were P16-positive. Individuals with HPV-positive cancers had 2-year overall survival of 94% and 2-year failure-free survival of 86% compared with 77% (p=0·007) and 75% (p=0·035), respectively, in those with HPV-negative tumors. When co-expression of HPV and P16 was correlated with survival outcomes, individuals with HPV-positive, P16-positive tumors had 2-year overall survival of 95% compared with 88% in those with HPV-negative, P16-positive cancers and 71% (p=0·003) in those with HPV-negative, P16-negative tumors. Similar results were noted for 2-year failure-free survival (89%, 86%, and 69%, respectively; p=0·002) and time to locoregional failure (93%, 95%, and 84%, respectively; p=0·051). By multivariable analysis, HPV 16 and P16 were identified as independent prognostic factors.

ECOG proposes induction chemotherapy with a triple drug regimen to reduce tumor burden to subclinical disease (clinical complete response at primary site) followed by lower dose radiation (total dose 54 Gy) and concurrent cetuximab. Overall survival and progression-free survival outcomes will be assessed and compared with results of the 2008 ECOG study.70 The main aim of this planned study is to assess potential for a lower dose of radiation to control disease and to investigate toxic effects and quality-of-life variables.

In summary, tumor HPV status is a prognostic factor for overall survival and progression-free survival and might also be a predictive marker of response to treatment. The method of in-situ hybridization provides a feasible approach for implementation in most diagnostic pathology laboratories, and immunohistochemical staining for P16 could be useful as a surrogate marker for HPV status. Seemingly, locoregional recurrence—but not the rate of distant disease—is diminished in patients with HPV-positive tumors. Smoking and tobacco exposure might modify survival and recurrence of HPV-positive tumors and should be considered in future trials for risk stratification of patients with HPV-positive malignant disease.

HCV and cancer

The contributions of hepatitis B virus and hepatitis C virus infections to cirrhosis and primary liver cancer worldwide
Joseph F. Perz, Armstrong GL, Farrington LA,  Hutin YJF, Bell BP
J Hepatol 2006; 45:529-538
http://dx.doi.org:/10.1016/j.jhep.2006.05.013

End-stage liver disease accounts for one in forty deaths worldwide. Chronic infections with hepatitis B virus (HBV) and hepatitis C virus (HCV) are well-recognized risk factors for cirrhosis and liver cancer, but estimates of their contributions to worldwide disease burden have been lacking. Methods: The prevalence of serologic markers of HBV and HCV infections among patients diagnosed with cirrhosis or hepatocellular carcinoma (HCC) was obtained from representative samples of published reports. Attributable fractions of cirrhosis and HCC due to these infections were estimated for 11 WHO-based regions. Results: Globally, 57% of cirrhosis was attributable to either HBV (30%) or HCV (27%) and 78% of HCC was attributable to HBV (53%) or HCV (25%). Regionally, these infections usually accounted for >50% of HCC and cirrhosis. Applied to 2002 worldwide mortality estimates, these fractions represent 929,000 deaths due to chronic HBV and HCV infections, including 446,000 cirrhosis deaths (HBV: n = 235,000; HCV: n = 211,000) and 483,000 liver cancer deaths (HBV: n = 328,000; HCV: n = 155,000). Conclusions: HBV and HCV infections account for the majority of cirrhosis and primary liver cancer throughout most of the world, highlighting the need for programs to prevent new infections and provide medical management and treatment for those already infected.

Among primary liver cancers occurring worldwide, hepatocellular carcinoma (HCC) represents the major histologic type and likely accounts for 70% to 85% of cases [2]. Cirrhosis precedes most cases of HCC, and may exert a promotional effect via hepatocyte regeneration [3,4]. Compared with other causes of cirrhosis, chronic infection with hepatitis B virus (HBV) or hepatitis C virus (HCV) is associated with a higher risk of developing HCC [3,5]. Alcohol abuse represents a leading cause of cirrhosis and is also a major contributor. dietary aflatoxin exposure in parts of Africa and Asia has been associated with primary liver cancer, especially in hosts with chronic HBV infection [8].

An understanding of the relative contribution of various etiologies to disease burden is important for setting public health priorities and guiding prevention programs [10,11]. The World Health Organization’s Global Burden of Disease (GBD) 2000 project aims to quantify the burden of premature morbidity and mortality from over 130 major causes [1,12]. Liver cancer and cirrhosis are included in the analysis, but with the exception of alcohol, the etiologies underlying these diseases have not been well accounted for [1,11,13]. In particular, HBV and HCV infections have been poorly characterized in previous WHO estimates since these were based primarily on the acute effects of infection and omitted the associated burdens of chronic liver disease [10,11].

The attributable fraction represents the proportion of disease occurrence that potentially would be prevented by eliminating a given risk factor. For cirrhosis, a systematic analysis of attributable fractions has been lacking altogether. For HCC, previous estimates of the attributable fractions due to HBV and HCV are available but are not comprehensive and do not correspond to the regional designations and related conventions of the current GBD project [14].

The prevalence of HBV and HCV infection among cirrhosis and HCC patients varied considerably within and between regions (Tables 2 and 3). These variations tended to reflect known patterns of HBV and HCV infection endemicity [99,100]. For example, in countries where HCV infection has long been endemic, such as Japan and Egypt, there were high prevalences of HCV infection among cirrhosis and HCC patients. The same held true for China and most of the African nations in our sample regarding HBV infection. Areas such as these, where HBV infection predominated, appeared to have a younger population of HCC cases, which is thought to reflect the preponderance of infections acquired early in life (e.g., perinatal HBV transmission) [8]. Patterns of HBV and HCV co-infection were also notable.

When we applied the HBV- and HCV-attributable fractions we derived to 2002 worldwide mortality estimates [1], we found that approximately 929,000 deaths from cirrhosis (n = 446,000) and primary liver cancer (n = 483,000) were likely due to chronic viral hepatitis infections. HBV infection accounted for 563,000 deaths (235,000 from cirrhosis and 328,000 from liver cancer) and HCV infection accounted for 366,000 deaths (211,000 from cirrhosis and 155,000 from liver cancer).

We showed that chronic viral hepatitis infections likely account for the majority of both cirrhosis and HCC globally and in nearly all regions of the world. One of the strengths of our analysis was that it employed simple and transparent methods. Our estimates of attributable fractions were derived from reviews of published studies reporting the prevalence of HBV and HCV infections in patients with cirrhosis or HCC in all regions of the world. Alternate approaches rely on estimates of the prevalence of risk factors and corresponding relative risks in the source populations. However, errors associated with extrapolating exposure or hazard from one population to another are a major source of uncertainty in efforts to characterize international health risks [12]. Given the lack of representative data regarding HBV and HCV infection prevalences worldwide along with uncertainties in deriving region specific risk estimates, we believe ours is the preferred approach.

Our findings help illustrate the great need for programs aimed at preventing HBV or HCV transmission. In 1992, WHO recommended that all countries include hepatitis B vaccine in their routine infant immunization programs. As of 2003, WHO/UNICEF estimated 42% hepatitis B vaccination coverage among the global birth cohort [106]. Therefore, implementation of this strategy, which represents the most effective way of preventing chronic HBV infection and related end stage liver disease, is far from complete [107,108]. Other key primary prevention strategies include screening blood donors and maintaining infection control practices to prevent the transmission of healthcare-related HBV and HCV infections [105,109,110]. In countries where these activities have not been fully implemented, they should be given a high priority. In most developed countries, injection drug use and high-risk sexual behaviors represent the major risk factors for HCV infection and HBV infection, respectively, indicating the importance of related prevention efforts (e.g., reducing the numbers of new initiates to injection drug use).

The role of programs to identify, counsel, and provide medical management for the many persons already infected with HBV or HCV requires careful consideration [105,110]. Counseling that includes advice regarding avoidance of alcohol and education regarding modes of transmission can help reduce the risks for developing chronic disease or spreading infection to susceptible persons. The widespread application of therapeutic interventions also has the potential to accelerate the declines in end-stage liver disease that will eventually follow from hepatitis B vaccination and other primary prevention efforts [104,107]. Recent advances have occurred in the therapeutic management of chronic hepatitis B and chronic hepatitis C, but treatments are long and involve substantial costs and side effects [111–113]. Countries will need to consider the potential benefits of treatment while insuring that scarce healthcare resources are allocated in a manner that does not undermine primary prevention efforts [114].

Risk of pancreatic cancer among individuals with hepatitis C or hepatitis B virus infection: a nationwide study in Sweden.

Huang J1, Magnusson M, Törner A, Ye W, Duberg AS.
Br J Cancer. 2013 Nov 26; 109(11):2917-23.
http://dx.doi.org:/10.1038/bjc.2013.689

A few studies indicated that hepatitis C and hepatitis B virus (HCV/HBV) might be associated with pancreatic cancer risk. The aim of this nationwide cohort study was to examine this possible association. Methods: Hepatitis C virus-
and hepatitis B virus-infected individuals were identified from the national surveillance database from 1990 to 2006, and followed to the end of 2008. The pancreatic cancer risk in the study population was compared with the general population by calculation of Standardized Incidence Ratios (SIRs), and with a matched reference population using a Cox proportional hazards regression model to calculate hazard ratios (HRs). Results: In total 340 819 person-years in the HCV cohort and 102 295 in the HBV cohort were accumulated, with 34 and 5 pancreatic cancers identified, respectively. The SIRHCV was 2.1 (95% confidence interval, CI: 1.4, 2.9) and the SIRHBV was 1.4 (0.5, 3.3). In the Cox model analysis, the HR for HCV infection was 1.9 (95% CI: 1.3, 2.7), diminishing to 1.6 (1.04, 2.4) after adjustment for potential confounders.
Conclusion: Our results indicated that HCV infection might be associated with an increased risk of pancreatic cancer but further studies are needed to verify such association. The results in the HBV cohort indicated an excess risk, however, without statistical significance due to lack of power.

Pancreatic cancer is one of the most rapidly fatal malignancies with a 5-year survival rate below 5%. The long-term survival is poor also for early diagnosed patients treated with resection surgery (Jemal et al, 2010). In Europe, it was estimated in a prediction model that in the year 2012 there would be 75 000–80 000 deaths from pancreatic cancer, which is the fourth most common cause of cancer-associated death for both men and women (Malvezzi et al, 2012). The incidence of pancreatic cancer is higher in the Nordic countries and Central Europe than in other parts of the world (Bosetti et al, 2012).

Tobacco smoking is a well-established risk factor for pancreatic cancer (Iodice et al, 2008), and a similar magnitude of excess risk as smoking was found among the users of Scandinavian snus (moist snuff) (Boffettaet al, 2005; Luo et al, 2007). Besides, accumulating evidence consistently shows that old age, male sex, diabetes mellitus, hereditary pancreatitis, chronic pancreatitis and family history are positively associated with this carcinoma (Pandol et al, 2012). Albeit the biological mechanism is unclear, recent epidemiological studies indicated that some infections, such as exposure to Helicobacter pylori (Trikudanathan et al, 2011), poor oral health (Michaud et al, 2007), hepatitis C virus (HCV) (Hassan et al, 2008; El-Serag et al, 2009) or hepatitis B virus (HBV) (Hassan et al, 2008; Iloeje et al, 2010; Wang et al, 2012a, 2012b) might be associated with pancreatic cancer risk.

Globally, ∼170 million people are chronically infected with HCV (World Health Organization, 1997) and an estimated 350 million with HBV (Custer et al, 2004). The prevalence rates of HCV and HBV infection vary widely in the world, and Sweden is a low endemic country with an estimated 0.5% of the population infected with HCV (Duberg et al, 2008a) and even lower rate for HBV infection. Both chronic HCV and HBV infections are main causes of hepatocellular carcinoma (HCC). Previous findings demonstrated that HBV may replicate within the pancreas (Shimoda et al, 1981; Yoshimura et al, 1981) and that HCV could be associated with pancreatitis (Alvares-Da-Silva et al, 2000; Torbenson et al, 2007). Some studies support that HCV and HBV may have a role in the development of pancreatic cancer, but the evidence is far from conclusive (Hassan et al, 2008; El-Serag et al, 2009; Iloeje et al, 2010; Wang et al, 2012a, 2012b), and more studies are needed. Towards this end, we utilised Swedish population-based nationwide registers, with documentation of all diagnosed HCV- and HBV-infected individuals in Sweden, to explore the association of HCV or HBV infection and the risk of pancreatic cancer.

Baseline characteristics of the HCV and HBV cohorts are presented in Table 1. In the HCV and chronic HBV cohorts the mean follow-up time were 9.1 and 9.4 years, with a total of 360 154 and 107 986 person-years at risk, respectively. There was a clear male dominance in the HCV cohort, and median age at entry into the HCV or HBV cohorts (notification date) was 38 and 31 years, respectively. A marked difference between cohorts was observed regarding the aspect of country of origin; HCV-infected individuals were more likely from Nordic countries, but persons with chronic HBV infection were often immigrants from non-Nordic countries.

Hepatitis C virus cohort

In the HCV cohort, there were 34 pancreatic cancer cases observed during 340 819 person-years of follow-up (first 6 months of follow-up excluded), whereas 16.5 were expected, yielding a statistically significant increased risk of pancreatic cancer (SIR: 2.1; 95% CI: 1.4, 2.9). The SIR did not alter substantially across sex or estimated duration of HCV infection (Table 2). The majority of cases were among the patients who were born before 1960.

From the Cox regression model, an ∼90% excessive risk for pancreatic cancer (HR 1.9; 95% CI: 1.3, 2.7) was observed after adjustment for age, sex and county of residence, which is similar to the result from the SIR analysis. This excess risk diminished somewhat but remained statistically significant after further adjustment for potential confounders (HR 1.6; 95% CI: 1.04, 2.4). The results did not vary markedly when stratified by sex (Table 3). In the additional analyses, excluding all individuals ever hospitalized with acute and/or chronic pancreatitis, the results did not alter notably (data not shown).

In the HCV cohort, the Standardized Incidence Ratio (SIR) for lung cancer was 2.3 (95% CI: 1.9, 2.7) and the Hazard Ratio (HR) for lung cancer was 2.2 (95% CI: 1.8, 2.7), decreasing to 1.6 (95% CI: 1.3, 2.1) after adjustment for the potential confounders used in the pancreatic cancer analyses.

Chronic HBV cohort

A total of five pancreatic cancer cases were found during 102 295 person-years of follow-up (first 6 months excluded), whereas 3.5 were expected. Compared with the age- and sex-matched Swedish general population, a 40% excess risk of pancreatic cancer was found in the chronic HBV cohort (SIR: 1.4; 95% CI: 0.5, 3.3), but without statistical significance. Because of the small number of pancreatic cancer cases, there was not enough power for additional stratified analyses (Table 4).

The Cox regression model revealed similar results as the SIR analysis. The point estimates were somewhat higher (HR=2.0 from the model adjusted for only matching factors and HR=1.8 from the fully adjusted model), but still statistically non-significant (Table 5). The SIR for lung cancer in the chronic HBV infection cohort was 1.7 (95% CI: 1.1, 2.5).

This population-based large cohort study revealed a doubled risk of pancreatic cancer among HCV-infected patients compared with the Swedish general population. The excess risk was persistent across strata by sex or duration of infection. Although further adjustment for potential confounders, i.e., chronic obstructive pulmonary disease (related to smoking), diabetes mellitus, chronic pancreatitis and alcohol-related disease, resulted in an attenuated relative risk, this finding still supports the hypothesis that HCV infection might be associated with an increased risk of pancreatic cancer. Besides, the result indicated a moderate excessive risk of pancreatic cancer among HBV-infected patients according to different statistical approaches, but the size of the study cohort and the observed number of cancers were too small to draw a sound conclusion. Pancreatic cancer is more common in older age groups, and the small number of pancreatic cancers among the HBV cohort was probably an effect of the relatively young cohort, concordant with the epidemiology of chronic hepatitis B in Sweden.

The strengths of this register-based study include population-based cohort design, relatively large sample size, independently collected data on documentation of HCV/HBV notifications and pancreatic cancer occurrence and high completeness of follow-up.

The parallel (laboratory and clinician) notification system of HCV/HBV infections in Sweden has a high coverage of those with a diagnosed infection; it is estimated that about 75–80% of HCV infections are diagnosed, but there still remain unknown infections, not yet diagnosed or documented. In addition, a small portion of the reported patients could have a resolved infection, spontaneously or by treatment, this could (probably insignificant) lower the risk in the HCV and HBV cohort.

The number of unidentified HCV/HBV-coinfected individuals is probably low in the studied cohorts. However, in the HCV cohort there could be some patients who were never diagnosed with hepatitis B but have serologic markers of a past HBV infection. In these patients we cannot exclude the possibility of occult hepatitis B.

The biological mechanism of the association between HCV and pancreatic cancer is unclear. However, virtually, the pancreas and liver share the common blood vessels and ducts, and prior evidence demonstrated that the pancreas is a remote location for hepatitis virus inhabitation and replication (Hassan et al, 2008). HCV infection is associated with type 2 diabetes, which is both a risk factor and might be a consequence of pancreatic cancer (Mehta et al, 2000; Sangiorgio et al, 2000). Besides, previous studies reported that subclinical/acute pancreatitis (Katakura et al, 2005) and hyperlipasemia (Yoffe et al, 2003) may be extrahepatic manifestations of HCV infection. In addition, pancreatic involvement was observed among patients who suffered from chronic hepatitis infection, resulting in mild pancreatic damage accompanied with increased serum levels of pancreatic enzyme (Taranto et al, 1989; Katakura et al, 2005). Immune response may lead to chronic inflammation in the targeted organs after long time persistent infection with HCV. Therefore, hepatitis C virus conceivably serves as a biological agent that may indirectly have a role in inflammation-associated pancreatic carcinogenesis. Although still unclear to what extent chronic inflammation contributes to pancreatic cancer development, it is postulated that HCV can induce inflammatory microenvironment with high concentration of growth factors and cytokines. This may exert effects by accumulating alterations in driver genes and promoting cancer cell growth and proliferation.

HIV AIDS and Cancer

http://www.cancer.gov/cancertopics/causes-prevention/risk/infectious-agents/hiv-fact-sheet

Key Points

  • People infected with human immunodeficiency virus (HIV) have a higher risk of some types of cancer than uninfected people.
  • A weakened immune system caused by infection with HIV, infection with other viruses, and traditional risk factors such as smoking all contribute to this higher cancer risk.
  • Highly active antiretroviral therapy and lifestyle changes may reduce the risk of some types of cancer in people infected with HIV.
  • The National Cancer Institute (NCI) conducts and supports a number of research programs aimed at understanding, preventing, and treating HIV infection, acquired immunodeficiency syndrome-related cancers, and cancer-associated viral diseases.
  1. Do people infected with human immunodeficiency virus (HIV) have an increased risk of cancer?

Yes. People infected with HIV have a substantially higher risk of some types of cancer compared with uninfected people of the same age (1). Three of these cancers are known as “acquired immunodeficiency syndrome (AIDS)-defining cancers” or “AIDS-defining malignancies”: Kaposi sarcoma, non-Hodgkin lymphoma, and cervical cancer. A diagnosis of any one of these cancers marks the point at which HIV infection has progressed to AIDS.

People infected with HIV are several thousand times more likely than uninfected people to be diagnosed with Kaposi sarcoma, at least 70 times more likely to be diagnosed with non-Hodgkin lymphoma, and, among women, at least 5 times more likely to be diagnosed with cervical cancer (1).

In addition, people infected with HIV are at higher risk of several other types of cancer (1). These other malignancies include anal, liver, and lung cancer, and Hodgkin lymphoma.

People infected with HIV are at least 25 times more likely to be diagnosed with anal cancer than uninfected people, 5 times as likely to be diagnosed with liver cancer, 3 times as likely to be diagnosed with lung cancer, and at least 10 times more likely to be diagnosed with Hodgkin lymphoma (1).

People infected with HIV do not have increased risks of breast, colorectal, prostate, or many other common types of cancer (1). Screening for these cancers in HIV-infected people should follow current guidelines for the general population

HIV and cancer of the cervix

Z.M. Chirenje
bestpracticeobgyn April 2005; 19(2):269–276
http://dx.doi.org/10.1016/j.bpobgyn.2004.10.002

Cancer of the cervix is the second most common cause of cancer-related death in women worldwide, and in some low resource countries accounts for the highest cancer mortality in women. The highest burden of the HIV/AIDS epidemic is currently in sub-Saharan Africa, where more than half of the people infected are women who have no access to cervical cancer screening. The association between HIV and invasive cervical cancer is complex, with several studies now clearly demonstrating an increased risk of pre-invasive cervical lesions among HIV-infected women. However, there have not been significantly higher incidence rates of invasive cervical cancer associated with the HIV epidemic. The highest numbers of HIV-infected women are in poorly-resourced countries, where the natural progression of HIV disease in the absence of highly active antiretroviral treatment sometimes results in deaths from opportunistic infections before the onset of invasive cervical cancer. This chapter will discuss the association of HIV and cervical intraepithelial neoplasia, the treatment of pre-invasive lesions, and invasive cervical cancer in HIV-infected women. The role of screening and the impact of antiretroviral treatment on the progression of pre-invasive and invasive cancer will also be discussed.

Anal cancer: an HIV-associated cancer

Klencke BJ, Palefsky JM
Hematology/oncology Clinics of North America [2003, 17(3):859-872]
http://dx.doi.org:/1016/S0889-8588(03)00039-X

Although not yet included in the Centers for Disease Control definition of AIDS, anal cancer clearly occurs more commonly in HIV-infected patients. An effective screening program for those groups who are at highest risk might be expected to impact rates of anal cancer just as significantly as did cervical Pap screening programs for the incidence of cervical cancer. Despite a relatively low rate of progression from AIN to invasive cancer, the scope of the problem is enormous based on the prevalence of anal HPV infection and the size of the HIV-infected, at-risk population. Thus, the potential benefits of screening, detection, and the development of more effective therapy also are enormous. Currently, therapeutic HPV vaccines for AIN represent an exciting avenue of research in HPV-related anogenital disease. Invasive anal cancer and HSIL (which is believed to be the precursor lesion) are expected to become increasingly important health problems for both HIV-infected men and women as their life expectancy lengthens. Although HAART may have improved the ability of many to tolerate CMT, it appears that toxicity of this therapy continues to be a problem for a proportion of HIV-infected subjects. The acute side effects present specific challenges to the clinician and patient, have an immediate impact on the patient’s plan of care and dose intensity of the treatment, and ultimately may impact the outcome of the planned treatment. Late toxicity may influence the long-term quality of life. Small patient numbers, variable radiation therapy doses, limited information about viral load, and a potential confounding effect of higher CD4+ levels make it difficult to draw any conclusions about the effect of HAART on anal cancer outcome. Large, prospective studies will be required before solid conclusions about the impact of various factors on anal cancer prognosis and outcome can be drawn.

The therapeutic potential of CXCR4 antagonists in the treatment of HIV infection, cancer metastasis and rheumatoid arthritis

Hirokazu Tamamura, and Nobutaka Fujii
Exp Opin on Ther Targets Dec 2005; 9(6): 1267-1282 http://dx.doi.org:/10.1517/14728222.9.6.1267

CXCR4 is the receptor of the chemokine CXCL12, which is involved in progression and metastasis of several types of cancer cells, HIV infection and rheumatoid arthritis. The authors developed selective CXCR4 antagonists, T22 and T140, initially as anti-HIV agents, which inhibit T cell line-tropic (X4-) HIV-1 infection through their specific binding to CXCR4. Recently, T140 analogues have also been shown to inhibit CXCL12-induced migration of breast cancer cells, leukaemia T cells, pancreatic cancer cells, small cell lung cancer cells, chronic lymphocytic leukaemia B cells, pre-B acute lymphoblastic leukaemia cells and so on in vitro. Biostable T140 analogues significantly suppressed pulmonary metastasis of breast cancer cells and melanoma cells in mice. Furthermore, these compounds significantly suppressed the delayed-type hypersensitivity response induced by sheep red blood cells and collagen-induced arthritis, which represent in vivo mouse models of arthritis. Thus, T140 analogues proved to be attractive lead compounds for chemotherapy of these problematic diseases. This article reviews recent research on T140 analogues, referring to several other CXCR4 antagonists.

Types of Cancer: AIDS/HIV related malignancies

http://cancer.northwestern.edu/cancertypes/cancer_type.cfm?category=1

People with HIV/AIDS are at high risk for developing certain cancers, such as Kaposi’s sarcoma, non-Hodgkin lymphoma, and cervical cancer. For people with HIV, these three cancers are often called “AIDS-defining conditions,” meaning that if a person with HIV has one of these cancers it can signify the development of AIDS. The connection between HIV/AIDS and certain cancers is not completely understood, but the link likely depends on a weakened immune system. Most types of cancer begin when normal cells begin to change and grow uncontrollably, forming a mass called a tumor. A tumor can be benign (noncancerous) or malignant (cancerous, meaning it can spread to other parts of the body). The types of cancer most common for people with HIV/AIDS are described in more detail below.

Kaposi’s sarcoma

Kaposi’s sarcoma is a type of skin cancer, which has traditionally occurred in older men of Jewish or Mediterranean descent, young men in Africa, or people who have received organ transplantation. Today, Kaposi’s sarcoma is found most often in homosexual men with HIV/AIDS and related to an infection with the human herpesvirus 8 (HHV-8). Kaposi’s sarcoma in people with HIV is often called epidemic Kaposi’s sarcoma. HIV/AIDS-related Kaposi’s sarcoma causes lesions to arise in multiple sites in the body, including the skin, lymph nodes, and organs such as the liver, spleen, lungs, and digestive tract.

Non-Hodgkin lymphoma

HIV/AIDS-related NHL is the second most common cancer associated with HIV/AIDS, after Kaposi’s sarcoma. There are many different subtypes of NHL. The most common subtypes of NHL in people with HIV/AIDS are primary central nervous system lymphoma (affecting the brain and spinal fluid), found in 20% of all NHL cases in people with HIV/AIDS, primary effusion lymphoma (causing fluid to accumulate around the lungs or in the abdomen), or intermediate and high-grade lymphoma. More than 80% of lymphomas in people with HIV/AIDS are high-grade B-cell lymphoma, while 10% to 15% of lymphomas among people with cancer who do not have HIV/AIDS are of this type. It is estimated that between 4% and 10% of people with HIV/AIDS develop NHL.

Other types of cancer

Other, less common types of cancer that may develop in people with HIV/AIDS are Hodgkin’s lymphoma, angiosarcoma (a type of cancer that begins in the lining of the blood vessels), anal cancer, liver cancer, mouth cancer, throat cancer, lung cancer, testicular cancer, colorectal cancer, and multiple types of skin cancer including basal cell carcinoma, squamous cell carcinoma, and melanoma.

Treatment options for the most common treatments for HIV/AIDS-related cancers are listed by the specific type of cancer. Treatment options and recommendations depend on several factors, including the type and stage of cancer, possible side effects, and the patient’s preferences and overall health.

Palliative care can help a person at any stage of illness. People often receive treatment for the cancer and treatment to ease side effects at the same time. In fact, patients who receive both often have less severe symptoms, better quality of life, and report they are more satisfied with treatment.

Palliative treatments vary widely and often include medication, nutritional changes, relaxation techniques, and other therapies. You may also receive palliative treatments similar to those meant to eliminate the cancer, such as chemotherapy, surgery, and radiation therapy.

It is extremely important that all patients with HIV/AIDS and an associated cancer receive treatment with highly active antiretroviral treatment (HAART) both during the cancer treatments and afterwards. HAART can effectively control the virus in most patients. Better control of the HIV infection decreases the side effects of many of the treatments, may decrease the chance of a recurrence, and can improve a patient’s chance of recovery from the cancer.

The treatment of HIV/AIDS-related Kaposi sarcoma usually cannot cure the cancer, but it can help relieve pain or other symptoms. This can be followed by palliative care for Kaposi sarcoma. Antiviral treatment for HIV/AIDS helps reduce a person’s chance of getting Kaposi sarcoma and can reduce the severity of Kaposi sarcoma. HAART helps treat the tumor and reduce the symptoms associated with Kaposi sarcoma for people with HIV/AIDS. It is usually used before other treatments, such as chemotherapy.

Curettage and electrodesiccation. In this procedure, the cancer is removed with a curette, a sharp, spoon-shaped instrument. The area can then be treated with electrodesiccation, which uses an electric current to control bleeding and kill any remaining cancer cells. Many patients have a flat, pale scar from this procedure.

Cryosurgery. Cryosurgery, also called cryotherapy or cryoablation, uses liquid nitrogen to freeze and kill cells. The skin will later blister and shed off. This procedure will sometimes leave a pale scar. More than one freezing may be needed.

In photodynamic therapy, a light-sensitive substance is injected into the lesion that stays longer in cancer cells than in normal cells. A laser is directed at the lesion to destroy the cancer cells.

Radiation therapy is the use of high-energy x-rays or other particles to destroy cancer cells. A doctor who specializes in giving radiation therapy to treat cancer is called a radiation oncologist. The most common type of radiation treatment is called external-beam radiation therapy, which is radiation given from a machine outside the body. When radiation therapy is given using implants, it is called internal radiation therapy or brachytherapy. External-beam radiation therapy may be given as a palliative treatment. A radiation therapy regimen (schedule) usually consists of a specific number of treatments given over a set period of time.

Side effects from radiation therapy may include fatigue, mild skin reactions, upset stomach, and loose bowel movements. Most side effects go away soon after treatment is finished. Learn more about radiation therapy.

Chemotherapy may help control advanced disease, although curing HIV/AIDS-related Kaposi sarcoma with chemotherapy is extremely rare. Usually, for HIV/AIDS-related Kaposi sarcoma, chemotherapy is used to help relieve symptoms and to lengthen a patient’s life. Common drugs for Kaposi sarcoma include: liposomal doxorubicin (Doxil), paclitaxel (Taxol, LEP-ETU, Abraxane), and vinorelbine (Navelbine, Alocrest).

The side effects of chemotherapy depend on the individual and the dose used, but they can include fatigue, risk of infection, nausea and vomiting, hair loss, loss of appetite, and diarrhea. These side effects usually go away once treatment is finished.

HIV/AIDS-related Kaposi sarcoma may receive alpha-interferon (Roferon-A, Intron A, Alferon), which appears to work by changing the surface proteins of cancer cells and by slowing their growth. Immunotherapy is generally used for people who are in the good-risk category in the immune system (I) factor of the TIS staging system (see Stages). The most common side effects of alpha-interferon are low levels of white blood cells and flu-like symptoms.

The main treatments for HIV/AIDS-related non-Hodgkin lymphoma are chemotherapy, targeted therapy, and radiation therapy.

Treatments for women with the precancerous condition called CIN (see   Overview) are generally not as effective for women with HIV/AIDS because of a weakened immune system. Often, the standard treatment for HIV/AIDS can lower the symptoms of CIN.

Women with invasive cervical cancer and HIV/AIDS that is well-controlled with medication, generally receive the same treatments as women who do not have HIV/AIDS. Common treatment options include surgery, radiation therapy, and chemotherapy.

Cytokines in cancer pathogenesis and cancer therapy

Glenn Dranoff
Nature Reviews Cancer Jan 2004; 4(11-22) http://dx.doi.org:/10.1038/nrc1252

The mixture of cytokines that is produced in the tumor microenvironment has an important role in cancer pathogenesis. Cytokines that are released in response to infection, inflammation and immunity can function to inhibit tumor development and progression. Alternatively, cancer cells can respond to host-derived cytokines that promote growth, attenuate apoptosis and facilitate invasion and metastasis. A more detailed understanding of cytokine–tumor-cell interactions provides new opportunities for improving cancer immunotherapy.

Dendritic Cells as Therapeutic Vaccines against Cancer
Jacques Banchereau and A. Karolina Palucka
Nature Reviews Immunology APR 2005; 5:296-306
http://cnc.cj.uc.pt/BEB/private/pdfs/2007-2008/Immunology/E/Rev_paper_E4.pdf

Mouse studies have shown that the immune system can reject tumours, and the identification of tumor antigens that can be recognized by human T cells has facilitated the development of immunotherapy protocols. Vaccines against cancer aim to induce tumor-specific effector T cells that can reduce the tumor mass, as well as tumor-specific memory T cells that can control tumor relapse. Owing to their capacity to regulate T-cell immunity, dendritic cells are increasingly used as adjuvants for vaccination, and the immunogenicity of antigens delivered by dendritic cells has now been shown in patients with cancer. A better understanding of how dendritic cells regulate immune responses will allow us to better exploit these cells to induce effective anti-tumor immunity.

