Leaders in Pharmaceutical Business Intelligence (LPBI) Group

Nonhematological cancers [4.2]

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

http://dx.doi.org:/2015/04/30/lhbern/nonhematological-cancers

Characteristics and Types

Tumors are considered to be cell growths that are either benign or malignant proliferations. Those that are benign may be reactive, but they do not have the characteristics of a malignancy.  The main features we are concerned with are:

1. Cancer cells utilize glucose by the anaerobic glycolysis energy pathway as the primary energy source, and this is despite a sufficient supply of oxygen. This characteristic is referred to as the Warburg Effect, as it was originally described by Otto Warburg in the 1920s, and he had derived a parallel to the observations of yeast cells by Louis Pasteur 60 years earlier.
2. Cancer cells proliferate and take on features common to cancer cells and less characteristic in expression than the cells of origin.
3. Cancer cells loose the properties of cell-cell attachment, and this is associated with metastasis to proximate or to distant sites.
4. As a result of Warburg’s original studies, he concluded that cancer cells have impaired respiration (mitochondria were not yet described).
5. It would be known much later that there is an impairment of the balance between cell repair and cell death.
6. Malignant tumors are divided into solid tumors and hematological malignancies. This discussion is focused only on malignant solid tumors.
7. The types of cancer can be classified according to the tissue of origin: mesenchymal (sarcoma) and epithelial (carcinoma), and by source of origin:

Brain Cancer
Breast Cancer
Kidney Cancer
Lung Cancer
Ovarian Cancer
Pancreatic Cancer
Prostate Cancer
Stomach Cancer

There are many studies showing positive associations between solid tumors and pesticide exposure. In particular, the large well-designed cohort studies consistently show statistically significant positive associations. The relationships are most consistent for high exposure levels such as those found in occupational settings. The results frequently show dose response relationships, and quality of studies was generally good. Overall, these findings strongly support a reduction of pesticide use, particularly for those individuals with occupational exposure (agriculture, pesticide applicators) at high doses.
Otto Warburg called attention to this in the 1950’s. However, we also know that viruses can have a role in the causation of cancers. Moreover, cancers may occur in sites of chronic inflammation.  I have not said anything about the association of specific mutations with types of cancer, and associations in some cases with specific populations at a greater risk than the broader population.

Profiling Solid Tumor Heterogeneity by LCM and Biological MS of Fresh-Frozen Tissue Sections

Donald J. Johann, Sumana Mukherjee, DaRue A. Prieto, Timothy D. Veenstra, Josip Blonder
Laser Capture Microdissection
Methods in Molecular Biology 2011; 755, pp 95-106

The heterogeneous nature of solid tumors represents a common problem in mass spectrometry (MS)-based analysis of fresh-frozen tissue specimens. Here, we describe a method that relies on synergy between laser capture microdissection (LCM) and MS for enhanced molecular profiling of solid tumors. This method involves dissection of homogeneous histologic cell types from thin fresh-frozen tissue sections via LCM, coupled with liquid chromatography (LC)-MS analysis. Such an approach enables an in-depth molecular profiling of captured cells. This is a bottom-up proteomic approach, where proteins are identified through peptide sequencing and matching against a specific proteomic database. Sample losses are minimized, since lysis, solubilization, and digestion are carried out directly on LCM caps in buffered methanol using a single tube, thus reducing sample loss between these steps. The rationale for the LCM-MS coupling is that once the optimal method parameters are established for a solid tumor of interest, homogeneous histologic tumor/tissue cells (i.e., tumor proper, stroma, etc.) can be effectively studied for potential biomarkers, drug targets, pathway analysis, as well as enhanced understanding of the pathological process under study.

A microRNA expression signature of human solid tumors defines cancer gene targets

Stefano Volinia*†‡, George A. Calin*‡, Chang-Gong Liu*, et al.
PNAS  Feb 14, 2006; 103(7): 2257–2261
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1413718/pdf/pnas-0510565103.pdf

Small noncoding microRNAs (miRNAs) can contribute to cancer development and progression and are differentially expressed in normal tissues and cancers. From a large-scale miRnome analysis on 540 samples including lung, breast, stomach, prostate, colon, and pancreatic tumors, we identified a solid cancer miRNA signature composed by a large portion of overexpressed miRNAs. Among these miRNAs are some with well characterized cancer association, such as miR-17-5p, miR-20a, miR-21, miR-92, miR-106a, and miR-155. The predicted targets for the differentially expressed miRNAs are significantly enriched for protein-coding tumor suppressors and oncogenes (P < 0.0001). A number of the predicted targets, including the tumor suppressors RB1 (Retinoblastoma 1) and TGFBR2 (transforming growth factor, beta receptor II) genes were confirmed experimentally. Our results indicate that miRNAs are extensively involved in cancer pathogenesis of solid tumors and support their function as either dominant or recessive cancer genes.

