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Posts Tagged ‘Non-small-cell lung carcinoma’


Diagnostics and Biomarkers: Novel Genomics Industry Trends vs Present Market Conditions and Historical Scientific Leaders Memoirs

Larry H Bernstein, MD, FCAP, Author and Curator

This article has two parts:

  • Part 1: Novel Genomics Industry Trends in Diagnostics and Biomarkers vs Present Market Transient Conditions

and

  • Part 2: Historical Scientific Leaders Memoirs

 

Part 1: Novel Genomics Industry Trends in Diagnostics and Biomarkers vs Present Market Transient Conditions

 

Based on “Forging a path from companion diagnostics to holistic decision support”, L.E.K.

Executive Insights, 2013;14(12). http://www.LEK.com

Companion diagnostics and their companion therapies is defined here as a method enabling

  • LIKELY responders to therapies that are specific for patients with ma specific molecular profile.

The result of this statement is that the diagnostics permitted to specific patient types gives access to

  • novel therapies that may otherwise not be approve or reimbursed in other, perhaps “similar” patients
  • who lack a matching identification of the key identifier(s) needed to permit that therapy,
  • thus, entailing a poor expected response.

The concept is new because:

(1) The diagnoses may be closely related by classical criteria, but at the same time they are
not alike with respect to efficacy of treatment with a standard therapy.
(2) The companion diagnostics is restricted to dealing with a targeted drug-specific question
without regard to other clinical issues.
(3) The efficacy issue it clarifies is reliant on a deep molecular/metabolic insight that is not available, except through
emergent genomic/proteomic analysis that has become available and which has rapidly declining cost to obtain.

The limitation example given is HER2 testing for use of Herceptin in therapy for non-candidates (HER2 negative patients).
The problem is that the current format is a “one test/one drug” match, but decision support  may require a combination of

  • validated biomakers obtained on a small biopsy sample (technically manageable) with confusing results.

While HER2 negative patients are more likely to be pre-menopausal with a more aggressive tumor than postmenopausal,

  • the HER2 negative designation does not preclude treatment with Herceptin.

So the Herceptin would be given in combination, but with what other drug in a non-candidate?

The point that L.E.K. makes is that providing highly validated biomarkers linked to approved therapies, it is necessary to pursue more holistic decision support tests that interrogate multiple biomarkers (panels of companion diagnostic markers) and discovery of signatures for treatments that are also used with a broad range of information, such as,

  • traditional tests,
  • imaging,
  • clinical trials,
  • outcomes data,
  • EMR data,
  • reimbursement and coverage data.

A comprehensive solution of this nature appears to be a distance from realization.  However, is this the direction that will lead to tomorrows treatment decision support approaches?

 Surveying the Decision Support Testing Landscape

As a starting point, L.E.K. characterized the landscape of available tests in the U.S. that inform treatment decisions compiled from ~50 leading diagnostics companies operating in the U.S. between 2004-2011. L.E.K. identified more than 200 decision support tests that were classified by test purpose, and more specifically,  whether tests inform treatment decisions for a single drug/class (e.g., companion diagnostics) vs. more holistic treatment decisions across multiple drugs/classes (i.e., multiagent response tests).

 Treatment Decision Support Tests

Companion Diagnostics
Single drug/class
Predict response/safety or guide dosing of a single drug or class

HercepTest   Dako
Determines HER2 protein overexpression for Herceptin treatment selection

Multiple drugs/classes

Vysis ALK Break
Apart FISH
Abbott Labs Predicts the NSCLC patient response to Xalkori

Other Decision Support
Provide prognostic and predictive information on the benefit of treatment

Oncotype Dx    Genomic Health, Inc.
Predicts both recurrence of breast cancer and potential patient benefit to chemotherapy regimens

PML-RARα     Clarient, Inc.
Predicts response to all-trans retinoic acid (ATRA) and other chemotherapy agents

TRUGENE    Siemens
Measures resistence to multiple  HIV-1 anti-retroviral agents

Multi-agent Response

Inform targeted therapy class selection by interrogating a panel of biomarkers
Target Now  Caris Life Sciences
Examines tumor’s molecular profile to tailor treatment options

ResponseDX: Lung    Response Genetics, Inc.
Examines multiple biomarkers to guide therapeutic treatment decisions for NSCLC patients

Source: L.E.K. Analysis

Includes IVD and LDT tests from

  1. top-15 IVD test suppliers,
  2. top-four large reference labs,
  3. top-five AP labs, and
  4. top-20 specialty reference labs.

For descriptive purposes only, may not map to exact regulatory labeling

Most tests are companion diagnostics and other decision support tests that provide guidance on

  • single drug/class therapy decisions.

However, holistic decision support tests (e.g., multi-agent response) are growing the fastest at 56% CAGR.
The emergence of multi-agent response tests suggests diagnostics companies are already seeing the need to aggregate individual tests (e.g., companion diagnostics) into panels of appropriate markers addressing a given clinical decision need. L.E.K. believes this trend is likely to continue as

  • increasing numbers of  biomarkers become validated for diseases and multiplexing tools
  • enabling the aggregation of multiple biomarker interrogations into a single test

to become deployed in the clinic.

Personalized Medicine Partnerships

L.E.K. also completed an assessment of publicly available personalized medicine partnership activity from 2009-2011 for ~150 leading organizations operating in the U.S. to look at broader decision support trends and emergence of more holistic solutions beyond diagnostic tests.

Survey of partnerships deals was conducted for

  • top-10 academic medical centers research institutions,
  • top-25 biopharma,
  • top-four healthcare IT companies,
  • top-three healthcare imaging companies,
  • top-20 IVD manufacturers,
  • top-20 laboratories,
  • top-10 payers/PBMs,
  • top-15 personalized healthcare companies,
  • top-10 regulatory/guideline entities, and
  • top-20 tools vendors for the period of 01/01/2009 – 12/31/2011.
    Source: Company websites, GenomeWeb, L.E.K. analysis

Across the sample we identified 189 publicly announced partnerships of which ~65% focused on more traditional areas (biomarker discovery, companion diagnostics and targeted therapies). However, a significant portion (~30%) included elements geared towards creating more holistic decision support models.

Partnerships categorized as holistic decision support by L.E.K. were focused on

  • mining large patient datasets (e.g., from payers or providers),
  • molecular profiling (e.g., deploying next-generation sequencing),
  • creating information technology (IT) infrastructure needed to enable holistic decision support models and
  • integrating various datasets to create richer decision support solutions.

Interestingly, holistic decision support partnerships often included stakeholders outside of biopharma and diagnostics such as

  • research tools,
  • payers/PBMs,
  • healthcare IT companies as well as
  • emerging personalized healthcare (PHC) companies (e.g., Knome, Foundation Medicine and 23andMe).

This finding suggests that these new stakeholders will be increasingly important in influencing care decisions going forward.

Holistic Treatment Decision Support

Holistic Decision   Support Focus

Technology Provider Partners
Stakeholder Deploying the Solution

Holistic Decision
Support Activities
Molecular Profiling

Life Technologies

TGEN/US
Oncology

Sequencing of triple-negative breast  cancer patients to identify potential treatment strategies

Foundation Medicine

Novartis

Deployment of cancer genomics analysis platform to support Novartis clinical research efforts
Predictive genomics

Clarient, Inc.
(GE Healthcare)

Acorn
Research

Biomarker profiling of patients within Acorn’s network of providers to support clinical research efforts

GenomeQuest

Beth Israel Deaconess
Medical Center

Whole genome analysis and to guide patient management
Outcomes Data Mining

AstraZeneca

WellPoint

Evaluate comparative effectiveness of selected marketed therapies

23andMe

NIH

Leverage information linking drug response and CYP2C9/CYP2C19 variation

Pfizer

Medco

Leverage patient genotype, phenotype and outcome for treatment decisions and target therapeutics
Healthcare IT Infrastructure

IBM

WellPoint

Deploy IBM’s Watson-based solution to evidence-based healthcare decision-making support

Oracle

Moffitt Cancer Center

Deploy Oracle’s informatics platform to store and manage patient medical information
Data Integration

Siemens Diagnostics

Susquehanna Health

Integration of imaging and laboratory diagnostics

Cernostics

Geisinger
Health

Integration of advanced tissue diagnostics, digital pathology, annotated biorepository and EMR
to create solutions
next-generation treatment decision support solutions

CardioDx

GE Healthcare

Integration of genomics with imaging data in CVD

Implications

L.E.K. believes the likely debate won’t center on which models and companies will prevail. It appears that the industry is now moving along the continuum to a truly holistic capability.
The mainstay of personalized medicine today will become integrated and enhanced by other data.

The companies that succeed will be able to capture vast amounts of information

  • and synthesize it for personalized care.

