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Old 02-13-2012, 08:52 PM
gdpawel gdpawel is offline
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Default Chasing Gene Mutations

At the 2012 American Association for Cancer Research (AACR) meeting recently held in Chicago, it was observed by some that the AACR presentations continue to diverge from those at the American Society of Clinical Oncology (ASCO). That is, all of the alphabet soup combinations that make up the sessions at ASCO are nowhere to be found at the AACR meeting. Instead, targeted agents, genomics, proteomics and the growing field of metabolomics reign supreme.

Just identifying molecular predisposing mechanisms still does not guarantee that a drug will be effective for an individual patient. Nor can it, for any patient or even large group of patients, discriminate the potential for clinical activity among different agents of the same class.

The challenge is to identify which patients targeted treatment will be most effective. One can chase all the mutations they want, because if you miss just one, it may be the one that gets through. Or you can look for the drugs that are "sensitive" to killing all of your cancer cells, not "theoretical candidates.

Tumors can become resistant to a targeted treatment, or the drug no longer works, even if it has previously been effective in shrinking a tumor. Drugs are combined with existing ones to target the tumor more effectively. Most cancers cannot be effectively treated with targeted drugs alone.

Molecular testing methods detect the presence or absence of selected gene or protein mutations which theoretically correlate with single agent drug activity. Cells are never exposed to anti-cancer agents.

Even patients who are found to have an activating EGFR mutation, Tarceva is considered acceptable but not a definite superior choice. Genetic variations alone do not determine response to targeted therapy. Those patients who test negative for EGFR are left to the same guesswork as conventional therapy.

There are lots of things which determine if the drug works, beyond the existence of a given target. Does the drug even get into the cancer cell? Does it get pumped out of the cell? Does the cell have ways of escaping drug effects? Can cells repair damage caused by the drug?

Tarceva could be given selectively to patients with EGFR negative NSCLC. It is a challenge to identify which patients targeted treatments like Tarceva will be effective. Patients across a broad range of clinical characteristics could benefit. Being EGFR negative is no reason not to be given this drug.

What is needed is to measure the net effect of all processes within the cancer, acting with and against each other in real time, and test living cells (not cell lines) actually exposed to drugs and drug combinations of interest. The key to understanding the genome is understanding how cells work. How is the cell being killed regardless of the mechanism?

Functional profiling assess the net effect of all inter-cellular and intra-cellular processes occurring in real time when cells are exposed to anti-cancer agents (targeted or conventional). Tests are performed using intact, living cancer cells plated in 3D microclusters. It allows for testing of different drugs within the same class and drug combinations to detect drug synergy and drug antagonism.

The core understanding 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 of these pathways, it is important to examine the effects of drug combinations within the context of the cell.

Both genomics and proteomics can identify potential therapeutic targets, but these targets require the determination of cellular endpoints. You still need to measure the net effect of all processes, not just the individual molecular targets.

Rating the efficacy of population research vs rating the efficacy of drugs actually tested against an individual's cancer cells.

References:

Eur J Clin Invest, Volume 37(suppl. 1):60, April 2007. Functional profiling with cell culture-based assays for kinase inhibitors and anti-angiogenic agents.

J Clin Onco, 2006 ASCO Annual Meeting Proceedings Part 1. Vol 24, No. 18S (June 20 Supplement), 2006: 17117. Genfitinib-induced cell death in short term fresh tumor cultures predicts for long term patient survival in previously-treated NSCLC.

Nagourney, R. et. al, Horizontal and vertical signal pathway inhibition in human tumor primary culture micro-spheroids. Abstract 1764, proceedings AACR 2010.

"Phase II Trial of Personalized Chemotherapy In Stage IV NSCLC: Clinical Application Of Functional Profiling In First-Line Therapy" (Abstract No. 7617; Citation: J. Clin Oncol 28:7s, 2010)

Nagourney RA, Kollin CA, Sommers B, Su Y-Z, Evans SS. Functional profiling of human tumors in primary culture: a platform for drug discovery and therapy selection, AACR abstract #1546, 2008

Survival among patients with platinum resistant, locally advanced non-small cell lung cancer treated with platinum-based systemic therapy. d'Amato TA, Pettiford BL, Schuchert MJ, Parker R, Ricketts WA, Luketich JD, Landreneau RJ. Ann Surg Oncol. 2009 Oct;16(10):2848-55. Epub 2009 Jul 16.

Functional profiling with cell culture-based assays for kinase and anti-angiogenic agents Eur J Clin Invest 37 (suppl. 1):60, 2007

Functional Profiling of Human Tumors in Primary Culture: A Platform for Drug Discovery and Therapy Selection (AACR: Apr 2008-AB-1546)

Journal of Clinical Oncology, 2006 ASCO Annual Meeting Proceedings Part I. Vol 24, No. 18S (June 20 Supplement), 2006: 17117

Ian A. Cree (ed.), Cancer Cell Culture: Methods and Protocols, Second Edition, Methods in Molecular Biology, vol. 731, DOI 10.1007/978-1-61779-080-5_22.