Diagnosis of and therapy for solid tumors with radiolabeled antibodies and immune fragments

Carrasquillo JA, Krohn KA, Beaumier P, McGuffin RW, et al.
Cancer Treatment Reports [1984, 68(1):317-328]
http://europepmc.org/abstract/med/6607111

Antibodies which are directed against human tumor-associated antigens can potentially be used as carriers of radioactivity for in vivo diagnosis (radioimmunodetection) or treatment (radioimmunotherapy) of solid tumors, including colon, hepatoma, cholangiocarcinoma,  and melanoma.  Murine  monoclonal antibodies (MOAB), produced by the hybridoma technique of Kohler and Milstein, are replacing conventional heterosera as sources of antibodies, because MOAB can be produced in large quantities as reproducible reagents with homogeneous binding properties. We have studied  human melanoma using MOAB IgG and Fab fragments that recognize the human melanoma-associated antigens p97and “high-molecular-weight antigen.” Both antigens are found in the membrane of melanomas at much larger concentrations than in normal adult tissues. We have performed radioimmunodetection studies with whole immunoglobulin and have detected 88% of lesions greater than 1.5 cm. We have used Fab fragments for radioimmunotherapy and have found that large doses of radiolabeled antibodies (up to 342 mCi) can be repetitively given to patients without excessive end-organ toxicity. Two of three patients treated with high-dose radiolabeled antimelanoma Fab showed an effect from the treatment. Although both technical and biologic problems remain, the use of radiolabeled antibodies that are directed against tumor-associated antigens holds future promise as a new therapeutic approach to solid tumors that are resistant to conventional therapy.

https://www.cirm.ca.gov/our-progress/disease-information/solid-tumor-fact-sheet

Solid tumors include cancers of the brain, ovary, breast, colon and other tissues. Many people believe that one quality solid tumors share is a reliance on cancer stem cells. These cancer stem cells are thought to divide to produce the bulk of the cells that make up the tumor.

The hypothesis suggests that unlike most cells of a tumor, the cancer stem cells divide very slowly and are less likely to be destroyed by chemotherapies that kill the fast-growing tumor cells. The thought is that cancers might recur because the chemotherapy kills the bulk of the tumor, but leaves behind the cancer stem cells that can, over time, form a new tumor.

Stem cell scientists are studying cancer stem cells from solid tumors in the lab to find ways of destroying them. If these cancer stem cells share characteristics that allow them to be destroyed by the same drug, then a single new drug could significantly improve cancer treatment for a range of different cancer types.

Resminostat – by 4SC

Despite decades of concentrated effort, medicine has yet to achieve a decisive breakthrough for many types of cancer. 4SC is focusing on fields of research with an especially high academic interest and future potential – such as epigenetics, cancer stem cells, cancer immunotherapy and other key molecular signal transduction pathways that contribute to the development and persistence of cancer diseases.

Resminostat is 4SC’s lead oncology compound. Resminostat is an oral histone-deacetylase (HDAC) inhibitor with an innovative epigenetic mechanism of action that potentially enables the compound to be deployed as a novel, targeted tumour therapy for a broad spectrum of oncological indications, both as a monotherapy and, in particular, in combination with other cancer drugs.

Epigenetic mode of action

HDAC inhibitors modify the three-dimensional chromatin DNA structure of tumour cells and can trigger cell differentiation, which can ultimately result in programmed cell death (apoptosis). HDAC inhibitors therefore offer a mechanism of action that has the potential to halt tumour progression and induce tumour regression. Furthermore, resminostat – due to its epigenetic mode of action – can develop an additional synergetic effect in combined treatments with other traditional cancer therapies and also fight the development of resistance to other cancer medications.

An example: In preclinical studies, resminostat has been shown to effectively inhibit epithelial-mesenchymal transition (EMT). EMT, which may be promoted through the administration of certain conventional cancer therapies, leads to the formation of particularly aggressive tumour cells, which ultimately may result in greater proliferation of cancer cells in patients and the patients’ death.

On the whole, a reinforcing positive therapeutic effect is expected to be achieved through well-tolerated parallel administration of an epigenetic compound such as resminostat and a traditional cancer drug. Combination therapy thus aims to improve the success of the treatment as a whole.

Resminostat – by 4SC in Europe and its Japanese development partner Yakult Honsha in Asia – has been investigated to date in a broad clinical Phase I/II program in the four indications of liver cancer (hepatocellular carcinoma, HCC), Hodgkin Lymphoma (HL), colorectal cancer (CRC), and non-small-cell lung cancer (NSCLC).

Notably, in both tumor indications, HCC and HL, gene expression levels of the new biomarker ZFP64 measured prior to study treatment start in blood cells of patients, were identified to be indicative of survival outcome upon treatment with resminostat. Hereby, the set of patients with a high level of ZFP64 gene expression at baseline showed a statistically significant increase of median overall survival compared with patients with low ZFP64 expression levels.

4SC is prioritizing the further development of resminostat in the liver cancer indication. 4SC’s goal is to progress resminostat in combination with sorafenib as a first-line therapy for HCC until market approval. 4SC’s main focus is the use of the resminostat/sorafenib combination as a first-line treatment for HCC patients, while the use as a second-line therapy remains an attractive additional option.

4SC Discovery is a drug discovery company based in Planegg-Martinsried near Munich. It was founded in December 2011 as a wholly owned subsidiary of 4SC AG.

Response Evaluation Criteria in Solid Tumors
http://en.wikipedia.org/wiki/Response_Evaluation_Criteria_in_Solid_Tumors

Response Evaluation Criteria In Solid Tumors (RECIST) is a set of published rules that define when tumors in cancer patients improve (“respond”), stay the same (“stabilize”), or worsen (“progress”) during treatment. The criteria were published in February 2000 by an international collaboration including the European Organisation for Research and Treatment of Cancer (EORTC), National Cancer Institute of the United States, and the National Cancer Institute of Canada Clinical Trials Group. Today, the majority of clinical trials evaluating cancer treatments for objective response in solid tumors use RECIST.

These criteria were developed and published in February 2000, and subsequently updated in 2009. They are specifically NOT meant to determine whether patients have improved or not, as these are tumor-centric, not patient centric criteria. This distinction must be made by both the treating physicians and the cancer patients themselves. Many oncologists in their daily clinical practice follow their patient’s malignant disease by means of repeated imaging studies and make decisions about continuing therapy on the basis of both objective and symptomatic criteria. It is not intended that these RECIST guidelines play a role in that decision making, except if determined appropriate by the treating oncologist.