Vaccines against infectious agents are one success of immunology and have spared countless individuals from diseases such as polio, measles, hepatitis B and tetanus8 . However, progress in the development of vaccines against infectious agents has been largely empirical and not always successful, as many infectious diseases still evade the immune system, particularly chronic infections such as tuberculosis, malaria and HIV infection. Further progress will be made through rational design based on our increased understanding of how the immune system works and how the induction of protective immunity is regulated. The same principle applies to vaccines against cancer, particularly as cancer is a chronic disease, and when it becomes clinically visible, tumor cells and their products have already been interacting with and affecting host cells for a considerable time to ensure the survival of the tumor. Ex vivo-generated, antigen-loaded DCs have now been used as vaccines to improve immunity9 . Numerous studies in mice have shown that DCs loaded with tumor antigens can induce therapeutic and protective antitumor immunity10. The immunogenicity of antigens delivered by DCs has been shown in patients with cancer9 or chronic HIV infection11, thereby providing proof of principle that using DCs as vaccines can work. Despite this, the efficacy of therapeutic vaccination against cancer has recently been questioned12 because of the undeniably limited rate of objective tumor regressions that has been observed in clinical studies so far. However, the question is not whether DC vaccines work but how to orient further studies to refine the immunological and clinical parameters of vaccination with DCs to improve its efficacy.

Vaccines against cancer Early studies in mice showed that the immune system can recognize and reject tumours13 and that immunodeficient mice (lacking interferon-γ (IFN-γ) and recombination-activating gene 2) have an increased incidence of cancer14 (BOX 1). In humans, the incidence of some cancers is increased in immunodeficient patients15 and is increased with age, owing to Immunosenescence16. These observations support the scientific rationale for immunotherapy for cancer. The term immunotherapy refers to any approach that seeks to mobilize or manipulate the immune system of a patient for therapeutic benefit17. In this regard, there are numerous strategies for improving the resistance of a patient to cancer. These include non-specific activation of the immune system with microbial components or cytokines, antigen-specific adoptive immunotherapy with antibodies and/or T cells, and antigen-specific active immunotherapy (that is, vaccination). The main limitation of using antibodies is that target proteins need to be expressed at the cell surface. By contrast, targets for T cells are usually peptides derived from intracellular proteins, which are presented at the cell surface in complexes with MHC molecules18. The identification of defined tumor antigens in humans19,20 prompted the development of adoptive T-cell therapy. Yet, the most attractive strategy is vaccination, which is expected to induce both therapeutic T-cell immunity (in the form of tumor-specific effector T cells) and protective T-cell immunity (in the form of tumor-specific memory T cells that can control tumor relapse)21–23. Numerous approaches for the therapeutic vaccination of individuals who have cancer have been developed, including the use of the following: autologous and allogeneic tumor cells (which are often modified to express various cytokines), peptides, proteins and DNA vaccines9,23–26. The observed results are variable; however, in many cases, a tumour-specific immune response has been induced, and tumor regressions, albeit limited, have occurred. These approaches rely on random encounter of the vaccine with host DCs. A lack of encounter of the vaccine antigen with DCs might result in the absence of an immune response. Alternatively, an inappropriate encounter — for example, with unactivated DCs or with the ‘wrong’ subset of DCs — might lead to silencing of the immune response27. Both of these situations could explain some of the shortcomings of current cancer vaccines. Furthermore, we do not know how tumor antigens need to be delivered to DCs in vivo to elicit an appropriate immune response.

Immature and mature dendritic cells have different functions. A | Immature dendritic cells (DCs) induce tolerance. Tissue DCs constantly sample their environment, capture antigens and migrate in small numbers to draining lymph nodes. In the absence of inflammation, the DCs remain in an immature state, and antigens are presented to T cells in the lymph node without costimulation, leading to either the deletion of T cells or the generation of inducible regulatory T cells. B | Mature DCs induce immunity. Tissue inflammation induces the maturation of DCs and the migration of large numbers of mature DCs to draining lymph nodes. The mature DCs express peptide–MHC complexes at the cell surface, as well as appropriate co-stimulatory molecules. This allows the priming of CD4+ T helper cells and CD8+ cytotoxic T lymphocytes (CTLs), the activation of B cells and the initiation of an adaptive immune response. To control the immune response, CD4+CD25+ regulatory T (TReg)-cell populations are also expanded. [ADCC, antibody-dependent  cell-mediated cytotoxicity; NK, natural killer; TCR, T-cell receptor].

Box 1 |

Mice

  • The immune system can reject tumors
  • Immune-mediated rejection of chemically induced tumours13
  • Increased cancer incidence in immunodeficient mice14

Humans

  • Increased cancer incidence in immunodeficient patients15
  • Increased cancer incidence with age (immunosenescence)16
  • Cancer regression in patients with paraneoplastic neurological disorders that are mediated by onconeuronal antibodies and specific CD8+ T cells136

Dendritic cells DC subsets. There are thought to be two main pathways of differentiation into DCs2,31 (FIG. 2). The myeloid pathway generates two subsets: Langerhans cells, which are found in stratified epithelia such as the skin; and interstitial DCs, which are found in all other tissues32. The lymphoid pathway generates plasmacytoid DCs (pDCs), which secrete large amounts of type I IFNs (IFN-α and IFN-β) after viral infection33,34. DCs and their precursors show remarkable functional plasticity. For example, pDCs form one of the first barriers to the expansion of intruding viruses, thereby functioning, through the release of type I IFNs, as part of the innate immune response. Subsequently, these cells differentiate into DCs that can present antigens to T cells, thereby functioning as members of the adaptive immune system35,36. Monocytes can differentiate into either macrophages, which function as scavengers, or DCs that induce specific immune responses37,38. Different cytokines skew the in vitro differentiation of monocytes into DCs with different phenotypes and functions (FIG. 3). So, after activation (for example, by granulocyte/ macrophage colony-stimulating factor, GM-CSF), monocytes that encounter interleukin-4 (IL-4) become DCs known as IL-4-DCs29,30,39. By contrast, after encounter with IFN-α, tumour-necrosis factor (TNF) or IL-15, activated monocytes differentiate into IFN-α-DCs40–43, TNF-DCs44 or IL-15-DCs45, respectively. Whether, in vivo, all interstitial DCs are derived from monocytes remains to be established, but myeloid DCs that are isolated from human peripheral blood also give rise to different DC types after exposure to different cytokines. Each of these DC subsets has both common and unique biological functions, which are determined by a unique combination of cell-surface molecule expression and cytokine secretion. For example, whereas IL-4-DCs are a homologous population of immature cells that is devoid of Langerhans cells, TNFDCs are heterogeneous and include both CD1a+ Langerhans cells and CD14+ interstitial DCs44.In vitro experiments showed that Langerhans cells and interstitial DCs that were generated from cultures of CD34+ hematopoietic progenitors differ in their capacity to activate lymphocytes: interstitial DCs induce the differentiation of naive B cells into immunoglobulin-secreting plasma cells4,32, whereas Langerhans cells seem to be particularly efficient activators of cytotoxic CD8+ T cells. They also differ in their cytokine-secretion pattern (only interstitial DCs produce IL-10) and their enzymatic activity4,32, which might be fundamental for the selection of peptides that are presented to T cells. Indeed, different enzymes are likely to degrade a given antigen into different sets of peptides, as has recently been shown for the HIV protein Nef 46. This then leads to different sets of peptide–MHC complexes being presented and thereby to distinct repertoires of antigen-specific T cells. So, these unique DCs are likely to yield unique immune effectors, thereby allowing the broad immune response that is required to combat permanently evolving microorganisms and tumors.

Distinct DC subsets induce distinct types of immune response. DCs have a crucial role in determining the type of response that is induced. There is evidence that either polarized DCs or distinct DC subsets might provide T cells with different signals that determine the class of immune response31. So, in mice, splenic CD8α+ DCs prime naive CD4+ T cells to produce TH1 cytokines in a process that involves IL-12, whereas splenic CD8α– DCs prime naive CD4+ T cells to produce TH2 cytokines47,48. Furthermore, this polarization into different T-cell subsets also depends on the signal received by a DC, as shown by the induction of IL-12 production and polarization towards TH1 cells when DCs are activated with Escherichia coli lipopolysaccharide (LPS), but the absence of IL-12 production and polarization towards TH2 cells when the same type of DC is exposed to LPS from Porphyromonas gingivalis 49. In humans, CD40 ligand (CD40L)-activated monocyte-derived DCs prime TH1-cell responses through an IL-12-dependent mechanism, whereas pDCs activated with IL-3 and CD40L have been shown to secrete negligible amounts of IL-12 and to prime TH2-cell responses50. So, both the type of DC subset and the activation signals to which DCs are exposed are important for polarization of T cells.

Mouse proof-of-principle in vivo studies

  • Ex vivo-generated, antigen-loaded dendritic cells (DCs) induce antigen-specific T-cell immunity137
  • Ex vivo gene-loaded DCs can induce humoral immunity138
  • Ex vivo-generated, antigen-loaded DCs induce tumor-specific immunity139,140
  • Ex vivo-generated DCs are superior to other types of vaccine141
  • Ex vivo-generated immature DCs induce tolerance142
  • Combination therapy with ex vivo-generated DCs improves vaccine efficacy112,113

This is an important parameter in vaccination against cancer, as type 1 immunity (including IFN-γ secretion) is desirable, whereas type 2 immunity (including IL-4 or IL-10 secretion) is considered deleterious. DCs and immune tolerance. DCs can induce and maintain immune tolerance27, both central and peripheral.

Central Tolerance depends on mature thymic DCs, which are essential for the deletion of newly generated T cells that have a receptor that recognizes self-components51. However, central tolerance might not be effective for all antigens. Furthermore, many self-antigens might not have access to the thymus, and others are only expressed later in life. So, there is a requirement for Peripheral Tolerance, which occurs in lymphoid organs and is mediated by immature DCs (FIG. 1a). Immature DCs present tissue antigens to T cells in the absence of appropriate co-stimulation, leading to T-cell Anergy or deletion27 or to the development of IL-10-secreting Inducible Regulatory T Cells52,53. The research groups of Nussenzweig and Steinman54 have elegantly shown that fusion proteins targeted to immature DCs lead to the induction of antigen-specific tolerance. By contrast, concomitant activation of these DCs with CD40- specific antibody results in a potent immune response, because the DCs are induced to express a large number of co-stimulatory molecules55. However, mature DCs might also contribute to peripheral tolerance by promoting the clonal expansion of naturally occurring CD4+CD25+ REGULATORY T (TReg) CELLS56, as discussed later. Therefore, the biology of DCs offers several targets for the control of cellular immunity. The parameters that need to be considered include DC-related factors, host-related factors and combining DC vaccines with other therapies.

Subsets of human dendritic cells. (Fig not shown). The population of dendritic cells (DCs) in the peripheral blood, which can be mobilized by treatment with FLT3L (fms-related tyrosine kinase 3 ligand), contains both CD11c+ myeloid DCs and CD11c– plasmacytoid DCs. So far, most studies of DCs have been carried out with DCs generated by culturing monocytes with granulocyte/macrophage colony-stimulating factor (GM-CSF) and interleukin-4 (IL-4); this simple procedure yields a homogenous population of DCs that resemble interstitial DCs, and the population is devoid of Langerhans cells. These DCs are immature and require exogenous factors for maturation. DCs can also be generated by culturing CD34+ haematopoietic progenitor cells (HPCs) or peripheral-blood monocytes with GM-CSF and tumour-necrosis factor (TNF). In this way, two DC subsets can be obtained: Langerhans cells, which might have improved efficacy for eliciting cytotoxic T lymphocytes; and interstitial DCs, which resemble monocyte-derived DCs. Adding IL-4 to CD34+ HPC cultures in the presence of GM-CSF and TNF inhibits the differentiation of Langerhans cells. [Green boxes indicate cell types that can be induced by culture with GM-CSF and TNF. Yellow boxes indicate cell types that can be induced by culture or mobilization with FLT3L].

Plasticity of monocyte-derived dendritic cells. (Fig not shown). Activated monocytes can differentiate into different types of dendritic cell (DC) after encounter with different cytokines. These distinct DCs will influence the differentiation of lymphocytes into immune effectors with different functions, leading to varied immune responses. For example, interleukin-15-DCs (IL-15- DCs) are remarkably more efficient at priming and maturation of rare antigen-specific cytotoxic T lymphocytes (CTLs) than are IL-4-DCs. Thymic stromal lymphopoietin-DCs (TSLP-DCs) induce CD4+ T cells to differentiate into pro-inflammatory T helper 2 (TH2) cells, which secrete large amounts of IL-13 and tumor-necrosis factor (TNF)143, whereas interferon-α-DCs (IFN-α-DCs) induce CD4+ T cells to differentiate into TH1 cells, which secrete IFN-γ and IL-10. The properties and function of TNF-DCs remain to be determined. [FLT3L, fms-related tyrosine kinase 3 ligand; GM-CSF, granulocyte/macrophage colony-stimulating factor].

Antigen loading. Loading MHC class I and class II molecules at the cell surface of DCs with peptides derived from defined antigens is the most commonly used strategy for DC-based vaccination22,87. Although this technique is important for proof-of-principle studies, the use of peptides has limitations: the restriction of a peptide to a given HLA type; the limited number of well-characterized Tumor-Associated Antigens; the relatively rapid turnover of exogenous peptide– MHC complexes, resulting in comparatively low antigen presentation by the time that the DC arrives in the draining lymph node after injection; and the induction of a restricted repertoire of T-cell clones, thereby limiting the ability of the immune system to control tumor-antigen variation. Yet another level of complexity is brought about by the use of MODIFIED HETEROCLITIC PEPTIDES. Some synthetic peptides, even those derived from immune-dominant antigens, do not bind MHC class I molecules with high affinity, possibly explaining their limited immunogenicity in vivo88. Therefore, the generation of peptide analogues with increased affinity for MHC class I molecules (known as heteroclitic peptides) could be used to improve peptide immunogenicity89,90. However, recent elegant studies in patients with malignant melanoma show that T cells elicited in vivo by vaccination with heteroclitic MART1 (melanoma antigen recognized by autologous T cells) or glycoprotein 100 (gp100) peptide show poor recognition of the endogenous melanoma-derived peptide and less efficient tumor-cell lysis compared with T cells specific for the native peptide91.

Immunoregulatory mechanisms

Naturally occurring CD4+CD25+ regulatory T cells

Cell-mediated suppression independent of interleukin-10 (IL-10) and/or transforming growth factor-β (TGF-β);
clonal expansion is regulated by mature dendritic cells (DCs)

Inducible regulatory T cells

Cytokine-mediated suppression through IL-10 and/or TGF-β; induction and clonal expansion is regulated by immature DCs

Natural killer T cells

Cytokine-mediated suppression through IL-13

Vaccine-induced B cells?

Cytokine-mediated regulation through IL-4, IL-6 and IL-10; competition with DCs for antigen uptake

Tumor-specific interferon-γ-secreting T cells?

Immunoediting and selection of escape variants (not discussed in main text)

Immune correlates of efficacy of dendritic-cell-based vaccines

  • Induction of broad tumour-specific T-cell immunity: T cells specific for several tumour antigens
  • Induction of effector T cells: T cells with immediate capacity to recognize tumour antigens and secrete cytokines such as tumour-necrosis factor and interferon-γ
  • Induction of memory T cells: T cells that secrete interleukin-2 and proliferate on re-exposure to tumour antigen
  • Induction of T cells that kill tumour cells
  • Decreased number of T cells with regulatory function

DCs are an attractive target for therapeutic manipulation of the immune system to increase otherwise insufficient immune responses to tumour antigens. However, the complexity of the DC system requires rational manipulation of DCs to achieve protective or therapeutic immunity. So, further research is needed to analyse the immune responses induced in patients by distinct ex vivo-generated DC subsets that are activated through different pathways. The ultimate ex vivo-generated DC vaccine will be heterogeneous and composed of several subsets, each of which will target a specific immune effector. These ex vivo strategies should help to identify the parameters for in vivo targeting of DCs, which is the next step in the development of DC-based vaccination. Indeed, distinct DC subsets express unique cell-surface molecules, such as different lectins131: Langerhans cells express langerin, which is crucial for the formation of Birbeck granules132,133; interstitial DCs express DCSIGN (dendritic-cell-specific intercellular-adhesionmolecule-3-grabbing non-integrin), which is involved in interactions with T cells and in DC migration but is also used by pathogens (such as HIV) to hijack the immune system; and pDCs express yet another lectin, BDCA2 (blood DC antigen 2)134,135. Such differential expression of cell-surface molecules might allow specific in vivo targeting of DC subsets for induction of the desired type of immune response.

9.1.2   Simultaneous Humoral and Cellular Immune Response against Cancer–Testis Antigen NY-ESO-1: Definition of Human Histocompatibility Leukocyte Antigen (HLA)-A2–binding Peptide Epitopes

Elke Jäger, Yao-Tseng Chen, Jan W. Drijfhout, Julia Karbach, et al.
J Exp Med. 1998 Jan 19; 187(2): 265–270.
A growing number of human tumor antigens have been described that can be recognized by cytotoxic T lymphocytes (CTLs) in a major histocompatibility complex (MHC) class I–restricted fashion. Serological screening of cDNA expression libraries, SEREX, has recently been shown to provide another route for defining immunogenic human tumor antigens. The detection of antibody responses against known CTL-defined tumor antigens, e.g., MAGE-1 and tyrosinase, raised the question whether antibody and CTL responses against a defined tumor antigen can occur simultaneously in a single patient. In this paper, we report on a melanoma patient with a high-titer antibody response against the “cancer–testis” antigen NY-ESO-1. Concurrently, a strong MHC class I–restricted CTL reactivity against the autologous NY-ESO-1–positive tumor cell line was found. A stable CTL line (NW38-IVS-1) was established from this patient that reacted with autologous melanoma cells and with allogeneic human histocompatibility leukocyte antigen (HLA)-A2−, NY-ESO-1–positive, but not NY-ESO-1–negative, melanoma cells. Screening of NY-ESO-1 transfectants with NW38-IVS-1 revealed NY-ESO-1 as the relevant CTL target presented by HLA-A2. Computer calculation identified 26 peptides with HLA-A2–binding motifs encoded by NY-ESO-1. Of these, three peptides were efficiently recognized by NW38-IVS-1. Thus, we show that antigen-specific humoral and cellular immune responses against human tumor antigens may occur simultaneously. In addition, our analysis provides a general strategy for identifying the CTL-recognizing peptides of tumor antigens initially defined by autologous antibody.

There is growing evidence for humoral and cellular immune recognition of cancer by the autologous human host (1–6). Based on CTL-dependent lysis of cultured melanoma cell lines, several categories of autoimmunogenic tumor antigens have been characterized, including differentiation antigens of specific cell lineages (7–9), individual antigens caused by point mutations (10, 11), and tumor antigens, such as MAGE, which are expressed in a variable proportion of different tumor types, but are silent in most normal tissues except the testis (12). CTL responses against melanoma antigens induced by peptide vaccines in vivo have been associated with a favorable development of advanced melanoma in some patients (6, 13). As immunoselection of antigen-negative tumor cell variants has been observed during peptide vaccination (14), the molecular characterization of additional CTL-defined tumor antigens is needed to develop polyvalent vaccines with broader immunotherapeutic effects.

Sahin et al. have recently introduced a powerful new methodology for identifying human tumor antigens eliciting humoral immune response (5). The method has been called SEREX, for serological expression cloning of recombinant cDNA libraries of human tumors. Novel and previously defined tumor antigens have been identified by the SEREX method, including MAGE-1 and tyrosinase, both originally identified by cloning the epitopes recognized by CTLs. Thus, antibody screening of cDNA libraries prepared from human tumors can be used to identify antigens eliciting a cellular immune response, including CTLs, circumventing the need for established cultured autologous cell lines and stable CTL lines.

We have recently identified a novel human tumor antigen by SEREX analysis of a human esophageal cancer (15). The antigen, NY-ESO-1, belongs to a growing number of human tumor antigens we have called “cancer–testis” antigens that include MAGE, GAGE, BAGE (1), and SSX2 (HOM-MEL-40) (5, 16). These antigens have the following characteristics: (a) they are expressed in a variable portion of a wide range of cancers, (b) their normal tissue expression is generally restricted to the testis, and (c) they are generally coded for by genes on the X chromosome. In a recent survey of sera from normal individuals and cancer patients, antibodies against NY-ESO-1 were found in ∼10% of patients with melanoma, ovarian cancer, and other cancers, but not in normal individuals (Stockert, E., manuscript in preparation). One patient with a high NY-ESO-1 antibody response was found to have specific CTL reactivity against cultured autologous melanoma cells. In the present study, we report that NY-ESO-1 encodes the CTL target in this patient and identify the NY-ESO-1 peptides that are recognized.

High-titer Antibody Reactivity against NY-ESO-1.

Melanoma patient NW38 presented with extensive metastases to inguinal lymph nodes having large areas of necrosis. Reverse transcriptase PCR of tumor RNA showed that this tumor expressed NY-ESO-1. Based on the hypothesis that exposure of the immune system to large amounts of intracellular tumor proteins released from the necrotic tumor might elicit a strong humoral immune response, the serum of patient NW38 was tested for specific reactivity against recombinant NY-ESO-1 protein. Fig. ​Fig.11 shows the reactivity of NW38 serum with the recombinant NY-ESO-1 protein, with a lysate of NY-ESO-1–transfected COS-7 cells, and with a lysate of the autologous NY-ESO-1 messenger RNA–positive tumor cell line NW-MEL-38. A 22-kD protein species was identified in both cell lysates, and comigrated with the purified recombinant NY-ESO-1 protein. The identity of this protein species as NY-ESO-1 was further confirmed by using an anti–NY-ESO-1 mouse monoclonal antibody. Reactivity against recombinant NY-ESO-1 protein was still detectable at a serum dilution of 1:100,000. No reactivity was detected against a lysate of untransfected COS-7 cells.
The correlation between NY-ESO-1 expression and NW38-IVS-1 reactivity suggested NY-ESO-1 as the antigenic target. To prove this, COS-7 cells were transfected with NY-ESO-1 cDNA and different MHC class I molecules and used as targets for NW38-IVS-1. Reactivity was measured in a standard TNF-α release assay. TNF release was found after stimulation of NW38-IVS-1 with COS-7 cells cotransfected with HLA-A2− and NY-ESO-1 cDNA. No reactivity was detected after stimulation with cotransfectants of pcDNA3.1(−)-NY-ESO-1− and pcDNA1Amp-HLA-A1 cDNA, COS-7 cells transfected with pcDNA3.1(−), or untransfected COS-7 cells (Fig. ​(Fig.3).3).

Peptide-specific CTLs.

26 different peptides encoded by NY-ESO-1 with theoretical binding motifs to the HLA-A2.1 molecule were tested for specific recognition by NW38-IVS-1. The target cells were peptide-pulsed T2 cells. Of these 26 peptides, three were recognized by NW38-IVS-1 as determined by a standard51Cr–release assay (Table ​(Table1).1). The peptide sequences SLLMWITQCFL, SLLMWITQC, and QLSLLMWIT are located between positions 155 and 167 of the NY-ESO-1 protein (15), and show overlapping sequences. The 11-mer SLLMWITQCFL (2 in Table ​Table1)1) and the 9-mer SLLMWITQC (12 in Table ​Table1)1) consist of identical amino acids at positions 1–9.

To provide additional confirmation of the peptide specificity, the 26 synthetic peptides were individually incubated with HLA-A2–transfected COS-7 cells and tested in the TNF release assay. Consistent with the results of 51Cr–release assay, specific TNF-α release was detected in tests with peptides SLLMWITQCFL, SLLMWITQC, and QLSLLMWIT. NY-ESO-1/HLA-A2 transfectants were used as a positive control in these assays (Fig. ​(Fig.4).4).

The search for tumor antigens that induce specific immune responses in cancer patients is the ongoing challenge in tumor immunology. Evidence for a specific humoral response to human cancer came from serological analysis of cell surface reactivity of sera from cancer patients for autologous cancer cells, an approach called autologous typing (4). However, with only a few exceptions, this approach did not allow for the structural definition of the antigenic target. An autologous typing system also provided the first evidence for the development of CTLs with specificity for human melanoma cells (3, 17, 21–24). Using specific antitumor CTLs as probes, a number of CTL targets have been cloned on the basis of MHC class I–restricted recognition (1, 6). However, this approach involves cultured cancer cell lines and stable CTL lines from the same patient, two requirements that cannot easily be met with many tumor types. With the demonstration that genes coding for CTL-recognized tumor antigens elicit humoral immunity and can be cloned by SEREX methodology, a technically less demanding approach defining immunogenic tumor antigens is now available, one that extends the range of analysis to tumor types that are not easily adaptable to in vitro growth and are not sensitive targets for CTLs. A number of novel tumor antigens have been defined by SEREX, including two new members of the cancer–testis antigenic family, SSX2 (HOM-MEL-40) (5, 16), and NY-ESO-1 (15).

In this study, we identified a melanoma patient, NW38, with high-titered antibody against NY-ESO-1. This patient had a large and highly necrotic tumor, and the sustained release of intracellular antigens that are usually inaccessible to the immune system may account for the high NY-ESO-1 titer. The establishment of an autologous cell line that typed NY-ESO-1 positive provided target cells for assessing CTL reactivity in this patient. A CTL line was established from this patient that lysed the autologous melanoma cell line in an HLA-A2–restricted fashion. Using target cells transfected with NY-ESO-1 and HLA-A2, the specificity of CTL reactivity was found to be coded by NY-ESO-1. Computer analysis of the NY-ESO-1 sequence identified 26 peptides with HLA-A2–binding motifs. Screening of these peptides presented by T2 cells identified three sequences that were confirmed to be specifically recognized by NW38-IVS-1. This is the first conclusive demonstration of simultaneous antibody and CTL responses against a cancer–testis antigen in a single patient.

The strategy used in this study to generate and analyze CTL reactivity to a SEREX-defined antigen can be used as a model for investigating cellular immune responses to the growing list of other SEREX antigens. Identification of clones in SEREX requires high-titered IgG antibody, and the development of such antibodies requires the help of CD4+ T cells. In this sense, SEREX can be thought of as a method to define the CD4+ T cell repertoire to human tumor antigens. Also, the presence of both NY-ESO-1 antibody and CTLs in patient NW38 suggests that screening for an antibody response may be a simple and effective way to identify patients with concomitant CTL reactivity, and this possibility is now being tested in other patients with NY-ESO-1 antibody. In the absence of autologous tumor cell lines, CD8+ T cells can be stimulated with autologous antigen-presenting cells that have been transfected with the coding gene or fed purified protein antigens. A similar strategy can be used to identify peptide targets for CD4+ T cells.

A major objective in defining immunogenic human tumor targets is to explore their use in the development of cancer vaccines, and a number of clinical trials with various vaccine constructs are currently underway. Although tumor regression is the desired goal of a therapeutic vaccine, this end point cannot be expected to be an effective way to develop maximally immunogenic tumor vaccines. For this purpose, reliable immunological assays are needed to monitor the specificity and strength of specific immune reactions generated by the vaccine. With the exception of vaccines aimed at inducing a humoral immune response such as GM2 ganglioside vaccines, most vaccine trials are designed to stimulate cellular immunity, particularly the development of CTLs and CD4+ T cells. These have been difficult to detect in vaccine trials with MAGE peptides (25), and difficult to interpret in trials with vaccines containing melanocyte differentiation antigens, since CTLs against these antigens can be generated in vitro from nonvaccinated melanoma patients as well as normal individuals (26, 27). However, de novo induction and increase of preexisting CTL reactivity have been detected after vaccination with melanocyte differentiation antigens and observed to be associated with cancer regressions in a limited number of patients (13). The demonstration of a simultaneous antibody and CTL response to NY-ESO-1 in the same patient suggests that serological methods may be useful in monitoring vaccine trials with NY-ESO-1 and other tumor antigens eliciting a humoral immune response.

9.1.3 Monoclonal Antibodies in Cancer Therapy

R K Oldham
JCO September 1983; 1(9): 582-590
http://jco.ascopubs.org/content/1/9/582.short


The need for improved specificity in cancer therapy is apparent. With the advent of monoclonal antibodies, the possibility of specifically targeted therapy is being considered. Early trials of monoclonal antibody in experimental animals and humans have indicated its ability to traffic to specific tumor sites and to localize on or around the tumor cells displaying antigens to which the antibody is directed. This evidence of specific targeting, along with preliminary evidence of therapeutic efficacy for monoclonal antibodies and immunoconjugates with drugs, toxins, and isotopes is encouraging. The current status of clinical trials with monoclonal antibodies is reviewed and an example of the experimental approach for the development of immunoconjugates in animal models is presented.

Monoclonal Antibodies in Cancer Therapy: 25 Years of Progress

Robert K. Oldham, Robert O. Dillman
JCO Apr 10, 2008: 26(11): 1774-1777
http://dx.doi.org:/10.1200/JCO.2007.15.7438

In 1983, it was apparent that a major problem with current modalities of cancer treatment was the lack of specificity for the cancer cell.1 It was predicted that a major advancement in treatment of cancer would be the development of a class of agents that would have a greater degree of specificity for the tumor cell. Based on many animal studies and the treatment of fewer than 100 patients, it was evident in 1983 that monoclonal antibodies would be that major advance.

The first patient treated in the United States with monoclonal antibody therapy was a patient with non-Hodgkin’s lymphoma.2 Nadler et al2 described the treatment using a murine monoclonal antibody designated AB 89. Although treatment was not successful in inducing a significant clinical response, it did represent the first proof of principle in humans that a monoclonal antibody could induce transient decreases in the number of circulating tumor cells, induce circulating dead cells, and form complexes with circulating antigen, all with minimal toxicity to the patient. Antibody could be detected on the surface of circulating lymphoma cells, and free antigen in the serum decreased with each infusion of antibody. After two courses of milligram doses of AB 89, a final and third course with 1.5 g of antibody was administered during a 6-hour period. A marked reduction in circulating antigen was noted, but these studies suggested to the authors that the quantity of circulating antigen was too great to effectively deliver AB 89 to the patient’s tumor cells in a therapeutically effective manner.2

In the Journal of Clinical Oncology review article cited earlier,1 evidence was reviewed from animal tumor models that clearly demonstrated both specificity and therapeutic efficacy with little serious toxicity. Whereas passive serotherapy of human cancer had shown little success,3 it was apparent in the earlier review that monoclonal antibodies could be used in the treatment of leukemia and lymphoma.4,5 In 1983, a review of the literature revealed approximately 10 published studies and one in-press article of therapeutic trials of monoclonal antibody therapy in humans. All of these studies used murine monoclonal antibodies and were phase I/II studies. Most were in leukemia or lymphoma, but the earliest solid tumor studies were also underway in melanoma6 and GI cancer.1

By 1983, the pioneers in monoclonal antibody research believed that a new era of cancer therapy had begun, and for the first time, true specific and targeted therapy was underway using hybridoma technology to produce monoclonal antibodies with exquisite specificity. It was also apparent, based on animal model studies, that monoclonal antibodies could be a vehicle to bring immunoconjugate therapy to the clinic by conjugating monoclonal antibodies to drugs, toxins, and radioisotopes using the specificity of the monoclonal antibody to carry enhanced killing capacity directly to the tumor cells. Thus, the era of monoclonal antibody therapy, as well as immunoconjugate therapy, had begun.

Although there was much excitement (and skepticism) about this new treatment modality (the use of a form of biologic therapy with great specificity in patients with advanced cancer) there were also problems and limitations. As presented in Table 1, there were clinical toxicities with murine monoclonal antibodies, most of which were secondary to the interaction with the target antigen.7 However, the major limitation was their immunogenicity. Murine proteins are highly immunogenic, and it was soon found that only a few infusions of these foreign proteins could be given to patients with cancer because of the development of human antimouse antibody.8 Another problem quickly became apparent, in that some of the antigens on cancer cell surfaces modulated off the surface and into the circulation when antibody attached. Modulation could also cause internalization of the complex. It was recognized that this could represent a therapeutic advantage by using the antibody as carrier to internalize the toxic component of an immunoconjugate, potentially making it more therapeutically active.

