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Gregory Pawelski
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Why hasn't there been any progress at all in drug selection through the use of molecular diagnostics and biomarkers? Simply put, they do not work! Little progress has been made in identifying which therapeutic strategies are likely to be effective for individual patients by molecular prognostic and predictive markers. It was hoped that any patient with cancer would have their tumor biopsied and profiled. The profile would then be displayed as a unique genetic signature, which would in turn predict which therapy would most likely work. However, gene-expression signatures are not ready for prime time. Although molecular profiling of tumors has led to the identification of gene-expression patterns, a new review published in the March 16, 2010 JNCI has found little evidence that any of the signatures are ready for use in the clinical setting. And then on July 22 and 23, 2010, the NCI suspended three clinical trials designed to apply gene profiling to select treatments for patients. The first chink in the armor came when scientific reviewers issued an "expression of concern" regarding the validity of the entire method. Further analyses revealed evidence that the technologies for the prediction of response in individual patients could not be reproduced. The NCI convened a group of 31 scientists, who concluded it's absolutely premature to use these prediction models to influence the therapeutic options open to cancer patients. The genomic methodology is not ready for clinical application. What went wrong? "The simple answer is that cancer isn’t simple," according to Dr. Robert Nagourney, one of the pioneers of functional profiling analysis. Cancer dynamics are not linear. Cancer biology does not conform to the dictates of molecular biologists. Once again, we are forced to confront the realization that genotype does not equal phenotype. In a nutshell, cancer cells utilize cross talk and redundancy to circumvent therapies. They back up, zig-zag and move in reverse, regardless of what the sign posts say. Using genomic signatures to predict response is like saying that Dr. Seuss and Shakespeare are truly the same because they use the same words. The building blocks of human biology are carefully construed into the complexities that we recognize as human beings. However appealing gene profiling may appear to those engaged in this field (such as Response Genetics, Caris, the group from Duke and many others) it will be years, perhaps decades, before these profiles can approximate the vagaries of human cancer. Functional profiling analyses, which measure biological signals rather than DNA indicators, will continue to provide clinically validated information and play an important role in cancer drug selection. The data that support functional profiling analyses is demonstrably greater and more compelling than any data currently generated from DNA analyses. Functional profiling remains the most validated technique for selecting effective therapies for cancer patients. There is a microvascular viability assay with functional profiling for anti-angiogenesis-related drugs (Avastin, Sutent and Nexavar), developed by another pioneer of functional profiling analysis, Dr. Larry Weisenthal. A major modification of the DISC (cell death) assay allows for the study of anti-microvascular drug effects of standard and targeted agents, such as Avastin, Nexavar and Sutent. The microvascular viability assay is based upon the principle that microvascular (endothelial and associated) cells are present in tumor cell microclusters obtained from solid tumor specimens. The assay which has a morphological endpoint, allows for visualization of both tumor and microvascular cells and direct assessment of both anti-tumor and anti-microvascular drug effect. CD31 cytoplasmic staining confirms morphological identification of microcapillary cells in a tumor microcluster. The principles and methods used in the microvascular viability assay include: 1. Obtaining a tissue, blood, bone marrow or malignant fluid specimen from an individual cancer patient. 