• CT and MRI are the best currently available and reproducible methods to measure target lesions selected for response assessment. Conventional CT and MRI should be performed with cuts of 10 mm or less in slice thickness contiguously. Spiral CT should be performed using a 5 mm contiguous reconstruction algorithm. This applies to tumors of the chest, abdomen and pelvis. Head and neck tumors and those of extremities usually require specific protocols.

• Lesions on chest X-ray are acceptable as measurable lesions when they are clearly defined and surrounded by aerated lung. However, CT is preferable.

• When the primary endpoint of the study is objective response evaluation, ultrasound (US) should not be used to measure tumor lesions. It is, however, a possible alternative to clinical measurements of superficial palpable lymph nodes, subcutaneous lesions and thyroid nodules. US might also be useful to confirm the complete disappearance of superficial lesions usually assessed by clinical examination.

• The utilization of endoscopy and laparoscopy for objective tumor evaluation has not yet been fully and widely validated. Their uses in this specific context require sophisticated equipment and a high level of expertise that may only be available in some centers. Therefore, the utilization of such techniques for objective tumor response should be restricted to validation purposes in specialized centers. However, such techniques can be useful in confirming complete pathological response when biopsies are obtained.

• Tumor markers alone cannot be used to assess response. If markers are initially above the upper normal limit, they must normalize for a patient to be considered in complete clinical response when all lesions have disappeared.

• Cytology and histology can be used to differentiate between PR and CR in rare cases (e.g., after treatment to differentiate between residual benign lesions and residual malignant lesions in tumor types such as germ cell tumors).

Baseline documentation of “Target” and “Non-Target” lesions

• All measurable lesions up to a maximum of 2 lesions per organ and 5 lesions in total, representative of all involved organs should be identified as target lesions and recorded and measured at baseline.
• Target lesions should be selected on the basis of their size (lesions with the longest diameter) and their suitability for accurate repeated measurements (either by imaging techniques or clinically).
• A sum of the longest diameter (LD) for all target lesions will be calculated and reported as the baseline sum LD. The baseline sum LD will be used as reference by which to characterize the objective tumor response.
• All other lesions (or sites of disease) should be identified as non-target lesions and should also be recorded at baseline. Measurements of these lesions are not required, but the presence or absence of each should be noted throughout follow-up.

Response Criteria

‘Evaluation of target lesions

• Complete Response (CR): Disappearance of all target lesions
• Partial Response (PR): At least a 30% decrease in the sum of the LD of target lesions, taking as reference the baseline sum LD
• Stable Disease (SD): Neither sufficient shrinkage to qualify for PR nor sufficient increase to qualify for PD, taking as reference the smallest sum LD since the treatment started
• Progressive Disease (PD): At least a 20% increase in the sum of the LD of target lesions, taking as reference the smallest sum LD recorded since the treatment started or the appearance of one or more new lesions

Evaluation of non-target lesions

• Complete Response (CR): Disappearance of all non-target lesions and normalization of tumor marker level
• Incomplete Response/ Stable Disease (SD): Persistence of one or more non-target lesion(s) or/and maintenance of tumor marker level above the normal limits
• Progressive Disease (PD): Appearance of one or more new lesions and/or unequivocal progression of existing non-target lesions

Evaluation of best overall response

The best overall response is the best response recorded from the start of the treatment until disease progression/recurrence (taking as reference for PD the smallest measurements recorded since the treatment started). In general, the patient’s best response assignment will depend on the achievement of both measurement and confirmation criteria

• Patients with a global deterioration of health status requiring discontinuation of treatment without objective evidence of disease progression at that time should be classified as having “symptomatic deterioration”. Every effort should be made to document the objective progression even after discontinuation of treatment.
• In some circumstances it may be difficult to distinguish residual disease from normal tissue. When the evaluation of complete response depends on this determination, it is recommended that the residual lesion be investigated (fine needle aspirate/biopsy) to confirm the complete response status.

Duration of stable disease

• SD is measured from the start of the treatment until the criteria for disease progression are met, taking as reference the smallest measurements recorded since the treatment started.
• The clinical relevance of the duration of SD varies for different tumor types and grades. Therefore, it is highly recommended that the protocol specify the minimal time interval required between two measurements for determination of SD. This time interval should take into account the expected clinical benefit that such a status may bring to the population under study.

Response review

• For trials where the response rate is the primary endpoint it is strongly recommended that all responses be reviewed by an expert(s) independent of the study at the study’s completion. Simultaneous review of the patients’ files and radiological images is the best approach.

Tumor microenvironment

http://en.wikipedia.org/wiki/Tumor_microenvironment

The tumor microenvironment is the cellular environment in which the tumor exists, including surrounding blood vessels, immune cells, fibroblasts, other cells, signaling molecules, and the extracellular matrix(ECM).^[1] The tumor and the surrounding microenvironment are closely related and interact constantly. Tumors can influence the microenvironment by releasing extracellular signals, promoting tumor angiogenesisand inducing peripheral immune tolerance, while the immune cells in the microenvironment can affect the growth and evolution of cancerous cells, such as in immuno-editing. The tumor microenvironment has been shown to contribute to tumour heterogeneity. In one of its earliest forms, this concept of interplay between the tumor and its microenvironment can be seen in Stephen Paget‘s “seed and soil” theory where he postulated that metastases of a particular type of cancer (“the seed”) often metastasizes to certain sites (“the soil”) based on the similarity of the environments of the original and secondary tumor sites.^[2] Later, experiments by Halachmi and Witz in mice showed that for the same cancer cell line, inoculation in mice (where the tumor microenvironment could affect the cancer) created greater tumorigenicity than the same strain inoculated in in vitro culture.^[3][4]

80-90% of cancer are carcinomas, or cancers that form in the epithelial tissue.^[5] This tissue is not vascularized, which prevents tumors from growing greater than 2mm in diameter without recruiting new blood vessels to feed itself.^[6] The process of angiogenesis is dysregulated to feed the cancer cells, and as a result the vasculature formed differs from that of normal tissue.