Holistic models will be powered by increasingly larger datasets and sophisticated decision-making algorithms.
This will require the participation of an increasingly broad range of participants to provide the

  • science, technologies, infrastructure and tools necessary for deployment.

There are a number of questions posed by this study, but only some are of interest to this discussion:

Group A.    Pharmaceuticals and Devices

  •  How will holistic decision support impact the landscape ?
    (e.g., treatment /testing algorithms, decision making, clinical trials)

Group B.     Diagnostics and   Decision Support

  •   What components will be required to build out holistic solutions?

– Testing technologies

– Information (e.g., associations, outcomes, trial databases, records)

– IT infrastructure for data integration and management, simulation and reporting

  •  How can various components be brought together to build seamless holistic  decision support solutions?

Group C.      Providers and Payers

  •  In which areas should models be deployed over time?
  • Where are clinical and economic arguments  most compelling?

Part 2: Historical Scientific Leaders Memoirs – Realtime Clinical Expert Support

Gil David and Larry Bernstein have developed, in consultation with Prof. Ronald Coifman,
in the Yale University Applied Mathematics Program,

A software system that is the equivalent of an intelligent Electronic Health Records Dashboard that

  • provides empirical medical reference and
  • suggests quantitative diagnostics options.

The current design of the Electronic Medical Record (EMR) is a linear presentation of portions of the record

  • by services
  • by diagnostic method, and
  • by date, to cite examples.

This allows perusal through a graphical user interface (GUI) that partitions the information or necessary reports

  • in a workstation entered by keying to icons.

This requires that the medical practitioner finds the

  • history,
  • medications,
  • laboratory reports,
  • cardiac imaging and
  • EKGs, and
  • radiology in different workspaces.

The introduction of a DASHBOARD has allowed a presentation of

  • drug reactions
  • allergies
  • primary and secondary diagnoses, and
  • critical information

about any patient the care giver needing access to the record.

The advantage of this innovation is obvious.  The startup problem is what information is presented and

  • how it is displayed, which is a source of variability and a key to its success.

We are proposing an innovation that supercedes the main design elements of a DASHBOARD and utilizes

  • the conjoined syndromic features of the disparate data elements.

So the important determinant of the success of this endeavor is that

  • it facilitates both the workflow and the decision-making process with a reduction of medical error.

Continuing work is in progress in extending the capabilities with model datasets, and sufficient data because

  • the extraction of data from disparate sources will, in the long run, further improve this process.

For instance, the finding of  both ST depression on EKG coincident with an elevated cardiac biomarker (troponin), particularly in the absence of substantially reduced renal function. The conversion of hematology based data into useful clinical information requires the establishment of problem-solving constructs based on the measured data.

The most commonly ordered test used for managing patients worldwide is the hemogram that often incorporates

  • the review of a peripheral smear.

While the hemogram has undergone progressive modification of the measured features over time the subsequent expansion of the panel of tests has provided a window into the cellular changes in the

  • production
  • release
  • or suppression

of the formed elements from the blood-forming organ into the circulation. In the hemogram one can view

  • data reflecting the characteristics of a broad spectrum of medical conditions.

Progressive modification of the measured features of the hemogram has delineated characteristics expressed as measurements of

  • size
  • density, and
  • concentration,

resulting in many characteristic features of classification. In the diagnosis of hematological disorders

  • proliferation of marrow precursors, the
  • domination of a cell line, and features of
  • suppression of hematopoiesis

provide a two dimensional model.  Other dimensions are created by considering

  • the maturity of the circulating cells.

The application of rules-based, automated problem solving should provide a valid approach to

  • the classification and interpretation of the data used to determine a knowledge-based clinical opinion.

The exponential growth of knowledge since the mapping of the human genome enabled by parallel advances in applied mathematics that have not been a part of traditional clinical problem solving.

As the complexity of statistical models has increased

  • the dependencies have become less clear to the individual.

Contemporary statistical modeling has a primary goal of finding an underlying structure in studied data sets.
The development of an evidence-based inference engine that can substantially interpret the data at hand and

  • convert it in real time to a “knowledge-based opinion”

could improve clinical decision-making by incorporating

  • multiple complex clinical features as well as duration of onset into the model.

An example of a difficult area for clinical problem solving is found in the diagnosis of SIRS and associated sepsis. SIRS (and associated sepsis) is a costly diagnosis in hospitalized patients.   Failure to diagnose sepsis in a timely manner creates a potential financial and safety hazard.  The early diagnosis of SIRS/sepsis is made by the application of defined criteria by the clinician.

  • temperature
  • heart rate
  • respiratory rate and
  • WBC count

The application of those clinical criteria, however, defines the condition after it has developed and

  • has not provided a reliable method for the early diagnosis of SIRS.

The early diagnosis of SIRS may possibly be enhanced by the measurement of proteomic biomarkers, including

  • transthyretin
  • C-reactive protein
  • procalcitonin
  • mean arterial pressure

Immature granulocyte (IG) measurement has been proposed as a

  • readily available indicator of the presence of granulocyte precursors (left shift).

The use of such markers, obtained by automated systems

  • in conjunction with innovative statistical modeling, provides
  • a promising approach to enhance workflow and decision making.

Such a system utilizes the conjoined syndromic features of

  • disparate data elements with an anticipated reduction of medical error.

How we frame our expectations is so important that it determines

  • the data we collect to examine the process.

In the absence of data to support an assumed benefit, there is no proof of validity at whatever cost.
This has meaning for

  • hospital operations,
  • for nonhospital laboratory operations,
  • for companies in the diagnostic business, and
  • for planning of health systems.

The problem stated by LL  WEED in “Idols of the Mind” (Dec 13, 2006): “ a root cause of a major defect in the health care system is that, while we falsely admire and extol the intellectual powers of highly educated physicians, we do not search for the external aids their minds require”.  HIT use has been

  • focused on information retrieval, leaving
  • the unaided mind burdened with information processing.

We deal with problems in the interpretation of data presented to the physician, and how through better

  • design of the software that presents this data the situation could be improved.

The computer architecture that the physician uses to view the results is more often than not presented

  • as the designer would prefer, and not as the end-user would like.

In order to optimize the interface for physician, the system would have a “front-to-back” design, with
the call up for any patient ideally consisting of a dashboard design that presents the crucial information

  • that the physician would likely act on in an easily accessible manner.

The key point is that each item used has to be closely related to a corresponding criterion needed for a decision.

Feature Extraction.

This further breakdown in the modern era is determined by genetically characteristic gene sequences
that are transcribed into what we measure.  Eugene Rypka contributed greatly to clarifying the extraction
of features in a series of articles, which

  • set the groundwork for the methods used today in clinical microbiology.

The method he describes is termed S-clustering, and

  • will have a significant bearing on how we can view laboratory data.

He describes S-clustering as extracting features from endogenous data that

  • amplify or maximize structural information to create distinctive classes.

The method classifies by taking the number of features

  • with sufficient variety to map into a theoretic standard.

The mapping is done by

  • a truth table, and each variable is scaled to assign values for each: message choice.

The number of messages and the number of choices forms an N-by N table.  He points out that the message

  • choice in an antibody titer would be converted from 0 + ++ +++ to 0 1 2 3.

Even though there may be a large number of measured values, the variety is reduced

  • by this compression, even though there is risk of loss of information.

Yet the real issue is how a combination of variables falls into a table with meaningful information. We are concerned with accurate assignment into uniquely variable groups by information in test relationships. One determines the effectiveness of each variable by

  • its contribution to information gain in the system.

The reference or null set is the class having no information.  Uncertainty in assigning to a classification is

  • only relieved by providing sufficient information.

The possibility for realizing a good model for approximating the effects of factors supported by data used

  • for inference owes much to the discovery of Kullback-Liebler distance or “information”, and Akaike
  • found a simple relationship between K-L information and Fisher’s maximized log-likelihood function.

In the last 60 years the application of entropy comparable to

  • the entropy of physics, information, noise, and signal processing,
  • has been fully developed by Shannon, Kullback, and others, and has been integrated with modern statistics,
  • as a result of the seminal work of Akaike, Leo Goodman, Magidson and Vermunt, and work by Coifman.

Gil David et al. introduced an AUTOMATED processing of the data available to the ordering physician and

  • can anticipate an enormous impact in diagnosis and treatment of perhaps half of the top 20 most common
  • causes of hospital admission that carry a high cost and morbidity.

For example: anemias (iron deficiency, vitamin B12 and folate deficiency, and hemolytic anemia or myelodysplastic syndrome); pneumonia; systemic inflammatory response syndrome (SIRS) with or without bacteremia; multiple organ failure and hemodynamic shock; electrolyte/acid base balance disorders; acute and chronic liver disease; acute and chronic renal disease; diabetes mellitus; protein-energy malnutrition; acute respiratory distress of the newborn; acute coronary syndrome; congestive heart failure; disordered bone mineral metabolism; hemostatic disorders; leukemia and lymphoma; malabsorption syndromes; and cancer(s)[breast, prostate, colorectal, pancreas, stomach, liver, esophagus, thyroid, and parathyroid].