Response to second-line Tarceva (erlotinib) in an EGFR mutation-negative patient with non-small-cell lung cancer

[url]http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3267591/
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Old 02-13-2012, 08:57 PM
gdpawel gdpawel is offline
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Default Metabolic Profiles Are Essential For Personalizing Cancer Therapy

The genomic profile is so complicated, with one thing affecting another, that it isn't sufficient and not currently useful in selecting drugs. Because metabolic changes are complex and hard to predict, metabolic profiling will be essential for selecting best treatment.

In drug selection, molecular (genomic) testing examines a single process within the cell or a relatively small number of processes. The aim is to tell if there is a theoretical predisposition to drug response. It attempts to link surrogate gene expression to a theoretical potential for drug activity.

It relies upon a handful of gene patterns which are thought to imply a potential for drug susceptibility. In other words, molecular testing tells us whether or not the cancer cells are potentially susceptible to a mechanism/pathway of attack.

It doesn't tell you if one targeted drug (or combination of targeted drugs) is better or worse than another targeted drug (or combination) which may target a certain or a small number of mechanisms/pathways.

Functional profile testing doesn't dismiss DNA testing, it uses all the information, both genomic and functional, to design the best targeted treatment for each individual, not populations. It tests for a lot more than just a few mutations.

Functional profiling consists of a combination of a (cell morphology) morphologic endpoint and one or more (cell metabolism) metabolic endpoints. It studies cells in small clusters or micro-spheroids (micro-clusters). The combination of measuring morphologic and metabolic effects at the whole cell level.

The cell is a system, an integrated, interacting network of genes, proteins and other cellular constituents that produce functions. One needs to analyze the systems' response to targeted drug treatments, not just a few targets (pathways).

[url]http://www.medicalnewstoday.com/releases/241306.php
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Old 02-13-2012, 08:59 PM
gdpawel gdpawel is offline
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Default Research in Combining Targeted Agents Faces Numerous Challenges

Testing for EGFR, KRAS and ALK pathways and coming up negative is no reason not to be given these drugs. All the mutation/amplification study can tell you is whether or not the cancer cells are "potentially" susceptible to this mechanism of attack. It cannot tell you if a targeted drug will actually work for your cancer cells, or not.

Tumor cells have such an uniqueness that not much is known of their respective reaction to targeted therapies. In other words, patients can benefit from targeted drugs regardless of mutation/amplification status. These targeted therapies produce limited results because they can help a relatively small subgroup of cancer patients.

But when they work, they produce very good responses. With targeted therapy, the trick is figuring out which patients will respond. Tests to pinpoint those patients cannot be accomplished with genetic testing.

In a conference sponsored by the Institute of Medicine, scientists representing both public and private institutions examined the obstacles that confront researchers in their efforts to develop effective combinations of targeted cancer agents.

In a periodical published by the American Society of Clinical Oncology (ASCO) in their September 1, 2011 issue of the ASCO Post, contributor Margo J. Fromer, who participated in the conference, wrote about it.

One of the participants, Jane Perlmutter, PhD, of the Gemini Group, pointed out that advances in genomics have provided sophisticated target therapies, but noted, “cellular pathways contain redundancies that can be activated in response to inhibition of one or another pathway, thus promoting emergence of resistant cells and clinical relapse.”

James Doroshow, MD, deputy director for clinical and translational research at the NCI, said, “the mechanism of actions for a growing number of targeted agents that are available for trials, are not completely understood.”

He went on to say that the “lack of the right assays or imaging tools means inability to assess the target effect of many agents.” He added that “we need to investigate the molecular effects . . . in surrogate tissues,” and concluded “this is a huge undertaking.”

Michael T. Barrett, PhD, of TGen, pointed out that “each patient’s cancer could require it’s own specific therapy.” This was followed by Kurt Bachman of GlaxoSmithKline, who opined, “the challenge is to identify the tumor types most likely to respond, to find biomarkers that predict response, and to define the relationship of the predictors to biology of the inhibitors.”

What they were describing was precisely the work that clinical oncologists involved with cell culture assays have been doing for the past two decades. The complexities and redundancies of human tumor biology had finally dawned on these investigators, who have clung to analyte-based molecular platforms.

The incidence of ALK gene rearrangement in patients with NSCLC is in the range of 2-4 percent, while EGFR mutations are found in approximately 15 percent. These are largely mutually exclusive events. Yet with an objective response rate of 10 percent (Von Hoff, et al JCO, Nov 2011) reported for a gene array/IHC platform that attempted to select drugs for individual patients, it doesn't seem to be a very accurate or validated methodology to use in patients with advanced NSCLC.

And those patients who do test negative for ALK and EGFR are left to the same guesswork that has provided responses in the range of 30 percent and survivals in the range of 12 months. It's interesting to note how quickly organizations like ASCO have embraced the expensive and comparatively inefficient molecular testing.