The enhanced permeability and retention effect (EPR effect) is the observation that the vasculature of tumors is often leaky and accumulates molecules in the blood stream to a greater extent than normal tissue. This effect linked to inflammation is not only seen in tumors, but in hypoxic area of cardiac muscles following a myocardial infarction (MI or heart attack).^[7][8] This leaky vasculature is thought to have several causes, including a dearth of pericytes and a malformed basement membrane.^[8

The tumor microenvironment is often hypoxic. As the tumor mass increases, the interior of the tumor grows farther away from existing blood supply. While angiogenesis can reduce this affect, the partial pressure of oxygen is below 5 mm Hg (venous blood has a partial pressure of oxygen at 40 mm Hg) in more than 50% of locally advanced solid tumors.^[9][10] The hypoxic environment leads to genetic instability, which is associated with cancer progression, via downregulating nucleotide excision repair (NER) and mismatch repair (MMR) pathways.^[11] Hypoxia also causes the upregulation of hypoxia-inducible factor 1 alpha (HIF1-α), which induces angiogenesis, and is associated with poorer prognosis and the activation of genes associated with metastasis.^[10]

While a lack of oxygen can cause glycolytic behavior in cells, tumor cells have also been shown to undergo aerobic glycolysis as well, in which they preferentially produce lactate from glucose even when there is abundant oxygen. This phenomenon is called the Warburg effect, in honor of its discoverer, Otto Warburg.^[12] No matter the cause, this leaves the extracellular microenvironment acidic (pH 6.5-6.9), while the cancer cells themselves are able to remain neutral (ph 7.2-7.4). It has been shown that this induces greater cell migration in vivo and in vitro, possibly by promoting degradation of the ECM.^[13][14]

The stroma of a carcinoma is the connective tissue below the basal lamina. This includes fibroblasts, ECM, immune cells, and other cells and molecules. The stroma surrounding a tumor often reacts to the intrusion via inflammation, similar to how it might with a wound, leading cancer to be called “wounds that do not heal.”^[15] Inflammation can encourage angiogenesis, speed the cell cycle, and prevent cell death, all of which augments tumor growth.

Carcinoma associated fibroblasts (CAFs) are a heterogenous group of fibroblasts whose function is pirated by cancer cells and then contribute toward carcinogenesis^[17] These cells usually are derived from the normal fibroblasts in the surrounding stroma but can also come from pericytes, smooth muscle cells, fibrocytes, mesenchymal stem cells (MSCs, often derived from bone marrow), or via epithelial-mesenchymal transition (EMT) or endothelial-mesenchymal transition (EndMT).^[18][19][20] Unlike their normal counterparts, CAFs do not retard cancer growth in vitro.^[21] Beyond simply lacking the ability of tumor inhibition, CAFs also perform several functions which support tumor growth, such as secreting vascular endothelial growth factor (VEGF), fibroblast growth factors (FGFs), platelet-derived growth factor (PDGF), and other pro-angiogenic signals to induce angiogenesis.^[9] CAFs can also secrete transforming growth factor beta (TGF-β), which is associated with EMT, a process by which cancer cells can metastasize,^[22] and is associated with inhibiting cytotoxic T cells and natural killer T cells.^[23] As fibroblasts, CAFs are able to rework the ECM to include more paracrine survival signals such as IGF-1 and IGF-2, thus promoting survival of the surrounding cancer cells.^[17] CAFs are also associated with the Reverse Warburg Effect where the CAFs perform aerobic glycolysis and feed lactate to the cancer cells.^[17]

Several markers are used to identify CAFs including expression of α smooth muscle actin (αSMA), vimentin, platelet-derived growth factor receptor α (PDGFR-α), platelet-derived growth factor receptor β (PDGFR-β), fibroblast specific protein 1 (FSP-1), and fibroblast activation protein (FAP).^[19] None of the factors can be used to differentiate CAFs from all other cells by itself.

Myeloid-derived suppressor cells (MDSCs) are a heterogenous population of cells of myelogenous origin with the potential to repress T cell responses. They regulate wound repair and inflammation and are rapidly expanded in cancer, correlating with that signs of inflammation are seen in most if not all tumor sites.^[24][25] Tumors can produce exosomes that stimulate inflammation via MDSCs.^[26][27] This group of cells include some tumor associated macrophages (TAMs).^[24] TAMs are a central component in the strong link between chronic inflammation and cancer. TAMs are recruited to the tumor as a response to cancer associated inflammation.^[28] Unlike normal macrophages, TAMs lack cytotoxic activity.^[29] TAMs have been induced in vitro by exposing macrophage progenitors to different immune regulatory cytokines, such as interleukin 4(IL-4) and interleukin 13 (IL-13).^[17] TAMs gather in necrotic regions of tumors where they have been associated with hiding the cancer cells from normal immune cells by secreting interleukin 10 (IL-10),^[30] aiding angiogenesis by secreting vascular endothelial growth factor(VEGF) and nitric oxide synthase(NOS),^[9] supporting tumor growth by secreting epidermal growth factor (EGF)^[30] and remodeling the ECM.^[9] TAMs show sluggish NF-κB activation, which allows for the smoldering inflammation seen in cancer.^[31] An increased amount of TAMs is associated with worse prognosis.^[32][33] TAMs represent a potential target for novel cancer therapies.