Rudolph RA, Bernstein LH, Babb J: Information-Induction for the diagnosis of myocardial infarction. Clin Chem 1988;34:2031-2038.

Bernstein LH (Chairman). Prealbumin in Nutritional Care Consensus Group.

Measurement of visceral protein status in assessing protein and energy malnutrition: standard of care. Nutrition 1995; 11:169-171.

Bernstein LH, Qamar A, McPherson C, Zarich S, Rudolph R. Diagnosis of myocardial infarction: integration of serum markers and clinical descriptors using information theory. Yale J Biol Med 1999; 72: 5-13.

Kaplan L.A.; Chapman J.F.; Bock J.L.; Santa Maria E.; Clejan S.; Huddleston D.J.; Reed R.G.; Bernstein L.H.; Gillen-Goldstein J. Prediction of Respiratory Distress Syndrome using the Abbott FLM-II amniotic fluid assay. The National Academy of Clinical Biochemistry (NACB) Fetal Lung Maturity Assessment Project.  Clin Chim Acta 2002; 326(8): 61-68.

Bernstein LH, Qamar A, McPherson C, Zarich S. Evaluating a new graphical ordinal logit method (GOLDminer) in the diagnosis of myocardial infarction utilizing clinical features and laboratory data. Yale J Biol Med 1999; 72:259-268.

Bernstein L, Bradley K, Zarich SA. GOLDmineR: Improving models for classifying patients with chest pain. Yale J Biol Med 2002; 75, pp. 183-198.

Ronald Raphael Coifman and Mladen Victor Wickerhauser. Adapted Waveform Analysis as a Tool for Modeling, Feature Extraction, and Denoising. Optical Engineering, 33(7):2170–2174, July 1994.

R. Coifman and N. Saito. Constructions of local orthonormal bases for classification and regression. C. R. Acad. Sci. Paris, 319 Série I:191-196, 1994.

Realtime Clinical Expert Support and validation System

We have developed a software system that is the equivalent of an intelligent Electronic Health Records Dashboard that provides empirical medical reference and suggests quantitative diagnostics options.

The primary purpose is to

  1. gather medical information,
  2. generate metrics,
  3. analyze them in realtime and
  4. provide a differential diagnosis,
  5. meeting the highest standard of accuracy.

The system builds its unique characterization and provides a list of other patients that share this unique profile, therefore utilizing the vast aggregated knowledge (diagnosis, analysis, treatment, etc.) of the medical community. The

  • main mathematical breakthroughs are provided by accurate patient profiling and inference methodologies
  • in which anomalous subprofiles are extracted and compared to potentially relevant cases.

As the model grows and its knowledge database is extended, the diagnostic and the prognostic become more accurate and precise. We anticipate that the effect of implementing this diagnostic amplifier would result in

  • higher physician productivity at a time of great human resource limitations,
  • safer prescribing practices,
  • rapid identification of unusual patients,
  • better assignment of patients to observation, inpatient beds,
    intensive care, or referral to clinic,
  • shortened length of patients ICU and bed days.

The main benefit is a real time assessment as well as diagnostic options based on

  • comparable cases,
  • flags for risk and potential problems

as illustrated in the following case acquired on 04/21/10. The patient was diagnosed by our system with severe SIRS at a grade of 0.61 .

Graphical presentation of patient status

The patient was treated for SIRS and the blood tests were repeated during the following week. The full combined record of our system’s assessment of the patient, as derived from the further hematology tests, is illustrated below. The yellow line shows the diagnosis that corresponds to the first blood test (as also shown in the image above). The red line shows the next diagnosis that was performed a week later.

Progression changes in patient ICU stay with SIRS

Chemistry of Herceptin [Trastuzumab] is explained with images in

http://www.chm.bris.ac.uk/motm/herceptin/index_files/Page450.htm

 

REFERENCES

The Cost Burden of Disease: U.S. and Michigan CHRT Brief. January 2010.
@www.chrt.org

The National Hospital Bill: The Most Expensive Conditions by Payer, 2006. HCUP Brief #59.

Rudolph RA, Bernstein LH, Babb J: Information-Induction for the diagnosis of myocardial infarction. Clin Chem 1988;34:2031-2038.

Bernstein LH, Qamar A, McPherson C, Zarich S, Rudolph R. Diagnosis of myocardial infarction: integration of serum markers and clinical descriptors using information theory. Yale J Biol Med 1999; 72: 5-13.

Kaplan L.A.; Chapman J.F.; Bock J.L.; Santa Maria E.; Clejan S.; Huddleston D.J.; Reed R.G.; Bernstein L.H.; Gillen-Goldstein J. Prediction of Respiratory Distress Syndrome using the Abbott FLM-II amniotic fluid assay. The National Academy of Clinical Biochemistry (NACB) Fetal Lung Maturity Assessment Project.  Clin Chim Acta 2002; 326(8): 61-68.

Bernstein LH, Qamar A, McPherson C, Zarich S. Evaluating a new graphical ordinal logit method (GOLDminer) in the diagnosis of myocardial infarction utilizing clinical features and laboratory data. Yale J Biol Med 1999; 72:259-268.

Bernstein L, Bradley K, Zarich SA. GOLDmineR: Improving models for classifying patients with chest pain. Yale J Biol Med 2002; 75, pp. 183-198.

Ronald Raphael Coifman and Mladen Victor Wickerhauser. Adapted Waveform Analysis as a Tool for Modeling, Feature Extraction, and Denoising. Optical Engineering 1994; 33(7):2170–2174.

  1. Coifman and N. Saito. Constructions of local orthonormal bases for classification and regression. C. R. Acad. Sci. Paris, 319 Série I:191-196, 1994.

W Ruts, S De Deyne, E Ameel, W Vanpaemel,T Verbeemen, And G Storms. Dutch norm data for 13 semantic categories and 338 exemplars. Behavior Research Methods, Instruments, & Computers 2004; 36 (3): 506–515.

De Deyne, S Verheyen, E Ameel, W Vanpaemel, MJ Dry, WVoorspoels, and G Storms.  Exemplar by feature applicability matrices and other Dutch normative data for semantic concepts.  Behavior Research Methods 2008; 40 (4): 1030-1048

Landauer, T. K., Ross, B. H., & Didner, R. S. (1979). Processing visually presented single words: A reaction time analysis [Technical memorandum].  Murray Hill, NJ: Bell Laboratories. Lewandowsky, S. (1991).

Weed L. Automation of the problem oriented medical record. NCHSR Research Digest Series DHEW. 1977;(HRA)77-3177.

Naegele TA. Letter to the Editor. Amer J Crit Care 1993:2(5):433.

Retinal prosthetic strategy with the capacity to restore normal vision, Sheila Nirenberg and Chethan Pandarinath

http://www.pnas.org/content/109/37/15012

 

Other related articles published in http://pharmaceuticalintelligence.com include the following:

 

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Larry H Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2012/08/13/the-automated-second-opinion-generator/

 

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Personalized Medicine in NSCLC

Reviewer: Larry H Bernstein, MD, FCAP

Introduction

Early in the 21st century, gefitinib, an epi­dermal growth factor receptor (EGFRtyrosine kinase inhibitor became available  for the treatment of non-small cell lung can­cer (NSCLC). Over 80% of selected patients

  • EGFR mutation-positive patients, respond to gefitinib treatment;
  • most patients develop acquired resistance to gefitinib within a few years.
Recently, many studies have been performed to determine precisely how to select patients who will respond to gefitinib, the best timing for its administration, and how to avoid the development of acquired resistance as well as adverse drug effects.
Lung cancers are classified according to their his­tological type. Because each variant has different bio­logical and clinical properties, including response to treatment, a precise classification is essential to pro­vide appropriate therapy for individual patients. Lung cancer consists of two broad categories—non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC).

NSCLC  – 20%–40% RR to chemotherapy

  • ade­nocarcinoma (AC),  40%–50% ( most common form)
    • higher sensitivity to chemotherapy than SCC or LC
  • squamous cell carcinoma (SCC),  ∼30%
  •  large cell carcinoma (LCC). 10%
The majority of patients with SCLC are diagnosed with
  • advanced cancer with distant metastasis
  • high sensitivity to chemotherapy.
  • response rate (RR) for SCLC is reportedly 60%–80%
  • complete remission is observed in only 15%–20% of patients
The Potential of Personalized Medicine in Advanced NSCLC
Personalized medicine—
  • matching a patient’s unique molecular profile with an appropriate targeted therapy—
  • is transforming the diagnosis and treatment of non–small-cell lung cancer (NSCLC).