In 1983, few specific antigens found only in cancer cells had been identified, and there was much debate about the specificity of these antigens. Many of the antigens to which monoclonal antibodies were made were embryonic antigens or shared antigens found on cancer cells and some normal cells. Therefore, although the specificity of the antibody was exquisite for the antigen, the specificity for the antibody or immunoconjugate for cancer was not absolute. One fairly clear exception occurred early in the 1980s when Levy et al9 developed monoclonal antibodies to the idiotype of B-lymphoma cells. The first patient given this anti-idiotypic antibody had a complete response to therapy, and his lymphoma went into a sustained remission that lasted for years. As a direct result of these early studies with anti-idiotypic antibodies, there is now a series of idiotype vaccines that are in phase III trials in patients with low-grade follicular lymphomas.10 These anti-idiotype vaccines will likely be the first truly custom-tailored, personalized anticancer vaccines to be approved for therapeutic use.

The major limitation of murine monoclonal antibody therapy was the immunogenicity of the mouse protein; a variety of investigators postulated that for monoclonal antibody therapy to be truly successful, human or humanized antibodies would be necessary. It was also known 25 years ago that the half-life of murine antibodies in the circulation was brief, and because of human antimouse antibody, became briefer with each infusion of murine monoclonal antibody. Previous studies of human immunoglobulin in clinical trials had demonstrated a much longer half-life for human immunoglobulin, which predicted that once human or humanized antibodies were available, the therapeutic efficacy of monoclonal antibodies and their immunoconjugates might be considerably enhanced.1
How has the field of monoclonal antibody and immunoconjugate therapy fared since the predictions of the early 1980s? Twenty-five years later, considerable progress has been made in this field.11,12 The US Food and Drug Administration has approved 21 monoclonal antibody products, with six of these biologic drugs approved specifically for cancer (Table 2). It was a landmark date in November 1997 when rituximab became the first monoclonal antibody approved specifically for cancer therapy.13 In addition to these six unconjugated monoclonal antibody therapies, one drug immunoconjugate, gemtuzumab ozogamicin (Mylotarg; Wyeth-Ayerst, Madison, NJ), has been approved. This humanized monoclonal antibody to CD33 is approved for use in acute myelogenous leukemia and uses the antibody conjugated to calicheamicin, a potent enediyene antibiotic originally isolated from aMicromonospora echoinospora.14 Two radioisotope-antibody conjugates, ytrrium-90 ibritumomab tiuxetan (Zevalin; Cell Therapeutics Inc, Seattle, WA) and iodine-131 tositumomab (Bexxar; GlaxoSmithKline, Middlesex, United Kingdom) have been approved.15 The murine form of these antibodies was retained in order to expedite clearance from the circulation. Both radiolabeled antibodies target the CD20 antigen on lymphoma cells.

Unlike the immunoconjugates, which are currently infrequently used, each of the six unconjugated antibodies approved for cancer therapy is currently frequently used in the treatment of humans with cancer. The use of techniques to humanize or chimarize monoclonal antibodies to decrease their murine components has been an important advance in the field. These molecules have a long half-life in the blood stream, and can interact with human complement or effector cells of the patient’s immune system. They behave in a manner similar to naturally occurring immunoglobulin and work along the lines of our normal antibody-based immune response as effective agents in treating patients with cancer.16

Rituximab has become the largest-selling biologic drug in clinical oncology, and is active in a variety of human lymphomas and chronic lymphocytic leukemia.17,18 This is a chimeric monoclonal antibody targeting the CD20 antigen found on both normal B cells and on most low-grade and some higher grade B-cell lymphomas. It is effective as a single agent in induction and maintenance therapy. It is primarily used, however, in combination with standard chemotherapies in the treatment of patients with non-Hodgkin’s B-cell lymphomas and chronic lymphocytic leukemia.19-22

A second monoclonal antibody that has proven highly effective in the clinic is trastuzumab, a humanized antibody that reacts with the second part of the human epidermal growth factor receptor 2.23 Like rituximab, it is effective as a single agent in induction and maintenance therapy, but is used primarily in conjunction with chemotherapy for patients with human epidermal growth factor receptor 2/neu–positive breast cancer.24,25

Alemtuzumab is a humanized monoclonal antibody targeting the CD52 antigen found on B lymphocytes and is used primarily for chronic lymphocytic leukemia.26 Like the two previously cited monoclonal antibody therapies, alemtuzumab is effective as induction and maintenance therapy. Alemtuzumab is also reactive with T lymphocytes, and unlike the other two antibodies, it is typically not combined with chemotherapy because of the increased risk of infection.(26)

Another humanized monoclonal antibody, bevacizumab, has been applied more broadly in human solid tumors because it targets vascular endothelial growth factor, which is the ligand for a receptor found on blood vessels.(27) Because this receptor is on endothelial cells, bevacizumab seems to be effective by reducing the blood supply to tumor nodules, thereby slowing or interrupting growth. Initially approved for advanced colorectal cancer,(28) it is now used in a variety of human solid tumors including cancers of the lung, kidney, and breast.(29-31)

The last two antibodies approved for clinical use were cetuximab (a chimeric antibody), and panitumumab (a completely human antibody). Both target the epidermal growth factor receptors found on a variety of human tumors.(32,33) Cetuximab was originally approved for use in combination with chemotherapy in metastatic colorectal cancer.(34) It also enhances chemotherapy and radiation therapy of squamous cell cancers of the head and neck.(35) Panitumumab was approved based on its single-agent activity in refractory colorectal cancer and is being combined with chemotherapy as well.

At the end of 2007, 25 years of clinical studies have resulted in the approval of six unconjugated, humanized, or chimeric monoclonal antibodies for cancer therapy along with one drug immunoconjugate and two radioisotope immunoconjugates. Although few in number, these monoclonal antibodies are changing the face of cancer therapy, bringing us closer to more specific and more effective biologic therapy of cancer as opposed to nonspecific cytotoxic chemicals.

Modern recombinant techniques have made it possible to rapidly produce both chimeric antibodies and humanized antibodies, and totally human antibodies are also being produced. Identification of surface receptors that are integral to proliferation and apoptosis has provided more targets for monoclonal antibodies beyond those originally identified by the murine immune system. In 2008, there are more than 100 monoclonal antibody–based biologic drugs in hundreds of clinical trials. Many of these are in phase II and phase III and will be coming before the US Food and Drug Administration for approval in the next few months and years. At long last, immunoconjugates are proving efficacious with acceptable toxicity and will extend our diagnostic (36) and therapeutic armamentarium (37) from mainly unconjugated monoclonal antibodies to a broad array of highly active and specific immunoconjugates.

On this silver anniversary for our 1983 review, “Monoclonal Antibodies in Cancer Therapy, ” we can confidently predict that progress toward more specific and less toxic therapy for human cancer is in our near future. The developments during the past 25 years in both biologic drugs and targeted small molecules place us on the verge of more cures with less toxicity for our patients with cancer.

9.1.4 Aptamers

Nanocarriers as an emerging platform for cancer therapy

Dan Peer1,7, Jeffrey M. Karp2,3,7, Seungpyo Hong, et al. 
Nature Nanotechnology
 2, 751 – 760 (2007)
http://dx.doi.org:/10.1038/nnano.2007.387

Nanotechnology has the potential to revolutionize cancer diagnosis and therapy. Advances in protein engineering and materials science have contributed to novel nanoscale targeting approaches that may bring new hope to cancer patients. Several therapeutic nanocarriers have been approved for clinical use. However, to date, there are only a few clinically approved nanocarriers that incorporate molecules to selectively bind and target cancer cells. This review examines some of the approved formulations and discusses the challenges in translating basic research to the clinic. We detail the arsenal of nanocarriers and molecules available for selective tumor targeting, and emphasize the challenges in cancer treatment.

Quantum Dot−Aptamer Conjugates for Synchronous Cancer Imaging, Therapy, and Sensing of Drug Delivery Based on Bi-Fluorescence Resonance Energy Transfer
Vaishali Bagalkot, L Zhang, E Levy-Nissenbaum, S Jon, PW Kantoff, et al.
Nano Letters 2007; 7(10):3065-3070
http://dx.doi.org:/10.1021/nl071546n

We report a novel quantum dot (QD)−aptamer(Apt)−doxorubicin (Dox) conjugate [QD−Apt(Dox)] as a targeted cancer imaging, therapy, and

sensing system. By functionalizing the surface of fluorescent QD with the A10 RNA aptamer, which recognizes the extracellular domain of the prostate specific membrane antigen (PSMA), we developed a targeted QD imaging system (QD−Apt) that is capable of differential uptake and imaging of prostate cancer cells that express the PSMA protein. The intercalation of Dox, a widely used antineoplastic anthracycline drug with fluorescent properties, in the double-stranded stem of the A10 aptamer results in a targeted QD−Apt(Dox) conjugate with reversible self-quenching properties based on a Bi-FRET mechanism. A donor−acceptor model fluorescence resonance energy transfer (FRET) between QD and Dox and a donor−quencher model FRET between Dox and aptamer result when Dox intercalated within the A10 aptamer. This simple multifunctional nanoparticle system can deliver Dox to the targeted prostate cancer cells and sense the delivery of Dox by activating the fluorescence of QD, which concurrently images the cancer cells. We demonstrate the specificity and sensitivity of this nanoparticle conjugate as a cancer imaging, therapy and sensing system in vitro.

Semiconductor nanocrystals known as quantum dots (QDs)

have been increasingly utilized as biological imaging and labeling probes because of their unique optical properties, including broad absorption with narrow photoluminescence spectra, high quantum yield, low photobleaching, and resistance to chemical degradation. In some cases, these unique properties have conferred advantages over traditional fluorophores such as organic dyes.1-4 The surface modification of QDs with antibodies, aptamers, peptides, or small

molecules that bind to antigens present on the target cells or tissues has resulted in the development of sensitive and specific targeted imaging and diagnostic modalities for in vitro and in vivo applications.5-7 More recently, QDs have been engineered to carry distinct classes of therapeutic agents for simultaneous imaging and therapeutic applications.8,9 While these combined imaging therapy nanoparticles represent an exciting advance in the field of nanomedicine, it would be ideal to engineer “smart” multifunctional nanoparticles that are capable of performing these tasks while sensing the delivery of drugs in a simple and easily detectable manner. One way to achieve this goal is to develop multifunctional nanoparticles capable of sensing the release of the therapeutic modality by a change in the fluorescence of the imaging modality.

Figure 1. (a) Schematic illustration of QD-Apt(Dox) Bi-FRET system. In the first step, the CdSe/ZnS core-shell QD are surface functionalized with the A10 PSMA aptamer. The intercalation of Dox within the A10 PSMA aptamer on the surface of QDs results in the formation of the QD-Apt(Dox) and quenching of both QD and Dox fluorescence through a Bi-FRET mechanism: the fluorescence of the QD is quenched by Dox while simultaneously the fluorescence of Dox is quenched by intercalation within the A10 PSMA aptamer resulting in the “OFF” state. (b)

Schematic illustration of specific uptake of QD-Apt(Dox) conjugates into target cancer cell through PSMA mediate endocytosis. The release of Dox from the QD-Apt(Dox) conjugates induces the recovery of fluorescence from both QD and Dox (“ON” state), thereby sensing the intracellular delivery of Dox and enabling the synchronous fluorescent localization and killing of cancer cells.

Figure 3. Fluorescence spectra. (a) QD-Apt conjugate (1 µM) with increasing molar ratio of Dox (from top to bottom: 0, 0.1, 0.3, 0.6, 1, 1.5, 2.1, 2.8, 3.5, 4.5, 5.5, 7, and 8) at an excitation of 350 nm. (b) Dox (10 µM) with increasing molar ratio of QD-Apt conjugate (from top to bottom: 0.02, 0.04, 0.07, 0.09, 0.12, 0.14, and 0.16) at an excitation of 480 nm.

In conclusion, herein we report to our knowledge the first example of a multifunctional nanoparticle that can detect cancer cells at a single cell level while intracellularly releasing a cytotoxic dose of a therapeutic agent in a reportable manner. We demonstrate the specificity and sensitivity of this cancer imaging, therapy and sensing nanoparticle conjugate system in vitro by using PCa cell lines. By functionalizing the surface of fluorescent QD with the A10 PSMA aptamer, and intercalating Dox into the double-stranded CG sequence of the A10 PSMA aptamer, we developed a targeted QD-Apt(Dox) conjugate with reversible Bi-FRET properties. The incorporation of multiple CG sequences within the stem of the aptamers may further increase the loading efficiency of Dox on these conjugates. The presence of additional Dox may enhance the selfquenching effect of QD-Apt(Dox) conjugates thereby improving their imaging sensitivity, while the higher dose of Dox may enhance the therapeutic efficacy of the conjugates. Furthermore, through the use of other disease-specific aptamers or other targeting molecules, similar multifunctional nanoparticles may potentially be developed for additional important medical applications

Oligonucleotide Aptamers: New Tools for Targeted Cancer Therapy

Hongguang Sun1, Xun Zhu2, Patrick Y Lu3, Roberto R Rosato, et al.
Molecular Therapy Nucleic Acids(2014) 3, e182;
http://dx.doi.org:/10.1038/mtna.2014.32

Aptamers are a class of small nucleic acid ligands that are composed of RNA or single-stranded DNA oligonucleotides and have high specificity and affinity for their targets. Similar to antibodies, aptamers interact with their targets by recognizing a specific three-dimensional structure and are thus termed “chemical antibodies.” In contrast to protein antibodies, aptamers offer unique chemical and biological characteristics based on their oligonucleotide properties. Hence, they are more suitable for the development of novel clinical applications. Aptamer technology has been widely investigated in various biomedical fields for biomarker discovery, in vitro diagnosis, in vivo imaging, and targeted therapy. This review will discuss the potential applications of aptamer technology as a new tool for targeted cancer therapy with emphasis on the development of aptamers that are able to specifically target cell surface biomarkers. Additionally, we will describe several approaches for the use of aptamers in targeted therapeutics, including aptamer-drug conjugation, aptamer-nanoparticle conjugation, aptamer-mediated targeted gene therapy, aptamer-mediated immunotherapy, and aptamer-mediated biotherapy.

The terms “aptamer” and “SELEX” were introduced by two independent groups in 1990.1,2 The term “aptamer” refers to small nucleic acid ligands that exhibit specific therapeutic functions and an unambiguous binding affinity for their targets. Conversely, Systematic Evolution of Ligands by EXponential enrichment (SELEX) technology is the method used for aptamer development. Although using small molecule nucleic acids as therapeutics has been explored for decades, development of SELEX and aptamer technology revolutionized this field.

The most important property of an aptamer, from the Latin aptus (to fit), is its high target selectivity. These short, chemically synthesized, single-stranded (ss) RNA or DNA oligonucleotides fold into specific three-dimensional (3D) structures with dissociation constants usually in the pico- to nano-molar range.3 Moreover, in contrast to other nucleic acid molecular probes, aptamers interact with and bind to their targets through structural recognition (Figure 1), a process similar to that of an antigen-antibody reaction. Thus, aptamers are also referred to as “chemical antibodies.”

Figure 1.

Schematic diagram of aptamer binding to its target.

Full figure (43K)

Due to their small size and oligonucleotide properties, aptamers offer several advantages over protein antibodies in both their extensive clinical applicability and a less challenging industrial synthesis process. Specifically, (i) aptamers can penetrate tissues faster and more efficiently due to their significantly lower molecular weight (8–25 kDa aptamers versus ~150 kDa of antibodies). Therefore, aptamers penetrate tissues barriers and reach their target sites in vivo more efficiently than the larger-sized protein antibodies. (ii) Aptamers are virtually nonimmunogenic in vivo. In principal, as aptamers are oligonucleotides they should not be recognized by the immune system. In practice, a recent clinical study showed that aptamers did not stimulate an immune response in vivo,4,5 as compared to protein antibodies that are highly immunogenic, especially following repeat injections. (iii) Aptamers are thermally stable. Based on the intrinsic property of oligonucleotides, even after a 95 °C denaturation, aptamers can refold into their correct 3D conformations once cooled to room temperature. In comparison, protein-based antibodies permanently lose their activity at high temperatures. More importantly, a well-established synthesis protocol and chemical modification technology lead to (iv) rapid, large-scale aptamer synthesis and modification capacity that includes a variety of functional moieties; (v) low structural variation during chemical synthesis; and (vi) have lower production costs. Moreover, aptamers specifically recognize a wide range of targets, such as ions, drugs, toxins, peptides, proteins, viruses, bacteria, cells, and even tissues.6,7,8,9,10,11,12 In the clinic, aptamer-based therapeutics are gaining momentum. For example, Macugen, a modified RNA aptamer, specifically targets vascular endothelial growth factor. It has been approved by the US Food and Drug Administration (FDA)13 for the treatment of wet age-related macular degeneration and is under evaluation for other conditions.14 In the cancer setting, AS1411 targets nucleolin, a protein over-expressed in a variety of tumors. It is currently being evaluated as a potential treatment option in solid tumors and acute myeloid leukemia.15 An updated list of therapeutic aptamers undergoing clinical trials is included in ref. 16 and Table 1. Taken together, these clinical studies highlight many possible uses that aptamers may have in a variety of biomedical fields, including therapeutics.17
Table 1 – A list of therapeutic aptamers undergoing clinical trials.

Since aptamer technology was first introduced, the RNA-based sequence library has been widely used for SELEX. Based on the existing evidence, it is believed that the presence of a 2′-OH group and non-Watson-Crick base pairing allows RNA aptamer oligonucleotides to fold into more diverse 3D structures than ssDNA molecules. Consequently, using the more flexible RNA sequences simplifies the development of high-affinity and -specificity aptamers. Despite their advantages, RNA sequences are very sensitive to nucleases present in biological environments and can be rapidly degraded.18 To increase nuclease resistance of RNA-based aptamers, several chemical modifications have been investigated. Evidence shows that 2′-OH group and phosphodiester linkages of RNA sequences are the sites of nuclease hydrolysis. Subsequently, substitutions of the 2′-OH functional group by 2′-fluoro, 2′-amino, or 2′-O-methoxy motifs, and/or changes to the phosphodiester backbone with boranophosphate or phosphorothioate are the most common modifications aimed at increasing nuclease resistance.19 More recently, Wu et al. developed a novel chemical modification method to increase siRNA stability, in which phosphorodithioate and 2′-O-Methyl were simultaneously substituted in the same nucleotide.20
This modification method significantly enhanced siRNA stability and represents a potential new direction for utilization of RNA-based therapies in complex biological systems. Other effective modifications recently reported utilize the locked nucleic acid technology16,21 or generate “mirror” RNA sequence structures, termed spiegelmers.22 These modifications result in structural changes to the RNA sequences, which cannot be digested by nucleases.

In addition to RNA aptamers, ssDNA-based aptamers have also been developed. Due to their lack of 2′-OH groups, DNA molecules are naturally resistant to 2′-endonucleases and are stable in biological environments. Recently, our group developed a biostable DNA-based aptamer specific for CD30, a protein biomarker that is over-expressed in Hodgkin and anaplastic large cell lymphomas. Functional analysis demonstrated that this ssDNA-based aptamer exhibited high CD30 binding affinity as low as 2 nmol/l and was stable in human serum for up to 8 hours. Conversely, an RNA-based CD30 aptamer was digested within 10 minutes under similar conditions.23
In summary, unique chemical features and biological functions have made aptamers a very attractive tool in biomedical research over the past two decades. Currently, there are over 4,000 published articles referenced in the PubMed database that include the term “aptamer.” Research areas that include aptamer technology cover bioassays, drug development, cell detection, tissue staining, in vitro and in vivo imaging, nanotechnology, and targeted therapy. As chemical antibodies, aptamers represent an excellent alternative to replace or supplement protein antibodies, which have been extensively used in the clinic.

Aptamers Specifically Targeting Cell Surface Biomarkers

Using SELEX technology to develop aptamers for cell surface biomarkers

SELEX, the methodology used to develop aptamers specific for a target of interest, is based on a repetitive amplification and enrichment process. The SELEX process follows several steps: first, a random ssDNA oligonucleotide library is chemically synthesized to contain between 1014–1015 unique random sequences flanked by conserved primer binding sites. This step utilizes the following universal scheme: 5′-sense primer sequence-(random sequence)-antisense primer sequence-3′, where the primer sequence ranges from 18 to 22 bases and the random sequence contains 20–40 nucleic acids. The general procedure consists of labeling the 5′-sense primer with a fluorochrome reporter for monitoring aptamer selection, while the 3′-antisense primer is labeled with an affinity molecule, such as biotin, that is used to separate single-stranded oligonucleotides generated in each amplification round. This random ssDNA library can be used directly to select an initial pool of DNA aptamers. Conversely, generation of RNA aptamers requires two extra steps. Specifically, a pool of random ssDNA oligonucleotides is generated, T7 RNA polymerase promoter sequence is added to the 5′-sense primer, and the DNA is then used as a template for T7 RNA polymerase-based transcription in the 5′ to 3′ direction. During the second SELEX step, the oligonucleotide library is heated and rapidly cooled to promote the formation of 3D structures. The library is then mixed with the target of interest for specific binding enrichment. In the third step, the unbound sequences are discarded through the use of membranes, columns, magnetic beads, and capillary electrophoresis.6,24,25 In the fourth step, the enriched sequences are amplified in vitro by either PCR (DNA aptamers) or RT-PCR (RNA aptamers) to generate a new sequence library for the next round of SELEX. The amplified sequence library may go through further negative-target selection, which eliminates the nonspecific sequences generated by binding of nontarget moieties. Lastly, aptamer selection goes through 4–20 rounds of amplification and enrichment. The exact number of required amplification and selection steps depends on the aptamer target being a purified protein or a living cell, and on the evolution of the aptamer sequence library, as that established by gel electrophoresis, flow cytometry (for target binding), classical cloning or sequencing methods, or by high throughput Next-Generation Sequencing (NGS). In recent years, the traditional SELEX method had also been modified to include the capillary electrophoresis (CE) SELEX, toggle selection, photo-SELEX, bead-based selection, X-Aptamers, and Slow Off-rate Modified Aptamers (SOMAmers) in order to maximize affinity and specificity, to improve the speed of selection and success rate, and to provide additional properties to the selected aptamers.26,27,28,29,30,31

Similar to protein antibody development, purified recombinant proteins or peptides expressed in prokaryotic or eukaryotic systems can be used as targets for aptamers selected by the SELEX method. However, because of the posttranslational modifications, especially in the case of highly glycosylated proteins, purified proteins or peptides often cannot fold into the correct 3D structure that is formed under physiologic conditions.32 Consequently, the newly synthesized aptamers may not be able to selectively recognize and interact with their corresponding targets, which would result in failure of the biomedical application. As this is a common problem, it is very important to choose biomarkers in their native conformation for aptamers selection. Taking this issue into an account, a modified SELEX technology that uses whole living cells, Cell-based SELEX (or Cell-SELEX), was recently established.33 To develop cell-specific aptamers, the Cell-SELEX method uses whole living cells that express surface biomarkers of interest. However, the presence of many different cell surface molecules in addition to the target biomarker(s) results in the synthesis of many unrelated/unwanted aptamers. Therefore, in addition to all the SELEX steps described above, Cell-SELEX technology also utilizes control cells that do not express the target biomarker(s) during the counter-selection step.33

Well-characterized biomarkers that are endogenously expressed at high levels, such as the ErbB superfamily, MUC1, EpCAM, and CD30, offer the best potential for cell-based aptamer development. Subsequently, cell lines that have high endogenous expression of cell-specific or cancer type-specific biomarker(s) are commonly used for Cell-SELEX. However, if such cell lines are unavailable, a biomarker of interest could be over-expressed in a particular cell line via gene transfection and the parental cells used for counter-selection. Using this approach, aptamers targeting the cancer stem cell (CSC) biomarker CD133 have been recently developed.34 In this study, CD133 cDNA was transfected into HEK293T cells that were then used for aptamer enrichment, with the parental HEK293T cells serving as a negative control. Similarly, an aptamer specific for the human receptor tyrosine kinase was recently developed.35

Figure 2.

Schematic diagram of our hybrid-SELEX method for selection of CD30-specific ssDNA aptamer. In our experiment, the hybrid-SELEX process is divided into (a) the cell-based SELEX selection and (b) CD30 protein-based SELEX enrichment. First, CD30-expressing lymphoma cells are used for positive selection and CD30-negative Jurkat cells are used in negative counter-selection. After 20 rounds of selection, the enriched aptamer pool is incubated with CD30 protein immobilized on magnetic beads for five additional rounds of enrichment. SELEX, Systematic Evolution of Ligands by EXponential enrichment.

Full figure and legend (183K)

Aptamers specific for cell surface biomarkers

Cell surface biomarkers are functionally important molecules involved in many biological processes, such as signal transduction, cell adhesion and migration, cell–cell interactions, and communication between the intra- and extra-cellular environments. An abnormal expression of cell surface biomarkers is often related to tumorigenesis.50 Clinically, it is estimated that about 60% of cancer-targeting drugs, including therapeutic antibodies and small molecule inhibitors, target cell surface biomarkers,51 making them attractive for disease treatment. In the last decade, many aptamers targeting cell surface biomarkers have been developed through the advancement of both the protein- and/or cell-based SELEX technologies (see Table 2 for detailed list). These aptamers have been extensively studied for diagnosis and/or treatment of hematological malignancies,7,23,49 lung,52,53,54 liver,55 breast,56,57 ovarian,58 brain,59,60colorectal,61 and pancreatic cancers,46 as well as for identification and characterization of CSCs.34,62

Aptamer-Mediated Targeted Therapies

Traditional cancer treatment approaches, such as chemotherapy, radiotherapy, photodynamic therapy, and photothermal therapy can cause serious side effects in patients due to their associated nonspecific toxicity. To minimize these side effects, a concept of personalized, targeted therapy has been gaining momentum. One of the main clinical approaches for targeted cancer therapy employs antibody-based drugs. Although antibody-mediated therapy is highly specific and results in fewer side effects, potential immunogenicity and high cost of production may limit its clinical applications. To overcome these obstacles, oligonucleotide aptamer-based targeted therapeutics and specific drug delivery systems have recently been explored. These studies revealed numerous advantages offered by the aptamer technology over protein-based antibody therapies, with some of these described in the section below.
Aptamer-drug conjugates

Aptamer-drug conjugation (ApDC) is a very simple yet effective model of noncovalently or covalently conjugating aptamer sequences directly with therapeutic agents (Figure 3). For example, aptamer-conjugated Doxorubicin (Dox), a chemotherapeutic agent extensively used in the treatment of various cancers, has recently been shown to have enhanced therapeutic efficacy over Dox alone. Mechanistically, Dox cytotoxicity is caused by its intercalation into the nucleic acid structure at the preferred paired CG or GC sites with subsequent inhibition of cancer cell proliferation. Taking advantage of its propensity for intercalation, Dox can be noncovalently conjugated to oligonucleotide aptamers containing CG/GC sequences through a simple incubation step. A recent report by Subramanian et al. describes the effectiveness of aptamer-Dox conjugates in the treatment of retinoblastoma.63 In their study, a 2′-fluoro modified RNA aptamer EpDT3 (specific for EpCAM, a CSC marker), was noncovalently conjugated with Dox. After binding to EpCAM molecules expressed at the cancer cell surface, the EpDT3-Dox conjugates were preferentially internalized by the cancer and not by the healthy cells, greatly enhancing therapeutic efficacy and reducing treatment-associated side effects. Several other studies also utilized aptamer-Dox conjugates for cancer therapy, such as HER2 aptamer-Dox conjugates targeting breast cancer,64 MUC1 aptamer-Dox conjugates targeting lung cancer,65 and PSMA aptamer-Dox conjugates targeting prostate cancer.66 Despite their obvious advantages, several concerns related to the use of aptamer-Dox conjugate have been raised. These include (i) instability of the aptamer-drug conjugate due to the reversible nature of noncovalent conjugation process; (ii) short circulating half-life of aptamer-drug conjugates in vivo due to their low molecular weight; and (iii) poor drug payload capacity due to a very simple structure of aptamers. These three disadvantages and technological approaches to improve them are described in greater detail below.

Figure 3.

Schematic diagram of noncovalent or covalent aptamer-drug conjugation.

Full figure (40K)

To enhance the stability of drug loading, Dox can be covalently conjugated to aptamer sequences via a functional linker moiety. For example, the DNA aptamer sgc8 possesses a strong affinity for PTK7 kinase that is abundantly expressed on the surface of CCRF-CEM T-cell acute lymphoblastic leukemia cells. To enhance its stability, this aptamer was covalently conjugated with Dox through an acid-labile linker.67 Once the sgc8 aptamer-Dox conjugate was preferentially bound and internalized by the target cells, the acid-labile linker was easily cleaved in the acidic lysosomal environment, releasing Dox and effectively killing target cells.67 On the other side of the spectrum, covalent conjugation is the most commonly used method of aptamer-drug conjugation, especially for agents that cannot intercalate into the nucleic acid structure or whose intercalation would disrupt aptamer structure.68 Evidence suggests that these covalently conjugated aptamer-drug compounds are significantly more stable than the corresponding noncovalently conjugated intercalations.69

Conjugation of aptamers with high molecular weight polymers, such as polyethylene glycol (PEG), has been examined in order to increase aptamer molecular weight. Specifically, PEG has been widely used in drug modifications, including synthesis of Macugen aptamers. This modification, resulting in PEGylated aptamers, not only increased the aptamer molecular weight and prolonged its circulating half-life, but also enhanced its stability and decreased its toxic accumulation in nontarget tissues.70,71

Finally, in order to increase aptamer-drug payload capacity, an innovative model named aptamer-tethered DNA nanotrains (aptNTrs) was recently introduced by Zhu et al. to deliver Dox to cancer cells.72 In this study, structure of the sgc8 aptamer that targets PTK7 was modified by adding a DNA trigger probe on the 5′-end. Consequently, the modified aptamer acted as a locomotive for targeting, while two hairpin monomers containing Dox intercalation sites acted as boxcars to deliver the drug. After self-assembly, the newly synthesized sgc8 aptamer-NTrs displayed high drug payload capacity, with the drug/sgc8 aptamer-NTr molar ratio of 50:1. Importantly, sgc8 aptamer-NTrs-Dox conjugates were preferentially internalized by the target cells, thereby inhibiting tumor cell growth in vitro and in vivo.72

Another strategy for increasing the aptamer payload capacity involves the construction of polyvalent aptamers. Polyvalent aptamers exhibit an increased target affinity and are more rapidly internalized by their target cells. To demonstrate this, Boyacioglu et al. developed a new DNA aptamer they termed SZTI01 against PSMA.69 First, a dimeric aptamer complex (DAC) was created for specific delivery of Dox to PSMA-expressing cancer cells. Then, the SZTI01aptamer was modified on the 3′-terminus with either a dA16 or dT16 single-stranded tail that contained CpG sites for loading Dox, and the two monomers were annealed in a 1:1 ratio to form the DAC structure. The results of the study showed that DACs have a high Dox payload capacity with the Dox/DAC molar ratio of about 4:1, and the DACs-Dox conjugates were stable under physiological conditions for up to 8 hours.69 In another study, a DNA aptamer targeting MUC1 was truncated and an aptamer containing three repeats of the active targeting region, termed L3, was synthesized. Although the Dox payload capacity was not specifically modified in the L3 aptamer, the L3-Dox conjugates showed a stronger affinity to target cells and lower cytotoxicity to off-target cells than the parental MUC1 aptamer.73 Finally, polyvalent aptamers can also be constructed through the rolling circle amplification (RCA) technology. Using the RCA method and the sgc8 aptamer sequence as a circular template, a polyvalent sgc8 aptamer, termed Poly-Aptamer-Drug, was synthesized.74 It was determined that the Dox payload capacity of the polyvalent sgc8 aptamer increased tenfold, as compared to the monovalent sgc8 aptamer. Moreover, because of their 40-fold greater binding affinity, the Poly-Aptamer-Drug conjugates were more effective than their monovalent counterparts in targeting and killing leukemia cells.74

Although Dox presents itself as a very attractive chemotherapeutic agent for use in aptamer conjugation, other drugs, such as Gemcitabine (Gem) and photosensitizers, can also be targeted to cancer cells through the aptamer technology. Gem is an FDA-approved deoxycytidine analog (dFdC) used for anticancer therapy. To deliver Gem specifically to pancreatic cancer cells, Ray et al. developed a novel aptamer-Gem polymer model. In this model, a single-stranded RNA polymer contained Gem that was enzymatically synthesized through a mutant T7 RNA polymerase-mediated transcription reaction and fused with a nuclease-resistant 2′-fluoro-modified RNA aptamer (E07) that selectively binds to EGFR on pancreatic cancer cells. The E07 aptamer structure was modified by introducing a 24-nucleotide sequence at the 3′ end and using it as an adaptor for Gem polymer binding. Following an annealing step, the Gem polymer complementary bound with the E07 aptamer and preferentially targeted the EGFR-expressing pancreatic cancer cells, inhibiting cell proliferation.75

Compared with the traditional chemotherapeutic agents, controlled conditional prodrug photosensitizers have also been extensively used for aptamer-mediated drug delivery. In this therapeutic approach, termed photodynamic therapy, or photodynamic therapy, photosensitizers are activated by light irradiation and induce production of intracellular reactive oxygen species, resulting in cytotoxicity. A study by Ferreira et al. describes the development of a DNA aptamer specific for MUC1 and covalently conjugated at the 5′ end with the photosensitizer chlorin e6.76 Upon light irradiation, MUC1-expressing epithelial cancer cells were preferentially killed with cytotoxicity about 500-fold higher than that of the control cells. Similar studies have reported using a necleolin aptamer (AS1411)-TMPyP4 for targeting breast cancer77 and the EGFR aptamer (R13)-TF70 for treatment of lung cancer.78

Finally, approaches to extend the scope of aptamer application have also been developed. Similar to bi-specific antibodies, bi-specific or even tri-specific aptamers can be constructed. A bi-specific aptamer for targeting different cells was recently described by Zhu et al. In their study, specific DNA aptamers sgc8 and sgd5a were conjugated through a dsDNA linker. Compared to each mono-aptamer, this bi-specific aptamer (named SD) could recognize its target cell simultaneously with equal specificity and affinity, while Dox intercalation into the dsDNA induced target cell cytotoxicity.79 In the same study, a Y-shape dsDNA linker was used to construct a tri-specific aptamer that also recognized its target cells with high specificity and affinity.79 Clinically, Min et al. proposed using a bi-specific aptamer for prostate cancer therapy. It is well established that prostate tumors may contain both PSMA-positive and -negative cell types. Thus, this study utilized two aptamers, a 2′-fluoro modified RNA aptamer targeting PSMA-expressing cells and a DUP-1 peptide aptamer specific to PSMA-negative cells, conjugated through streptavidin. Moreover, intercalating Dox into the PSMA aptamer of this bi-specific aptamer model could serve as a tool to target all prostate cancer cell types.80

Aptamer-nanoparticle therapeutics

Nanoparticles (NPs) are attractive vehicles to increase both the half-life and the drug payload capacity of aptamer-mediated drug delivery. In addition to their common features, such as biocompatibility for clinical applications, large surface for enhanced aptamer and drug loading, and uniform size and shape for excellent biodistribution, NPs have other individual physical and chemical properties defined by their materials. For example, copolymers and liposomes are biodegradable, while metal materials offer exceptional photothermal and magnetic performance.