TAMs have recently been associating with using exosomes (vesicles used by mammalian cells to secrete intracellular contents) to deliver invasion-potentiating microRNA (miRNA) into cancerous cells, specifically breast cancer cells.^[26][34]

Fibroblasts are in charge of laying down most of the collagens, elastin, glycosaminoglycans, proteoglycans (e.g. perlecan), and glycoproteins in the ECM. As many fibroblasts are transformed into CAFs during carcinogenesis, this reduces the amount of ECM produced and the ECM that is produced can be malformed, like collagen being loosely woven and non-planar, even curved.^[37] In addition, CAFs produce matrixmatrix metalloproteinases (MMP), which cleave the proteins within the ECM.^[9] CAFs are also able to disrupt the ECM via force, generating a track that a carcinoma cell can follow directly behind.^[38] In either case, destruction of the ECM allows cancer cells to escape from their in situ location and intravasate into the blood stream where they can metastasize systematically. It can also provide passage for endothelial cells to complete angiogenesis to the tumor site.

Destruction of the ECM also modulates the signaling cascades controlled by the interaction of cell-surface receptors and the ECM, and it also reveals binding sites previously hidden, like the integrin alpha-v beta-3(αVβ3) on the surface of melanoma cells can be ligated to rescue the cells from apoptosis after degradation of collagen.^[39][40] In addition, the degradation products may have downstream effects as well that can increase tumorigenicity of cancer cells and can serve as potential biomarkers.^[39] The destruction of the ECM also releases the cytokines and growth factors stored therein (for example, VEGF, basic fibroblast growth factor (bFGF), insulin-like growth factors (IGF1 and IGF2), TGF-β, EGF, heparin-binding EGF-like growth factor (HB-EGF), and tumor necrosis factor (TNF), which can increase the growth of the tumor.^[37][41]Cleavage of ECM components can also release cytokines that inhibit tumorigenesis, such as degradation of certain types of collagen can form endostatin, restin, canstatin, & tumstatin, which have antiangiogenic functions.^[37]

Stiffening of the ECM is associated with tumor progression.^[42] This stiffening may be partially attributed to CAFs secreting lysyl oxidase (LOX), an enzyme that cross-links the collagen IV found in the ECM.^[19][43]

Numerous high throughput screens for cancer therapeutics are performed in vitro on cancer cell lines without the accompanying microenvironment, but current studies are also investigating the effects of supportive stroma cells on the biology of cancer cells and their resistance to therapy.^[44] These studies revealed that there are interesting therapeutic targets in the microenvironment like integrins or chemokines.^[44] These were missed by initial screens for anti-cancer drugs and might also help explain why so few initially identified drugs are highly potent in vivo.

Much effort has been devoted into developing nanocarrier vehicles (~20-200 nm in diameter) for transportation of drugs and other therapeutic molecules, so that these therapies can be targeted to selectively extravasate through tumor vasculature via the EPR effect. Using a nanocarrier is now considered the gold standard of targeted cancer therapy because it targets almost all tumors besides those few that are hypovascularized, like prostate and pancreatic tumors.^[8][45] These efforts include protein capsids^[46] and liposomes.^[47] However, as some important, normal tissues, like the liver and kidneys, also have fenestrated endothelium, great care must be taken with using the correct size (10-100 nm, with greater retention in tumors seen in using larger nanocarriers) and charge (anionic or neutral).^[8] Lymphatic vessels do not usually develop with the tumor, leading to increased interstitial fluid pressure, which made abrogate the journey of these nanocarriers to the tumor.^[8][48]

Bevacizumab is clinically approved to treat a variety of cancer by targeting VEGF-A, which is produced by both CAFs and TAMs, thus slowing angiogenesis. Many other small molecule inhibitors exist that block the receptors for the growth factors released, thus making the cancer cell deaf to much of the paracrine signaling produced by CAFs and TAMs. These inhibitors include Sunitinib, Pazopanib, Sorafenib, and Axitinib, all of which inhibit platelet derived growth factor receptors (PDGF-Rs) and VEGF receptors (VEGFRs). Cannabidiol, a cannabis derivate without psychoactive side effects, has also been shown to inhibit the expression of VEGF in Kaposi’s sarcoma cells.^[49]

Natalizumab is a monoclonal antibody that was designed to target one of the molecules responsible for cell adhesion (integrin VLA-4) and has promising in vitro activity in B cell lymphomas and leukemias.^[44]

Also, Trabectedin is known to have immunomodulatory effects that inhibit TAMs.^[30]

Current formulations of liposomes encapsulating anti-cancer drugs for selective uptake to tumors via the EPR effect include: Doxil and Myocet, both of which encapsulate doxorubicin (a DNA intercalator and common chemotherapeutic); DaunoXome, which encapsulates daunorubicin (another DNA intercalator similar to doxorubicin); and Onco-TCS, which encapsulates vincristine (a molecule which constitutively induces formation of microtubules, dysregulating cell division). Another novel utilization of the EPR effect comes from Protein-bound paclitaxel (marketed under the trade name Abraxane) where paclitaxel (a molecule which dysregulates cell division via stabilization of microtubules) is bound to albumin to add bulk and aid delivery.