Through molecular diagnostics, tumor cells may be differentiated based on the presence or absence of

  • receptor proteins,
  • driver mutations, or
  • oncogenic fusion/rearrangements.

The convergence of advancing research in drug development and genetic sequencing has permitted the development of therapies specifically targeted to certain biomarkers, which may offer a differential clinical benefit.

Putting personalized medicine in NSCLC into practice
With the data on the prognostic and predictive biomarkers EGFR and ALK, biomarker testing is increasingly important in therapy decisions in NSCLC.1,2
Biomarker Testing in Advanced NSCLC: Evolution in Pathology Clinical Practice
http://www.medscape.com/infosite/letstest/article-3
Multidisciplinary Approaches in the Changing Landscape of Advanced NSCLC
http://www.medscape.com/infosite/letstest/article-4
Oncology Perspectives on Biomarker Testing
http://www.medscape.com/infosite/letstest/article-1

References
1. National Comprehensive Cancer Network (NCCN). NCCN Clinical Practice Guidelines in Oncology™: Non-Small Cell Lung Cancer. Version 2.2012.
http://www.nccn.org/professionals/physician_gls/PDF/nscl.pdf.                   August 6, 2012.
2. Gazdar AF. Epidermal growth factor receptor inhibition in lung cancer: the evolving role of individualized therapy. Cancer Metastasis Rev. 2010;29(1):37-48.

Over the last decade, a growing number of biomarkers have been identified in NSCLC.3,4 To date, 2 of these molecular markers have been shown to have both prognostic and predictive value in patients with advanced NSCLC: epidermal growth factor receptor (EGFR) mutations and anaplastic lymphoma kinase (ALK) rearrangements.5-8 Testing for these biomarkers may provide physicians with more information on which to base treatment decisions, and reflex testing may permit consideration of appropriate therapy from the outset of treatment.2,9,10

References:
Lovly CM, Carbone DP. Lung cancer in 2010: one size does not fit all. Nat Rev Clin Oncol. 2011;8(2):68-70.
Dacic S. Molecular diagnostics of lung carcinomas. Arch Pathol Lab Med. 2011;135(5):622-629.
Herbst RS, Heymach JV, Lippman SM. Lung cancer. N Engl J Med. 2008;359(13):1367-1380.
Quest Diagnostics. Lung Cancer Mutation Panel (EGFR, KRAS, ALK).                       Sept 17, 2012
http://questdiagnostics.com/hcp/intguide/jsp/showintguidepage.jsp?fn=Lung/TS_LungCancerMutation_Panel.htm.

Rosell R, Gervais R, Vergnenegre A, et al. Erlotinib versus chemotherapy (CT) in advanced non-small cell lung cancer (NSCLC) patients (p) with epidermal growth factor receptor (EGFR) mutations: interim results of the European Erlotinib Versus Chemotherapy (EURTAC) phase III randomized trial. Presented at: 2011 American Society of Clinical Oncology (ASCO) Annual Meeting, J Clin Oncol. 2011;29(suppl). Abstract 7503.                        Aug 6, 2012.                    http://www.asco.org/ASCOv2/Meetings/Abstracts?&vmview=abst_detail_view&confID=102&abstractID=78285.
Mok TS, Wu YL, Thongprasert S, et al. Gefitinib or carboplatin-paclitaxel in pulmonary adenocarcinoma. N Engl J Med. 2009;361(10):947-957.
Kwak EL, Bang YJ, Camidge DR, et al. Anaplastic lymphoma kinase inhibition in non–small-cell lung cancer. N Engl J Med. 2010;363(18):1693-1703.
National Comprehensive Cancer Network (NCCN). NCCN Clinical Practice Guidelines in Oncology™: Non-Small Cell Lung Cancer. Version 2.2012.
http://www.nccn.org/professionals/physician_gls/PDF/nscl.pdf.                        Aug 6, 2012
College of American Pathologists (CAP)/International Association for the Study of Lung Cancer (IASLC)/Association for Molecular Pathology (AMP) expert panel. Lung cancer biomarkers guideline draft recommendations. http://capstaging.cap.org/apps/docs/membership/transformation/new/lung_public_comment_supporting_materials.pdf.      Aug 6, 2012.
Gazdar AF. Epidermal growth factor receptor inhibition in lung cancer: the evolving role of individualized therapy. Cancer Metastasis Rev. 2010;29(1):37-48.

 Background Studies
In 2002, gefitinib (ZD1839; AstraZeneca) , the first epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor, became available as an innovative molecular-targeted drug for the treatment of unresectable NSCLC. Initially, many NSCLC patients were expected to respond to gefitinib because many solid tumors, including NSCLC, are known to overexpress EGFR, which has a role in tumor pro­liferation and is used as a biomarker to predict poor prognosis. Gefitinib was shown to have a dra­matic effect on a limited number of patients; but  it was ineffective in 70%–80% of patients with NSCLC. There have been reports of death caused by interstitial pneumonia (IP), one of the critical adverse drug reactions (ADRs) associated with gefitinib use. Therefore, there is a need for  predicting the effects of gefitinib, and criteria for select­ing patients who could be treated with gefitinib.
 In 2004, Lynch et al. and Paez et al. each pub­lished, on the same day, sensational reports in the New England Journal of Medicine and Science, identifying somatic mutations in the tyrosine kinase domain of the EGFR gene in patients with gefitinib-sensitive lung cancer, as compared with none of the patients who had no response. Therefore, screening for EGFR mutations in lung cancer showed potential for identifying patients who would respond to gefi­tinib therapy. It then was found that patients with EGFR mutations in the area of the gene cod­ing for the ATP-binding pocket of the tyrosine kinase domain responded to gefitinib. Consequently, the EGFR genotyping has been used to select patients who will respond to gefitinib. Other genetic mutations have also been reported as indicators of the response or resistance to gefitinib; for example, mutations of the KRAS gene are associated with primary resistance to gefitinib. Thus, screening of EGFR and KRAS is used to
  • predict the effects of gefi­tinib and
  • to select patients who will respond to gefitinib in the clinical setting.
Until now, the effects of gefitinib have been predicted only by genotyping factors, such as EGFR and KRAS mutations. However, Nakamura et al showed a relationship between the blood concentration of gefitinib and its clinical effects. In their study of 23 NSCLC patients with EGFR mutations, the ratio of the gefitinib concentration on day 8 to that on day 3 after the first administration of gefitinib (C8/C3) correlated with the progression-free survival (PFS) period. Patients with a higher C8/C3 ratio had a significantly lon­ger PFS (P = 0.0158, 95% confidence interval [CI]: 0.237–0.862), which  suggests the importance of the PK of gefitinib on its clinical outcome.   Chmielecki et al. concurrently reported that maintain­ing a high concentration of erlotinib, another EGFR tyrosine kinase inhibitor (EGFR-TKIs) with the same mechanism of action as gefitinib, could
  1. delay the establishment of drug-resistant tumor cells and
  2. decrease the proliferation rate of drug-resistant cells compared to
    • treatment using a lower concentration of erlotinib.
Pharmacogenetic profile
Initially, gefitinib was expected to induce a response in patients with tumors that overexpressed EGFR because it exerts its antineoplastic effects by com­petitively inhibiting the binding of ATP to the ATP-binding site of EGFR.  A number of studies contradict this hypothesis:
(1) while approxi­mately 40%–80% of NSCLC overexpress EGFR, only 10%–20% of NSCLC patients respond to gefi­tinib;5,6 and
(2) while EGFR overexpression is known to be more common in SCC than AC, gefitinib shows a higher antineoplastic effect on AC than on SCC, while other reports indicated no correlation between the expression levels of EGFR and clinical outcomes.
In 2004, somatic mutations were identified in the EGFR tyrosine kinase domain of patients with gefitinib-responsive lung cancer, as compared with no mutations in patients exhibiting no response, and the presence of an EGFR mutation was highly correlated with a good response to gefitinib.The conformational change of the EGFR ATP-binding site caused by genetic mutations constitutively acti­vates the EGFR downstream signaling pathway and increases the malignancy of cancer. Conversely, the conformational change of the ATP-binding site can also increase its affinity for gefitinib; therefore, gefi­tinib can inhibit the downstream signaling pathway more easily, strongly induces apoptosis, and reduces the proliferation of cancer cells.
Mutations in exons 18–21 of EGFR are predictive factors for the clinical efficacy of gefitinib;
  • deletions in exon 19 and missense mutations in exon 21 account for ∼90% of these mutations.

The detection of EGFR muta­tions in exons 19 and 21 is considered to be essential to predict the clinical efficacy of gefitinib.
Acquired resistance
All responders eventually develop resistance to gefitinib but in 2005, an EGFR mutation in exon 20, which substitutes methionine for threonine at amino acid position 790 (T790M), was reported to be one of the main causes of acquired resistance to gefitinib. The EGFR T790M vari­ant

  1. changes the structural conformation of the ATP-binding site, thereby
  2. increasing the affinity of ATP to EGFR, while
  3. the affinity of gefitinib to ATP is unchanged.