Conclusion

Antibody-based targeted therapeutics provide high target specificity and affinity. However, their potential for immunogenicity is of a great concern, as is their high production cost, both of which have limited their clinical applicability. As discussed in this review, when compared to protein antibodies, oligonucleotide aptamers offer many advantages, including simple chemical synthesis, virtual nonimmunogenicity, smaller size, faster tissue penetration, ease of modification with different functional moieties, low cost of production, and high biological stability. Therefore, aptamers have become a promising new class of molecular ligands that could replace or supplement protein antibodies. In summary, aptamer technology has a strong market value and may be applied in various biomedical fields, including in vitro cancer cell detection, in vivo tumor imaging, and targeted cancer therapy (Figure 7).

Figure 7.

Summary of various aptamer applications.

Full figure (58K)

Although aptamer technology has a great potential in the biomedical field, several technical challenges remain and must be addressed. These include: (i) how can aptamers be rapidly adapted for specific targets by decreasing false-positive/-negative selection? Primarily dependent on the natural properties of targets of interest, such as proteins versus cells or tissues, the process of aptamer selection is usually time-consuming, and the success rate is sometimes low. To improve the speed and success rate, novel methods for aptamer selection have been recently described. They include bead-based selection, that can select aptamers as rapidly as a single round of selection,27,28 and the SOMAmer, which improves the aptamer production success rate from less than 30% to over 50%.29,30 More recently, a study by Cho et al. devised a Quantitative Parallel Aptamer Selection System (QPASS) method, which integrates microfluidic selection, NGS, and in situ-synthesized aptamer arrays. This approach allows for the simultaneous measurement of affinity and specificity for thousands of candidate aptamers in parallel.116 In addition to QPASS, evolving modifications to the Cell-SELEX approach are beginning to address difficulties with successful removal of the influence stemming from the presence of dead cells, slow enrichment aptamers recognizing targets of interest, and contamination with unwanted aptamer sequences. As described above, utilization of the above-mentioned FACS-mediated SELEX44,45 and hybrid-SELEX23 offers novel approaches that address these technical challenges.

(ii) How can we select cancer-relevant targets for aptamer development and clinical applications? Tumorigenesis is a dynamic process that includes multiple constantly changing factors. Therefore, a one-size-fits-all cancer-specific biomarker is unlikely to ever be identified. Yet, it has been established that certain biomarkers present in healthy tissues are highly expressed in cancer cells. Moreover, certain biomarkers are associated with particular cancer cell types making them to be considered as useful targets for development of targeted cancer therapy. However, while use of cancer cells to identify biomarkers and to develop therapeutic agents is a reasonable approach, cultured cells, especially immortalized cell lines, greatly differ from tumor tissues in vivo. To overcome these limitations and to select more reliable cancer-relevant biomarkers for aptamer development, several innovative SELEX methods have been recently described. Of particular interest are the tissue-based SELEX117 and the in vivo-SELEX,118 which offer target selection under more relevant pathologic conditions. This cell/tissue-specific biomarker selection can also be utilized for development of noncancer related therapies, as shown for aptamers targeting the adipose tissue in obesity119 and for aptamers designed to penetrate the blood-brain barrier in order to combat brain diseases.120 Hence, we believe that the careful selection of cancer-associated biomarkers and cell/tissue type-specific biomarkers will expand the scopes of aptamer applicability and improve the feasibility of clinical applications.

(iii) What methods could improve aptamer biostability in vivo? Unmodified RNA-based aptamers are very susceptible to the nuclease-mediated degradation in vivo. Although many chemical modifications aimed at increasing biostability of the RNA aptamers have been developed, including 2′-modifications, 3′-modifications, phosphodiester backbone modifications,19,20 and utilizations of novel nucleic acids (locked nucleic acid and Spiegelmers),16,21,22 their effectiveness is still limited. When it was first described, PEGylation was a very attractive strategy for prolonging aptamer circulation half-life and enhancing their biostability. However, a recent report showed that the in vivo use of PEGylated aptamers induced production of anti-PEG antibodies,121 emphasizing the need for the development of alternative approaches.

(iv) How can aptamer technology be modified to achieve a more effective drug delivery? Many drug delivery systems described in this review are tested in vitroor in animal models. Yet, as with any compound that is translated from the bench to the bedside, aptamer-drug conjugates may behave differently in a human patient than they do in laboratory animals. Therefore, aptamer-drug conjugation remains an important challenge that must be considered. Specifically, various coupling approaches lead to different pharmacokinetics, biodistribution, and tolerability in vivo, which in turn greatly affect treatment effectiveness. In the same vein, we must consider the effectiveness of aptamer-mediated target gene therapy. Gene therapy, including siRNA and miRNA aimed at silencing specific genes, is considered the next generation therapeutic approach. However, silencing a single pathogenic gene may not be a viable therapeutic option because tumorigenesis is a process regulated by multiple genes and signaling pathways. Therefore, combining targeted therapeutics with gene therapy may represent the most effective strategy. Such combinational therapy approaches can greatly improve the therapeutic efficacy while reducing the required dosages of both drugs and small molecule RNAs,122 and, more importantly, may offer new alternatives to combat chemotherapy-resistant cancers.110

(v) The last important point to consider is whether aptamer-mediated biotherapies can become effective, FDA-approved medications. Following Macugen approval by the FDA, many aptamer-mediated biotherapies have been evaluated in clinical trials. Of particular interest is AS1411, an antitumor aptamer that has completed several Phase I clinical trials.15 Trial results are promising and offer useful insights into further modifications that could be applied to therapeutic aptamer development.

Taken together, although some technical challenges remain to be addressed, oligonucleotide aptamers have become an attractive and promising tool for targeted cancer therapy. As more clinical data are accumulated, we and others will be better equipped to optimize aptamer formulations, leading to the expansion of aptamer use in the clinic.

9.1.5 Tumor Suppressors

Intrinsic Disorder in PTEN and its Interactome Confers Structural Plasticity and Functional Versatility
Prerna Malaney, Ravi R Pathak, Bin Xue, VN Uversky & Vrushank Davé
Scientific Reports 20 June 2013; 3(2035)
http://dx.doi.org:/10.1038/srep02035

IDPs, while structurally poor, are functionally rich by virtue of their flexibility and modularity. However, how mutations in IDPs elicit diseases, remain elusive. Herein, we have identified tumor suppressor PTEN as an intrinsically disordered protein (IDP) and elucidated the molecular principles by which its intrinsically disordered region (IDR) at the carboxyl-terminus (C-tail) executes its functions. Post-translational modifications, conserved eukaryotic linear motifs and molecular recognition features present in the C-tail IDR enhance PTEN’s protein-protein interactions that are required for its myriad cellular functions. PTEN primary and secondary interactomes are also enriched in IDPs, most being cancer related, revealing that PTEN functions emanate from and are nucleated by the C-tail IDR, which form pliable network-hubs. Together, PTEN higher order functional networks operate via multiple IDP-IDP interactions facilitated by its C-tail IDR. Targeting PTEN IDR and its interaction hubs emerges as a new paradigm for treatment of PTEN related pathologies.

The concept of “Intrinsic Disorder” in proteins has rapidly gained attention as the preponderance and functional roles of IDPs are increasingly being identified in eukaryotic proteomes1, 2. Structured proteins adopt energetically stable three-dimensional conformations with minimum free energy. In contrast, IDPs, due to their unique amino acid sequence arrangements, cannot adopt energetically favorable conformations and, thus, lack stable tertiary structure in vitro3. This structural plasticity allows IDPs to operate within numerous functional pathways, conferring multiple regulatory functions4, 5, 6. Indeed, mutations in and dysregulation of IDPs are associated with many diseases including cancer1, 6, 7, signifying that IDPs play vital roles in functional pathways. Evidence suggests that ~80% of proteins participating in processes driving cancer contain IDRs6. For example, tumor suppressor p53 as an IDP, functions via its C-terminal IDR, which simultaneously exists in different conformations, each of which function differently1. Since PTEN is the second most frequently mutated tumor suppressor with versatile functions8, we hypothesized that PTEN may contain IDR(s) that can be exploited for therapeutic targeting in cancers and diseases associated with pathogenic PI3K/Akt/mTOR (Phosphoinositide 3-Kinase/Akt/ mammalian Target of Rapamycin) signaling9, 10, 11.

PTEN (phosphatase and tensin homolog), a 403 amino acid dual protein/lipid phosphatase converts phosphatidylinositol(3,4,5)-triphosphate (PIP3) to phosphatidylinositol(4,5)-bisphosphate (PIP2), thereby regulating the PI3K/Akt/mTOR pathway involved in oncogenic signaling, cell proliferation, survival and apoptosis12. PTEN, as a protein phosphatase, autodephosphorylates itself13. Deficiency or dysregulation of PTEN drives endometrial, prostate, brain and lung cancers, and causes neurological defects14, 15. PTEN is activated after membrane association16, providing conformational accessibility to the catalytic phosphatase domain (PD) that converts PIP3 to PIP216(Figure 1a). Because PTEN reduces PIP3 levels and inhibits pathogenic PI3K signaling, therapeutically targeting PTEN to the membrane to enhance its activity is of significance in treating several pathologies including cancer.

Figure 1: PTEN: A newly identified IDP.

PTEN - A newly identified IDP. srep02035-f1

PTEN – A newly identified IDP. srep02035-f1

http://www.nature.com/srep/2013/130620/srep02035/images_article/srep02035-f1.jpg

(a) Diagrammatic representation of PTEN structure. PTEN, a 403 amino acid protein, comprises of PBM: PIP2 Binding Module (AA 1–13; in green), a phosphatase Domain (AA 14–185; in pink), C2 Domain (AA 190–350; in blue), C-terminal region or Tail (AA 351–400; in orange) and a PDZ binding domain (AA 401–403; in dark blue). The PDZ-binding motif is considered as a part of the C-terminal region. *Figure not to scale. (b) Crystal structure of PTEN. Only the phosphatase (in pink) and C2 domain (in blue) are amenable to crystallization. The first seven residues and the last 50 residues represent unstructured/loosely-folded regions that are yet to be crystallized. These regions represent the N- and C-termini of PTEN, respectively. (Source: RCSB Protein Data Bank). (c) Disorder analysis of PTEN. PONDR-VLXT and PONDR-FIT prediction tools were used to determine the disorder score of PTEN. Any value above 0.5 indicates intrinsic disorder. There are several disordered stretches within the PTEN protein, however, the most prominent of these disordered regions is a 50 amino-acid stretch located at the C-terminus of the PTEN protein. (d) IDPs are enriched in polar (R, Q, S, T, E, K, D, H) and structure breaking (G, P) amino acids and are depleted in hydrophobic (I, L, V, M, A), aromatic (Y, W, F) and cysteine (C) and asparagine (N) residues. The amino acid sequence of PTEN highlights these classes of residues with their relative distribution. (e) Composition profiling for full-length PTEN (in green), its ordered domain (in yellow) and its IDR (in red). The tool used is Composition Profiler (Vacic et al, 2007). As shown in the graph, the disordered region in PTEN is enriched in polar residues (specifically H, T, D, S and E), structure breaking residues (specifically P) and is depleted in all hydrophobic residues, cysteine and all aromatic residues. (f) Histogram representing the percentage of hydrophobic, polar, aromatic, structure breaking, cysteine and asparagines residues in ordered vs. disordered regions. The disordered region has an amino acid composition in line with the definition of IDPs.

PTEN crystal structure revealed that the PD and membrane-binding C2 domains are ordered (Figure 1b); however, the structures of the N-terminus, the CBR3 loop and the 50 amino-acid C-tail remain undetermined17. The C-tail is of particular significance due to its ability to regulate PTEN membrane association, activity, function, stability18, 19, 20, 21. Herein, we identify PTEN as an IDP with its C-tail being intrinsically disordered. The PTEN C-tail IDR is heavily phosphorylated by a number of kinases and regulates the majority of PTEN functions, including a large number of PPIs that forms the PTEN primary and secondary interactomes, comprising critical functional protein hubs, most of which are related to cancer. Our analysis provides a mechanistic insight into the functioning of the PTEN C-tail IDR at the systems level, including inter- and intra-molecular interactions that will aid in designing drugs to enhance the lipid phosphatase activity of PTEN for the pharmacotherapy of cancers and pathological conditions driven by hyperactive PI3K-signaling.

PTEN is an IDP

Utilizing two disorder prediction software programs, PONDR-VLXT and PONDR-FIT22, 23, we have identified PTEN as a bona fide IDP. PTEN has a highly disordered, functionally versatile, C-tail encompassing amino acids 351–403 (Figure 1a and 1c). A PDZ-binding motif (amino acids 401–403) is part of the disordered region. Thus, the PTEN C-tail IDR facilitates interactions with a vast repertoire of PDZ domain-containing proteins (Figs. 1a and 2d). The unique amino acid composition of IDRs dictates their structural plasticity3, 23, 24. IDRs are enriched in polar and structure-breaking amino acid residues, depleted in hydrophobic and aromatic residues and, rarely, contain Cys and Asn residues1, 23, 24. The ordered region of PTEN (AA 1–350) has 25% hydrophobic, 43% polar, 9% structure breaking, 13% aromatic and 9% Cys and Asn residues. In contrast, the PTEN C-tail (AA 351–403) is enriched in polar (66%) and structure breaking (11%) residues and is depleted in hydrophobic (11%), aromatic (6%) and Cys and Asn residues (6%), indicating an ideal profile for the IDR (Figs. 1d and 1f ). Further, compositional analysis of PTEN using the Composition Profiler24 reveals that the disordered region in PTEN is enriched in polar residues (specifically H, T, D, S and E) and structure breaking residues (specifically P) but is depleted in all aromatic and hydrophobic residues in addition to cysteine. (Figure 1e), again exhibiting universal characteristics of IDPs. Taken together, we establish the PTEN C-tail as a functional IDR and classify PTEN as a new IDP.

Figure 2: The functional relevance of the PTEN IDR.

The functional relevance of the PTEN IDR. srep02035-f2

The functional relevance of the PTEN IDR. srep02035-f2

http://www.nature.com/srep/2013/130620/srep02035/images_article/srep02035-f2.jpg

(a) The number of mutations observed in PTEN over its 403 amino-acid stretch is plotted. Fewer mutations are observed in the tail region (in red) possibly indicating the deleterious nature of mutations in the functionally critical C-terminal region. [Source: Sanger Institute Catalogue of Somatic Mutations in Cancer (COSMIC), Human Gene Mutation Database (HGMD)]. (b) Number of mutations in every successive 50 amino-acid stretch of the PTEN protein. The last 50 amino-acid stretch, representing the tail region has at least one-eighth the number of mutations seen in any other 50 amino-acid stretch along PTEN, pointing to its critical function in cell homeostasis. (c) Correlation of mutations with the amino acid composition of PTEN. The ratio of mutations in specific residues in the disordered vs. ordered region are represented in this graph. The residues considered here are those used to define IDRs: hydrophobic, polar, aromatic, structure-breaking, cysteine and asparagine residues. Compared to the other classes of residues, mutations in aromatic residues are much higher in the disordered region when compared to the ordered region. (d) The PTEN primary interactome. Forty proteins interact with known regions of PTEN. There are approximately 340 more proteins that interact with PTEN at sites that are yet to be determined (see Supplementary Table S2). Proteins shown in pink interact with the phosphatase domain, those in blue interact with the C2 domain and those in orange interact with the disordered tail. (Visualization tool: Cytoscape). (e) The PTEN C-tail has a higher propensity for PPIs. Of the 40 mapped proteins, 60% interact with the disordered indicating a strong correlation between degree of disorder and the number of protein interactions. (f) Most proteins within the PTEN interactome are highly disordered. Approximately 80% of PTEN-interacting proteins within the primary interactome are disordered, as indicated in red. The proteins within the interactome that are ordered are indicated in blue.

Low mutability of PTEN IDR suggests critical biological functions

Mutations in PTEN are associated with several types of cancers14. To correlate PTEN mutations to its structure, we analyzed all human PTEN mutations deposited in the COSMIC Database (http://www.sanger.ac.uk/genetics/CGP/cosmic/). The disordered PTEN C-tail IDR shows unusually low mutability (~8-fold less) compared to any other 50 amino-acid stretch of PTEN (Figure 2a and 2b). To confirm our finding of the low mutability of the C-tail region, we also analyzed all human PTEN mutations deposited in the Human Gene Mutation Database (HGMD,http://www.hgmd.cf.ac.uk/ac/index.php)25 (Figure 2a), cBioPortal for Cancer Genomics26, 27(Supplementary Figure S1) and the Roche Cancer Genome Database28 (Supplementary Figure S1) which was consistent with the COSMIC database mutational data. It is likely that evolutionary pressure maintains a survival advantage and ipso facto abrogates progeny with mutations in highly functional protein sequences29, 30, 31. Thus, the functionally versatile PTEN C-tail IDR cannot afford mutations, hence showing least number of mutations. It is equally likely that mutations in individual residues within the IDR are well tolerated, as the evolutionary pressure may have shifted to maintaining global biophysical properties and structural malleability of the IDR to safeguard the critical protein function29. In either case, on a global scale, the versatile structural pliability of the PTEN IDR dictates functional diversity and biological activities29. Thus, the slightest functional perturbation in the PTEN IDR due to mutations, either within the IDR or in domains interacting with it, could disrupt cellular homeostasis as seen in cancers and neurodegenerative disorders associated with PTEN mutations. This is supported by our data indicating that PTEN, as an IDP when mutated, causes several cancers14.

Moreover, the PTEN C-tail IDR exhibits preferential mutations in aromatic residues compared to the ordered region (Figure 2c). The ratio of mutations in aromatic residues in the disordered to ordered region is much higher than any other class of residues (structure breaking, hydrophobic, polar, Cys and Asn), likely attributed to the structure-imparting property of aromatic residue32. Specifically, aromatic residues within IDRs engage in stacking interactions, enhancing nucleation between distinct residues at functional protein-protein interaction interfaces32. Thus loss of this critical structural and functional property imparted by aromatic residues is associated with a disease phenotype. In summary, the disordered PTEN C-tail IDR has functionally evolved to contain a combination of peptides that cannot tolerate mutations.

Disorderliness in PTEN primary interactome drives functional networks

Protein-Protein Interactions (PPIs) typically occur between conserved, structurally rigid regions of two or more proteins, particularly ordered proteins that display energetically favorable, highly-folded conformations. Intriguingly, IDPs lack tertiary structure, yet engage in PPIs, albeit with lower affinities but high specificity1. The lack of structure within IDPs enhances their biophysical landscape, conferring them with the ability to attain structural complementarities required for PPIs. Since IDPs do not conform to a stable structure, they are less compact, providing a larger physical interface and energetic adaptability to interact with multiple proteins1, 7. Thus, conditional folding within IDPs is effectively utilized for interaction with a multitude of binding partners, enabling them to shuttle between several signaling cascades as efficient “cogs”, mediating and regulating PPIs4,7, 33, 34, 35, 36. Indeed, we discovered that PTEN, being an IDP, interacted with more than 400 proteins (Supplementary Table S1) when a combination of online software, literature search and database mining tools were used. Proteins with known PTEN interaction domains were classified as “mapped” (Figure 2d and Supplementary Table S1), whereas those with uncharacterized/predicted interactions were designated as “unmapped” proteins (Supplementary Table S1). Derivation of PTEN primary interactome from the mapped proteins using Cytoscape (http://www.cytoscape.org/) indicated that PTEN disorderliness is efficiently used for interaction with 40 proteins, most existing in distinct functional pathways (Figure 2d, 2e and Supplementary Table S2).

Interestingly, within the PTEN primary interactome, 60% of interactions occurred within the disordered C-tail region. Furthermore, disorder analysis on the primary interactome revealed that 33 proteins (>82%) were IDPs, of which two-thirds interacted with the C-tail IDR (Figure 2e, 2f andSupplementary Table S3), indicating a high propensity for disorder-disorder (D-D)-type interactions.

In order to study evolutionary conservation of the PTEN C-tail and its interactions across species, several sequence alignments were performed (Figure 3a). Sequence alignment of the entire PTEN protein from different animal species shows a good conservation of the catalytic phosphatase domain between vertebrates and invertebrates with 100% sequence conservation for the dual specificity phosphatase catalytic motif HCKAGKGR8 (Supplementary Figure S2). The C-tail shows good conservation in the vertebrate species, likely indicating the recent emergence of the function of PTEN C-tail region in regulating PTEN activity and enriching its PPI potential, translating to its versatile functions. In order to examine the conservation across species for the PTEN C-tail interacting proteins, a literature search was conducted to identify experimentally verified domains/motifs involved in interaction with the C-tail. The domains involved in these interactions with the C-tail for 13 proteins with relevant literature sources for these interactions are part of Supplementary Figure S3. Subsequent sequence alignments for these thirteen proteins (Supplementary Figure S3) shows good sequence homology for the domains/motifs involved in interaction with the PTEN C-tail. These findings support the concept that the PTEN C-tail has evolved in vertebrates to incorporate features that allow it to interact with these proteins.

Figure 3: Sequence conservation in PTEN and its interacting partners reflects functionality.

Sequence conservation in PTEN and its interacting partners reflects functionality. srep02035-f3

Sequence conservation in PTEN and its interacting partners reflects functionality. srep02035-f3

http://www.nature.com/srep/2013/130620/srep02035/images_article/srep02035-f3.jpg

(a) Sequence alignment of the PTEN protein for vertebrate and invertebrate animals. Green color indicates sequence similarity while red indicates sequence dissimilar amino acid residues. All comparisons are made with respect to the human PTEN protein. (b) Network analysis for PTEN was performed to assess its potential as a network hub. The network shows multiple secondary interactions within the 40 mapped proteins, indicating their role in multiple signaling cascades mediated via PTEN. The proteins SMAD2/3, AR, PCAF, ANAPC7, B-arrestin 1 and p53 appear to be critical within these signaling cascades and also happen to be intrinsically disordered (Supplementary Table S3), reinforcing the concept of preferential interactions between disordered proteins. (Analysis Tool: Metacore by GeneGo).

Further, to assess whether PTEN acts as a functional hub protein and regulates pathways through its protein-binding partners, we performed functional network analysis using the Analyze Network option from MetaCore (GeneGo Inc, Thomson Reuters, 2011) (Figure 3b). The PTEN primary interactome was used as input with PTEN as the central node. We identified multiple interactions not only between PTEN (node) and SMAD2/3, AR, PCAF, ANAPC3, ANAPC4, Caveolin, β-arrestin 1 and p53 (edges), but also amongst the edge proteins themselves (Figure 3b). Interestingly, all the edge proteins are themselves highly disordered (Supplementary Table S3). Further supporting this finding, our functional enrichment revealed that 13 proteins (one-third) of the PTEN primary interactome were cancer-related and highly disordered (Figure 4a, Supplementary Table S3 and S4).

Figure 4: Derivation and disorder analysis of the PTEN cancer interactome.

Derivation and disorder analysis of the PTEN cancer interactome. srep02035-f4

Derivation and disorder analysis of the PTEN cancer interactome. srep02035-f4

http://www.nature.com/srep/2013/130620/srep02035/images_article/srep02035-f4.jpg

  • Derivation of the PTEN Cancer Interactome. Functional enrichment of the PTEN primary interactome identified 13 cancer-related proteins which are also intrinsically disordered. Subsequently, the PTEN secondary interactome was derived from the primary PTEN interacting proteins. A subset of the secondary interactome was designated as the PTEN Cancer Interactome and it represents the proteins that interact with the 13 cancer-related proteins of the primary interactome. (b) PTEN Cancer Interactome. PTEN is the primary node that interacts with the 13 cancer-related proteins representing the partial primary interactome. Proteins that interact with each of the 13 cancer-related proteins comprise the secondary interactome. Disordered proteins are represented in red while ordered proteins are shown in blue. Cancer-related proteins in the PTEN primary interactome were identified using IPA (Ingenuity® Systems, ingenuity.com). (c) We identified 40 proteins that are part of the PTEN primary interactome of which 13 are highly disordered (IDP) and identified as potential cancer network hubs based on functional network analysis. We further identify 299 IDPS from the secondary PTEN interactome. A filter for cancer-related proteins revealed that approximately two-thirds of the IDPs that form the secondary interactome (193 out of 299) are involved in oncogenesis, suggesting a high degree of functional enrichment. (Functional network analysis was performed using IPA (Ingenuity® Systems,www.ingenuity.com).Full size image (805 KB)

Pliant PTEN secondary interactome relays function of the primary network

The disorderliness of the PTEN primary interactome prompted us to investigate the possibility that PTEN radiates its function via a malleable network of IDPs that extends beyond the primary interactome. Therefore, we derived the PTEN secondary interactome (Supplementary Table S5) and ascertained the interaction of 13 cancer-related proteins identified in the primary interactome (Figure 4a). The entire PTEN secondary interactome consisted of 299 IDPs, of which 193 IDPs (two-thirds) were associated with the 13 cancer-related proteins, generating a “PTEN-Cancer Interactome” (Figure 4, Supplementary Table S5 and S6). Thus, two-third of the IDPs within the PTEN secondary interactome associates with one-third of the cancer related IDPs within the PTEN primary interactome, indicating that cancer-related functions are driven by IDPs in the PTEN interactome and that the flexibility of IDP-IDP interactions modulates diverse functions; dysregulation of which causes cancers.

Functional network analysis of the 193 cancer-related IDPs identified 31 proteins that shared multiple nodes (Figure 5a and Supplementary Table S6). We overlaid this network with the cancer-related IDPs of the primary interactome to predict functionally critical protein hubs (indicated in yellow circles in Figure 5a and b). Our analysis revealed 16 proteins as highly populated hubs, most enriched in disordered regions, again demonstrating that a high degree of structural and functional association between the hubs required IDP-IDP interactions (Figure 5b). The involvement of these hubs in multiple, critical oncogenic signaling pathways make them attractive drug targets in the field of clinical oncology. Our bioinformatic analysis resonates well with observed biological phenomena as seen in the case of MDM2 protein, which is a major PPI hub regulating p53. Interaction of the human androgen receptor (AR) protein and MDM2 influences prostate cell growth and apoptosis37. Mdm2-Daxx interaction activates p53 following DNA damage38, and Daxx binds and inhibits AR function39. Conversely, the breast cancer susceptibility gene 1 (BRCA1) interacts directly with AR and enhances AR target genes, such as p21(WAF1/CIP1), that may result in the increase of androgen-induced cell death in prostate cancer cells40. Further, BRCA1 complexes with Smad3 and is inactivated, leading to early-onset familial breast and ovarian cancer41. Within the same network, MDM2 inhibits the transcriptional activity of SMAD proteins including SMAD342, thereby, emerging as a major player in prostrate, breast and ovarian cancer. Loss of PTEN, on the other hand, results in resistance to apoptosis by activating the MDM2-mediated antiapoptotic mechanism. We also identified proteins like NCL, DAXX and SUMO that play critical roles in mediating cancers as being a part of the PTEN centric cancer interactome (Figure 5b). Interestingly, all of the 16 predicted hubs can be traced back to PTEN (either directly or through other signaling adaptors) reinforcing our analysis (Figure 5c). These findings support the prevailing concept of preferential interaction between disordered regions of two distinct proteins; with PTEN being the common disordered interacting hub, giving functional centrality to PTEN in many critical cellular pathways.

Figure 5: Predicting functionally relevant network hubs in the PTEN cancer interactome.

Predicting functionally relevant network hubs in the PTEN cancer interactome. srep02035-f5

Predicting functionally relevant network hubs in the PTEN cancer interactome. srep02035-f5

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(a) Methodology to identify functional hubs within the PTEN Cancer Interactome. The PTEN Cancer Interactome contains 193 IDPs that are potential hubs. Over-represented IDPs (or IDPs with multiple occurrences) in the PTEN Cancer Interactome would have a greater propensity to function as hubs. Upon sorting for over-represented IDPs the list of 193 proteins is brought down to 31 proteins. In order to assess the possibility of these 31 proteins as functional hubs a network analysis is warranted. (b) We identified 31 potential hubs based on multiple associations from within the 193 cancer-associated IDPs of the PTEN secondary interactome. Regulatory networks derived from these 31 proteins were overlaid with a similar network from the 13 cancer-related proteins. Based on the number of associations within the network, we identify 16 potential functional hubs in the PTEN cancer interactome (indicated in yellow). Regulatory interactions were generated using the Transcriptome Browser tool (Lopez et al, 2008). (c) Functional network analysis of the 16 predicted hubs. In order to assess the functional association of the 16 predicted hubs with PTEN – a network analysis with PTEN as a central node was done. The analysis identifies MDM2 protein, a major regulator of p53, as one of the major PPI hubs in the PTEN cancer interactome. A number of other critical cancer-related proteins, such as AR, SMAD2/3 and PDGFRB that are part of the PTEN primary interactome, feature prominently in the PTEN cancer interactome. We also identified proteins like NCL, DAXX and SUMO that play critical roles in mediating cancers as being a part of the PTEN centric cancer interactome. Interestingly, all of the 16 predicted hubs can be traced back to PTEN (either directly or through other signaling adaptors) reinforcing our analysis. (Functional network analysis was performed using IPA (Ingenuity® Systems, www.ingenuity.com).

To further validate our methodology in using intrinsic disorder and cancer as filters to identify key signaling hubs, we compared our data sets with a previously published cancer signaling data set. We derived 7 common hubs (Supplementary Table S7), which were extended using the expansive human signaling network described previously43, 44, 45, 46 to obtain the PTEN associated cancer interactome (Figure 6a). An extensive disease associated network analysis using IPA validated our predictions as all the seven predicted hubs had an extensive cross-talk across multiple cancer disease types (Figure 6b).