1. Michael J. Duffy The biochemistry of metastasis Advances in Clinical Chemistry, Volume 32 1996, Pages 135–160
2. Fabienne Danhier, Olivier Feron, Véronique Préat To exploit the tumor microenvironment: Passive and active tumor targeting of nanocarriers for anti-cancer drug delivery Journal of Controlled Release, Volume 148, Issue 2, 1 December 2010, Pages 135–146 http://dx.doi.org/10.1016/j.jconrel.2010.08.027
3. Cynthia E. Weber, Paul C. Kuo The tumor microenvironment Surgical Oncology, Volume 21, Issue 3, September 2012, Pages 172–177 http://dx.doi.org/10.1016/j.suronc.2011.09.001
4. Mikhail V. Blagosklonny Antiangiogenic therapy and tumor progression Cancer Cell, Volume 5, Issue 1, January 2004, Pages 13–17 http://dx.doi.org/10.1016/S1535-6108(03)00336-2
5. Ranjit S. Bindra, Peter M. Glazer Genetic instability and the tumor microenvironment: towards the concept of microenvironment-induced mutagenesis Mutation Research/Fundamental and Molecular Mechanisms of Mutagenesis, Volume 569, Issues 1–2, 6 January 2005, Pages 75–85 http://dx.doi.org/10.1016/j.mrfmmm.2004.03.013
6. Robert A. Gatenby & Robert J. Gillies Why do cancers have high aerobic glycolysis? Nature Reviews Cancer Volume 4, November 2004, Pages 891-899 http://dx.doi.org/10.1038/nrc1478
7. Veronica Estrella, Tingan Chen, Mark Lloyd, Jonathan Wojtkowiak, Heather H. Cornnell, Arig Ibrahim-Hashim, Kate Bailey, Yoganand Balagurunathan, Jennifer M. Rothberg, Bonnie F. Sloane, Joseph Johnson, Robert A. Gatenby, and Robert J. Gillies Acidity Generated by the Tumor Microenvironment Drives Local Invasion Cancer Research, Volume 73, Issue 5, 1 March 2013, Pages 1524-1535 http://dx.doi.org/10.1158/0008-5472.CAN-12-2796
8. Joydeb Kumar Kundu, Young-Joon Surh Inflammation: Gearing the journey to cancer Mutation Research/Reviews in Mutation Research, Volume 659, Issues 1–2, July–August 2008, Pages 15–30 http://dx.doi.org/10.1016/j.mrrev.2008.03.002
9. Kati Räsänen, Antti Vaheri Activation of fibroblasts in cancer stroma Experimental Cell Research, Volume 316, Issue 17, 15 October 2010, Pages 2713–2722 http://dx.doi.org/10.1016/j.yexcr.2010.04.032
10. Timothy Marsh, Kristian Pietras, Sandra S. McAllister Fibroblasts as architects of cancer pathogenesis Biochimica et Biophysica Acta (BBA) – Molecular Basis of Disease Online 30 October 2012http://dx.doi.org/10.1016/j.bbadis.2012.10.013
11. Michael Quante, Shui Ping Tu, Hiroyuki Tomita, Tamas Gonda, Sophie S.W. Wang, Shigeo Takashi, Gwang Ho Baik, Wataru Shibata, Bethany DiPrete, Kelly S. Betz, Richard Friedman, Andrea Varro, Benjamin Tycko, & Timothy C. Wang Bone Marrow-Derived Myofibroblasts Contribute to the Mesenchymal Stem Cell Niche and Promote Tumor Growth Cancer Cell, Volume 19, Issue 2, 15 February 2011, Pages 257–272 http://dx.doi.org/10.1016/j.ccr.2011.01.02

Pathology Outlines _ Nat Pernick, MD
Copyright: (c) 2002-2015, PathologyOutlines.com, Inc.

Stains
Immunohistochemistry basics

Reviewer: Nat Pernick, M.D. (see Reviewers page)
Revised: 21 March 2014, last major update August 2013
Copyright: (c) 2002-2013, PathologyOutlines.com, Inc.

General
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• Immunohistochemistry (IHC) is a tool for surgical pathology and research
• Diagnosis should be based on H&E morphology, with confirmation by immunohistochemistry or molecular testing; it is dangerous to use immunohistochemistry alone to make the diagnosis
• A stain / result is not just positive or negative; focus on the types of cells that are immunoreactive and determine if they are tumor cells, inflammatory cells, normal cells or stromal cells; comparing the results to an H&E stained section or a negative control of the same block may be helpful (Am J Surg Pathol 2007;31:1627, J Clin Pathol 2011;64:466)
• After you identify the type of cell staining, it is helpful to note the percentage of these cells staining, the intensity of staining (weak, 1+, 2+, 3+, 4+) and the pattern of staining (membranous, cytoplasmic, nuclear, dot-like)
• The pattern of immunoreactivity should follow the anatomic distribution of the antigen before it is called positive / immunoreactive
• Reference: CAP Laboratory Improvement Programs: Principles of Analytic Validation of Immunohistochemical Assays

Common errors
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• Not using a positive or negative control; they are helpful in interpreting the staining pattern, particularly if it is heavy or weak
• Other sources of error are ectopic antigen expression (may be due to abundant endogenous biotin, Hum Pathol 2011;42:369), cross reactions (Mod Pathol 2012;25:231), less specificity than thought (Int J Clin Exp Pathol 2012;5:137), use of the wrong secondary antibody (EJN Blog) or rarely the wrong primary antibody

http://www.pathologyoutlines.com/topic/stainsihcbasics.html

Immunohistochemistry – common panels

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• Epithelial markers: low molecular weight keratin (CAM 5.2), AE1-AE3 cytokeratin cocktail, CK7, CK20, CEA and EMA
• Alternative epithelial markers on sarcomatoid carcinoma include p63, MOC-31 and TTF1 (Mod Pathol 2005;18:1471)
• Melanocytic markers: S100 (also a mesenchymal marker), HMB45, MelanA / Mart1
• Lymphoid markers: CD3 (T cells), CD20 (B cells), CD15 (Hodgkin), CD30 (Hodgkin & other) and various others
• Histiocytic markers: CD68, lysozyme, CD1a (Langerhans cells)
• Neuroendocrine markers: neuron specific enolase, chromogranin, synaptophysin, CD56 and CD57
• Mesenchymal markers: vimentin (non-specific), factor XIIIa (fibrous histiocytoma), factor VIII (vessels), CD31 (vessels), CD34 (vessels), D2-40 (lymphatics), HHF35 (actin), smooth muscle actin and desmin
• Cell proliferation / apoptosis markers: Ki-67, bcl2

http://www.pathologyoutlines.com/topic/stainsihcpanel.html

Tissue of origin / unknown primary

PubMed Search: tissue of origin[title]