Screening methods for EGFR and KRAS mutations
The detection of EGFR and KRAS mutations has been usually achieved by sequencing DNA amplified from tumor tissues; however, sequencing techniques are too complex, time-consuming, and expensive.  The selection of an appropri­ate method to detect EGFR and KRAS mutations is essential to make an exact prediction of the efficacy of gefitinib in individual patients. Advances in diagnostics and treatments for NSCLC have led to better outcomes and higher standards of what outcomes are expected. These new understandings and treatments have raised multiple new questions and issues with regard to the decisions on the appropriate treatment of NSCLC patients.

  • Biomarkers are increasingly recognized and applied for guidance in diagnosis, prognosis and treatment decisions and evaluation.
  • Biologics and newer cancer treatments are enabling the possibility for new combined treatment modalities in earlier stage disease
  • Maintenance therapy has been shown to be useful, but optimal therapy choices before and after maintenance therapy need clarification
  • The importance of performance status on treatment decisions
  • Comparative effectiveness is becoming an expectation across all treatments and diseases, and will prove difficult to accomplish within the complexity of cancer diseases
NCCN Molecular Testing White Paper: Effectiveness, Efficiency, and Reimbursement
PF Engstrom, MG Bloom,GD Demetri, PG Febbo, et al.
Personalized medicine in oncology is maturing and evolving rapidly, and the use of molecular biomarkers in clinical decisionmaking is growing. This raises important issues regarding the safe, effective, and efficient deployment of molecular tests to guide appropriate care, specifically regarding laboratory-developed tests and companion diagnostics. In May 2011, NCCN assembled a work group composed of thought leaders from NCCN Member Institutions and other organizations to identify challenges and provide guidance regarding molecular testing in oncology and its corresponding utility. The NCCN Molecular Testing Work Group identified
challenges surrounding molecular testing, including health care provider knowledge, determining clinical utility, coding and billing for molecular tests, maintaining clinical and analytic validity of molecular tests, efficient use of specimens, and building clinical evidence. (JNCCN 2011;9[Suppl 6]:S1–S16)
Executive Summary
The FDA recently announced plans for oversight of laboratory-developed tests (LDTs) and released draft guidance regarding the development of companion diagnostics concurrently with therapeutics, both areas over which the FDA has regulatory authority. As recognized by the FDA, these types of diagnostic tests are used increasingly to directly inform treatment decisions, and this especially impacts patients with cancer and their oncologists. However, because of the increasing complexity of some LDTs and increasing commercial interest in oncology-related LDTs in general, the FDA is considering whether its policy of exercising “enforcement discretion”

for LDTs is still appropriate. To provide guidance regarding challenges of molecular testing to health care providers and other stakeholders, NCCN assembled a work group composed of thought leaders from NCCN Member Institutions and other organizations external to NCCN.  The NCCN Molecular Testing Work Group agreed to define molecular testing in oncology as

  • procedures designed to detect somatic or germline mutations in DNA and
  • changes in gene or protein expression that could impact the
    • diagnosis,
    • prognosis,
    • prediction, and
    • evaluation of therapy of patients with cancer.
Therefore, the discussion focused on molecular tests that predict outcomes for therapy.
Realizing the importance of personalized medicine in advanced NSCLC
E Topol, B Buehler, GS Ginsburg.       Medscape Molec Medicine
With the data on the prognostic and predictive biomarkers EGFR and ALK, biomarker testing is increasingly important in therapy decisions in NSCLC
http://www.nccn.org/professionals/physician_gls/PDF/nscl.pdf/
Lung Cancer in the Never Smoker Population: An Expert Interview With Dr. Nasser Hanna

Lung cancer in the never smoker population is a distinct disease entity with specific molecular changes, offering the potential for targeted therapy.
Experts And Viewpoint, Medscape Hematology-Oncology, December 2007

An Update on New and Emerging Therapies for NSCLC
Simon L. Ekman, MD, PhD; Fred R. Hirsch, MD, PhD
On completion of these readings participants will be thoroughly familiar with these issues:
  1. The influence of histologic types and genetic and molecular markers on choosing and personalizing therapy in patients with advanced NSCLC
  2. The role of the pathologist in properly classifying subtypes of NSCLC and reporting the presence of molecular markers in tumor samples
  3. Familiarize themselves with effective methods of obtaining adequate tissue samples from patients and recognize the importance of accurate pathologic assessment of NSCLC
The rapid developments in molecular biology have opened up new possibilities for individualized treatment of non-small cell lung cancer (NSCLC), and, in recent years, has mainly focused on the epidermal growth factor receptor (EGFR). A greater understanding of the molecular mechanisms behind
  • tumorigenesis and
  • the identification of new therapeutic targets
    • have sparked the development of novel agents
    • intended to improve the standard chemotherapy regimens for NSCLC.
Along with the advent of targeted therapy, identifying biomarkers to predict the subset of patients more likely to benefit from a specific targeted intervention has become increasingly important.
EGFR TYROSINE KINASE INHIBITORS 
tumor-associated mutations in the tyrosine kinase domain of EGFR have been associated with response to EGFR TKIs
The most common EGFR-sensitizing mutations encompass deletions in exon 19 and a point mutation at L858R in exon 21; together,
  • they account for approximately 85% of EGFR mutations in NSCLC.
  • Other EGFR mutations have been detected, particularly in exon 20.
    •  mutations identified in exon 20 have been linked to resistance to EGFR TKIsNon-Small Cell Lung Cancer: Biologic and Therapeutic Considerations for Personalized Management
      Taofeek K. Owonikoko, MD, PhD
What is the role and application of molecular profiling in the management of NSCLC?
It is essential to:
  1. Identify advances in the understanding of molecular biology and histologic profiling in the treatment of NSCLC
  2. Summarize clinical data supporting the use of tumor biomarkers as predictors of therapeutic efficacy of targeted agents in NSCLC
  3. Devise an individualized treatment plan for patients with advanced NSCLC based on a tumor’s molecular profile
  4. Identify methods for overcoming barriers to effective incorporation of molecular profiling for the management of NSCLC into clinical practice
Non-small cell lung cancer (NSCLC),the most common type of lung cancer, usually grows and spreads more slowly than small cell lung cancer.
The three common forms of NSCLC are:
  1. Adenocarcinomas are often found in an outer area of the lung.
  2. Squamous cell carcinomas are usually found in the center of the lung next to an air tube (bronchus).
  3. Large cell carcinomas occur in any part of the lung and tend to grow and spread faster than the other two types
Smoking causes most cases of lung cancer. The risk depends on the number of cigarettes you smoke every day and for how long you have smoked. Some people who do not smoke and have never smoked develop lung cancer.
Working with or near the following cancer-causing chemicals or materials can also increase your risk:
  • Asbestos
  • Chemicals such as uranium, beryllium, vinyl chloride, nickel chromates, coal products, mustard gas, chloromethyl ethers, gasoline, and diesel exhaust
  • Certain alloys, paints, pigments, and preservatives
  • Products using chloride and formaldehyde
Non-small cell lung c

ancer
(NSCLC) accounts for
  • approximately 85% of all lung cancers.
Lung cancer  may produce no symptoms until the disease is well advanced, so early recognition of symptoms may be beneficial to outcome.
At initial diagnosis,
  • 20% of patients have localized disease,
  • 25% of patients have regional metastasis, and
  • 55% of patients have distant spread of disease.
Revisiting Doublet Maintenance Chemo in Advanced NSCLC 
H. Jack West, MD
  • Pemetrexed Versus Pemetrexed and Carboplatin as Second-Line Chemotherapy In Advanced Non-Small-Cell Lung Cancer
Ardizzoni A, Tiseo M, Boni L, et al
J Clin Oncol. 2102;30:4501-4507
Historically, our second-line therapy has evolved into a strategy of pursuing single-agent therapies for patients with advanced non-small cell lung cancer (NSCLC) who have received prior chemotherapy. This approach was developed on the basis of benefits conferred by such established treatments as docetaxel, pemetrexed, and erlotinib — each well-tested as single agents — and evidence indicating a survival benefit in previously treated patients.
A study out of Italy by Ardizzoni and colleagues published in the Journal of Clinical Oncology directly compares carboplatin/pemetrexed with pemetrexed alone, and
  • it provides more evidence that our current approach of sequential singlet therapy remains appropriate.
This randomized phase 2 trial enrolled 239 patients with advanced NSCLC, initially of any histology, then later amended (September 2008) to enroll
  • only patients with non-squamous NSCLC because of mounting evidence that pemetrexed is not active in patients with the squamous subtype of advanced NSCLC.
Patients must have received prior chemotherapy (without restriction on regimen except that it could not include pemetrexed). Participants were randomly assigned 1:1 to receive pemetrexed at the standard dose of 500 mg/m2 IV every 21 days or the same chemotherapy with carboplatin at an area under the curve of 5, also IV every 21 days.
The primary endpoint for the trial was progression-free survival (PFS), and the trial was intended to have results pooled with a nearly identically designed trial that was done in The Netherlands. The Dutch trial compared pemetrexed with carboplatin/pemetrexed at the same dose and schedule. The vast majority of patients (97.5%) had a performance status of 0 or 1, and the median age was 64 years.
The Italian study found no evidence to support a benefit in efficacy from the more aggressive doublet regimen. Specifically,
  • median PFS was 3.6 months with pemetrexed alone vs 3.5 months with carboplatin/pemetrexed.
  • Response rate (RR) and median overall survival (OS) were also no better with the doublet regimen
      • RR 12.6% vs 12.5%, median OS 9.2 vs 8.8 months, for pemetrexed and carboplatin/pemetrexed.