Figure 7: Biochemical features modulating PTEN PPIs.

Biochemical features modulating PTEN PPIs. srep02035-f7

Biochemical features modulating PTEN PPIs. srep02035-f7

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(a) A PTEN linked cancer network was derived using seven of the 16 predicted cancer hubs that were common with the human cancer associated gene set. The associated partners of the seven hubs were extracted from the human signaling network (Cui et al, 2007, Awan et al, 2007, Li et al, 2012 and Newman et al, 2013). Red color denotes the potential cancer hubs and blue color are their associated partners. Topological analysis identifies p53 as the most significant network hub in the PTEN linked cancer network (Supplementary Table S7). (b) Disease associated network of PTEN cancer hubs. A functional network was constructed with the seven topologically relevant hubs identified previously using the Core Analysis function from the IPA suite to derive the primary network (denoted as MP). A disease network was constructed using the Path Designer option and disease associated biological functions were overlaid on the primary network. Fx denotes the different functions associated with the members of the networks.

Modulation of PTEN PPIs by linear binding motifs

Recent evidence has shown that IDPs mediate PPIs via short linear amino acid sequences (~20 residues) called Molecular Recognition Elements (MoREs) or Molecular Recognition Features (MoRFs)35, 47. MoRFs undergo disorder-to-order transitions upon binding and adopt thermodynamically stable well-defined structures47, increasing the propensity of IDPs to interact with a vast repertoire of proteins. MoRFs also display molecular recognition elements that capture the binding partner proteins with high specificity. These partner-dependent conformational differences are critical to imparting versatile binding properties to IDRs35.

Since the PTEN IDR engages in multiple PPIs, we tested the possibility for the existence of MoRFs. The MORFP red algorithm48 revealed that PTEN contains major MoRF sites at amino acids 273–279 (part of the disordered CBR3 loop of the C2 domain), amino acids 339–347 (in close vicinity of the disordered C-tail) and amino acids 395–403 (part of the disordered C-tail) (Figure 7a and Supplementary Figure S4). The primary restriction of MoRFs to the PTEN C-tail IDR or adjacent regions indicates that these MoRFs directly participate in modulating PPI functions (Figure 7a). However, mutational analysis within MoRFs is required to establish their active role in functional PPIs.

Figure 7: Biochemical features modulating PTEN PPIs.

Biochemical features modulating PTEN PPIs. srep02035-f7

Biochemical features modulating PTEN PPIs. srep02035-f7

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(a) MoRFs in the PTEN C-tail IDR. MoRFpred (Disfani et al, 2012), a computational tool, was used to identify MoRF regions within the PTEN protein (Supplementary Figure S4). The MoRFs in the vicinity of the C-tail IDR are highlighted in red. Interestingly, all of the major MoRFs (with a length greater than 5 residues) are observed in the vicinity of disordered regions (either part of the disordered CBR3 loop of the C2 domain or the C-tail IDR) indicating a positive correlation between intrinsic disorder and PPIs. (b) ELMs in PTEN C-tail IDR. Eukaryotic Linear Motifs (or ELMs) are 3–11 amino acid long sequences that mediate PPIs. IDRs are particularly enriched in ELMs (Dinkel et al, 2012). The linear motifs occurring in the disordered segment of PTEN (tail + PDZ domain) have been highlighted. The motifs with a high conservation score (>0.75) are indicated in red. Interestingly, all of the motifs with a high conservation score are restricted to the C-tail IDR. (c) Phosphorylation sites in the C-tail IDR. Phosphorylation of PTEN, particularly on serine and threonine residues in the disordered region, regulates the function and stability of PTEN. Phosphorylation occurs at Ser 362, Thr 366, Ser 370, Ser 380, Thr 382, Thr 383, Ser 385 by various enzymes such as Casein Kinase II, Glycogen synthase kinase 3-B and Polo-like kinase 3. Each of these phosphorylation events helps regulate the availability and stability of the PTEN molecule within the cell.

Protein-protein interactions are also facilitated by very short motifs (3–10 amino acids) called Short Linear Motifs (SLiMs) or Eukaryotic Linear Motifs (ELMs)49, 50. Because of their short sequences, ELMs arise/disappear by simple point mutations, providing the evolutionary plasticity that the ordered protein domains lack. Thus, ELMs easily adapt to novel interactions in signaling pathways, where rapid assembly/disassembly of multi-protein complexes is a prerequisite. The frequent occurrence of ELMs in a typical proteome indicates their critical cellular functions. Consistent with this notion, a higher density of ELMs are observed in hub proteins and IDPs50. Since ELMs have short sequences, they interact with low-affinity, however, they engage in highly cooperative binding in protein complexes, triggering productive signaling50. Therefore, at increased intracellular local concentrations they competitively bind to mutually overlapping physiological targets of each other as seen with PDZ, SH2 and PTB interaction domains found in cancer-associated proteins and in IDRs49, 50. As PTEN contains a PDZ-binding motif within the IDR (Figure 1a and c), we probed for the existence and features of ELMs in PTEN using The Eukaryotic Linear Motif Resource (http://elm.eu.org). We identified 34 different classes of ELMs in PTEN that mediate PPIs (Supplementary Figure S5). Interestingly, the four ELMs that are most conserved (conservation score>0.75) occurred within the PTEN C-tail IDR, indicating its high level of functional/biological significance (Figure 7b). ELM functions are further modulated by post-translational modifications, mainly by phosphorylation50. Indeed, the PTEN IDR possesses nine phosphorylation sites51, 52(Figure 7c).

PTEN phosphorylation modulates intramolecular association and PPI function

Post-translational Modifications (PTMs) in IDPs facilitate PPIs5. Modifying enzymes readily dock on structurally flexible IDRs, making them a hot spot for PTMs4, 7, 53, 54. Consistent with this notion, regulatory cancer-associated proteins have twice as much disorder and undergo more frequent phosphorylation/dephosphorylation than other cellular proteins as predicted by DISPHOS (a DISorder-enhanced PHOSphorylation prediction software)54, implicating a tight interconnection between protein phosphorylation and disorder. Consistent with the function of PTM in IDRs, clustering of Ser and Thr phosphorylation sites (Figure 7c) in the C-tail IDR regulates PTEN stability, membrane association and activity19, 20. Phosphorylation in the PEST [proline (P), glutamic acid (E), serine (S) and threonine (T)] domain within the C-tail IDR (amino acids 352 to 399) inhibits degradation of PTEN51. Casein kinase II (CK II), Glycogen synthase kinase 3-beta (GSK3-β) and PLK3 (Polo-like kinase 3) phosphorylate Ser and Thr residues within the IDR, each providing a distinct function51 (Figure 7c). The microtubule-associated serine/threonine (MAST), serine/threonine kinase 11(STK11) or LKB1 and casein kinase I (CKI) kinases have also been implicated in PTEN phosphorylation. STK11/LKB1 modifies T383, while CKI modifies T366, S370 and S38552. Indeed, our DISPHOS prediction for C-tail IDRs supports these experimental observations (Supplementary Figure S6).

Substrate-kinase interactions are typically of the disordered-ordered (D-O) type and are stabilized by hydrogen bonding (Figure 7c), a hallmark of IDRs54. Indeed, computational analysis revealed that large ordered regions comprising the catalytic domains of CKII, GSK3B, PLK3, Rak, and Src kinases interact with the C-tail IDR (Supplementary Table S8), indicating that PTEN engages in D-O type intermolecular interactions with the modifying kinases.

At the intramolecular level, phosphorylation at C-tail residues triggers a conformational change in PTEN, inhibiting its membrane association and, therefore, its lipid phosphatase activity18, 19, 21, 55. The phosphorylated C-tail IDR folds onto the PD and C2 domains giving rise to the “closed-closed” conformation of PTEN (Figure 8a) that is incapable of interaction with the membrane18, 20. The “closed- closed” form of PTEN is enzymatically inactive and cannot convert PIP3 to PIP2. The identification of the exact resides involved in this intramolecular interaction remains an active area of research18, 20, 56.

Figure 8: Targeting PTEN C-tail IDR.
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Most PTEN functions emanate from the C-tail IDR, including aberrant PPIs that hyper-activate oncogenic pathways. (a) Phosphorylation mediates an intramolecular interaction in the PTEN molecule. Phosphorylation causes a conformational change in PTEN converting it to the enzymatically inactive “closed closed ” form wherein the flexible tail folds onto residues in the C2 and phosphatase domain, thereby making it incapable of interacting with the membrane. Dephosphorylation (by an unknown phosphatase or via auto-dephosphorylation) converts PTEN to the “open-closed” form. Electrostatic interactions, mediated by the PBM, further convert PTEN to the “open-open” form wherein it binds to the membrane and acts as a lipid phosphatase converting PIP3 to PIP2, thereby, abrogating signaling via the PI3K/Akt/mTOR pathways. Subsequent to membrane binding, several E3 ubiquitin ligases polyubiquitinate PTEN marking it for proteasomal degradation. Phosphorylation, by inducing the intramolecular interaction, masks the ubiquitination sites thereby increasing the half-life of the PTEN protein within the cell. Therefore, phosphorylation negatively regulates PTEN function but positively regulates its stability. (b) PTEN IDR engages in PPIs of the disorder:order type (D-O type). As revealed in the present study, this occurs via the use of a MoRF or SLiM region. Therefore, designing a peptidomimetic drug molecule that competes with the PTEN MoRF/SLiM binding to the ordered protein will abrogate PTEN binding, therefore PTEN function. PTEN IDR is highly accessible to multiple kinases that phosphorylate and modulate PTEN function, mainly its inhibition via intra-molecular interactions. PTEN inhibition hyper-activates the PI3K/AKT/mTOR pathway, which increase the oncogenic potential of the cell and drives cancer growth. Therefore, targeting the PTEN C-tail IDR with small molecules that bind and sterically hinder PTEN phosphorylation and/or intra-molecular interactions will be an ideally adjunctive therapy to multiple inhibitor therapy targeting of the PI3/AKT/mTOR pathway.

It was recently shown that the phosphorylation events of PTEN occur in two independent cascades of ordered events, with the S380–S385 cluster being modified prior to the S361–S70 cluster52. Even within the two clusters, the phosphorylation events follow a specific pattern with a distributive kinetic mechanism. Not surprisingly, distributive kinetics is energetically favorable on protein domains that are highly disordered with multiple ensembles of flexible structures52. Thus the dynamic nature of these phosphorylation events is contingent to the inherent flexibility in the PTEN structure driven by intrinsically disordered C-tail crucial for PTEN stability and localization within the cell (Figure 8a).

Targeting intrinsic disorder in PTEN and its interactome

Drug targeting to critical protein regions can mitigate aberrant cellular processes driving oncogenesis57. However, despite numerous clinical trials with molecularly targeted therapies, failure rates for cancer treatments remain high. Conventional therapies targeting pathway-specific kinases suffer from “off-target effects” and often fail due to the emergence of compensatory and alternative pathways58. As a novel approach, facile drug targeting to IDRs within critical signaling hub proteins is highly plausible59, 60, 61. Moreover, as IDRs undergo extensive PTMs53 and engage in PPIs4, 34, 36, the multitude of resulting protein interactions (normal and aberrant) can be targeted concomitantly with a cocktail of distinct inhibitors, which dampens oncogenic signaling60.

Indeed, targeting PPIs is a more selective treatment strategy over conventional enzyme inhibitors60. However, disruption of multiple ordered interfaces within PPIs by small molecule inhibitors remains challenging62. The advantage of targeting IDPs engaged in PPIs is that, unlike ordered proteins, they engage in PPIs via MoRFs or ELMs, which are small peptide regions that bind with low affinity and thus are susceptible to disruption by small molecule inhibitors59. Consistent with this notion, small molecules disrupted highly disordered complexes of p53-Mdm2 and c-Myc-Max interactions by inducing order upon binding60, 63. Likewise, targeting the PTEN C-tail IDR may reduce its intra- and inter-molecular interactions and limit accessibility to enzymes mediating PTMs (Figure 8b), providing a means to increase PTEN activity. Our analysis shows that since the C-tail IDR is rich in conserved MoRFs/SLiMS, targeting these regions will prove to be a rational therapeutic modality for a large number of cancers that show compromised PTEN activity or hyperactivation of the oncogenic PI3K/AKT/mTOR pathway9, 10, 11. Since reductions in the levels and activity of PTEN are sufficient to drive oncogenesis11, 14, 15, increasing PTEN activity is an ideal therapy for cancers associated with hyperactive PI3K-signaling.

Discussion

Recent studies on genome- and proteome-wide molecular alterations in diseases indicate that pathological conditions are caused by perturbations in complex, highly interconnected biological networks64. Thus, current reductionist approach of studying structure-function relationship in diseases has limited our abilities to discover effective targeted therapeutics. In an attempt to overcome these limitations, in the current study, we have undertaken a novel approach to drug discovery that exploits systems and network biology at the structural, topological and functional level. Using PTEN, a tumor suppressor, we have applied computational and systems biology approaches and integrated extensive data-mining and biochemical properties of IDP interactions to reach a finer understanding of PTEN function. These results have identified PTEN C-tail IDR and several hub proteins in PTEN-driven molecular network implicated in human diseases as therapeutic targets, enhancing the repertoire of clinically relevant biological targets for pharmacotherapy.

Our derivation and analysis of PTEN primary and secondary interactome indicates that altered levels or interactions of IDPs perturb myriad cellular signaling pathways, leading to pathological conditions including cancer. IDPs have the propensity to aggregate and cause cellular toxicity65. Therefore, PTEN as an IDP has evolved a mechanism, wherein, the level of active PTEN, its cellular localization and PTEN-PPIs are regulated via phosphorylation of the C-tail IDR. Furthermore, evolutionarily conserved ELMs and MoRFs that we have identified within the C-tail IDR may play a critical role in orchestrating the formation and function of the PTEN interactome.

Increase in complexity of PPIs is either directed by the number and type of proteins or by increasing the number of interactions required to execute cellular functions66. To delineate how PTEN executes myriad functions, we first derived the PTEN primary interactome. We found 40 proteins to directly interact on the PTEN molecule, out of which 25 were associated with the C-tail IDR, consistent with the concept that disorderliness within PTEN executes its myriad functions. To enhance our understanding of PTEN functions in the context of multiple distinct pathways at the systems-level, we delineated functional networks operating within the primary interactome. Our findings showed a high degree of cross-talk between edges, implying that shared regulatory modules, comprised of multiple signaling cascades, operate via PTEN-mediated interaction networks. When these networks are altered, diseases ensue with extreme functional penalties. We also found that the edge proteins were themselves highly disordered indicating that disorderliness within the PTEN primary interactome confers functional versatility. Supporting this notion, 13 proteins that were functionally classified as cancer-related were also highly disordered forming a pliable “PTEN-Cancer Interactome”. Thus, PTEN lesions influence the flexibility of IDP-IDP interactions modulating diverse functions, likely causing cancer.

Owing to the inherent ability of PPIs to be flexible while being complex, specific cellular functions are readily fine-tuned as per the biological demands. Emerging evidence suggests that certain features on the IDRs are recognized as a way of conferring plasticity to protein interaction networks. Consistent with this concept, our data suggest that PTEN, a hub protein containing an IDR, likely utilizes MoRFs and ELMs, gets differentially modified via PTMs, acquiring complementary structures to engage and modulate PPI activity by facilitating adaptive binding to multiple protein partners in many cellular pathways. Thus, our present work provide a novel entrée in targeting intrinsic disorder in PTEN and its interactome to dampen the aberrant PI3K-signaling that drives many cancers. First, imparting order to the PTEN structure may help dampen multiple oncogenic signaling pathways mediated via the 16 hub proteins identified in the present study, by limiting their affinity for PPIs. Second, targeting intrinsic disorder in PTEN and its interactome can become an adjunctive or alternative approach to the use of various kinase inhibitors, which are toxic and have many off-target effects when used to mitigate the aberrant hyperactivation of PI3K/AKT/mTOR oncogenic signaling pathway. Taken together, the present findings provide a novel entrée to design strategies for drug discovery and may become a logical intervention in the pharmacotherapy of cancer and other PTEN-associated disease treatment modalities.

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Personalized Medicine in Cancer [Chapter 3]

Writer and Curator:  Larry H Bernstein, MD, FCAP

Personalized Medicine in Cancer

This chapter has the following ten Subsection:

3.1 The path to personalized medicine

3.2 Role of Nanobiotechnology in Developing Personalized Medicine for Cancer

3.3 The HER-2 Receptor and Breast Cancer: Ten Years of Targeted
Anti–HER-2 Therapy and Personalized Medicine

3.4 Personalized Medicine is not yet here

3.5 Biomarkers for personalized oncology: recent advances and future challenges.

3.6 Personalized oncology: recent advances and future challenges.

3.7  Pharmacogenomic biomarkers for personalized cancer treatment.

3.8 Limits to forecasting in personalized medicine: An overview

3.9 The genome editing toolbox: a spectrum of approaches for targeted modification

3.10 The Path to Personalized Medicine

 

3.1 The path to personalized medicine

Joanne M Meyer* and Geoffrey S Ginsburg
Current Opinion in Chemical Biology 2002, 6:434–438

Advances in personalized medicine, or the use of an individual’s molecular profile to direct the practice of medicine, have been greatly enabled through human genome research. This research is leading to the identification of a range of molecular markers for predisposition testing, disease screening and prognostic assessment, as well as markers used to predict and monitor drug response. Successful personalized medicine research programs will not only require strategies for developing and validating biomarkers, but also coordinating these efforts with drug discovery and clinical development.

The realization of personalized medicine, or the fine tailoring of the practice of medicine to an individual, is being fostered through numerous efforts aimed at characterizing individual differences in molecular processes underlying disease pathogenesis, disease progression and the response to therapeutics. Once these molecular differences are understood, therapeutic development will be enhanced by using the information to identify individuals more likely to benefit from a given intervention strategy. High-throughput genomic technologies are already providing the data that will serve as the foundation of personalized medicine.

Individual differences in the development of disease and response to therapeutics
Clearly, for many common diseases, there is abundant evidence to suggest that the molecular underpinnings of disease susceptibility, and its natural history, differ markedly among individuals. For example, while it has been demonstrated in numerous investigations that the development of obesity, asthma, type 2 diabetes and cardiovascular disease are under genetic control [1–4], there is no evidence to suggest that the genetic basis is due to variation in just a single gene. Instead, the consensus has emerged that subtle genetic differences in one or many of several genes serve as risk factors for these illnesses. Thus, while genetic variants in the melanocortin-4 receptor may explain some risk for developing obesity [5], and polymorphisms in PPARgamma may correlate with the risk of developing type 2 diabetes [6•], these variants do not explain all of these genetic diseases. There are certainly more genetic variants, or predisposition markers, to uncover. In the context of personalized medicine, the ultimate goal of these types of studies is to provide a suite of markers that can be used to assess one’s lifetime risk of developing disease in the presence of various environmental (e.g. diet, lifestyle) variables.

As with disease predisposition, individual differences characterize disease progression. For example, some individuals with impaired glucose tolerance will proceed quite rapidly to type 2 diabetes, whereas others proceed slowly. Similarly, individuals diagnosed with rheumatoid arthritis may or may not develop erosive disease. In both of these cases, genetic variation, that is, variation measured at the DNA level, may be a good predictor of the individual differences that emerge as disease progresses. For example, Brinkman et al. [7] have demonstrated that a polymorphism in TNF-α correlates with erosive rheumatoid arthritis, but shows no association with non-erosive disease. Alternatively, variation in disease progression may be best predicted by a combination of genetic and environmental factors, the impact of which is indexed through changes in gene expression in relevant tissues, or changes in secreted protein levels in serum or synovial fluid. In our laboratories, we are using a range of genomics technologies to find markers for disease progression that are both stable (DNA) as well as dynamic (mRNA, protein), giving us the opportunity to evaluate the utility of both types of markers in prospective studies.

Given that individual variability in disease predisposition and progression exists and has the potential of being molecularly characterized, it is not at all surprising that such differences also characterize response to therapeutics (see Figure 1). Marked individual variation in the efficacy and toxicity of therapeutic compounds is common and can have a profound impact on the success of a pharmaceutical clinical development program. Clearly, molecular markers that predict the variation in these endpoints could be extremely useful in clinical trials, drug development and clinical practice, as they would allow the identification of patients who would benefit most from the drug.

Technological advances drive broad biomarker discovery. While the existence of individual differences in disease predisposition, progression and response to therapeutics is far from a novel concept, our ability to comprehensively measure the molecular markers that track these processes, and draw proper inferences from large amounts of molecular data, is novel. Over the past decade, significant advancements have been made in technologies to discover variation at the mRNA, DNA and protein levels. Indeed, with the advent of glass and nylon microarray technologies for gene-expression studies, it is quite feasible to characterize the expression levels of 30 000 genes in tissue samples from dozens, if not hundreds, of individuals. Certainly, several years ago, although it would have been theoretically possible to assess this number of genes using northern blot analysis, it never would have been undertaken in a sample from even a single individual. In the same fashion, highthroughput technologies for DNA polymorphism discovery and single nucleotide polymorphism (SNP) genotyping, coupled with broad academic and commercial initiatives to characterize genetic variation genome-wide [8•], are resulting in catalogs of variants that can be used in large-scale experiments. To complement these efforts, searches for ‘haplotype blocks’, or correlated patterns of SNPs that can be adequately represented by fewer SNPs, are underway and have the promise of reducing the amount of genotyping required for genome-wide searches [9•,10•]. For proteinbased discovery initiatives, traditional 2D electrophoresis experiments are used in conjunction with advanced mass spectrometry to discover protein markers in a range of complex fluids, including serum, plasma, synovial fluid and cerebral spinal fluid.

Coupled with the advent of these technologies have been extensive efforts to collect appropriate tissues and fluids for mRNA, DNA and protein analysis. These collections have been part of pharmaceutical clinical trials, as well as clinical studies established for the purpose of characterizing biomarkers. The latter studies may involve small numbers of patient samples for initial biomarker discovery efforts, as well as large-scale, disease registry initiatives designed to evaluate and, in some cases, prospectively validate, biomarkers in the relevant patient populations.

Figure 1  (not shown) The role of molecular biomarkers in disease management. Areas where molecular biomarkers will benefit personalized medicine include disease predisposition, screening and prognosis, as well as drug response and drug monitoring. The nature of the markers (DNA, mRNA or protein) will vary with the disease and the stage of their application. Rx indicates treatment.

The predictive value of biomarkers The impact that advanced genomic technologies and carefully designed biomarker studies will have on the personalization of medicine is foreshadowed in the current literature. For example, Mallal et al. [13•] conducted a pharmacogenetic investigation (i.e. a genetic study of drug response) of abacavir, an HIV-1 nucleoside reverse transcriptase inhibitor. They implicated MHC alleles that predict response to hypersensitivity among 5% of the HIV cases receiving the drug. Their findings suggest that screening patients for the presence of the predisposing MHC haplotype could reduce the prevalence of hypersensitivity to abacavir from 9% to 2.5%. While this study is small in scale in its characterization of genetic variation, it adds to the existing literature on several other variants (including those in MDR1, the multidrug transporter P-glycoprotein and CYP2D6, a cytochrome P450 isoszyme) that correlate with the pharmacokinetic (drug clearance) characteristics of protease inhibitors and non-nucleoside reverse transcriptase inhibitors [14]. Additionally, genetic polymorphisms in chemokines and chemokine receptors (including RANTES, MIP-1α and CCR5) have been found to correlate with both the susceptibility to HIV-1 infection and the progression of disease [15•]. Taken together, these findings may lead to the development of a panel of polymorphisms that would personalize HIV therapy, by determining when to initiate therapy and how to choose compounds that will maximize efficacy and minimize adverse effects.

Figure 2 (not shown) Personalized medicine — integrating drug discovery and development through molecular medicine. Genomically derived biomarkers are being identified throughout the drug discovery and clinical development process. They will not only support personalized medicine, but will also enhance drug discovery and clinical development by generating new targets, validating targets and identifying patients that will benefit from novel therapeutics.

Pharmacogenetic efforts have also successfully characterized polymorphisms that correlate with response to asthma therapeutics. For example, Drazen et al. [16•] showed that a promotor polymorphism in 5-lipoxygenase, which alters transcription levels of the gene, also correlates with response to a derivative of the drug Zileuton, a 5-lipoxygenase inhibitor. Of the individuals who did not respond to Zileuton, 20% carried rare variant alleles at this locus. By contrast, all of the responders had wild-type alleles. Similarly in a study of genetic polymorphisms of the β-adrenergic receptor, Drysdale et al. [17•] demonstrated that a haplotype, or SNP signature across the gene, correlated strongly with asthma patients’ response to β-agonists. These two examples again demonstrate the possibility of using an individual’s genotype to suggest a therapeutic strategy that is more likely to be efficacious. Certainly, before such tests are incorporated into clinical practice, additional genetic markers would have to be coupled with the existing polymorphisms to make the resulting tests highly sensitive and specific.

In addition to these DNA-based strategies, recent applications of proteomics and expression profiling have generated a range of screening, prognostic and drug-response or ‘pharmacogenomic’ biomarkers. Many advances in the use of these technologies have been in oncology, where there is a tremendous need for serum-based screening markers and where tissue samples for expression profiling studies are easily obtained. For example, Petricoin et al. [18•] demonstrated that proteomic spectra, derived from a mass spectrometry analysis of serum, could be used to distinguish women with ovarian cancer from unaffected women. Indeed, the protein markers on a ‘training set’ of 100 samples and a validation set of 110 additional samples, had a sensitivity of 100% and a specificity of 94%. These encouraging results suggest that a serum-based protein assay may indeed become a viable mode of ovarian cancer screening in the general population. mRNA strategies for identifying prognostic markers for cancers have also proved successful. For example, in our collaborative studies [19•], we have shown that Melastatin, a melanocyte-specific gene identified through a genomics analysis of benign and malignant melanoma, is an effective prognostic marker for cutaneous malignant melanoma. In this work, uniform melastatin mRNA expression correlated strongly with disease-free survival, even after adjusting for other prognostic factors. In a similar fashion, mRNA strategies have generated pharmacogenomic markers for ovarian cancer. Hartmann et al. [20] studied the expression of 30 000 human genes in 51 tumors that were sensitive and resistant to platinum–paclitaxel chemotherapy and identified a subset of 10 markers that were highly predictive of outcome in an independent sample of tumors. Overall, these examples of biomarker studies in oncology demonstrate the broad application such markers will have for cancer screening, prognosis and response to therapeutics.

Turning biomarker discoveries into personalized medicines All of the examples cited provide excellent demonstrations of the power of new technologies to deliver a range of biomarkers that index individual differences in disease predisposition, progression and response to therapeutics. Thus, they clearly form a basis for the ‘personalization’ of medicine. However, the discovery of these markers is not sufficient for the pharmaceutical industry to deliver personalized medicines. Indeed, the delivery of such medicines will require the careful integration of biomarker discovery and validation programs into drug discovery and clinical development programs (see Figure 2). This integration will serve two key purposes. First, and foremost, by initiating SNP, expression profiling and proteomics biomarker programs early on in the drug discovery process, one can carefully weave the discovery and validation of biomarkers into drug discovery and development timelines; the risk of ‘retro-fitting’ biomarker programs to a clinical trial would be avoided.

Conclusions Clearly, several challenges remain to achieve a successful integration of large-scale, biomarker studies with drug development. While there has been an incredible advance in high-throughput, molecular technologies, over the past several years, further improvements in technologies and validation strategies are required to capture the true extent of individual differences in molecular markers. For example, although it is plausible to consider screening the genome for SNPs or haplotypes that correlate with disease pre-disposition or drug response, the current cost of SNP genotyping makes this impractical. Additionally, bioinformatic and statistical advances are needed to extract the most relevant data from the wealth of molecular information generated by new technologies, and these advances must be effectively communicated to the heath-care environment. Finally, and most importantly, plans must be in place to provide adequate validation for the enormous number of candidate biomarkers that will emerge from the studies. Validation will require access to large, and in some cases, prospective, collections of well annotated clinical samples with appropriate consent and security issues addressed. While these issues, as well as the commercial and regulatory considerations around the development of personalized medicines, are indeed challenging, the successful execution of biomarker programs will have an enormous impact on our ability to tailor medical practice to the individual.

3.2 Role of Nanobiotechnology in Developing Personalized Medicine for Cancer

K. K. Jain
Technol Cancer Res Treat Dec 2005; 4(6): 645-650

http://dx.doi.org:/10.1177/153303460500400608

Personalized medicine simply means the prescription of specific therapeutics best suited for an individual. Personalization of cancer therapies is based on a better understanding of the disease at the molecular level. Nanotechnology will play an important role in this area. Nanobiotechnology is being used to refine discovery of biomarkers, molecular diagnostics, drug discovery and drug delivery, which are important basic components of personalized medicine and are applicable to management of cancer as well. Examples are given of the application of quantum dots, gold nanoparticles, and molecular imaging in diagnostics and combination with therapeutics – another important feature of personalized medicine. Personalized medicine is beginning to be recognized and is expected to become a part of medical practice within the next decade. Personalized management of cancer, facilitated by nanobiotechnology, is expected to enable early detection of cancer, more effective and less toxic treatment increasing the chances of cure.

3.3 The HER-2 Receptor and Breast Cancer: Ten Years of Targeted Anti–HER-2 Therapy and Personalized Medicine

Jeffrey S. Ross,  Elzbieta A. Slodkowska,  W. Fraser Symmans, et al.
The Oncologist 2009; 14:320 –368
http://cme.theoncologist.com

Objectives:

  1. Contrast the current strengths and limitations of the three main slide-based techniques (IHC, FISH, and CISH) currently in clinical use for testing breast cancer tissues for HER-2 status.
  2. Compare the efficacy of trastuzumab- and lapatinib-based regimens in the adjuvant and metastatic settings as reported in published clinical trials and regulatory approval databases.
  3. Contrast the list of biomarkers that have been associated with clinical resistance to trastuzumab and lapatinib and describe their current level of validation.

The human epidermal growth factor receptor (HER-2) oncogene encodes a transmembrane tyrosine kinase receptor that has evolved as a major classifier of invasive breast cancer and target of therapy for the disease. The validation of the general prognostic significance of HER-2 gene amplification and protein overexpression in the absence of anti–HER-2 targeted therapy is discussed in a study of 107 published studies involving 39,730 patients, which produced an overall HER-2– positive rate of 22.2% and a mean relative risk for overall survival (OS) of 2.74. The issue of HER-2 status in primary versus metastatic breast cancer is considered along with a section on the features of metastatic HER- 2–positive disease. The major marketed slide-based HER-2 testing approaches, immunohistochemistry, fluorescence in situ hybridization, and chromogenic in situ hybridization, are presented and contrasted in detail against the background of the published American Society of Clinical Oncology–College of American Pathologists guidelines for HER-2 testing. Testing issues, such as the impact of chromosome 17 polysomy and local versus central HER-2 testing, are also discussed. Emerging novel HER-2 testing techniques, including mRNA-based testing by real-time polymerase chain reaction and DNA microarray methods, HER-2 receptor dimerization, phosphorylated HER-2 receptors, and HER-2 status in circulating tumor cells, are also considered. A series of biomarkers potentially associated with resistance to trastuzumab is discussed with emphasis on the phosphatase and tensin homologue deleted on chromosome ten/Akt and insulin-like growth factor receptor pathways. The efficacy results for the more recently approved small molecule HER- 1/HER-2 kinase inhibitor lapatinib are also presented along with a more limited review of markers of resistance for this agent. Additional topics in this section include combinations of both anti–HER-2 targeted therapies together as well as with novel agents including bevacizumab, everolimus, and tenespimycin. A series of novel HER-2–targeting agents is also presented, including pertuzumab, ertumaxomab, HER-2 vaccines, and recently discovered tyrosine kinase inhibitors. Biomarkers predictive of HER-2 targeted therapy toxicity are included, and the review concludes with a consideration of HER-2 status in the prediction of response to non–HER-2 targeted treatments including hormonal therapy, anthracyclines, and taxanes.