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• 3-5% of cancer diagnoses
• Choice of marker depends on what tumors are logically within the differential diagnosis
• Molecular products must be validated to show adequate performance characteristics for clinical use (Arch Pathol Lab Med 2010;134:216)
• Analysis may be affected by tumor heterogeneity (Genome Med 2013;5:29)
• Tumors of unknown primaries, even when accurately classified by molecular methods, may harbour molecular/genetic traits distinct from tumors of known primaries, and have poorer response to treatment (Cancer Treat Rev 2009;35:221)
• Immunohistochemistry profiles:
  • Carcinoma of unknown primary, 18 markers (MD Anderson): table, Gastrointest Cancer Res 2007;1:229
  • Adenocarcinoma, 12 markers + PCR (Turin, Italy): algorithm, J Transl Med 2012;10:12
  • Adenocarcinoma, 15 markers (Tokyo, Japan): algorithm, PLoS One 2012;7:e31181
• Gene expression assays:
  • Measures expression of up to thousands of genes simultaneously to identify those whose expression has changed compared to baseline (normal) levels
  • Adenocarcinoma (Amsterdam): J Clin Oncol 2008;26:4435
  • Carcinoma of unknown primary determined using Pathwork Tissue of Origin Test: Am J Surg Pathol 2013;37:1067, Diagn Pathol 2010;5:26
    • Test also works on body fluid specimens: Cancer Cytopathol 2012;120:62
    • Test may soon be offered by Response Genetics
  • Poorly differentiated / undifferentiated tumors-1550 gene expression profile (The Methodist Hospital): J Clin Oncol 2009;27:2503
  • Carcinoma of unknown primary determined using microarray reference database (Helsinki, Finland): Genome Med 2011;3:63
• Hybrid using IHC and gene expression assays:
  • Carcinoma of unknown primary (Moffitt Cancer Center): J Mol Diagn 2010;12:476
• RT-PCR:
  • RT-PCR (bioTheranostics): Oncologist 2010;15:500, J Clin Oncol 2013;31:217
• Computational:
  • Computational strategy using high-throughput sequencing (ISOLATE): Bioinformatics 2009;25:2882
• MicroRNA based PCR methods:
  • Rosetta Genomics: Oncologist 2012;17:801, Mol Cancer 2013;12:57
  • CNS metastases (Heidelberg, Germany): Oncologist 2011;16:165
  • 47 miRNA signature (Ferrara, Italy): J Pathol 2011;225:43
  • 48 miRNA signature (MD Anderson)Clin Cancer Res 2011;17:4063

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3380879/bin/onc0061210700003.jpg

CD Markers

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CD: cluster designation or cluster of differentiation; a protocol to identify and investigate cell surface molecules

Nomenclature proposed in 1982 at First International Workshop and Conference on Human Leukocyte Differentiation Antigens (HLDA)

A classification system for monoclonal antibodies generated by laboratories worldwide against cell surface molecules, initially on leukocytes, but now also from other cell types

Data is collated and analyzed by cluster analysis based on pattern of binding to leukocytes or other cell types

Must be at least two monoclonal antibodies for each antigen

“w” indicates that the CD is not well characterized or is represented by only one monoclonal antibody

Current CD markers range from CD1 to CD363

Interpretation should be based on cellular distribution of staining (i.e. membranous, cytoplasmic, nuclear), proportion of positively stained cells, staining intensity and cutoff levels

Physiology

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CD molecules have various functions, including receptors or ligands; also cell adhesion, antigen presentation

Although commonly used by pathologists to characterize cells, they most likely also have an important (although sometimes unknown) function in cell physiology

http://www.pathologyoutlines.com/topic/cdmarkersgeneral.html

Enzyme cytochemistry

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• Detects enzymatic activity in cytoplasm
• Advantage over immunocytochemistry is determination of enzyme’s intracellular localization and intensity of catalytic activity (for research purposes)
• Flow cytometry and immunocytochemistry are often preferred to determine presence of enzyme molecule (but not catalytic activity or localization)
• Enzyme product unites with coupler, which produces localized color at site of enzyme activity
• Fresh smears are preferred, especially for myeloperoxidase; if not possible, store unstained slides away from light

Methods
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• Simultaneous capture: reagent in incubation medium combines with reaction product (example: diazo method for alkaline phosphatase)
• Post-incubation coupling: insoluble reaction product is coupled with a colored or opaque substance (example: Rutenburg and Seligman method for acid phosphatase)
• Self-colored substrate reaction: water-soluble dye is made insoluble when enzyme removes a hydrophilic group, leading to colored precipitate at site of enzyme activity
• Intramolecular rearrangement: produces a colored insoluble precipitate at sites of enzyme activity of an otherwise colorless substrate (University of Iowa)