Moreover, pooling the data from the Italian trial with the Dutch trial demonstrated no significant differences between the 2 strategies. Subgroup analysis showed that

  • the patients with squamous NSCLC had a superior median PFS of 3.2 months with the carboplatin doublet vs 2.0 months with pemetrexed alone.

Unfortunately, this only confirms that adding a second agent is beneficial for patients receiving an agent previously shown to be ineffective in that population.

Viewpoint
Putting it in the context of previous data, these results only provide further confirmation that more is not better.
  • combinations are associated with more toxicity than single-agent therapy, and
  • this is likely to be especially relevant in previously treated patients whose ability to tolerate ongoing therapy over time may be reduced.

It is critical to balance efficacy with tolerability to enable us to deliver the treatment over a prolonged period. We need to recognize the importance of pacing ourselves if our goal is to administer treatments in a palliative setting for an increasingly longer duration.

Epidermal growth factor receptor (EGFR) signal...

Epidermal growth factor receptor (EGFR) signaling pathway. (Photo credit: Wikipedia)

EGFR structure

EGFR structure (Photo credit: Wikipedia)

ATP synthase

ATP synthase (Photo credit: Ethan Hein)

Non-small cell carcinoma - FNA

Non-small cell carcinoma – FNA (Photo credit: Pulmonary Pathology)

Articles on NSCLC in Pharmaceutical Intelligence:
Key Sources:
  1. Realizing the importance of personalized medicine in advanced NSCLC
    E Topol, B Buehler, GS Ginsburg. 

    Medscape Molec Medicine The Potential of Personalized Medicine in Advanced NSCLC

    With the data on the prognostic and predictive biomarkers EGFR and ALK, biomarker testing is increasingly important in therapy decisions in NSCLC
  2. Revisiting Doublet Maintenance Chemo in Advanced NSCLC
    H. Jack West, MD     http://www.medscape.com/viewarticle/777367
    Pemetrexed Versus Pemetrexed and Carboplatin as Second-Line Chemotherapy In Advanced Non-Small-Cell Lung Cancer
    Ardizzoni A, Tiseo M, Boni L, et al
    J Clin Oncol. 2102;30:4501-4507
  3. Lung Cancer in the Never Smoker Population: An Expert Interview With Dr. Nasser Hanna
    Experts And Viewpoint, Medscape Hematology-Oncology, December 2007
  4. Non-Small Cell Lung Cancer: Biologic and Therapeutic Considerations for Personalized Management
    Taofeek K. Owonikoko, MD, PhD   August 24, 2011.   Medscape
  5. An Update on New and Emerging Therapies for NSCLC
    Simon L. Ekman, MD, PhD; Fred R. Hirsch, MD, PhD     Medscape
  6. Lovly CM, Carbone DP. Lung cancer in 2010: one size does not fit all. Nat Rev Clin Oncol. 2011;8(2):68-70.
  7. Dacic S. Molecular diagnostics of lung carcinomas. Arch Pathol Lab Med. 2011;135(5):622-629.

  8. Herbst RS, Heymach JV, Lippman SM. Lung cancer. N Engl J Med. 2008;359(13):1367-1380.
  9. Gazdar AF. Epidermal growth factor receptor inhibition in lung cancer: the evolving role of individualized therapy.

    Cancer Metastasis Rev. 2010;29:37-48.

  10. NCCN Oncology Insights Report on Non-Small Cell Lung Cancer 1.2010
  11.   Review of the Treatment of Non-Small Cell Lung Cancer with Gefitinib
    T Araki, H Yashima, K Shimizu, T Aomori
    Clinical Medicine Insights: Oncology 2012:6 407–421  http://dx.doi.org/10.4137/CMO.S7340

 

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Non-small Cell Lung Cancer drugs – where does the Future lie?

In focus: Tarceva, Avastin and Dacomitinib

 

UPDATED on July 5, 2013

(from reports published in New England Journal of Medicine on drug, crizotinib)

 

Curator: Ritu Saxena, Ph.D.

 

Introduction

Non-small cell lung cancer (NSCLC) is the most common type of lung cancer and usually grows and spreads more slowly than small cell lung cancer.

There are three common forms of NSCLC:

  • Adenocarcinomas are often found in an outer area of the lung.
  • Squamous cell carcinomas are usually found in the center of the lung next to an air tube (bronchus).
  • Large cell carcinomas can occur in any part of the lung. They tend to grow and spread faster than the other two types.

Lung cancer is by far the leading cause of cancer death among both men and women. Each year, more people die of lung cancer than of colon, breast, and prostate cancers combined. The American Cancer Society’s most recent estimates for lung cancer in the United States for 2012 reveal that about 226,160 new cases of lung cancer will be diagnosed (116,470 in men and 109,690 in women), and there will be an estimated 160,340 deaths from lung cancer (87,750 in men and 72,590 among women), accounting for about 28% of all cancer deaths.

Treatment

Different types of treatments are available for non-small cell lung cancer. Treatment depends on the stage of the cancer. For patients in whom the cancer has not spread to nearby lymph nodes are recommended surgery. Surgeon may remove- one of the lobes (lobectomy), only a small portion of the lung (wedge removal), or the entire lung (pneumonectomy). Some patients require chemotherapy that uses drugs to kill cancer cells and stop new cells from growing.

FDA approved drugs for NSCLC

Abitrexate (Methotrexate)
Abraxane (Paclitaxel Albumin-stabilized Nanoparticle Formulation) 
Alimta (Pemetrexed Disodium)
Avastin (Bevacizumab)
Bevacizumab
Carboplatin
Cisplatin
Crizotinib
Erlotinib Hydrochloride
Folex (Methotrexate)
Folex PFS (Methotrexate)
Gefitinib
Gemcitabine Hydrochloride
Gemzar (Gemcitabine Hydrochloride)
Iressa (Gefitinib)
Methotrexate
Methotrexate LPF (Methotrexate)
Mexate (Methotrexate)
Mexate-AQ (Methotrexate)
Paclitaxel
Paclitaxel Albumin-stabilized Nanoparticle Formulation
Paraplat (Carboplatin)
Paraplatin (Carboplatin)
Pemetrexed Disodium
Platinol (Cisplatin)
Platinol-AQ (Cisplatin)
Tarceva (Erlotinib Hydrochloride)
Taxol (Paclitaxel)
Xalkori (Crizotinib)

On the basis of target, the drugs have been classified as follows:

Image

NSCLC Drug Market Analysis

NSCLC drug market expected to grow from $4.2 billion in 2010 to $5.4 billion in 2020

Although, a whole list of agents is available for the treatment of NSCLC, the market for NSCLC drugs is expected to expand from $4.2 billion in 2010 to $5.4 billion in 2020 in the United States, France, Germany, Italy, Spain, the United Kingdom and Japan.   

However, drug sales for metastatic/advanced squamous cell non-small-cell lung cancer, which comprises only a small fraction of the market, will decrease from nearly 17 percent in 2010 to approximately 13 percent in 2020. According to surveyed U.S. oncologists and MCO pharmacy directors, increasing overall survival is one of the greatest unmet needs in first-line advanced squamous non-small-cell lung cancer.

In 2009, antimetabolites dominated the NSCLC market, with Eli Lilly’s Alimta (Pemetrexed) accounting for nearly three-quarters of sales within this drug class. Since then, Alimta has faced tough competition from a number of similar drugs and from emerging therapies. It was speculated that the antimetabolites market share would reduce significantly making it the second-largest drug class in NSCLC, while the epidermal growth factor receptor (EGFR) inhibitor class will garner the top market share by 2019.