Biology, Pathology, Diagnosis, And Clinical Significance Of Her-2–Positive Breast Cancer

The human epidermal growth factor receptor 2 (HER-2, HER-2/neu, c-erbB-2) gene, first discovered in 1984 by Weinberg and associates [1], is localized to chromosome 17q and encodes a transmembrane tyrosine kinase receptor protein that is a member of the epidermal growth factor receptor (EGFR) or HER family (Fig. 1) [2]. This family of receptors is involved in cell– cell and cell–stroma communication primarily through a process known as signal transduction, in which external growth factors, or ligands, affect the transcription of various genes, by phosphorylating or dephosphorylating a series of transmembrane proteins and intracellular signaling intermediates, many of which possess enzymatic activity. Signal propagation occurs as the enzymatic activity of one protein turns on the enzymatic activity of the next protein in the pathway [3]. Major pathways involved in signal transduction, including the Ras/mitogen-activated protein kinase pathway, the phosphatidylinositol 3 kinase (PI3K)/Akt pathway, the Janus kinase/signal transducer and activator of transcription pathway, and the phospholipase C pathway, ultimately affect cell proliferation, survival, motility, and adhesion. Receptor activation requires three variables, a ligand, a receptor, and a dimerization partner [4]. After a ligand binds to a receptor, that receptor must interact with another receptor of identical or related structure in a process known as dimerization in order to trigger phosphorylation and activate signaling cascades. Therefore, after ligand binding to an EGFR family member, the receptor can dimerize with various members of the family (EGFR, HER-2, HER-3, or HER-4). It may dimerize with a like member of the family (homodimerization) or it may dimerize with a different member of the family (heterodimerization). The specific tyrosine residues on the intracellular portion of the HER-2/neu receptor that are phosphorylated, and hence the signaling pathways that are activated, depend on the ligand and dimerization partner. The wide variety of ligands and intracellular crosstalk with other pathways allow for significant diversity in signaling. Although no known ligand for the HER-2 receptor has been identified, it is the preferred dimerization partner of the other family members. HER-2 heterodimers are more stable [5, 6] and their signaling is more potent [7] than receptor combinations without HER-2. HER-2 gene amplification and/or protein overexpression has been identified in 10%–34% of invasive breast cancers [1]. Unlike a variety of other epithelial malignancies, in breast cancer, HER-2 gene amplification is uniformly associated with HER-2 (p185neu) protein overexpression and the incidence of single copy overexpression is exceedingly rare [8]. HER-2 gene amplification in breast cancer has been associated with increased cell proliferation, cell motility, tumor invasiveness, progressive regional and distant metastases, accelerated angiogenesis, and reduced apoptosis [9].When classified by routine clinicopathologic parameters and compared with HER-2– negative tumors, HER-2–positive breast cancer is more often of intermediate or high histologic grade, more often lacking estrogen receptors (ERs) and progesterone receptors (PgRs) (ER and PgR negative), and featuring positive lymph node metastases at presentation [1]. In the recent molecular classification of breast cancer, positive HER-2 status does not constitute a unique molecular category and is identified in both the “HER-2” and “luminal” tumor classes [10].

Figure 1 (not shown)

Figure 1. The human epidermal growth factor receptor (HER) gene family. This image depicts the complex crosstalk between members of the HER family of receptor tyrosine kinases and intracellular signaling. Activated HER receptors can function to both stimulate and inhibit downstream signaling of members of other biologic pathways. Note that HER-2 has no activating ligands and HER-3 lacks a tyrosine kinase domain. HER-2–mediated signaling is associated with cell proliferation, motility, resistance to apoptosis, invasiveness, and angiogenesis. The figure shows the complexity of signaling pathways initiated by, and influenced by, HER family protein receptors at the cell surface.

HER-2 Status and Prognosis in Breast Cancer Both morphology-based and molecular-based techniques have been used to measure HER-2/neu status in breast cancer clinical samples [11–117]. By a substantial majority, abnormalities in HER-2 expression at the gene, message, or protein level have been associated with adverse prognosis in both lymph node–negative and lymph node–positive breast cancer. Of the 107 studies considering 39,730 patients listed in Table 1, 95 (88%) of the studies determined that either HER-2 gene amplification or HER-2 (p185 neu) protein overexpression predicted breast cancer outcome on either univariate or multivariate analysis. In 68 (73%) of the 93 studies that featured multivariate analysis of outcome data, the adverse prognostic significance of HER-2 gene, message, or protein overexpression was independent of all other prognostic variables. In only 13 (12%) of the studies, no correlation between HER-2 status and clinical outcome was identified. Of these 13 noncorrelating studies, eight (62%) used immunohistochemistry (IHC) on paraffin-embedded tissues as the HER-2/protein detection technique, two (15%) used fluorescence in situ hybridization (FISH), two (15%) used Southern analysis, and one (7%) used a real-time polymerase chain reaction (RT-PCR) technique. Of the 15 studies that used the FISH technique, 13 (87%) showed univariate prognostic significance of gene amplification, and 11 of these (85%) showed prognostic significance on multivariate analysis as well. The two studies that used chromogenic in situ hybridization (CISH) HER-2 gene amplification detection techniques both found that HER-2 amplification was an independent predictor of outcome on multivariate analysis [100, 112]. However, interpretation of these studies is complicated by the fact that most studies included patients who received variable types of systemic adjuvant therapy; therefore, the pure prognostic value of HER-2 overexpression in the absence of any systemic adjuvant therapy is incompletely understood.

Table 1 HER-2 status and prognosis in breast cancer (not shown)

HER-2 Positivity Rates The frequency of HER-2 positivity in all of the studies presented in Table 1 was 22.2%, with a range of 9%–74%. The HER-2–positive rate was similar for IHC, at 22% (range, 10%–74%), and FISH, at 23.9% (range, 14.7%– 68%). In current practice, HER-2–positive rates have trended below 20%, with most investigators currently reporting that the true positive rate is in the range of 15%–20%. The HER-2– positive rate may be higher when metastatic lesions are tested, and tertiary hospitals and cancer centers report slightly higher rates than community hospitals and national reference laboratories. Relative Risk and Hazard Ratio In Table 1, a number of studies provided data as to the relative risk (RR) of untreated HER-2–positive breast cancer being associated with an adverse clinical outcome. For OS, the mean RR was 2.74 (range, 1.39 – 6.93) and the median was 2.33; for disease-free survival (DFS), the mean RR was 2.04 (range, 1.30 –3.01) and the median was 1.8. In several studies, the RR was estimated with a hazard ratio (HR) model. The mean HR was 2.12 (range, 1.6 –2.7) and the median was 2.08. HER-2 Expression and Breast Pathology The association of HER-2–positive status with specific pathologic conditions of the breast is summarized in Table 2. HER-2 overexpression has been consistently associated with higher grades and extensive forms of ductal carcinoma in situ (DCIS) and DCIS featuring comedo-type necrosis [118 –121]. The incidence of HER-2 positivity in DCIS has varied in the range of 24%–38% in the published literature, which appears to be slightly higher than that for invasive breast cancer [118 –121]. Routine testing for HER-2 status in DCIS is not widely performed. However, should anti– HER-2 targeted therapies directed at HER-2–positive DCIS result in a reduction in the development of invasive disease, the widespread use of HER-2 testing in DCIS would be adopted. Finally, the invasive carcinoma that develops in association with HER-2–positive DCIS may, on occasion, not feature a HER-2–positive status, a finding that has led investigators to believe that HER-2 gene amplification may not be required for the local progression of breast cancer [122]. Compared with invasive ductal carcinoma (IDC), HER-2 gene amplification occurs at a significantly lower rate in invasive lobular carcinoma (ILC) (10%), but has also been linked to an adverse outcome [85]. HER-2 positivity is linked exclusively to the pleomorphic variant of ILC and is not encountered in classic ILC [123]. HER-2 amplification is strongly correlated with tumor grade in both IDC and ILC. For example, in one study, only one of 73 grade I IDC cases and one of 67 low-grade classic ILC cases showed HER-2 amplification detected by FISH [86]. HER-2 overexpression and HER-2 amplification have been a consistent feature of both mammary and extramammary Paget’s disease [124, 125] (Fig. 2). HER-2 amplification and HER-2 overexpression have been associated with adverse outcome in some studies of male breast carcinoma [126 –129], but not in others [130 –132]. The incidence of HER-2 positivity appears to be lower in male breast cancer than in female breast cancer [126 –132]. Documented responses in male breast cancer to HER-2–targeting agents have been described, and therefore treatment with trastuzumab is an acceptable option for these patients, but the true activity rate remains uncertain [133]. The rate of HER-2 overexpression in mucinous (colloid) breast cancers is extremely low, although, on occasion, it has been associated with aggressive disease [134 –136]. In medullary breast carcinoma, HER-2 testing has consistently found negative results [137]. Similarly, HER-2 positivity is extremely rare in cases of tubular carcinoma [138]. HER-2 status has not been consistently linked to the presence of inflammatory breast cancer [139, 140]. Molecular studies of hereditary breast cancer including cases with either BRCA1 or BRCA2 germline mutations have found a consistently lower incidence of HER-2–positive status for these tumors [141].

Figure 2 not shown

Figure 2. Human epidermal growth factor receptor (HER)-2–positive Paget’s disease of the nipple. In this patient, who presented with HER-2–positive invasive duct carcinoma, classic clinical features of Paget’s disease of the nipple were present. A section of the nipple from the mastectomy specimen shows 3+ continuous cell membrane immunoreactivity for HER-2 protein. Nearly 100% of Paget’s disease of the breast cases are HER-2 positive (see text).

Breast sarcomas and phyllodes tumors have consistently been HER-2 negative [142]. Finally, low-level HER-2/neu overexpression has been identified in benign breast disease biopsies and is associated with a greater risk for subsequent invasive breast cancer [143].

HER-2 Status in Primary Versus Metastatic Breast Cancer The majority of studies that have compared the HER-2 status in paired primary and metastatic tumor tissues have found an overwhelming consistency in the patient’s status regardless of the method of testing (IHC versus FISH) [144 –151]. However, several recent studies indicated 20%–30% discordance rates between the HER-2 status of primary and metastatic lesions. Some of these studies have featured relatively high HER-2–positive rates on both paired specimens (> 35% positive), which has created concern about the conclusions of these reports [152]. Also, considering that 10%–30% discordance rates have been reported even when the same tumor is tested repeatedly, it remains uncertain if the discordance rates seen between primary and metastatic sites is higher than expected by the less than perfect reproducibility of the various HER-2 assays. Increasingly, emerging data suggest that there are changes in HER-2 expression between primary and metastatic disease. This is particularly true after intervening HER-2– directed therapy, but also happens in the absence of such treatment. In cases where the original primary HER-2 test result is questioned because of technical or interpretive issues and in patients where there has been an unusually long (i.e., > 5-year) interval between the primary occurrence and the detection of metastatic disease, retesting of a metastatic lesion may be warranted. Thus, although routine HER-2 testing of metastatic disease is advocated by some investigators, the preponderance of data indicates that the HER-2 status remains stable and that routine retesting of HER-2 may not be needed for most patients with metastatic disease.

Features of Metastatic HER-2–Positive Breast Cancer Metastatic HER-2–positive breast cancer retains the phenotype of the primary tumor not only in HER-2 status, but also is typically ER/PgR negative, moderate to high tumor grade, DNA aneuploid with high S phase fraction, and featuring ductal rather than lobular histology. In the era prior to the initiation of HER-2–targeted therapy, HER-2–positive breast cancer was more likely to spread early to major visceral sites including the axillary lymph nodes, bone marrow, lungs, liver, adrenal glands, and ovaries [153]. In the post–HER-2 targeted therapy era, the incidence of progressive visceral metastatic disease in HER-2–positive tumors has diminished and has frequently been superseded by the development of clinically significant central nervous system (CNS) metastatic disease [154 –157]. It is widely held that the success in the control of visceral disease with trastuzumab has unmasked previously occult CNS disease and, because of the inability of the therapeutic antibody to cross the blood– brain barrier, allowed brain metastases to progress during the extended OS duration of treated patients [154, 155]. The small-molecule drug lapatinib has shown some promise for targeting HER-2–positive CNS metastases that are resistant to trastuzumab-based therapies in initial studies [158].

Interaction of HER-2 Expression with Other Prognosis Variables HER-2 gene amplification and protein overexpression have been associated consistently with high tumor grade, DNA aneuploidy, high cell proliferation rate, negative assays for nuclear protein receptors for estrogen and progesterone, p53 mutation, topoisomerase IIa amplification, and alterations in a variety of other molecular biomarkers of breast cancer invasiveness and metastasis [159 –161].

Figure 3. Human epidermal growth factor receptor (HER)-2 testing.
(not shown)  (A): Immunohistochemistry (IHC). This panel depicts the four categories of HER-2 IHC staining including 0 and 1+ (negative), 2+ (equivocal), and 3+ (positive) using the American Society of Clinical Oncology–College of American Pathologists guidelines for HER-2 IHC scoring. (B): Fluorescence in situ hybridization (FISH). This panel demonstrates a case of invasive duct carcinoma, on the left, negative for HER-2 gene amplification (gene copy number < 4) and a case of HER-2 gene–amplified breast cancer (gene copy number > 6),

FISH. The FISH technique (Fig. 3B), like IHC, is a morphology-driven slide-based DNA hybridization assay using fluorescent-labeled probes. Both the hybridization steps and the slide scoring can be automated. FISH has the advantages of a more objective scoring system and the presence of a built-in internal control consisting of the two HER-2 gene signals present both in benign cells and in malignant cells that do not feature HER-2 gene amplification.

IHC Versus FISH. Although the FISH method is more expensive and time-consuming than IHC, numerous studies have concluded that this cost is well borne by the greater accuracy and more precise use of anti–HER-2 targeted therapies [179 –180, 182–183]. FISH is considered to be more objective and reproducible in a number of systematic reviews [165, 180, 183–186]. In one study, the concordance rates between IHC and FISH were highest in tumors scored by IHC as 0 and 1+ and lowest for 2+ and 3+ cases [183]. Currently, the majority (approximately 80%) of HER-2 testing in the U.S. commences with a screen by IHC, with results of 0 and 1+ considered negative, 2+ considered equivocal and referred for FISH testing, and 3+ considered positive. In a pharmacoeconomic study of patients being considered for trastuzumab-based treatment for HER-2– positive tumors, FISH was found to be a cost-effective diagnostic approach “from a societal perspective” [187].

CISH and Silver In Situ Hybridization. The CISH method (Fig. 3E) and silver in situ hybridization (SISH) method feature the advantages of both IHC (routine microscope, lower cost, familiarity) and FISH (built-in internal control, subjective scoring, the more robust DNA target) [190, 191]. The CISH technique uses a single HER-2 probe, detects HER-2 gene copy number only, and was recently approved by the FDA to define patient eligibility for trastuzumab treatment. The SISH method employs both HER-2 and chromosome 17 centromere probes hybridized on separate slides and is currently under review by the FDA. Numerous studies have confirmed a very high concordance between CISH and FISH, typically in the 97%–99% range [191–203]. Similar to FISH, CISH has its highest correlation with IHC 0, 1+, and 3+ results and lowest correlation with IHC 2+ staining.

Chromosome 17 Polysomy. The incidence of chromosome 17 polysomy has varied from as low as 4% to as high as 30% in studies of invasive breast cancer [204 –208]. This may reflect differences in the definition of polysomy ranging from a low-level definition of more than two copies per cell to a high of more than four copies per cell of the chromosome. Most studies have linked chromosome 17 polysomy with greater HER-2 protein overexpression [204 –207], but some have found that protein overexpression only occurs in the presence of selective HER-2 gene amplification [204].

The 2007 ASCO-CAP Guidelines. In early 2007, a combined task force from ASCO and the CAP issued a series of recommendations designed to improve the accuracy of tissue-based HER-2 testing in breast cancer [212]. A summary of the ASCO-CAP guidelines is provided in Table 4. Highlights of these recommendations include (a) standardizing fixation in neutral-buffered formalin for no less than 6 hours and no more than 48 hours, (b) unlike their respective FDA-approval specifications, defining equivocal zones for the IHC, FISH, and CISH tests, (c) establishing a standardized quality assurance program for testing laboratories, and (d) requiring the participation of these laboratories in a proficiency testing program [212]. The published guidelines were designed to improve the overall precision and reliability of all types of slide-based HER-2 tests and remained neutral as to the relative superiority of one test over the others.

Figure 4. Real-time polymerase chain reaction (RT-PCR). In this RT-PCR assay using the Taqman RT-PCR System (Applied Biosystems Inc., Foster City, CA), note the detection of increased human epidermal growth factor receptor(HER)-2 mRNA expression in green detected at lower numbers of amplification cycles compared with the two housekeeping genes shown in red and blue.

Figure 5. DNA microarray. In this image, increased expression of human epidermal growth factor receptor (HER)-2 mRNA has been detected using a proprietary DNA microarray system (Millennium Pharmaceuticals, Inc., Cambridge, MA). The microarray demonstrates the coexpression of seven genes (HER-2 is second from the bottom) related to the amplification of HER-2 DNA in this case of HER-2–positive breast cancer.

Her-2–Targeted Therapy and the Treatment of Her-2–Positive Breast Cancer

Trastuzumab: HER-2 Testing and the Prediction of Response to Trastuzumab Therapy Using recombinant technologies, trastuzumab (Herceptin; Genentech, South San Francisco, CA), a monoclonal IgG1 class humanized murine antibody, was developed by the Genentech Corporation to specifically bind the extracellular portion of the HER-2 transmembrane receptor. This antibody therapy was initially targeted specifically for patients with advanced relapsed breast cancer that overexpresses HER-2 protein [262]. Since its launch in 1998, trastuzumab has become an important therapeutic option for patients with HER-2–positive breast cancer and is widely used for its approved indications in both the adjuvant and metastatic settings (Fig. 6) [185, 263–265]. Although trastuzumab is approved as a single-agent regimen, most patients are treated with trastuzumab plus cytotoxic agents. Table 5 summarizes the significant clinical trials that contributed to the regulatory approvals of trastuzumab.

This topic is scheduled for another article.

Trastuzumab Combinations. Since the FDA approval in 1998 of two trastuzumab plus chemotherapy combinations, a number of additional approaches have gained favor in the clinical practice community. The National Comprehensive Cancer Network (NCCN) Clinical Practice Guidelines [284] currently recommend the following regimens for the first-line treatment of HER-2–positive MBC: trastuzumab plus single agents— either paclitaxel (every 3 weeks or weekly), docetaxel (every 3 weeks or weekly), or vinorelbine (weekly). For combination therapies, the NCCN recommends trastuzumab plus paclitaxel and carboplatin (every 3 weeks) or docetaxel plus carboplatin. Recently, carboplatin-based trastuzumab combinations have gained interest as a result of both the apparent boost in efficacy as measured by a higher overall response rate and longer progression-free survival time and the cardioprotective benefits of avoiding an anthracycline-containing regimen [285].

Neoadjuvant Setting The results of trastuzumab-based neoadjuvant studies (Table 5) have received significant recent interest in the oncology community [289]. Virtually all completed and in progress clinical trials have demonstrated a significant enhancement in the rate of pathologic complete response (pCR), the primary endpoint in these studies, in cases of patients with HER-2–positive breast cancer that received trastuzumab in the neoadjuvant setting [290 –297]. This benefit of the addition of trastuzumab in the neoadjuvant setting appears to be independent of, if not enhanced by, the coexistence of ER positivity [297]. Among the potential explanations for the apparent greater chemosensitivity of HER-2–positive tumors cotreated with trastuzumab in the neoadjuvant setting is the concept that HER-2 gene amplification is in some way related to the growth and survival of breast cancer stem cells [298, 299].

Biomarkers of Trastuzumab Resistance Since trastuzumab was introduced for the treatment of MBC in 1998, there has been growing interest in the discovery and potential clinical utility of biomarkers designed to predict resistance to the drug. Current approaches to HER-2 testing provide a negative predictor of drug response: the test does not predict which patients will respond to trastuzumab, it predicts which patients are unlikely to benefit.

Neoadjuvant Setting The Neo-ALTTO trial is a randomized, open-label, multicenter, phase III study comparing the efficacy of neoadjuvant lapatinib plus paclitaxel with that of trastuzumab plus paclitaxel and with concomitant lapatinib and trastuzumab plus paclitaxel given as neoadjuvant treatment in HER-2– positive primary breast cancer [337].

Biomarkers of Lapatinib Resistance In that lapatinib was approved 9 years after trastuzumab, considerably less information has been published concerning markers of efficacy or resistance to the drug [331, 341– 343].

Trastuzumab Since its introduction in the MBC setting and continuing throughout its advance into use in both the adjuvant and neoadjuvant settings, trastuzumab has been associated with the development of a variety of toxicities [384]. In the original registration trial for MBC, trastuzumab was associated with a variety of adverse events, including pain, gastrointestinal disturbances, minor hematologic deficiencies, pulmonary symptoms, and congestive heart failure (CHF) [265]. Cardiac toxicity has remained the most significant limiting factor for the use of trastuzumab [384 –389]. A major consideration in the development of cardiac toxicity in patients treated with trastuzumab has been their prior or concomitant exposure to anthracycline drugs, also associated with dose-dependent irreversible heart damage [384 – 389].

Lapatinib The most frequent adverse reactions in the lapatinib– capecitabine registration trial for MBC combination were diarrhea (65%), palmar–plantar erythrodysesthesia (53%), nausea (44%), rash (28%), vomiting (26%), and fatigue (23%) [332]. In a comprehensive analysis of the clinical trials featuring lapatinib in combination with various other agents, the overall incidence of LVEF decline was 1.6%, with 0.2% of patients experiencing symptomatic CHF [389].

HER-2 Status and the Prediction of Response to Non–HER-2 Targeted Therapy The use of HER-2 status to predict responsiveness or resistance to hormonal therapies, advocated by a number of oncologists, remains controversial. It has been reported that ER-positive/HER-2–positive patients are either less responsive or completely resistant to single-agent tamoxifen [391–393]. When measured as continuous variables, the expression of HER-2 appears to be inversely related to the expression of ER and PgR even in hormone receptor–positive tumors [394].

Anthracyclines HER-2 overexpression has also been associated with enhanced response rates to anthracycline-containing chemotherapy regimens in most, but not all, studies [42, 410 – 414].

Radiation Therapy Initially, in the era prior to the introduction of anti–HER-2 targeted therapy, HER-2–positive status was associated with a higher rate of local recurrence in some studies of breast cancer treated with surgery and radiation therapy alone, but not in others [427– 429]. However, although large-scale, randomized, prospective studies are lacking, HER-2–positive tumors treated with trastuzumab-based neoadjuvant chemotherapy combined with external-beam radiation have indicated a favorable response in locally advanced breast cancer [430].

Summary The history of the discovery of the HER-2 oncogene in an animal model in 1984, the translation of this finding to the clinical behavior of human breast cancer, and the introduction of the first anti-HER targeted therapy in 1998 is clearly a triumph of “bench to bedside” medicine. In the 10 years that have now passed since the regulatory approval of the first anti–HER-2 targeted therapy, trastuzumab, thousands of preclinical and clinical studies have considered HER-2 as a prognostic factor, its ability to predict response to hormonal and cytotoxic treatments, the best way to test for it in routine specimens, and the clinical efficacy of targeting it in a wide variety of clinical settings. Given the proven efficacy of trastuzumab and lapatinib for the treatment of MBC, and also in the adjuvant and neoadjuvant settings, the critical issue as to which test (IHC versus FISH versus CISH versus mRNA based) is the most accurate and reliable method to determine HER-2 status in breast cancer has continued to increase in importance.

3.4 Personalized Medicine is not yet here

ESMO Personalized Medicine
Written by Dr Marina Garassino for ESMO
https://www.esmo.org/content/download/20122/337223/file/ESMO-Patient-Guide-Personalised-Cancer-Medicine.pdf

The aim of personalised medicine is clearly to make therapy more efficient for patients. A very, very small step in the process is to try to identify for every patient the main molecular driver of their tumour. We have to understand that patients differ between each other, although they may have the same cancer type; for example, every patient with breast cancer or bowel cancer will have a unique tumor. This is entirely new knowledge, so what we are trying to do now in the medical community is to identify for each patient his/ her type of disease and then to give the drug that will work best. We are moving forward with an incredible amount of new data and innovative knowledge on genetic characteristics and subsequent proteomic changes* in the tumor. The challenge is now about how to exploit this information in order to offer targeted treatment and generally improve patient care.

For a number of years we have classified tumors according to their site of origin and using a classification system called “TNM”. Researchers and clinicians once thought that all cancers that derived from the same site were biologically similar and they differed perhaps only in their pathohistological* grading. This grading is a score which classifies tumors from 1 to 3, where 1 is the least aggressive tumor and 3 is the most undifferentiated tumor. Other clinical differences were distinguished based on the presence of regional node metastases or distant metastases. Most of the tumors were therefore classified within the “TNM” system, where T corresponds to the diameter of the primary tumor, N to the presence of regional nodes, and M to distant metastases. For at least three decades, personalization of oncology was based only on these parameters and on the patient’s physical condition, and even now these represent the fundamental elements for treatment decisions. Chemotherapy, surgery and radiation therapy were once the only treatment options for cancer. Although these treatments are still used, oncologists know that some patients respond better to certain drugs than to others and that a surgical approach is not always indicated. In recent years, researchers have studied thousands upon thousands of samples from all types of tumors. They have discovered that tumors derived from the same body site can differ in very important ways.

Firstly, there is histology*. The pathologist is able to distinguish different subtypes of cancer with the microscope. When a patient is diagnosed with a cancer, he/she will undergo a biopsy or a fine-needle aspiration. In some tumor types, debulking or removal of the primary tumor also allows sampling for tissue examination. Some cells of the tumor which have been removed will be taken and analyzed. This examination allows the pathologist to confirm a cancer diagnosis, but, through particular colorations of the tissue sample, the pathologist is also able to provide clinicians with a lot of additional information, such as the tumor’s histological characterization, its hormone sensitivity, and its grade of differentiation*.

For example, in the treatment of lung cancer the histology provides very useful tools to decide the best drug for the treatment of the patient. Clinical studies have shown that for a patient with lung adenocarcinoma* there might be more chance of a response if the drugs pemetrexed or bevacizumab are added to the chemotherapy, while for a patient with lung cancer of squamous* histology, it would be more beneficial to add gemcitabine or vinorelbine. A similar example may be observed Personalization of Oncological Treatments: The Story 12 for other cancers. For the treatment of esophageal cancer it is mandatory to know if the tumor is squamous or not, because although deriving from the same organ, the treatment approach is completely different.

This information is a useful tool in the first step of the personalization process. For example, lung cancer can be divided as a first step into non-small cell lung cancer and small cell lung cancer, which are two completely different neoplasms*. Within the non-small cell lung cancer category, there are again several different tumor types. Breast cancer can also be divided into two major categories: the hormone-sensitive neoplasms and the HER2-positive diseases. Lung and breast cancers are only two examples, because it is possible to recognize several entities within the same tumor type for many other cancers.

Molecular subsets of lung adenocarcinoma Lung cancer subtypes
Figure 2. Lung Cancer – Not One Disease: Histological (Tissue) and Molecular Subtypes of Lung Cancer (not shown) On the left side, four histological subtypes of lung cancer. On the right side, a pie chart showing the percentage distribution of molecular subsets of lung adenocarcinoma. Adapted from Petersen I. Dtsch Arztebl Int 2011; 108(31-32):525-531 (left) and Pao W & Hutchinson KE. Nature Med 2012; 18(3): 349-351.

Personalization depends on a multidisciplinary approach; we need a range of experts, because we need the medical oncologist, the surgeon and the expertise of the molecular pathologist, who should be part of the team in a more effective, integrated way than before. We don’t need the pathology report alone; we need to interact with all professionals, including nurses, who are dealing with the patient. This, to me, will create a lot of problems in terms of organization of care and in terms of cost, but it is the only way to bring together knowledge on the biology and pathology of tumors for effective treatment in every single patient. Our effort at ESMO is to bring this broad knowledge to the general public, to medical oncologists and to the community of doctors involved in cancer.

We have to deeply analyze each tumor of every patient in order to identify those genetic characteristics that make the tumor able to survive. As a result, we can choose the appropriate drugs to target the specific alterations. The clearest examples of this process are in melanoma, lung cancer and breast cancer. For instance, in lung cancer, the presence of mutations in the epidermal growth factor receptor (EGFR) renders the tumor highly sensitive to EGFR tyrosine kinase inhibitors. When oncologists identify these mutations in a patient’s tumor, they may observe that the lesion disappears a few weeks after treatment. A similar response may be observed after treatment with BRAF inhibitors in patients with melanoma or with gastrointestinal stromal tumors (GIST) that express the c-kit gene. Unfortunately, oncogene addiction is not the only process underlying carcinogenesis* and tumor growth. The tumor environment and so-called “epigenetic” alterations* play an important role in rendering the fight against cancer more and more challenging. Despite the enormous recent advances, a specific alteration has not been identified in all cancers. The hope is that the possibility of sequencing the full genome – which means every gene – will give us new insights and therefore new drugs for our patients.

In the DNA of some individuals a “germline” mutation* may be present. This means that a particular mutation is conferring susceptibility to that person to develop a particular type of cancer during his/her life. For instance, BRCA is an alteration for which there is a particular predisposition to have a breast cancer or ovarian cancer in one’s life. A woman with a BRCA gene mutation can transmit this alteration to her female descendants, so her daughters and following generations of female family members can therefore inherit this predisposition.

Mutations that are not germline are called somatic mutations*, which are acquired mutations and are found generally only in the tumor. Distinct from germline mutations, somatic mutations are not inherited.

The move from blockbuster or empirical medicine* towards personalized medicine is a stepwise process. We are currently on the second step of stratified medicine and moving up the stairs towards personalized medicine.

Will molecular pathology evolve from pathology? You need to give a name to a tumor, and a pathologist is the professional who gives a name to tumors. The variety of cancers is broad; when we say “sarcoma”, “carcinoma”, or “lymphoma”, we actually say nothing, because we have hundreds and hundreds of diseases within these categories that need to be recognized. And the reason for recognizing them is exactly related to personalization. The biology of cancer is very complex, and admittedly we have been very naive in the past. We always thought that the problem was how genes become altered in the cancer cell, but actually it is even more complex than that and also involves the way genes direct how they are read; it is the flow of information that comes from genes to the making of their proteins which is as important as the aberration of the genome.

We are facing obstacles currently because the whole issue of tissue sampling has been regulated under the umbrella of privacy, which is of course important. Defending your rights as a human being is a key issue, but we should also try to focus a little bit on the necessity to use that tissue. Of course, we need to have rules, but the approach we are currently facing is basically preventing clinical research and translational research under the excuse of protecting our privacy as human beings, and this is an increasing obstacle. We as researchers, as molecular geneticists, as pathologists, are really looking into a future in which it is becoming increasingly difficult to try to answer the basic question of cancer genomics. Why? Because it is becoming increasingly difficult to use tissue for these purposes.

With the new therapeutic approach and the use of targeted therapy, molecular testing is gaining a very relevant role. It is very important for us, as advocates, to educate patients in these issues. So patients have to receive very clear and transparent information. It should be the doctor who explains to the patient the reason why molecular testing is performed; the doctor has to explain that molecular testing will find whether there is some tumor characteristic which can be targeted with one of these therapies, in order to determine if maybe the patient is the right candidate to receive targeted therapy and perhaps to benefit from it. The communication between the doctor and patient must be very accurate and must educate, meaning that the patient has to understand the precise situation. This can be important also to empower the patient in treatment decisions, but it is important that he/she knows that not every patient may be a candidate for receiving targeted therapy and to understand why this is the case.

  • Different tumour types are increasingly divided into very small subgroups carrying a rare molecular alteration.
  • Most new drugs are targeting these infrequent events.
  • Clinical trials are testing the use of high throughput molecular technologies* in the context of personalized cancer medicine.
  • There are a growing number of newer techniques to optimize genomic testing, including the virtual cell program, which foresees testing of a piece of patient’s tumor tissue in the laboratory in order to mimic what would happen in the human body (e.g. drug sensitivity).
  • Clinical research is today focusing on target identification at the patient level.

Targeted therapy drugs work differently to standard chemotherapeutic drugs. They attack cancer cells and, in particular, the targets which are strategic points for cell survival, cell replication and metastases. They generally create little damage to normal cells. In fact, these drugs tend to have different side effects to traditional chemotherapeutic drugs. Targeted therapies are used to treat many kinds of tumors: certain types of lung, pancreatic, head and neck, liver, colorectal, breast, melanoma and kidney cancers. Targeted therapies are a major focus of cancer research today

Many future advances in cancer treatment will probably come from this area. There are many different targeted therapies in use and new forms are appearing all the time. Depending on the type of cancer and the way it spreads, targeted therapy can be used to cure the cancer, to slow the cancer’s growth, to kill cancer cells that may have spread to other parts of the body or to relieve symptoms caused by the cancer.