2. Exposing viable tumor cells to anti-neoplastic drugs. 3. Measuring absolute in vitro drug effect. 4. Finding a statistical comparision of in vitro drug effect to an index standard, yielding an individualized pattern of relative drug activity. 5. Information obtained is used to aid in selecting from among otherwise qualified candidate drugs. It is the only assay which involves direct visualization of the cancer cells at endpoint, allowing for accurate assessment of drug activity, discriminating tumor from non-tumor cells, and providing a permanent archival record, which improves quality, serves as control, and assesses dose response in vitro. Photomicrographs of the assay can show that some clones of tumor cells don't accumulate the drug. These cells won't get killed by it. The assay measures the net effect of everything which goes on (Functional Tumor Cell Profiling methodology). Are the cells ultimately killed, or aren't they? This kind of technique exists today and might be very valuable, especially when active chemoagents are limited in a particular disease, giving more credence to testing the tumor first. After all, cutting-edge techniques can often provide superior results over tried-and true methods that have been around for many years. Bibliography relevant to AngioRx/Microvascular Viability assay (MVVA) 1. Weisenthal, L. M. Patel,N., Rueff-Weisenthal, C. (2008). "Cell culture detection of microvascular cell death in clinical specimens of human neoplasms and peripheral blood." J Intern Med 264(3): 275-287. 2. Weisenthal, L., Lee,DJ, and Patel,N. (2008). Antivascular activity of lapatinib and bevacizumab in primary microcluster cultures of breast cancer and other human neoplasms. ASCO 2008 Breast Cancer Symposium. Washington, D.C.: Abstract # 166. Slide presentation at: 3. Weisenthal, L. M. (2010). Antitumor and anti-microvascular effects of sorafenib in fresh human tumor culture in comparison with other putative tyrosine kinase inhibitors. J Clin Oncol 28, 2010 (suppl; abstr e13617) 4. Weisenthal, L., H. Liu, Rueff-Weisenthal, C. (2010). "Death of human tumor endothelial cells in vitro through a probable calcium-associated mechanism induced by bevacizumab and detected via a novel method." Nature Precedings 28 May 2010. from
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Investigators of a randomized, phase III trial of Avastin with paclitaxel in patients with metastatic breast cancer discussed the lack of an overall survival benefit in light of a significant and clinically meaningful improvement in progression free survival. The authors noted the possibility of accelerated tumor regrowth (tumor rebound) compared with chemotherapy alone. It was speculated whether increased in VEGF levels upon discontinuation of Avatin might have resulted in more aggressive disease (Miller K, Wang M, Gralow J, et al. Paclitaxel plus bevacizumab versus paclitaxel alone for metastatic breast cancer. N Engl J Med 2007;357:2666-2676). Serum from Avastin treated patients actually support endothelial cell growth in cell culture better than serum from control patients, without Avastin treatment. When you get rid of VEGF with Avastin, the body cranks out other types of blood vessel growth/survival factors. It will take combination antivascular therapy to make a big difference, but this is definitely coming and it's the most promising thing on the near term therapeutic horizon. However, there are multiple ways by which tumors can evolve that are independent of VEGF and independent of angiogenesis. Tumors can acquire a blood supply by three different mechanisms: angiogenesis; co-option of existing blood vessels; and vasculogenic mimicry. All must be inhibited to consistently starve tumors of oxygen. Instead of growing new blood vessels, tumor cells can just grow along existing blood vessels. This process, called co-option, cannot be stopped with drugs that inhibit new blood vessel formation. Some types of cancers form channels that carry blood, but are not actual blood vessels. Drugs that target new blood vessel formation also cannot stop this process, called vasculogeneic mimicry.