Genentech/OSI Pharmaceuticals/Roche/Chugai Pharmaceutical’s Tarceva belongs to the EGFR inhibitor class, and has been prescribed principally along with Eli Lilly’s Alimta, to NSCLC patients.Both these drugs have dominated the NSCLC market till 2010, however, their market hold is expected to weaken from 2015-2020, as claimed by Decision Resources Analyst Karen Pomeranz, Ph.D. Decision Resources is a research and advisory firms for pharmaceutical and healthcare issues.

Tarceva (Erlotinib)

Generic Name: Erlotinib, Brand Name: Tarceva

Other Designation: CP 358774, OSI-774, R1415, RG1415, NSC 718781

Mechanism of Action: Tarceva, a small molecule quinazoline, directly and reversibly inhibits the epidermal growth factor receptor (EGFr) tyrosine kinase. Detailed information on how it works could be found at the Macmillian Cancer support website.

Tarceva has been approved for different cancers and several indications have been filed-

  • non-small cell lung cancer (nsclc), locally advanced or metastatic, second line, after failure of at least one prior chemotherapy regimen (2004)
  • pancreatic cancer, locally advanced or metastatic, in combination with gemcitabine, first line (2005)
  • non-small cell lung cancer (nsclc), advanced, maintenance therapy in responders following first line treatment with platinum-based chemotherapy (2010)
  • non-small cell lung cancer (nsclc) harboring epidermal growth factor (EGFr)-activating mutations, first line treatment in advanced disease

Sales of Tarceva 

May, 2012 sales of Tarceva in the US have been reported to be around $564.2 million.

In a recent article published by Vergnenègre et al in the Clinicoeconomic Outcomes Research journal (2012), cross-market cost-effectiveness of Erlotinib was analyzed. The study aimed at estimating the incremental cost-effectiveness of Erlotinib (150 mg/day) versus best supportive care when used as first-line maintenance therapy for patients with locally advanced or metastatic NSCLC and stable disease.

It was determined that treatment with erlotinib in first-line maintenance resulted in a mean life expectancy of 1.39 years in all countries, compared with a mean 1.11 years with best supportive care, which represents 0.28 life-years (3.4 life-months) gained with erlotinib versus best supportive care.

According to the authors analysis, there was a gain in the costs per-life year as $50,882, $60,025, and $35,669 in France, Germany, and Italy, respectively. Hence, on the basis of the study it was concluded that Erlotinib is a cost-effective treatment option when used as first-line maintenance therapy for locally advanced or metastatic NSCLC.

Avastin (Bevacizumab)

Generic Name: Avastin, Brand Name: Bevacizumab

Other Designation: rhuMAb-VEGF, NSC-704865, R435, RG435

Mechanism of Action

Bevacizumab is a recombinant humanized Mab antagonist of vascular endothelial growth factor A (VEGFA) acting as an angiogenesis inhibitor.

Targets

Vascular endothelial growth factor (VEGF, VEGF-A, VEGFA)

Avastin is the only currently approved VEGF inhibitor that selectively targets VEGF-A.

Three other approved oral drugs, pazopanib (Votrient; GlaxoSmithKline), sunitinib (Sutent; Pfizer) and sorafenib (Nexavar; Onyx Pharmaceuticals) are orally available multi-targeted receptor tyrosine kinase inhibitors that include VEGF receptors among their tar­gets.

Avastin has been approved for different cancers and several indications have been filed:

  • colorectal cancer, advanced, metastatic, first line, in combination with a 5-FU based chemotherapy regimen
  • colorectal cancer, relapsed, metastatic, second line, in combintion with 5-FU-based chemotherapy (2004)
  • non-small cell lung cancer (nsclc), non-squamous, inoperable, locally advanced, recurrent or metastatic, in combination with carboplatin and paclitaxel chemotherapy, first line (2006)
  • breast cancer, chemotherapy naive, first line, locally recurrent or metastatic, in combination with taxane chemotherapy (2008, revoked in 2011)
  • non-small cell lung cancer (nsclc), non-squamous, inoperable, locally advanced, recurrent or metastatic, in combination with platinum-based chemotherapy, first line
  • renal cell carcinoma (RCC), metastatic, in combination with interferon (IFN) alpha, first line (2009)
  • glioblastoma multiforme (GBM), relapsed after first line chemoradiotherapy
  • breast cancer, chemotherapy naive, first line, locally recurrent or metastatic, HEr2 negative, in combination with capecitabine (2009)
  • ovarian cancer, in combination with standard chemotherapy (carboplatin and paclitaxel) as a first line treatment following surgery for women with advanced (Stage IIIb/c or Stage IV) epithelial ovarian, primary peritoneal or fallopian tube cancer
  • ovarian cancer, in combination with carboplatin and gemcitabine as a treatment for women with recurrent, platinum-sensitive ovarian cancer

SOURCE:

New medicine Oncology Knowledge Base

Sales of Avastin 

As of May, 2012, sales of Avastin in the US have been reported to be around $2.66 billion.

It attracted a lot of attention over the past few years after its use as a breast cancer treatment. Avastin was approved by the FDA under its fast-track program. However, the data released by the FDA from follow-up studies led to questioning the use of Avastin as a breast cancer drug. Infact, Genentech pulled the indication from Avastin’s label. Henceforth, the FDA did cancel that approval in late 2011. Doctors, however, can still prescribe it off-label. Potential adverse effects of Avastin that came under scrutiny along with unfavorable cost benefit analyses might pose challenges to its growth potential and continued widespread use. However, the sales of Avastin have continued to increase and it has been reported by Fierce Pharma as one of the 15 best-selling cancer drugs list. (Fierce Pharma)

Dacomitinib: New promising drug for NSCLC

Generic Name: Dacomitinib

Other Designation: PF-299804, PF-00299804, PF-299,804, PF00299804

PF-299804 is an orally available irreversible pan-HEr tyrosine kinase inhibitor.

Dacomitinib is a promising new drug on the market. Phase III trials are ongoing for advanced and refractory NSCLC, locally advanced or metastatic NSCLC and the EGFr mutation containing locally advanced or metastatic NSCLC in several countries including those in Europe, Asia, and America.

SOURCE:

New medicine Oncology Knowledge base

Dacomitinib bests Erlotinib in advanced NSCLC:  Comparison of its Progression-Free Survival (PFS) with the NSCLC marketed drug, Erlotinib.

In September of 2012, a study was published by Ramalingam et al in the Journal of Clinical Oncology, which was a randomized open-label trial comparing dacomitinib with erlotinib in patients with advanced NSCLC. On the basis of the study it was concluded that dacomitinib demonstrated significantly improved progression-free survival (PFS*) as compared to erlotinib, with a certain degree of toxicity.

SOURCE:

Randomized Phase II Study of Dacomitinib Versus Erlotinib in Patients With Advanced Non-Small-Cell Lung Cancer

The results indicated indicated the following:

  • Median PFS was significantly greater with Dacomitinib than Erlotinib, at 2.86 versus 1.91.
  • Mean duration of response was 16.56 months for dacomitinib and 9.23 months for erlotinib.

Patients were divided into groups by tumor type and following results were obtained:

  • Median PFS was 3.71 months with dacomitinib and 1.91 with erlotinib in patients with KRAS wild-type tumors
  • Median PFS was 2.21 months and 1.68 months, in patients with KRAS wild-type/EGFR wild-type tumors.
  • PFS was significantly better in the molecular subgroups harboring a mutant EGFR genotype.

The study also highlighted the side effects which might be more of concern and probably limiting for Dacomitinib.

Although adverse side effects were uncommon in both the groups, certain side effects such as:

  • mouth sores,
  • nailbed infections, and
  • diarrhea

were more common and tended to be more severe with Dacomitinib as compared to Tarceva.

Therefore, for patients for whom side effects of Tarceva seem challenging might face more difficulty with Dacomitinib treatment. Nonetheless, the results of PFS were promising enough and provide a greater efficacy in several clinical and molecular subgroups targeting a larger population than Tarceva. Authors, thus, suggested a larger, randomized phase III trial with the same design.

Current status of Dacomitinib

Based on positive performance of Dacomitinib published in research studies, Pfizer has entered into a collaborative development agreement with the SFJ Pharmaceuticals Group to conduct a phase III clinical trial across multiple sites in Asia and Europe, to evaluate dacomitinib (PF-00299804) as a first line treatment in patients with locally advanced or metastatic non-small cell lung cancer (nsclc) with activating mutations in the epidermal growth factor receptor (EGFr). Under the terms of the agreement, SFJ will provide the funding and clinical development supervision to generate the clinical data necessary to support a registration dossier on Dacomitinib for marketing authorization by regulatory authorities for this indication. If approved for this indication, SFJ will be eligible to receive milestone and earn-out payments.