Molecular Pathology

Authors: Zubair W. Baloch, M.D., Ph.D., Joshua Bradish, M.D., Betty Chung, D.O., M.P.H., M.A., Rodney E. Shackelford, D.O., Ph.D.; Editors: Liang Cheng, M.D., Gregory A. Hosler, M.D., Ph.D. (see Reviewers page)

http://www.pathologyoutlines.com/molecularpath.html

DNA purification: introduction analyzing purity basic protocol anion exchange chromatography cesium chloride density gradient centrifugation commercial DNA extraction machines ethanol precipitation organic extraction PCR inhibitors RNA purification silica adsorption tissue preparation

DNA sequencing: history Maxam-Gilbert sequencing Sanger sequencing capillary electrophoresis other innovations real time pyroseqencing nanotechnology Roche 454 FLX pyrosequencer Illumina Genome Analyzer HeliScope Sequencer

FISH: general probes protocol probe patterns images

Microarray: introduction history basics considerations errors
variations: antibody bead based cellular CGH solid phase tissue (TMA)

PCR: definition history basics Taq polymerase reaction stages thermocyclers applications
variations: general methylation specific multiplex nested real-time reverse transcriptase  

http://www.pathologyoutlines.com/images/groupphotobig.jpg

Contact us (248/646-0325) with any questions

Pathology Outline

http://www.tumorlibrary.com/outline.jsp

Below is a comprehensive categorization of the diseases documented in this site. Click on a section name, to view the Cases. For many of the diseases we have also provided descriptions in PDF format. To read the disease description, click on the PDF icon next to the disease name.

Diagnosis

–	A > Z
–	by Location
–	by Treatment
–	by Image Type

Tumor Types

–	Bone Tumors
–	Histiocytoses
–	Pseudotumors
–	Soft Tissue Tumors

There are some important issues related to the pathology of cancer that need to be addressed. The two references above are both valuable for a source useful for reference to the characterization and methods of identification of most tumors. The second is concerned with soft tissue and bone sarcomas.
PathologyOutlines is also an excellent source for soft tissue and bone sarcomas.

It is important to realize that despite enormous progress in the molecular biology of carcinomas and sarcomas, there is a characteristic natural history and clinical presentation, and the ability to distinguish within types is related to differential expression that is related to metabolic characteristics and tissue differentiation.  The pathologist uses a system of morphological grading based on the nuclear to cytoplasmic ratio, the loss of architecture (such a glandular anaplasia) that is important, but not sufficient.  The staging is based on regional lymph node extension, and to distant metastasis.  In addition, the use of cell differentiation markers and immunohistochemical staining is essential.

However, the field is now being rewritten in a large way that will not have a significant effect for perhaps a decade by the clinical pathology and molecular diagnostics measurement of miRNAs and lncRNAs, that are measureable in tissue and in serum, and the expanded use of mass spectrometry, and MS combined with optical methods. This is important for the differentiation of types of malignant expression within cell types, and will be important for matching malignancy to pharmaceutical targets.  Despite the use of the term cancer targeting, the reality has been that single chemotherapy has not been sufficient in the treatment of advanced disease.  This I attribute to the complexity of the interactions between affected dysregulated pathways. The same problem has been encountered in the multiple hit progression of infection to systemic inflammatory response to sepsis to multiple organ failure. The assumption that there is a magic bullet has been an illusion.  This is where the mathematical modeling has become important because we are dealing with more than one major variable:

1. Local control
2. Cell-like cell interactions
3. Cell-unlike cell interactions
4. Level of disruption involving cell migration
5. The level of mitochondrial respiration
6. The degree of loss of apoptosis

There is also a consideration of age, sex, and endocrine factors.  This is particularly illustrated in the case of childhood malignancies, such as neuroblastoma.  In the case of bone tumors, it is not widely recognized that there is a relationship between muscle and bone in the remodeling process, and a relationship between the type of neoplasm and the anatomical location, and also a relationship to the loss of remodeling control after age 65 years.

This is illustrated by the classification of bone tumors as – periosteal and endosteal, and as epiphyseal, metaphyseal, and diaphyseal (for long bones).
The parosteal sarcoma may be fibrosarcoma or osteosarcoma, and may be derived from a fibrous dysplasia, a myositis ossificans, a fibroxanthoma, a lipoma, or malignant transformation in an osteochondroma.  The prognosis for such a cancer after a local wide excision is far better than a cancer within the bone.  This was the case 40 years ago, long before modern molecular diagnostics.  In the case of epiphyseal lesions, one expects the cancer to be dictated by cartilaginous origin, but it also can arise from a cystic lesion at the joint margin. The growth and development of bone and the greatest activity of growth in length of a long bone is at the growth plate, in the metaphysis.  This also happens to be the site most affected by scurvy, rickets (articular cartilage and metaphysis), and by hyperparathyroidism. The metaphysis is where the cartilage is converted to calcified bone matrix, which is remodeled by the removal of bone by osteoblasts and the laying down of bone by osteoblasts.  Stable bone at equilibrium is maintained by osteocytes.  The circulation in bone is in Volkmann’s canals.  What types of tumors do we find at the metaphysis? Malignant Giant Cell Tumor and Osteosarcoma.  Chondrosarcomas may arise there also from an enchondroma, a benign tumor within the bone at the metaphysis, or an osteochondroma.  Perhaps the most wild type of bone tumor is the malignant combined giant cell and osteogenic sarcoma that arises in Paget’s disease.  This is a disease that occurs in older age which is characterized by a loss of control of bone remodeling resulting in the rapid remodeling of bone with the generation of a primitive bone that can be called – pumice bone. It is easily fractured.  Bone remodels to a peak in the late 30’s, and then slows down, but occurs throughout life. The bone becomes more compact.  In remodeling bone is removed by osteoclasts and bone is added by osteoblasts.  A single osteoclast removes 100 microns of bone that is replaced by 100 osteoblasts adding 1 micron each.  This dynamic was measured by Dr. Lent C. Johnson.

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