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The new paradigm of requiring a companion diagnostic as a condition for approval of new targeted therapies has placed pressure so great that the companion diagnostics they've approved often have been mostly or totally ineffective at identifying clinical responders (durable and otherwise) to the various therapies. It should be in the FDA's interest in saving the healthcare system perhaps billions of dollars a year (and thereby the healthcare system itself) by ensuring that expensive treatments are used appropriately. It should serve their interest not only in discovering new cancer treatments, but also using currently-available cell culture technologies to improve the effectiveness of existing drugs and save lives today by administering the right drug to the right patient at the right time. The headlong rush to develop companion diagnostics to identify molecular predisposing mechanisms does not guarantee that a cancer drug will be effective for an "individual" patient. Nor can they, for any patient or even large group of patients, discriminate the potential for clinical activity among different cancer agents of the same class. The drug discovery model over the last number of years has been limited to one gene/protein, one target, one drug. The "cell" is a system, an integrated, interacting network of genes, proteins and other cellular constituents that produce functions. You need to analyse the systems' response to drug treatments, not just one target or pathway. The decoding of the human genome in 2000, sparked hopes that a new era of tailored medicine was just around the corner. However, uncovering the genetic differences that determine how a person responds to a drug, and developing tests, or biomarkers, for those differences, is proving more challenging than ever. As a result, patients with cancer are still being prescribed medicines on a trial-and-error basis or one-size-fits-all. The key to understanding the genome is understanding how cells work. The ultimate driver is "functional profiling" (is the cell being killed regardless of the mechanism) as opposed to "molecular profiling" (does the cell express a particular target that the drug is supposed to be attacking). While a "molecular profiling" tells you whether or not to give "one" drug, "functional profiling" can find other compounds and combinations and can recommend them from the one test. The core of "functional profiling" is the cell, composed of hundreds of complex molecules that regulate the pathways necessary for vital cellular functions. If a "targeted" drug could perturb any one of these pathways, it is important to examine the effects of the drug within the context of the cell. Both genomics and proteomics can identify potential new thereapeutic targets, but these targets require the determination of cellular endpoints. Cell-based "functional profiling" is being used for screening compounds for efficacy and biosafety. The ability to track the behavior of cancer cells permits data gathering on functional behavior not available in any other kind of testing. Molecular profiling, important in order to identify new therapeutic targets and thereby to develop useful drugs, are years away from working successfully in predicting treatment response for "individual" patients. Perhaps this is because they are performed on dead, preserved cells that are never actually exposed to the drugs whose activity they are trying to assess. It will never be as effective as the cell "function" methodology, which has existed for the last twenty years and is not hampered by the problems associated with gene expression tests. That is because they measure the net effect of all processes within the cancer, acting with and against each other in real-time, and it tests "living" cells actually exposed to drugs and drug combinations of interest. It would be more advantageous to sort out what's the best "profile" in terms of which patients benefit from this drug or that drug. Can they be combined? What's the proper way to work with all the new drugs? If a drug works extremely well for a certain percentage of cancer patients, identify which ones and "personalize" their treatment. If one drug or another is working for some patients then obviously there are others who would also benefit. But, what's good for the group (population studies) may not be good for the individual. Patients would certainly have a better chance of success had their cancer been "chemo-sensitive" rather than "chemo-resistant," where it is more apparent that chemotherapy improves the survival of patients, and where identifying the most effective chemotherapy would be more likely to improve survival above that achieved with "best guess" empiric chemotherapy through clinical trials. It may be very important to zero in on different genes and proteins. However, when actually taking the "targeted" drugs, do the drugs even enter the cancer cell? Once entered, does it immediately get metabolized or pumped out, or does it accumulate? In other words, will it work for every patient? All the validations of this gene or that protein provides us with a variety of sophisticated techniques to provide new insights into the tumorigenic process, but if the "targeted" drug either won't 'get in' in the first place or if it gets pumped out/extruded or if it gets immediately metabolized inside the cell, it just isn't going to work. To overcome the problems of heterogeneity in cancer and prevent rapid cellular adaptation, oncologists are able to tailor chemotherapy in individual patients. This can be done by testing "live" tumor cells to see if they are susceptible to particular drugs, before giving them to the patient. DNA microarray work will prove to be highly complementary to the parellel breakthrough efforts in targeted therapy through cell function analysis. As we enter the era of personalized medicine, it is time to take a fresh look at how we evaluate new medicines and treatments for cancer. More emphasis should be put on matching treatment to the patient, through the use of individualized pre-testing. Upgrading clinical therapy by using drug sensitivity assays measuring cell-death (apoptosis) of three dimensional microclusters of 'live' fresh tumor cell, can improve the situation by allowing more drugs to be considered. The more drug types there are in the selective arsenal, the more likely the system is to prove beneficial.
Toggle Commented Jul 17, 2010 on The Long Tail of Cancer Research at Onco Chat
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Jul 16, 2010