We can divide targeted therapies into two main categories: antibody drugs and small molecules. Antibody drugs are man-made versions of immune system proteins that have been designed to attack the external part of cells at certain targets, generally called receptors. Receptors can be considered the antennas of the cells. They transmit signals from the surrounding environment to the nucleus of the cell. Some receptors are fundamental to the vital processes of the cell. Targeting certain receptors means preventing the transmission of some survival signals to the tumor cells.

Trastuzumab (Herceptin®) is, after tamoxifen, the second targeted therapy drug ever used to treat cancer and it is a monoclonal antibody directed at a receptor called HER2. This targeted therapy greatly improves the survival rate of women with breast cancer expressing the HER2 receptor. Therefore, the determination on tissue blocks of the presence of expression of HER2 is one of the best examples of personalization of treatment.

A knowledge of the cancer characteristics and a determination of the tissue characteristics of each patient allows the doctor to select patients for the best treatment.

Other examples of monoclonal antibodies are cetuximab and panitumumab, which have been developed to treat colon cancer. At first it seemed as if these drugs were a failure, because they did not work in many patients. Then it was discovered that if a cancer cell has a specific genetic mutation, known as KRAS, these drugs will not work.

This is another excellent example of using individual tumor genetics to predict whether or not a treatment will work. In the past, the oncologist would have had to try each therapy on every patient and then change the therapy if the cancer continued to grow.

The other type of targeted therapy drugs are not antibodies. Since antibodies are large molecules, this other type is called “small-molecule” targeted therapy drugs. The small molecules attack cancer cells from the inner vital processes. Also, in this case, the small molecules prevent the broadcast of vital signals that regulate the survival of the tumor. There are several examples of targeted drugs that changed the natural history of some cancers.

One example is imatinib mesylate (Gleevec®), which is used in GIST, a rare cancer of the gastrointestinal tract, and in certain kinds of leukemia. Imatinib targets abnormal proteins, or enzymes, that form on and inside cancer cells and promote uncontrolled tumor growth. Blocking these enzymes inhibits cancer cell growth. Gefitinib (Iressa®) is used to treat advanced non-small cell lung cancer. This drug hits the internal part of the EGFR. These receptors are found on the surface of many normal cells, but certain cancer cells have many more of them. EGFR take in the signal that tells the cell to grow and divide. When gefitinib blocks this signal, it can slow or stop cell growth. However, gefitinib does not work in all patients when trying to treat lung cancer, but only

Personalization of Treatment in a particular subtype. About 10% of patients show genetic alterations called “EGFR mutations” in their tumors at diagnosis. These particular mutations mean that the EGFR is always turned on and therefore there is a continuous signal to the cell to grow and divide. Gefitinib is able to switch off this signal and to stop cell growth in this subtype of patients. After a few weeks, the tumor disappears. Unfortunately, these mutations are rare and they are mainly present in never-smokers, who are the minority of patients.

Another, similar example in lung cancer is provided by crizotinib (Xalkori®). Patients with ALK translocations, which is another rare type of alteration present mainly in never smokers, experience a rapid shrinkage in their tumors when treated with this drug.

Another example of small molecules is represented by sunitinib (Sutent®). This drug is used to treat advanced kidney cancer and some GIST. Sunitinib is considered a multitarget agent because it blocks the vascular endothelial growth factor (VEGF) receptor and other enzymes. By doing all of this, sunitinib slows cancer growth and stops tumors from creating their own blood vessels to help them grow and metastasize. In this case, no biomarkers have been identified to help select patients who are responders from patients who are nonresponders.

Exploring the clinical utility of comprehensive genomic testing. After the patient’s informed consent, tumor and normal DNA is extracted in a certified laboratory. After targeted somatic mutation testing, more extended testing is performed in a research environment. Test results are shared with the treating oncologists, and validation of research findings is pursued if any clinically relevant research findings are found. Therapeutic decisions are based only on validated test results.

We really have to strengthen and reinforce in the future all the collaborative ways to work, without any – or minimal, at least – competitive ways of thinking. We have to work together to make the science evolve and forget about the national or regional representation of research that we have had in the past. I think the priority now is to have really good networks of institutions in order to make new treatments rapidly reach our patients.

3.5 Biomarkers for personalized oncology: recent advances and future challenges.

Kalia M
Metabolism. 2015 Mar;64(3 Suppl 1):S16-21
http://dx.doi.org:/10.1016/j.metabol.2014.10.027

Cancer is a group of diseases characterized by the uncontrolled growth and spread of abnormal cells and oncology is a branch of medicine that deals with tumors. The last decade has seen significant advances in the development of biomarkers in oncology that play a critical role in understanding molecular and cellular mechanisms which drive tumor initiation, maintenance and progression. Clinical molecular diagnostics and biomarker discoveries in oncology are advancing rapidly as we begin to understand the complex mechanisms that transform a normal cell into an abnormal one. These discoveries have fueled the development of novel drug targets and new treatment strategies. The standard of care for patients with advanced-stage cancers has shifted away from an empirical treatment strategy based on the clinical-pathological profile to one where a biomarker driven treatment algorithm based on the molecular profile of the tumor is used. Recent advances in multiplex genotyping technologies and high-throughput genomic profiling by next-generation sequencing make possible the rapid and comprehensive analysis of the cancer genome of individual patients even from very little tumor biopsy material. Predictive (diagnostic) biomarkers are helpful in matching targeted therapies with patients and in preventing toxicity of standard (systemic) therapies. Prognostic biomarkers identify somatic germ line mutations, changes in DNA methylation, elevated levels of microRNA (miRNA) and circulating tumor cells (CTC) in blood. Predictive biomarkers using molecular diagnostics are currently in use in clinical practice of personalized oncotherapy for the treatment of five diseases: chronic myeloid leukemia, colon, breast, lung cancer and melanoma and these biomarkers are being used successfully to evaluate benefits that can be achieved through targeted therapy. Examples of these molecularly targeted biomarker therapies are: tyrosine kinase inhibitors in chronic myeloid leukemia and gastrointestinal tumors; anaplastic lymphoma kinase (ALK) inhibitors in lung cancer with EML4-ALk fusion; HER2/neu blockage in HER2/neu-positive breast cancer; and epidermal growth factor receptors (EGFR) inhibition in EGFR-mutated lung cancer. This review presents the current state of our knowledge of biomarkers in five selected cancers: chronic myeloid leukemia, colorectal cancer, breast cancer, non-small cell lung cancer and melanoma.

3.6 Personalized oncology: recent advances and future challenges.

Kalia M1
Metabolism. 2013 Jan;62 Suppl 1:S11-4
http://dx.doi.org:/10.1016/j.metabol.2012.08.016

Personalized oncology is evidence-based, individualized medicine that delivers the right care to the right cancer patient at the right time and results in measurable improvements in outcomes and a reduction on health care costs. Evolving topics in personalized oncology such as genomic analysis, targeted drugs, cancer therapeutics and molecular diagnostics will be discussed in this review. Biomarkers and molecular individualized medicine are replacing the traditional “one size fits all” medicine. In the next decade the treatment of cancer will move from a reactive to a proactive discipline. The essence of personalized oncology lies in the use of biomarkers. These biomarkers can be from tissue, serum, urine or imaging and must be validated. Personalized oncology based on biomarkers is already having a remarkable impact. Three different types of biomarkers are of particular importance: predictive, prognostic and early response biomarkers. Tools for implementing preemptive medicine based on genetic and molecular diagnostic and interventions will improve cancer prevention. Imaging technologies such as Computed Tomography (CT) and Positron Emitted Tomography (PET) are already influencing the early detection and management of the cancer patient. Future advances in imaging are expected to be in the field of molecular imaging, integrated diagnostics, biology driven interventional radiology and theranostics. Molecular diagnostics identify individual cancer patients who are more likely to respond positively to targeted chemotherapies. Molecular diagnostics include testing for genes, gene expression, proteins and metabolites. The use of companion molecular diagnostics is expected to grow significantly in the future and will be integrated into new cancer therapies a single (bundled) package which will provide greater efficiency, value and cost savings. This approach represents a unique opportunity for integration, increased value in personalized oncology.

3.7  Pharmacogenomic biomarkers for personalized cancer treatment.

Rodríguez-Antona C1, Taron M.
J Intern Med. 2015 Feb; 277(2):201-17
http://dx.doi.org:/10.1111/joim.12321

Personalized medicine involves the selection of the safest and most effective pharmacological treatment based on the molecular characteristics of the patient. In the case of anticancer drugs, tumor cell alterations can have a great impact on drug activity and, in fact, most biomarkers predicting response originate from these cells. On the other hand, the risk of developing severe toxicity may be related to the genetic background of the patient. Thus, understanding the molecular characteristics of both the tumor and the patient, and establishing their relation with drug outcomes will be critical for the identification of predictive biomarkers and to provide the basis for individualized treatments. This is a complex scenario where multiple genes as well as pathophysiological and environmental factors are important; in addition, tumors exhibit large inter- and intraindividual variability in space and time. Against this background, the huge amounts of biological and genetic data generated by the high-throughput technologies will facilitate pharmacogenomic progress, suggest novel druggable molecules and support the design of future strategies aimed at disease control. Here, we will review the current challenges and opportunities for pharmacogenomic studies in oncology, as well as the clinically established biomarkers. Lung and renal cancer, two areas in which huge progress has been made in the last decade, will be used to illustrate advances in personalized cancer treatment; we will review EGFR mutation as the paradigm of targeted therapies in lung cancer, and discuss the dissection of lung cancer into clinically relevant molecular subsets and novel advances that suggest an important role of single nucleotide polymorphisms in the response to antiangiogenic agents, as well as the challenges that remain in these fields. Finally, we will present new approaches and future prospects for personalizing medicine in oncology.

3.8 Limits to forecasting in personalized medicine: An overview

John Ioannidis
International Journal of Forecasting 2009; 25(4):773-783.
http://dx.doi.org:/10.1016/j.ijforecast.2009.05.003

Biomedical research is generating massive amounts of information about potential prognostic factors for health and disease. However, few prognostic factors or systems are robustly validated, and still fewer have made a convincing difference in health outcomes or in prolonging life expectancy. For most diseases and outcomes, a considerable component of the prognostic variance remains unknown, and may remain so for the foreseeable future. I discuss here some of the main problems in medical forecasting that pose obstacles to personalized medicine. Their recognition may help identify solutions to improve personalized prognosis, or at least understand and cope with the component of the future that we cannot predict. Much prognostic research is stuck at generating “publishable units”, without any interest in conclusively proving their worth, let alone moving them into real life applications. Information is reported selectively and reporting is deficient. The replication record of prognostic claims is poor. Even among replicated prognostic effects, few are convincingly shown to add much information besides what is already known through more simple, traditional measurements. There are few efforts to systematize prognostic knowledge. Most prognostic effects are subtle when traced to the molecular level, where most current research operates. Many researchers, clinicians, and the public are not appropriately educated to interpret prognostic information. We still have not even agreed on what the important health outcomes are that we want to predict and intervene for, and some subjectivity may be unavoidable. Finally, without concomitant effective, affordable, and non-harmful interventions, prognosis alone is of questionable value, and wrong prognosis or a wrong interpretation thereof can be harmful. The identification of these problems also suggests a roadmap on what could be done to amend them. Solutions include a systematic approach to the design, conduct, reporting, replication, and clinical translation of prognostic research; as well as the education of researchers, clinicians, and the general public. Finally, we need to recognize that perfect individualized health forecasting is not a realistic target in the foreseeable future, and we have to live with considerable residual uncertainty.
Limits to forecasting in personalized medicine: An overview. Available from: https://www.researchgate.net/publication/223240409_Limits_to_forecasting_in_personalized_medicine_An_overview [accessed May 12, 2015].

3.9 The genome editing toolbox: a spectrum of approaches for targeted modification

Joseph K Cheng,  Hal S Alper

Current Opinion in Biotechnology 2014; 30C:87-94.
http://dx.doi.org:/10.1016/j.copbio.2014.06.005

The increase in quality, quantity, and complexity of recombinant products heavily drives the need to predictably engineer model and complex (mammalian) cell systems. However, until recently, limited tools offered the ability to precisely manipulate their genomes, thus impeding the full potential of rational cell line development processes. Targeted genome editing can combine the advances in synthetic and systems biology with current cellular hosts to further push productivity and expand the product repertoire. This review highlights recent advances in targeted genome editing techniques, discussing some of their capabilities and limitations and their potential to aid advances in pharmaceutical biotechnology.
The genome editing toolbox: a spectrum of approaches for targeted modification. Available from: https://www.researchgate.net/publication/263816651_The_genome_editing_toolbox_a_spectrum_of_approaches_for_targeted_modification [accessed May 12, 2015].

3.10 The Path to Personalized Medicine

Margaret A. Hamburg, and Francis S. Collins
N Engl J Med Jul 22, 2010; 363(4): 301-304
http://stanford.edu/class/gene210/files/readings/hamburg_collins.pdf

Researchers have discovered hundreds of genes that harbor variations contributing to human illness, identified genetic variability in patients’ responses to dozens of treatments, and begun to target the molecular causes of some diseases. In addition, scientists are developing and using diagnostic tests based on genetics or other molecular mechanisms to better predict patients’ responses to targeted therapy.

The challenge is to deliver the benefits of this work to patients. As the leaders of the National Institutes of Health (NIH) and the Food and Drug Administration (FDA), we have a shared vision of personalized medicine and the scientific and regulatory structure needed to support its growth. Together, we have been focusing on the best ways to develop new therapies and optimize prescribing by steering patients to the right drug at the right dose at the right time.

We recognize that myriad obstacles must be overcome to achieve these goals. These include scientific challenges, such as determining which genetic markers have the most clinical significance, limiting the off-target effects of gene-based therapies, and conducting clinical studies to identify genetic variants that are correlated with a drug response. There are also policy challenges, such as finding a level of regulation for genetic tests that both protects patients and encourages innovation. To make progress, the NIH and the FDA will invest in advancing translational and regulatory science, better define regulatory pathways for coordinated approval of codeveloped diagnostics and therapeutics, develop risk-based approaches for appropriate review of diagnostics to more accurately assess their validity and clinical utility, and make information about tests readily available.

Moving from concept to clinical use requires basic, translational, and regulatory science. On the basic-science front, studies are identifying many genetic variations underlying the risks of both rare and common diseases. These newly discovered genes, proteins, and pathways can represent powerful new drug targets, but currently there is insufficient evidence of a downstream market to entice the private sector to explore most of them. To fill that void, the NIH and the FDA will develop a more integrated pathway that connects all the steps between the identification of a potential therapeutic target by academic researchers and the approval of a therapy for clinical use. This pathway will include NIH-supported centers where researchers can screen thousands of chemicals to find potential drug candidates, as well as public– private partnerships to help move candidate compounds into commercial development.

The NIH will implement this strategy through such efforts as the Therapeutics for Rare and Neglected Diseases (TRND) program. With an open environment, permitting the involvement of all the world’s top experts on a given disease, the TRND program will enable certain promising compounds to be taken through the preclinical development phase — a time-consuming, high-risk phase that pharmaceutical firms call “the valley of death.” Besides accelerating the development of drugs to treat rare and neglected diseases, the TRND program may also help to identify molecularly distinct subtypes of some common diseases, which may lead to new therapeutic possibilities, either through the development of targeted drugs or the salvaging of abandoned or failed drugs by identifying subgroups of patients likely to benefit from them.

Another important step will be expanding efforts to develop tissue banks containing specimens along with information linking them to clinical outcomes. Such a resource will allow for a much broader assessment of the clinical importance of genetic variation across a range of conditions. For example, the NIH is now supporting genome analysis in participants in the Framingham Heart Study, obtaining biologic specimens from babies enrolled in the National Children’s Study, and performing detailed genetic analysis of 20 types of tumors to improve our understanding of their molecular basis.

As for translational science, the NIH is harnessing the talents and strengths of its Clinical and Translational Sciences Award program, which currently funds 46 centers and has awardees in 26 states, and its Mark O. Hatfield Clinical Research Center (the country’s largest research hospital, in Bethesda, MD) to translate basic research findings into clinical applications. Just as the NIH served as an initial home for human gene therapy, the Hatfield Center can provide specialized diagnostic services for rare and neglected diseases, offer a state-of-the-art manufacturing facility for novel therapies, and pioneer clinical trials of other innovative biologic therapies, such as those using human embryonic stem cells or induced pluripotent stem cells.

Today, about 10% of labels for FDA-approved drugs contain pharmacogenomic information — a substantial increase since the 1990s but hardly the limit of the possibilities for this aspect of personalized medicine.1 There has been an explosion in the number of validated markers but relatively little independent analysis of the validity of the tests used to identify them in biologic specimens.

The success of personalized medicine depends on having accurate diagnostic tests that identify patients who can benefit from targeted therapies. For example, clinicians now commonly use diagnostics to determine which breast tumors overexpress the human epidermal growth factor receptor type 2 (HER2), which is associated with a worse prognosis but also predicts a better response to the medication trastuzumab. A test for HER2 was approved along with the drug (as a “companion diagnostic”) so that clinicians can better target patients’ treatment (see table).

Increasingly, however, the use of therapeutic innovations for a specific patient is contingent on or guided by the results from a diagnostic test that has not been independently reviewed for accuracy and reliability by the FDA. For example, in 2006, the FDA granted approval to rituximab (Rituxan) for use as part of firstline treatment in patients with certain cancers. Since then, a laboratory has marketed a test with the claim that it can identify the approximately 20% of patients who are more likely to have a response to the drug. The FDA has not reviewed the scientific justification for this claim, but health care providers may use the test results to guide therapy. This undermines the approval process that has been established to protect patients, fails to ensure that physicians have accurate information on which to make treatment decisions, and decreases the chances that physicians will adopt a new therapeutic–diagnostic approach. The FDA is coordinating and clarifying the process that manufacturers must follow regarding their claims, including defining the times when a companion diagnostic must be approved or cleared before or concurrently with approval of the therapy. The agency will ensure that claims that a test will improve the care of patients are based on solid evidence, and developers will get straightforward, consistent advice about the standards for review and the best way to demonstrate that the combination works as intended.

In February, the NIH and the FDA announced a new collaboration on regulatory and translational science to accelerate the translation of research into medical products and therapies; this effort includes a joint funding opportunity for regulatory science. Working with academic experts, companies, doctors, patients, and the public, we intend to help make personalized medicine a reality. A recent example of this collaboration is an effort to identify new investigational agents to which certain tumors, identified by their genetic signatures, are responsive. Real progress will come when clinically beneficial new products and approaches are incorporated into clinical practice. As the field advances, we expect to see more efficient clinical trials based on a more thorough understanding of the genetic basis of disease. We also anticipate that some previously failed medications will be recognized as safe and effective and will be approved for subgroups of patients with specific genetic markers.

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Cancer Biomarkers [11.3.2.3]

Writer and Curator: Larry H. Bernstein, MD, FCAP

Cancer Biomarkers

This discussion is extracted from the Special Section – Cancer Biomarker Update – in May Arch Pathology and Lab Med.  It is not intended to be complete, but it has quite timely content.  There are three articles I shall cover.

11.3.2.3 Cancer Biomarkers

11.3.2.3.1 Cancer Biomarkers in Structured Data Reporting

11.3.2.3.2 Cancer Biomarkers in Myeloid Malignancies

11.3.2.3.3 National Comprehensive Cancer Network Consensus on Use of Cancer Biomarkers

Cancer Biomarkers – The Role of Structured Data Reporting
Simpson,  RW; Berman, MA; Foulis PR, et al.
Arch Pathol Lab Med. 2015;139:587–593
http://dx.doi.org:/10.5858/arpa.2014-0082-RA

The College of American Pathologists has been producing cancer protocols since 1986 to aid pathologists in the diagnosis and reporting of cancer cases. Many pathologists use the included cancer case summaries as templates for dictation/data entry into the final pathology report. These summaries are now available in a computer-readable format with structured data elements for interoperability, packaged as ‘‘electronic cancer checklists.’’ Most major vendors of anatomic pathology reporting software support this model. Objectives.—To outline the development and advantages of structured electronic cancer reporting using the electronic cancer checklist model, and to describe its extension to cancer biomarkers and other aspects of cancer reporting. Data Sources.—Peer-reviewed literature and internal records of the College of American Pathologists. Conclusions.—Accurate and usable cancer biomarker data reporting will increasingly depend on initial capture of this information as structured data. This process will support the standardization of data elements and biomarker terminology, enabling the meaningful use of these datasets by pathologists, clinicians, tumor registries, and patients.

Narrative Versus Structured Data Reporting Clinical laboratory reports typically consist of discrete data elements with structured qualitative or quantitative information, often using standardized laboratory methods, data elements, and units. When discrete data elements are electronically transmitted to external clinical information systems, the transmitted information may be annotated with one or more terminologies such as Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT)4 and Logical Observation Identifiers Names and Codes (LOINC),5 although the consistent application of such codes to structured laboratory data is not yet an interoperable standard. Because the structure of clinical laboratory data tends to be fixed and standardized before the point of data entry, reporting these data elements in a tabular synoptic format is a relatively simple process. The report output may not include all data collected (eg, methodologic details), but clinically relevant data can be easily extracted by computer algorithm and automatically reported in easily readable format (including custom text, result explanations, and test value trends).

Anatomic pathology reports, by contrast, have traditionally been narrative and recorded as unstructured or partially structured fields of text. Unfortunately, narrative reporting often lacks consistency in organization, content, units, terminology, and completeness.6–8 These structural inconsistencies create difficulties in finding and understanding clinically important data and increase the chance of omitting key data elements and misinterpreting information present in the narrative. This is particularly problematic when clinicians encounter reports from multiple pathology laboratories or when patients receive care at multiple institutions. Narrative reporting has equally negative effects on computer readability; the ability of computers to correctly parse and classify information contained in a narrative report is imperfect even when using advanced natural language processing software designed specifically for anatomic pathology.9,10 Natural language processing–parsed text must always undergo human review, editing, and signoff before release for patient care or research.

Ensuring consistency and readability of cancer and biomarker reports requires a reporting solution integrated into the pathologist workflow that supports entry of standardized data directly into a laboratory information system and/or electronic health record system. These systems can produce highly readable synoptic reports and can include computer-based report validation of standardized data elements to reduce or eliminate the chance of omitting required data elements. With the transition from narrative to synoptic reporting for cancer cases, many laboratories have been using modified CCPs or locally developed templates or macros, which may or may not contain all required data elements. This common mode of data entry fits well into the pathologist workflow and can result in organized, highly readable synoptic reports, but generally results in information stored as text in a single large data field. Even when results are entered as discrete data elements, subsequent storage mechanisms usually result in nonstructured text or nonstandard custom data fields in a local computer system. Unfortunately, narrative and nonstandardized data sets are very difficult to reliably aggregate and analyze for laboratory quality assurance, research, or cancer registry surveillance. Such aggregated data also remain relatively unreliable because of changes in information systems. Many of these issues can be eliminated by entering and reporting structured data with standardized electronic templates.

CAP eCC History, Development, and Adoption Efforts to bring structure to cancer pathology reporting began in the late 1980s and early 1990s1,11,12 with publication of templates that were the precursors of the current CCPs (Table). The primary goal was to improve the care of cancer patients by improving the reporting rate of clinically important data elements. The checklist approach was adopted to help standardize terminology and ensure all relevant data elements are reported. The 66 current CCPs, 3 new cancer biomarker templates,13–16 and 85 eCC templates represent the evolution of the original 1986 CCP model. The CCPs and templates are created and maintained through the ongoing work of the CAP Cancer and Cancer Biomarker Reporting Committees. The CCPs are widely adopted by laboratories and used for accreditation purposes by the American College of Surgeons–Commission on Cancer17 and CAP Laboratory Accreditation Program.18

During the past several years, the CAP has worked to create standardized pathology reporting templates that enable individual pathologists and software vendors to capture, store, retrieve, transmit, and analyze diagnostic cancer pathology information. Electronic versions of these templates, the eCCs, are based on consistent structured data representation, which enables simple yet robust computerization of cancer pathology data elements suitable for patient care, cancer registry transmission, and research. Synoptic reports are not the same as ‘‘structured data.’’ Although synoptic reports are formatted for optimum human readability and understanding, they consist of textbased questions and answers (ideally one pair per line) that present problems for computer readability and interoperability. Structured data, by contrast, refers to representation of data elements in a computer-readable data exchange format such as XML. The structured data model used by eCC XML templates assigns a unique identifier (a composite key) to every question and answer choice, template, section, and note listed in the template. Composite keys are used throughout the entire eCC life cycle to transmit the precise identity of each data element and its origin in a specific version of an eCC template.

The CAP eCC model has been implemented province wide by Cancer Care Ontario through their multiyear synoptic pathology reporting and change-management project.19–21 The Canadian Partnership Against Cancer is also currently working with several other Canadian provinces to implement population-level electronic synoptic reporting based on the CAP eCC. The Cancer Care Ontario project has shown that there is high acceptability among pathologists and clinicians22 and that data are usable for the secondary needs of tumor registries,20 but there remains room for improvement. For instance, both the Reporting Pathology Protocols project reports23–25 and the Cancer Care Ontario implementation reports22 suggest that pathologists require more time to complete the reporting task.

While this may meet quality and data reporting needs, it remains a potential barrier to acceptance. Automated human-readable report generation also could be improved, especially in terms of creating best practice guidelines for report output. Both data entry and report generation have traditionally been supported by laboratory information systems vendors, but the success of implementation has varied, and often significant effort is required to modify the resultant human readable report to satisfy local clinical needs. Because the final report remains most important for patient care, the CAP Diagnostic Intelligence in Health Information Technology and Pathology Electronic Reporting committees have initiated work on creating and promoting a standardized data structure within cancer pathology reports.

Abbreviated CAP eCC History and Milestones

2010–2012 CCO successfully implements population level electronic synoptic reporting in nearly all disease sites based on 2010 CAP eCC standards, which include AJCC 7th edition TNM staging; 97% of labs report using structured data from eCC.20

2010 CAP Laboratory Accreditation Program begins to survey institutions for inclusion of required CCP data elements in AP reports.38

2010 NAACCR Pathology Data Workgroup develops implementation guide to assist with CAP eCC-based transmissions of cancer data to central cancer registries.39

2011 CCO user acceptability data demonstrate high level of acceptance for eCC-derived synoptic reports among clinicians and pathologists.22

2012 CAP forms the multi-organizational Cancer Biomarker Reporting Workgroup, tasked to produce standardized reporting templates for breast, colorectal, and lung cancer biomarkers.40

2013 eCC-based reporting in Ontario is used to improve quality and practice performance.20

2013 The first cancer biomarker templates are produced for breast, colorectal, and lung cancer.13–16 They are available on the http://www.cap.org/cancerprotocols Web site in Word and PDF format (accessed April 28, 2014). The eCC versions are available through CAP.

2013 Launch of CAP eFRM, a software product to aid vendor integration of eCCs into AP-LIS systems or for use as a standalone product.

2014 By December 2013, CAP is maintaining current versions of 66 CCPs, 3 cancer biomarker templates, and 85 corresponding eCC templates.

References

13. Cagle PT, Sholl LM, Lindeman NI, et al. Template for reporting results of biomarker testing of specimens from patients with non–small cell carcinoma of the lung. Arch Pathol Lab Med. 2014; 138(2):171–174. http://dx.doi.org:/10.5858/arpa.2013-0232-CP

14. Cagle PT, Allen TC, Olsen RJ. Lung cancer biomarkers: present status and future developments. Arch Pathol Lab Med. 2013; 137(9):1191–1198.
http://dx.doi.org:/10.5858/arpa.2013-0319-CR

15. Bartley AN, Hamilton SR, Alsabeh R, et al. Template for reporting results of biomarker testing of specimens from patients with carcinoma of the colon and rectum. Arch Pathol Lab Med. 2014; 138(2):166–170.
http://dx.doi.org:/10.5858/arpa.2013-0231-CP

16. Fitzgibbons PL, Dillon DA, Alsabeh R, et al. Template for reporting results of biomarker testing of specimens from patients with carcinoma of the breast. Arch Pathol Lab Med. 2014; 138(5):595–601.
http://dx.doi.org:/10.5858/arpa.2013-0566-CP

20. Srigley J, Lankshear S, Brierley J, et al. Closing the quality loop: facilitating improvement in oncology practice through timely access to clinical performance indicators. J Oncol Pract. 2013; 9(5):e255–e261. http://dx.doi.org:/10.1200/JOP.2012.000818

22. Lankshear S, Srigley J, McGowan T, Yurcan M, Sawka C. Standardized synoptic cancer pathology reports—so what and who cares?: a population-based satisfaction survey of 970 pathologists, surgeons, and oncologists. Arch Pathol Lab Med. 2013; 137(11):1599–1602.
http://dx.doi.org:/10.5858/arpa.2012-0656-OA

38. College of American Pathologists. CAP cancer protocols frequently asked questions. http://www.cap.org/apps//cap.portal
39. Klein WT, Havener LA, eds. Standards for Cancer Registries Volume V: Pathology Laboratory Electronic Reporting, Version 4.0. Springfield, IL: North American Association of Central Cancer Registries; 2011:1–310.
40. Fitzgibbons PL, Lazar AJ, Spencer S. Introducing new College of American Pathologists reporting templates for cancer biomarkers. Arch Pathol Lab Med. 2014; 138(2):157–158. http://dx.doi.org:/10.5858/arpa.2013-0233-ED

41. Amin MB. The 2009 version of the cancer protocols of the College of American Pathologists. Arch Pathol Lab Med. 2010; 134(3):326–330.
http://dx.doi.org:/10. 1043/1543-2165-134.3.326.

Figure 1. (not shown) Narrative versus synoptic versus structured reporting of breast biomarker testing (excerpts). The narrative row shows a portion of a dictated biomarker report. The synoptic row satisfies the College of American Pathologists (CAP) synoptic reporting requirements, but is not computer readable.

 

 

Figure 2. (not shown) The College of American Pathologists (CAP) Cancer Protocols (CCPs) are developed by the CAP Cancer Committee. Each CCP is reformulated as question/answer structures, entered into the CAP electronic Cancer Checklist (eCC) Template Editor (not shown), and stored in the eCC template database. The eCC files in XML format are produced from this database and delivered to vendors of anatomic pathology/laboratory information system (LIS) software systems. Vendors convert the eCC files into data entry form implementations using their local technologies. In addition, most vendors create eCC-based templates for creating synoptic reports. When pathologists enter data into the eCC-based data-entry forms, the vendor software is able to run validation checks such as assessing whether all CCP-required data elements are recorded. Synoptic reports are developed from the eCC-derived data and delivered to health care providers for patient care. The eCC-structured data is stored in the vendor database, where it can be transmitted in interoperable format to other computer systems. Secondary uses of eCC-based data include cancer registry reporting, quality assurance, biospecimen annotation, research, decision support, and financial reporting. The horizontal arrows involve the exchange of eCC composite keys, preserving the fidelity of the data as part of an eCC template, providing the foundation for interoperable data transmission formats, and enabling the regeneration of eCC datasets in the exact format in which they were recorded. Activity columns that directly impact health care activities are shaded in light blue. Abbreviation: EHR, electronic health record.

Future The use of standardized, structured data elements is foundational for the development of improved reporting and clinical decision support for biomarker results. Clinicians are currently faced with synthesizing data from multiple narrative reports to decide on treatment options. Often these narrative reports are from different laboratories with very different report formats and include variable methodologic details, all of which hinders understanding of important results. For biomarkers that determine a patient’s eligibility for specific drugs, a computer-generated report that presents test results in a tabular form, similar to antibiotic susceptibility testing, may be desirable. This reporting method would allow for display of biomarker test results over time and could also link to other databases.

Structured data allows for clinical decision support such that the report displays only eligible drugs, or the report displays a note stating that a test result suggests a patient is not eligible for a specific drug. Using standardized terminology allows these rules to be the same between institutions, even if electronic health record system vendors use different means of implementation.

Figure 3. (not shown) College of American Pathologists electronic Cancer Checklist lung cancer biomarker template—anaplastic lymphoma kinase (ALK). Abbreviations: EML4, echinoderm microtubule-associated protein-like 4; KIF5B, kinesin family member 5B; KLC1, kinesin light chain 1; TFG, tropomyosin receptor kinase–fused gene.