SOURCE:

New medicine Oncology Knowledge base

*PFS or Progression-free survival is defined as the length of time during and after the treatment of as disease, such as cancer, that a patient lives with the disease but it does not get worse. In a clinical trial, measuring the progression-free survival is one way to see how well a new treatment works.

REFERENCES

Recently, another drug PF-02341066 (crizotinib), was tested on patients with non-small cell lung cancer and the results were published in New England Journal of Medicine (2013). Crizotinib is an orally available aminopyridine-based inhibitor of the) and the c-Met/hepatocyte growth factor receptor (HGFR). Crizotinib, in an ATP-competitive manner, binds to and inhibits ALK kinase and ALK fusion proteins. In addition, crizotinib inhibits c-Met kinase, and disrupts the c-Met signaling pathway. Altogether, this agent inhibits tumor cell growth.

  • Shaw and colleagues (2013) investigated whether crizotinib is superior to standard chemotherapy with respect to efficacy. To answer the question, Pfizer launched a phase III clinical trial (NCT00932893; http://clinicaltrials.gov/show/NCT00932893) comparing the safety and anti-tumor activity of PF-02341066 (crizotinib) versus pemetrexed or docetaxel in patients with advanced non-small cell lung cancer harboring a translocation or inversion event involving the ALK gene. Shaw and colleagues (2013) published the results of the clinical trial in a recent issue of New England Journal of Medicine.  A total of 347 patients with locally advanced or metastatic ALK-positive lung cancer who had received one prior platinum-based regimen were recruited for the trial and patients were randomly assigned to receive oral treatment with crizotinib (250 mg) twice daily or intravenous chemotherapy with either pemetrexed (500 mg per square meter of body-surface area) or docetaxel (75 mg per square meter) every 3 weeks. Patients in the chemotherapy group who had disease progression were permitted to cross over to crizotinib as part of a separate study. The primary end point was progression-free survival. According to the results, the median progression-free survival was 7.7 months in the crizotinib group and 3.0 months in the chemotherapy group. Hazard ratio (HR) for progression or death with crizotinib was 0.49 (95% CI, P<0.001). The response rates were 65% with crizotinib, as compared with 20% with chemotherapy (P<0.001). An interim analysis of overall survival showed no significant improvement with crizotinib as compared with chemotherapy (hazard ratio for death in the crizotinib group, 1.02; 95% CI, P=0.54). Common adverse events associated with crizotinib were visual disorder, gastrointestinal side effects, and elevated liver aminotransferase levels, whereas common adverse events with chemotherapy were fatigue, alopecia, and dyspnea. Patients reported greater reductions in symptoms of lung cancer and greater improvement in global quality of life with crizotinib than with chemotherapy.In conclusion, the results from the trial indicate that crizotinib is superior to standard chemotherapy in patients with previously treated, advanced non–small-cell lung cancer with ALK rearrangement. (Shaw AT, et al, Crizotinib versus Chemotherapy in Advanced ALK-Positive Lung Cancer. N Engl J Med 2013; 20 June, 368:2385-2394; http://www.ncbi.nlm.nih.gov/pubmed/23724913).

However, in the same issue of New England Journal of Medicine, Awad and colleagues (2013) reported from a phase I clinical trial (NCT00585195; http://clinicaltrials.gov/show/NCT00585195), that a patient with metastatic lung adenocarcioma harboring a CD74-ROS1 rearrangement who had initially shown a dramatic response to treatment, showed resistance to crizotinib. Biopsy of the resistant tumor identified an acquired mutation leading to a glycine-to-arginine substitution at codon 2032 in the ROS1 kinase domain. Although this mutation does not lie at the gatekeeper residue, it confers resistance to ROS1 kinase inhibition through steric interference with drug binding. The same resistance mutation was observed at all the metastatic sites that were examined at autopsy, suggesting that this mutation was an early event in the clonal evolution of resistance. The study was funded by Pfizer (Awad MM, et al, Acquired resistance to crizotinib from a mutation in CD74-ROS1. N Engl J Med. 2013 Jun 20;368(25):2395-401; http://www.ncbi.nlm.nih.gov/pubmed/23724914)

Reference: 

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Reporter: Aviva Lev-Ari, PhD, RN

Medical Education Firm Launches Online Tool to Help Docs Guide Personalized Rx Decisions in NSCLC

September 12, 2012
Clinical Care Options, a developer of continuing education and medical decision support resources, has launched a web-based tool to help oncologists figure out which lung cancer patients may benefit from molecularly guided personalized treatments.

The online decision-support tool provides oncologists with expert recommendations on first-line and maintenance treatment options for non-small cell lung cancer patients based on their patients’ medical information and tumor features, including oncogenic markers.

Clinical Care Options developed the online tool based on the treatment choices made by five US experts who were presented 96 cases with specific variables regarding patients’ medical history, such as tumor histology, genomic mutations, age, and smoking history.

In order to use the tool, oncologists select their patients’ medical information and desires and select their treatment of choice. The tool then displays how the five experts would treat this patient. The program then surveys users about how the expert recommendations impacted their treatment decisions.

The firm presented the results of this survey in a poster at the Chicago Multidisciplinary Symposium in Thoracic Oncology this week. The tool has been used by approximately 1,000 physicians around the world, according to Jim Mortimer, senior director of oncology programs and partnership development at Clinical Care Options. Overall, approximately 23 percent of clinicians who used the tool have said it helped change their decisions, while 50 percent indicated the tool helped confirm their initial treatment strategy.

Specifically, with regard to genomically guided personalized NSCLC treatments, all five of the experts selected Pfizer’s Xalkori (crizotinib) whenever a patient case involved the ALK fusion gene. However, out of 80 cases entered by oncologists involving this marker, only around 40 percent selected Xalkori. And although in NSCLC cases with mutated EGFR the experts selected Genentech’s Tarceva (erlotinib), only 60 percent of the 100 such cases entered by clinicians into the tool chose the drug.

The data collected by Clinical Care Options suggest that its decision-support tool may be a useful resource when oncologists want to assess how their peers would prescribe a genomically targeted personalized treatment. These drugs, compared to standard treatments, are relatively new to the market and expensive. Pfizer’s Xalkori was approved by the US Food and Drug Administration last year while Genentech is in the process of getting approval for Tarceva in the US as a first-line treatment for NSCLC patients who have EGFR mutations. Last year, the European Commission approved the use of Tarceva as a first-line treatment for NSCLC in patients with EGFR mutations (PGx Reporter 9/7/2011).

Clinical Care Options said launched the online tool because it noticed that physicians often look for advice beyond broad treatment guidelines when it comes to making decisions for specific patients.

“The tool recommendations align very well with the treatment guidelines but the advantage of the tool is the granularity of the case specifics. Users of the tool can quickly enter in details of a case and see the results for what five experts would recommend,” Mortimer told PGx Reporter. “This contrasts with guidelines that apply to broad groups and provide lists of suitable treatments.”

Mortimer noted that some of the experts’ recommendations included in the tool are outside of the exact indication of a particular drug. However, because the experts’ treatment decisions were evidence based, they “did not indicate any issues with reimbursement.”

Clinical Care Options has developed a continuing medical education-certified program that includes the tool with educational grants from Genentech and Pfizer.

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Reporter: Aviva Lev-Ari, PhD, RN

Comprehensive genomic characterization of squamous cell lung cancer

Nature (2012) doi:10.1038/nature11404

Received 09 March 2012 
Accepted 09 July 2012 
Published online 09 September 2012

 

 

Correspondence to: 

The primary and processed data used to generate the analyses presented here can be downloaded by registered users fromThe Cancer Genome Atlas (https://tcga-data.nci.nih.gov/tcga/tcgaDownload.jsp,https://cghub.ucsc.edu/ and https://tcga-data.nci.nih.gov/docs/publications/lusc_2012/).

 

Lung squamous cell carcinoma is a common type of lung cancer, causing approximately 400,000 deaths per year worldwide. Genomic alterations in squamous cell lung cancers have not been comprehensively characterized, and no molecularly targeted agents have been specifically developed for its treatment. As part of The Cancer Genome Atlas, here we profile 178 lung squamous cell carcinomas to provide a comprehensive landscape of genomic and epigenomic alterations. We show that the tumour type is characterized by complex genomic alterations, with a mean of 360 exonic mutations, 165 genomic rearrangements, and 323 segments of copy number alteration per tumour. We find statistically recurrent mutations in 11 genes, including mutation of TP53 in nearly all specimens. Previously unreported loss-of-function mutations are seen in the HLA-A class I major histocompatibility gene. Significantly altered pathways included NFE2L2 andKEAP1 in 34%, squamous differentiation genes in 44%, phosphatidylinositol-3-OH kinase pathway genes in 47%, and CDKN2A and RB1 in 72% of tumours. We identified a potential therapeutic target in most tumours, offering new avenues of investigation for the treatment of squamous cell lung cancers.

Source:

 

 

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