Figure 4. (not shown) Examples of tumor biomarker dashboards. Abbreviations: ALK, anaplastic lymphoma kinase; ROS1, ROS proto-oncogene 1, receptor tyrosine kinase.

This system would allow for more efficient, more accurate, and safer methods of providing data for optimizing patient care, with all of the discrete data transmitted electronically and linked to the original tumor report. In Ontario, Canada, this vision is rapidly advancing, as demonstrated by the Cancer Care Ontario successes with eCC implementation and current plans to implement the eCC biomarker templates across the province. Future challenges include the identity and tracking of related tumor samples over time and integration of testing from different laboratories. Because testing on a given specimen can be performed at different times and in different laboratories, a future standard must address the annotation of results with tumor source, procurement dates, and other biospecimen-specific data.30 The relationship of test results from multiple specimens from the same patient needs to be recorded in a standard format so that this parent-child hierarchical relationship can be analyzed over time.

Pathologists are increasingly asked to provide biomarker information for patient care, tumor registries, epidemiologic studies, translational research, and quality improvement activities.20 The eCC model provides a pathway to meet these demands, with efficient and error-free data entry, reporting, and transmission of data elements, and with the ability to produce output that is human readable, efficient to use, and easy to interpret. As the CCPs and eCCs have matured, Ontario pathologists and cancer registries have demonstrated success with large-scale implementations. However, continued improvements are needed. As the field of pathology grows, particularly in the area of biomarkers, structured electronic reporting will become critical to helping physicians provide optimal patient care and will facilitate secondary uses of pathology data.

  1. Robb JA, Gulley ML, Fitzgibbons PL, et al. A call to standardize preanalytic data elements for biospecimens. Arch Pathol Lab Med. 2014; 138(4):526–537.

Molecular Genetic Biomarkers in Myeloid Malignancies
Matynia AP, Szankasi P, Shen W, Kelley TW.
Arch Pathol Lab Med. 2015;139:594–601
http://dx.doi.org:/10.5858/arpa.2014-0096-RA

Recent studies using massively parallel sequencing technologies, so-called next-generation sequencing, have uncovered numerous recurrent, single-gene variants or mutations across the spectrum of myeloid malignancies. Objectives.—To review the recent advances in the understanding of the molecular basis of myeloid neoplasms, including their significance for diagnostic and prognostic purposes and the possible implications for the development of novel therapeutic strategies. Data Sources.—Literature review. Conclusions.—The recurrent mutations found in myeloid malignancies fall into distinct functional categories.

These include (1) cell signaling factors, (2) transcription factors, (3) regulators of the cell cycle, (4) regulators of DNA methylation, (5) regulators of histone modification, (6) RNA-splicing factors, and (7) components of the cohesin complex. As the clinical significance of these mutations and mutation combinations is established, testing for their presence is likely to become a routine part of the diagnostic workup. This review will attempt to establish a framework for understanding these mutations in the context of myeloproliferative neoplasms, myelodysplastic syndromes, and acute myeloid leukemia.

Pathways Affected by Recurrent Mutations in Myeloid Malignancies

Cell Signaling The ability of a cell to respond to diverse physiologic stimuli, including cytokines, chemokines, growth factors, and hormones, or to the presence of bacteria and other microorganisms is mediated via the interaction of specific ligands and their corresponding cell surface receptors. Ligand binding usually results in receptor dimerization and activation of a tyrosine kinase, either intrinsically present in the cytoplasmic domain or as an associated polypeptide. Further propagation of the signal from the cell surface to the nucleus involves the formation of macromolecular complexes and the activation or inactivation of various enzymes. The final outcome of the signal transduction is modulation of the expression of certain genes and their products, which ultimately produces a cellular response. In normal cells, this process is tightly regulated owing to the involvement of negative or inhibitory signals. In tumor cells these processes may be perturbed owing to mutations that impart inappropriate activation or deactivation of enzymatic function. Genes for receptor protein tyrosine kinases, such as FLT3 and KIT, or receptor-associated kinases, such as JAK2, are the most commonly mutated cell-signaling factors in myeloid malignancies. Activating mutations in these proteins occur in narrowly defined hotspots, resulting in ligand-independent dimerization or constitutive kinase activation. An example is the protein tyrosine kinase JAK2, which transduces signals from ligand-bound cell surface receptors for thrombopoietin (TPOR/MPL) and erythropoietin (EPOR).

Activating mutations in JAK2 are commonly found in the myeloproliferative neoplasms (MPNs): polycythemia vera (PV), essential thrombocythemia (ET), and primary myelofibrosis (PMF). These disorders appear to be driven, in large part, by the inappropriate activation of growth factor– signaling pathways, and JAK2 is central to signaling from EPOR and TPOR/MPL via STAT5, STAT3, the RAS-MAP kinase pathway, and the PI-3 kinase–AKT pathway. Many negative regulators of cytokine signaling, such as SH2B adaptor protein 3 (SH2B3, also known as LNK)1,2 and cytokine-inducible SH2-containing protein (CISH, also known as SOCS)3 keep the pathway in balance. Downstream RAS signaling is counteracted by NF1, a protein that stimulates the intrinsic RAS guanosine triphosphatase activity. An effect similar to JAK2 mutations may be achieved through mutations in other proteins involved in these pathways, including activating mutations of a surface receptor (MPL) or loss-of-function mutations in negative regulators (SH2B3, CISH), all of which promote survival, proliferation, and differentiation of committed myeloid progenitors.4 Example genes included in this group: JAK2, MPL, KIT, FLT3, CSF3R, PTPN11, KRAS, NRAS, and NF1.

Transcription Transcription is a tightly regulated process that depends on the formation and assembly of protein and protein-DNA complexes. These complexes, called transcription factors, bind to specific DNA sequences adjacent to the genes they regulate and promote (in the case of an activator) or block (in the case of a repressor) the recruitment of RNA polymerases to those genes. This regulatory activity controls the formation of messenger RNA (mRNA) transcripts. Mutations that block the activity of transcriptional activators may, in certain circumstances, lead to a block in cellular differentiation due to the lack of the necessary gene products. Many of the transcription factors that are recurrently mutated in myeloid malignancies, such as RUNX1, GATA1, GATA2, and CEBPA, are involved in fundamental aspects of myelopoiesis and it is believed that these mutations lead to a block in myeloid differentiation.  Example genes included in this group: RUNX1, CEBPA, GATA1, GATA2, ETV6, and PHF6.

Epigenetic Modifiers: Regulation of DNA Methylation DNA methylation involves the addition of a methyl group to cytosine bases in the context of cytosine-guanine sequences (so-called CpG sites), leading to the creation of 5-methylcytosine. CpG islands are usually located in or near promoter regions. Their methylation is an important epigenetic mechanism for regulating gene expression and, in the context of heritable methylation patterns, underlies the process of genomic imprinting. Additionally, it has been hypothesized that aberrant DNA methylation may contribute to the pathogenesis of cancers,5–8 including myeloid neoplasms. Although cancer genomes tend to be globally hypomethylated, in comparison with normal tissues, hypermethylation of specific CpG islands at tumor suppressor genes, resulting in their inactivation, is common in many tumors.9

ormation of compact, inactive heterochromatin.10 Several factors regulate the process of DNA methylation. Mutations in some of these factors have been found recurrently in myeloid neoplasms.11–13 DNA methyltransferases catalyze the methylation at the 50 position of cytosine. DNMT3A and DNMT3B are involved in de novo methylation, whereas DNMT1 maintains hemimethylated DNA during replication. Once created, 5-methylcytosine can be further modified by a group of methylcytosine dioxygenases (Ten Eleven Translocation dioxygenases: TET1, TET2, and TET3) to 50-hydroxymethylcytosine, a presumed short-lived intermediary that may lead to demethylation of cytosine.

Mutations in both DNMT3A and TET2 likely lead to loss of function of the respective enzyme activities. Recently, mutations in IDH1 and IDH2 have been identified in myeloid neoplasms and other cancers. Interestingly, recurring mutations of an arginine residue in the active site (R132 in IDH1 and R140 in IDH2) prevent the normal catalytic function of the enzyme (conversion of isocitrate to aketoglutarate) and appear to induce a neomorphic enzyme activity resulting in the formation of the rare oncometabolite 2-hydroxyglutarate.14 TET2 belongs to a family of dioxygenases that requires a-ketoglutarate as a cofactor.15,16 It has been shown that 2-hyroxyglutarate acts as a competitive inhibitor of a-ketoglutarate–dependent dioxygenases, which include TET2 and members of the KDM family of histone demethylases, thereby inducing epigenetic changes at both the level of DNA methylation and histone modification.14,17

Therapeutic inhibitors of mutant forms of IDH proteins and the resulting 2-hydroxyglutarate are also under investigation.18 Example genes included in this group: DNMT3A, TET2, IDH1, and IDH2.

Epigenetic Modifiers: Mutations Affecting Histone Function  Histone proteins are involved in the dynamic organization of DNA into zones of active euchromatin and inactive heterochromatin in a process that is regulated, in part, by a complex series of posttranslational modifications to histone tails, including acetylation and methylation. These modifications affect the recruitment of regulatory proteins such as transcription factors, corepressors, and coactivators, as well as histone-modifying enzymes themselves. Trimethylation of the lysine at position 27 in histone H3 (H3K27), one of the more common modifications, generally leads to reduced gene expression and it would be expected that mutations that reduce methylation at H3K27 would activate transcription. Recently, recurrent mutations in several genes encoding histone regulators, including ASXL1, EZH2, SUZ12, and KDM6A (also known as UTX), have been identified.

Perturbations in epigenetic pathways result in global, genome-wide effects and it is often difficult to identify which altered cellular function eventually leads to neoplasia. The same also holds true for perturbations in the RNA splicing machinery and the cohesion complex (see below). Example genes included in this group: ASXL1, EZH2, SUZ12, and KDM6A.

Cohesin Complex Genes  The cohesin complex is a conserved multimeric protein complex that regulates cohesion of sister chromatids during cell division,21 postreplicative DNA repair,22,23 and global gene expression.24–28
Example genes included in this group: STAG2, RAD21, SMC1A, and SMC3.

RNA-Splicing Factors  RNA splicing results in the formation of mature mRNA transcripts derived from exons, the protein coding portion of the genome. Splicing occurs in a macromolecular complex of small nuclear RNAs and proteins assembled de novo on each pre-mRNA strand in a multistep process. This complex is known as the spliceosome. Transcripts may undergo alternative splicing in a tissue, or context-specific manner and the protein products of alternatively spliced transcripts may have altered function.
Example genes included in this group: SF3B1, SRSF2, ZRSR2, and U2AF1.

Cell Cycle Regulators  Example genes included in this group: TP53 and NPM1.

Genetic Biomarkers in Myeloid Malignancies

Myeloproliferative Neoplasms  Myeloproliferative neoplasms encompass a group of clonal stem cell disorders characterized by expansion of 1 or more of the myeloid lineages resulting in bone marrow hypercellularity and increased peripheral blood myeloid cell counts. The MPN category includes chronic myelogenous leukemia, PV, ET, PMF, chronic neutrophilic leukemia, mastocytosis, and others. The underlying genetic landscape of some of these disorders is very well understood, as in the case of chronic myelogenous leukemia with t(9;22), but is much less well understood in many other entities.

The discovery of a recurrent codon 617 activating mutation (V617F) in exon 14 of the tyrosine kinase JAK237–40 and additional mutations in JAK2 exon 1241 provided the first genetic evidence of the importance of dysregulated growth factor signaling in these disorders. The prevalence of JAK2 mutations in classical MPNs varies from 95% to 99% in PV, 50% to 70% in ET, 40% to 50% in PMF,37–41,43 and molecular tests for their detection are available and widely used in clinical practice. Similarly, activating mutations in the MPL gene, encoding the thrombopoietin receptor, are present in approximately 4% of ET cases and approximately 11% of PMF cases.44–47 Recently, calreticulin (CALR), encoding an endoplasmic reticulum chaperone, has also been shown to be important. Somatic CALR mutations are found in 70% to 84% of patients with ET or PMF with wild-type JAK2 and MPL, 8% of MDS cases, and occasionally in other myeloid neoplasms.48 Clonal analyses suggest CALR mutations act as an initiating mutation in some patients.48 In ET and PMF, CALR mutations and JAK2 and MPL mutations are mutually exclusive,49 and CALR mutations appear to be absent in PV.49 CALR mutations appear to be primarily insertion or deletion mutations that result in a frameshift and the subsequent generation of a novel C-terminal peptide.48,49

Many other genes involved in intracellular signaling, such as negative regulators of the JAK2 signaling pathway, are mutated in MPNs. Among these is SH2B3, which negatively regulates JAK2 activation through its SH2 domain. Mutations in SH2B3 during the chronic phase are uncommon, fewer than 5% in ET and PMF50; however, their frequency increases during leukemic transformation, suggesting a role in disease progression.51 Another negative regulator found mutated in MPNs is the Cbl proto-oncogene, E3 ubiquitin protein ligase gene (CBL). CBL acts as a multifunctional adapter with ubiquitin ligase activity and by competitive blockade of signaling.

A shift from a simple, chronic myelogenous leukemia–like model for MPN pathophysiology to a more complex model occurred with the emergence of evidence of a ‘‘pre-JAK2’’ genetic event. This concept is based on the observation that mutations in signaling molecules are not sufficient for disease development and that several cooperating genetic hits appear to be required.4 Mutations in genes involved in epigenetic regulation, including EZH2, ASXL1, and TET2 (also found in many other myeloid neoplasms), are postulated to act as those initialing events, preceding JAK2V617F mutations.55 EZH2 mutations do not occur in ET, but are present in 3% of PVs and 13% of MFs.56 ASXL1 mutations are found in only approximately 7% of patients with ET and PV but more frequently in PMF cases (from 19%–40%).57,58 TET2 mutations occur in approximately 14% of MPNs, ranging from 11% in ETs to 19% in PMFs.59,60 Finally, there are mutations that are rarely found during the chronic phase but which may be present at transformation, and are therefore thought to play a role in disease progression. IDH1 and IDH2 mutations, for example, have a low frequency in the chronic phase (0.8% in ET, 1.9% in PV, and 4.2% in MF) but a much higher frequency in blast phase.61

Myelodysplastic Syndromes and MDS/MPN Overlap Disorders 

The myelodysplastic syndromes are a group of clonal hematopoietic stem cell disorders characterized by ineffective hematopoiesis, morphologic evidence of dysplasia in at least 1 of the myeloid lineages, peripheral cytopenias, bone marrow hypercellularity, and an increased risk of development of AML.74 Clonal cytogenetic abnormalities, including large deletions and chromosome gains, as well as balanced translocations, are observed in approximately 50% of MDS cases by routine methods,74 and their identification aids in establishing the diagnosis and may provide prognostic information.

Acute Myelogenous Leukemia  Acute myeloid leukemia is a genetically heterogeneous disease resulting in the accumulation of myeloblasts in bone marrow with a concomitant reduction in normal hematopoiesis. The diagnosis and subclassification of AML depends on detecting the presence of recurrent cytogenetic abnormalities.74 In many cases, particularly those that are cytogenetically normal (CN-AML), several single-gene mutations further aid in the stratification of disease outcomes. The significance of mutations in genes such as FLT3, NPM1, and CEBPA is well established but nextgeneration sequencing has led to the discovery of numerous additional recurrent mutations, including in TET2,12,59 ASXL1,104 IDH1/IDH2,13,105,106 DNMT3A,11,107 and PHF6.108

Among the most common mutations found in de novo AML are NMP1, FLT3, and DNMT3A mutations, present in 22% to 29%, 22% to 37%, and 15% to 26% of samples, respectively.31,110,111 Other genes less commonly targeted by mutations are IDH1/IDH2 (15%– 20%), KRAS/NRAS (12% combined), RUNX1 (5%–10%),TET2 (8%–14%), TP53 (2%–8%), CEBPA (6%–14%), WT1 (6%–8%), PTPN11 (4%), and KIT (4%–6%).31,110,111

The prognostic significance of a subset of recurrent mutations is well established. In CN-AML, biallelic CEBPA mutations127,128 and NPM1 mutations without FLT3-ITD mutations129–133 are associated with a favorable prognosis. In contrast, FLT3-ITD without NPM1 mutations112,113,129–132 and MLL–partial tandem duplication mutations134–136 portend poor outcome. KIT mutations in AML with t(8;21) or inv(16)131,137 are also associated with unfavorable outcome. The European LeukemiaNet panel138 first proposed a standardized classification according to both cytogenetic and molecular genetic data to allow a better comparison of prognosis among patients with AML. However, only mutations of NPM1, CEBPA, and FLT3 were included in their recommendations. The relevance of more recently discovered mutations, including IDH1, IDH2, WT1, TET2, ASXL1, among others, remains unclear.139–142 The presence of certain mutations may also allow for more targeted therapeutic regimens; for example, FLT kinase inhibitors may be useful in cases with mutations and IDH1 inhibitors are under investigation in patients with IDH1 mutations.143,144

An enormous amount of new information illuminating the genetic complexity of myeloid neoplasms has been generated during the last few years. Much work remains to be done but it is clear that the future role of the pathologist in collecting and interpreting this information will be an essential component of the management of these patients.

 

The Cancer Genomics Resource List 2014
Zutter MM, Bloom KJ, Cheng L, Hagemann IS, et al.
Arch Pathol Lab Med. http://dx.doi.org:/10.5858/arpa.2014-0330-C

Optimizing the Clinical Utility of Biomarkers in Oncology: The NCCN Biomarkers Compendium
Marian L. Birkeland, Joan S. McClure
Arch Pathol Lab Med. 2015;139:608–611
http://dx.doi.org:/10.5858/arpa.2014-0146-RA

The rapid development of commercial biomarker tests for oncology indications has led to confusion about which tests are clinically indicated for oncology care. By consolidating biomarker testing information recommended within National Comprehensive Cancer Network Clinical Practice Guidelines in Oncology (NCCN Guidelines), the NCCN Biomarkers Compendium aims to ensure that patients have access to appropriate biomarker testing based on the evaluations and recommendations of the expert NCCN panel members.
Objectives.—To present the recently launched NCCN Biomarkers Compendium. Data Sources.—Biomarker testing information recommended within NCCN Clinical Treatment Guidelines as well as published resources for genetic and biological information. Conclusions.—The NCCN Biomarkers Compendium is a continuously updated resource for clinicians who need access to relevant and succinct information about biomarker testing in oncology and is linked directly to the recommendations provided within the NCCN Clinical Practice Guidelines.

Most recommendations contained within the NCCN Guidelines are based upon lower-level evidence and uniform NCCN consensus (category 2A).1 This is not a deficiency of the guidelines, but is rather because high-level evidence is not available for most decisions across the continuum of care. A deeper look at what constitutes a ‘‘recommendation’’ might begin to clarify that issue. A recommendation can include all of the recommended workup, surgical options, options for chemotherapy, and tests recommended for ongoing surveillance. Although many of these options are routinely used as standard of care in clinical practice, there is often not the available body of high-level evidence that supports category 1 recommendations, thus most are category 2A levels of evidence and consensus. In other instances, recommendations for chemotherapy regimens for which there is high-level, randomized clinical trial evidence are listed as category 1.

Several derivative products arise from the NCCN Guidelines. The NCCN Drugs & Biologics Compendium (NCCN Compendium) is a resource outlining appropriate use of drugs and biologics as recommended in the NCCN Guidelines. To be included in the compendium, an agent must first be recommended in at least 1 of the NCCN Guidelines. The compendium is typically used by clinicians and payors to determine appropriate use and as a standard to determine coverage. The rapid development and commercialization of biomarker and companion diagnostic testing in cancer gave rise to the NCCN Biomarkers Compendium, to be used by both payors and clinicians to facilitate identification of biomarker tests recommended for use by NCCN guideline panels. The NCCN uses a broad definition of ‘‘biomarker’’ for the purposes of this compendium. All tests measuring genes or gene products, which are used for diagnosis, screening, monitoring, surveillance, or for providing predictive or prognostic information, are included in the biomarkers compendium. This compendium focuses on the biology of the biomarker itself and its clinical utility in supporting clinical decision making. Information is organized by the biomarker being measured, and not by listing of commercially available tests or test kits. Close to 1000 biomarker testing recommendations are included in the NCCN Biomarkers Compendium.

The NCCN Biomarkers Compendium is presented on the NCCN Web site as a series of drop-down menus, allowing users to pick from menus listing Guideline, Disease, Molecular Abnormality, or Gene Symbol.3 Users can retrieve all recommendations for a particular disease, or can select a gene-based search in order to show which diseases have a validated use for a particular gene test. Additional fields can be displayed by selecting from a series of boxes to the right of the drop-down menus (see Figure 1, which shows default fields for RAS testing in colon cancer). Once records are displayed, the resulting table can be sorted by the information in any of the displayed columns. If a searcher chooses, all records can be displayed and then searched with any text term or sorted by any of the columns for a more comprehensive picture of the contents of the database.

Figure 1. (not shown)  KRAS mutation testing recommendation from the National Comprehensive Cancer Network (NCCN) Biomarkers Compendium.3 Reproduced with permission from the NCCN Biomarkers Compendium [1] 2014 National Comprehensive Cancer Network, Inc. (NCCN.org; accessed February 21, 2014). To view the most recent and complete version of the NCCN Biomarkers Compendium, go online to NCCN.org. National Comprehensive Cancer Network, NCCN, NCCN Guidelines, and all other NCCN content are trademarks owned by the National Comprehensive Cancer Network, Inc.

Disease Description Colon cancer
Specific Indication Metastatic disease
Molecular Abnormality KRAS/NKRAS mutation
Test KRAS/NKRAS
Chromosome 1p13.2, 12p12.1
Gene Symbol KRAS/NKRAS
Test Detects Mutation
Methodology
Category of Evidence 2A
Specimen Types FFPE tumor tissue
Recommendation …Determination of RAS mutations.
Test Purpose Predictive
Guideline Page COL 4 of 5, COL 4, COL 9
Note All patients with metastatic colorectal cancer should be genotyped for RAS mutations. At the very least …

Figure 2. (Table)  Example of PDF file generated from ‘‘print’’ command of National Comprehensive Cancer Network (NCCN) Biomarkers Compendium record. Reproduced with permission from the NCCN Biomarkers Compendium [1] 2014 National Comprehensive Cancer Network, Inc (NCCN.org; accessed February 21, 2014). To view the most recent and complete version of the NCCN Biomarkers Compendium, go online to NCCN.org. National Comprehensive Cancer Network, NCCN, NCCN Guidelines, and all other NCCN content are trademarks owned by the National Comprehensive Cancer Network, Inc.

Table 2. (List) Summary of Testing Types Included in the National Comprehensive Cancer Network Biomarkers Compendiuma,b

Protein expression
Translocation
Mutation
Chromosomal defect
Gene rearrangement
Virus detection
Antigen expression
Serum proteins
Amplification
Short repeated sequences
Promoter methylation
Gene expression pattern
Helicobacter pylori

Table 3. Predictive Tests Used for Treatment Decision Making, Extracted From National Comprehensive Cancer Network Guidelines and Biomarkers Compendiuma,b

Test   Disease
21-gene RT-PCR

BCR-ABL1 translocation

Breast cancer
ABL1 mutation Ph+ acute lymphoblastic leukemia, chronic myelogenous leukemia
ALK rearrangement Non–small cell lung cancer
BRAF mutation Non–small cell lung cancer, melanoma, colon cancer, rectal cancer
EGFR mutation Non–small cell lung cancer
ERBB2 amplification/overexpression Breast cancer, esophageal and esophagogastric junction cancers, gastric cancer
ESR1 expression Breast cancer
KIT mutation Soft tissue sarcoma: GIST
KRAS mutation Colon cancer, rectal cancer, non–small cell lung cancer
MGMT promoter methylation Central nervous system cancers: anaplastic glioma/glioblastoma
MLH1, MSH2, MSH6, PMS2 expression and/or mutation, MSI testing Colon cancer, rectal cancer
PDGFRA mutation Soft tissue sarcoma: GIST
PGR expression Breast cancer
ROS1 rearrangement Non–small cell lung cancer

A large number of tests were grouped for the purposes of this simplified table into the category of gross chromosomal abnormalities. Interestingly, the guidelines so far contain only a single recommendation for the use of a gene expression profiling test, and this is the 21-gene reverse transcription–polymerase chain reaction test recommended within the breast cancer treatment guideline, where the score for this test can be used as part of a decision-making process for chemotherapy recommendations in node negative, hormone receptor–positive, HER2-negative disease.

Table 3 summarizes the biomarker tests included in the NCCN Biomarkers Compendium that are predictive for either responsiveness (eg, BRAF mutation and vemurafenib sensitivity) or nonresponsiveness (eg, KRAS mutation testing and cetuximab or panitumumab insensitivity) to a particular type of therapy. As the number of companion diagnostics and targeted therapies grows, we expect this category of test to become one of the largest categories of testing contained within the Biomarkers Compendium, and it may be surprising to note that only 15 of these types of test are currently recommended within the NCCN Guidelines.

The NCCN Biomarkers Compendium generally avoids recommendations for particular methodologies or test kits to use to assess mutations and translocations. The choice of methodology and supplier for carrying out the recommended biomarker tests remains that of the treating oncologists and pathologists.

The NCCN Biomarkers Compendium may be used by payers as a reference for coverage decisions and by clinicians as a guide to which biomarkers are appropriate to test. The Biomarkers Compendium focuses on the clinical usefulness of biomarker testing rather than specific tests or test kits that identify the presence or absence of the marker. Other groups are continuing to assess clinical and analytic validity for specific biomarker test methodologies. Even the US Food and Drug Administration approval process is limited to clinical and analytic validity, and does not specifically address clinical utility. The NCCN Biomarkers Compendium is complementary to these other efforts. By providing biomarker testing information, the NCCN Biomarkers Compendium aims to ensure that patients have coverage and access to appropriate biomarker testing, based on the evaluations and recommendations of the expert NCCN panel members.

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Notes On Tumor Heterogeneity: Targets and Mechanisms, from the 2015 AACR Meeting in Philadelphia PA

Reporter: Stephen J. Williams, Ph.D.

The following contain notes from the Sunday April 19, 2015 AACR Meeting (Pennsylvania Convention Center, Philadelphia PA) 1 PM Major Symposium Session on Tumor Heterogeneity: Targets and Mechanism chaired by Dr. Charles Swanton.

Speakers included: Mark J. Smyth, Charles Swanton, René H. Medema, and Catherine J. Wu

Tumor heterogeneity is a common feature of many malignancies, especially the solid tumors and can drive the evolution and adaptation of the growing tumor, complicating therapy and resulting in therapeutic failure, including resistance. This session at AACR described the mechanisms, both genetic and epigenetic, which precipitate intratumor heterogeneity and how mutational processes and chromosomal instability may impact the tumor progression and the origin of driver events during tumor evolution. Finally the session examined possible therapeutic strategies to take advantage of, and overcome, tumor evolution. The session was chaired by Dr. Charles Swanton. For a more complete description of his work, tumor heterogeneity, and an interview on this site please click on the link below:

Issues in Personalized Medicine in Cancer: Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing

and

Issues in Personalized Medicine: Discussions of Intratumor Heterogeneity from the Oncology Pharma forum on LinkedIn

 

Notes from Charles Swanton, Cancer Research UK; Identifying Drivers of Cancer Diversity

Dr. Swanton’s lecture focused on data from two recent papers from his lab by Franseco Favero and Nicholas McGranahan:

  1. Glioblastoma adaptation Traced Through Decline of an IDH1 clonal driver and macro-evolution of a double-minute chromosome (Annals of Oncology, 2015)[1]

This paper described the longitudinal Whole Genome Sequencing (WGS) study of a 35 year old female whose primary glioblastoma (GBM) was followed through temozolomide treatment and ultimately recurrence.

  • In 2008 patient was diagnosed with primary GBM (three biopsies of unrelated sites were Grade II and Grade IV; temozolomide therapy for three years then relapse in 2011
  • WGS of 2 areas of primary tumor showed extensive mutational and copy number heterogeneity; was able to identify clonal TP53 mutations and clonal IDH1 mutation in primary tumor with different patterns of clonality based on grade
  • Amplifications on chromosome 4 and 12 (PDGFRA, KIT, CDK4)
  • After three years of temozolomide multiple translocations found in chromosome 4 and 12 (6 translocations)
  • Clonal IDH1 R132H mutation in primary tumor only at very low frequency in recurrent tumor
  • The WGS on recurrent tumor (sequencing took ONLY 9 days from tumor resection to sequence results) showed mutation cluster in KIT/PDGFRA.PI3K.mTOR axis so patient treated with imatinib
  • However despite rapid sequencing and a personalized approach based on WGS results, tumor progressed and patient died shortly: tumor evolution is HUGE hurdle for personalized medicine

As Dr. Swanton stated:

“we are underestimating the frequency of polyclonal evolution”

  1. Clonal status of actionable driver events and the timing of mutational processes in cancer evolution (Science Translational Medicine, 2015)[2]
  • analyzed nine cancer types to determine the subclonal frequencies of driver events, to time mutational processes during cancer evolution, and to identify drivers of subclonal expansions.
  • identified later subclonal “actionable” mutations, including BRAF (V600E), IDH1 (R132H), PIK3CA (E545K), EGFR (L858R), and KRAS (G12D), which may compromise the efficacy of targeted therapy approaches.
  • > 20% of IDH1 mutations in glioblastomas, and 15% of mutations in genes in the PI3K (phosphatidylinositol 3-kinase)–AKT–mTOR (mammalian target of rapamycin) signaling axis across all tumor types were subclonal
  • Mutations in the RAS–MEK (mitogen-activated protein kinase kinase) signaling axis were less likely to be subclonal than mutations in genes associated with PI3K-AKT-mTOR signaling

Branched chain can converge on single resistance mechanism; clonal resistance (for example to PI3K inhibitors can get multiple PTEN mutations in various metastases

Targeting Tumor Heterogeneity

  • Identify high risk occupants (have to know case history)
  • Mutational landscape interferes with anti-PD1 therapies
  • Low frequency mutations affect outcome

Notes from Dr. Catherine J. Wu, Dana-Farber Cancer Institute: The evolutionary landscape of CLL: Therapeutic implications

  • Clonal evolution a key feature of cancer progression and relapse
  • Hypothesis: evolutionary dynamics (heterogeneity) in chronic lymphocytic leukemia (CLL) contributes to variations in response and disease “tempo”
  • Used whole exome sequencing and copy number data of 149 CLL cases to discover early and late cancer drivers: clonal patterns (Landau et. al, Cell 2013); some drivers correspond to poor clinical outcome
  • Methylation studies suggest that there is epigenetic heterogeneity which may drive CLL clonal evolution
  • Developing methodology to integrate WES to determine mutations with immunogenic potential for development of personalized immunotherapy for CLL and other malignancies

References

  1. Favero F, McGranahan N, Salm M, Birkbak NJ, Sanborn JZ, Benz SC, Becq J, Peden JF, Kingsbury Z, Grocok RJ et al: Glioblastoma adaptation traced through decline of an IDH1 clonal driver and macro-evolution of a double-minute chromosome. Annals of oncology : official journal of the European Society for Medical Oncology / ESMO 2015, 26(5):880-887.
  2. McGranahan N, Favero F, de Bruin EC, Birkbak NJ, Szallasi Z, Swanton C: Clonal status of actionable driver events and the timing of mutational processes in cancer evolution. Science translational medicine 2015, 7(283):283ra254.

 

Other related articles on Tumor Heterogeneity were published in this Open Access Online Scientific Journal, include the following:

 

Issues in Personalized Medicine: Discussions of Intratumor Heterogeneity from the Oncology Pharma forum on LinkedIn

Issues in Personalized Medicine in Cancer: Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing

CANCER COMPLEXITY: Heterogeneity in Tumor Progression and Drug Response – 2015 Annual Symposium @Koch Institute for Integrative Cancer Research at MIT – W34, 6/12/2015 9:00 AM EDT – 4:30 PM EDT

My Cancer Genome from Vanderbilt University: Matching Tumor Mutations to Therapies & Clinical Trials

Tumor Imaging and Targeting: Predicting Tumor Response to Treatment: Where we stand?

Mitochondrial Isocitrate Dehydrogenase and Variants

War on Cancer Needs to Refocus to Stay Ahead of Disease Says Cancer Expert

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