[url]http://www.ascopost.com/articles/september-1-2011/research-in-combining-targeted-agents-faces-numerous-challenges.aspx
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Old 02-14-2012, 09:54 PM
gdpawel gdpawel is offline
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Default The ROS1 Gene Mutation

The ROS1 mutation is a gene for DNA repair and the tyrosine kinase binding portion (the part that gets turned on to set off a cascade of downstream intracellular events) for ROS1 is very similar to ALK (ALK inhibitors can also inhibit ROS1). It seems like the results with Xalkori in some ROS1 mutation patients are very encouraging so far.

The ROS1 mutation occurs in about 1% of the lung cancer population, patients who are never-smokers, have poorly-differentiated and higher grade adenocarcinoma with bronchiololoalveolar cell carcinoma, and negative for EGFR, KRAS or ALK.

In lung cancer, well- and moderately-differentiated tumors are slow-growing tumors, while poorly-differentiated tumors are fast-growing (high-grade) tumors, thus very aggressive. So, poorly-differentiated, fast-growing tumors are generally treated with chemotherapy, while slow-growing ones (well- and moderately-differentiated) can be treated with biotherapy (targeted therapy).

A published report to characterize the frequency and clinical features of the ROS1 rearrangement came from Massachusetts General Hospital and Vanderbilt University. The article looked at the molecular features of 1073 tumors from patients and found that 18 (1.7%) had the ROS1 rearrangement and 31 (2.9%) had the ALK rearrangement.

Both ROS1 and ALK patients share some clinical features, like a much younger median age than the broader NSCLC population. If testing for these few mutations has any significance, then use those tests for those "mutation targeted" drugs, but in the meantime, we've got the other 97.1% to 98.3% of chemotherapy in NSCLC patients to worry about.

According to Research To Practice, Massachusetts General (MGH) published a mutation paper focused on the new translocation called ROS1 (a receptor tyrosine kinase of the insulin receptor family). The article has been released electronically by the JCO and details the genetic and clinical characteristics of ROS1-positive tumors and also describes the case of a 31-year-old man who, according to Dr. Tom Lynch, was “on his deathbed” when he was found to have a ROS1 rearrangement.

Prior in vitro work, also conducted by the MGH group, had shown ROS1 cells to be sensitive to ALK inhibitors, so the patient was treated with Xalkori (crizotinib) as part of a newly launched Phase I trial. The patient experienced rapid tumor shrinkage with a near complete response and almost a year later he remains on that agent with no evidence of recurrence.

The ROS1 translocation is found mainly in younger never smokers with adenocarcinoma. Like ALK, it is detected by FISH assay and has some sequence homology to ALK — perhaps explaining why Xalkori (crizotinib) is effective in vitro and in at least one patient. Of particular interest, this rearrangement has also been observed in glioblastomas and cholangiocarcinomas, but the impact of an agent like Xalkori (crizotinib) is unknown.

Winter Lung faculty member Dr. Pasi Jšnne wrote an accompanying JCO editorial and commented during the meeting that oncologists must be on the lookout for nonsmokers who test negative for EGFR and ALK, and while ROS1 is thought to occur in only about 2% of non-small cell cases, this translates to approximately 4,000 people a year in the United States alone.

The appearance of yet another potentially “druggable” target in NSCLC should be no surprise considering recent research demonstrating that so-called driver mutations occur in perhaps as many as 60% of pulmonary adenocarcinomas. As a result, we are now approaching or have arrived at a situation very similar to breast cancer with ER, HER2 and the 21-gene Recurrence Score, in that the treatment algorithm changes dramatically based on the results of tissue assays.

In cancer medicine, the new paradigm establishing a requirement of a companion diagnostic as a condition for approval of new targeted therapies. However, it puts such great pressure that the companion diagnostics that are approved often have been mostly or totally ineffective at identifying clinical responders to the various therapies. That is because genomics are far too limited in scope to encompass the vagaries and complexities of human cancer biology.

Pharmacogenomics is defined as the study of how a person's genetic makeup determines response to a drug. Although any number of labs and techniques can detect mutant genes, this area of pharmacogenomics was ripe for proprietary tests, invented alongside the drug and owned by the drug developer and/or a partner in the diagnostics field.

This business opportunity evolved as more drugs were approved with companion diagnostics. Unfortunately, the introduction of these new drugs has not been accompanied by specific predictive tests allowing for a rational and economical use of the drugs. There is still a lot of trial-and-error treatment going on.

Top pharmaceutical firms specializing along disease management lines: in-licensing or co-marketing portfolios of personalized, smaller-market drugs as a package deal to physician specialties, along with a test or two. Drug and diagnostic companies working together, with drug targets perhaps based on a diagnostic marker - not the other way around - could grease the wheels for personalized medicine.

Pharmacogenomics relies on the marriage of pharmacology and genetic testing. Where cell function analysis finds the optimal treatment or combination from an array of possibilities, pharmacogenomics normally focuses on one or more genes targeted by a single drug. Gene-based tests lend themselves to the drug/diagnostic brand of personalized medicine.

Functional profiling methodology maintains cancer cells in their native state, making analysis of "targeted" compounds more reliable. Cellular tests have the advantage over genetic tests because the complexities and redundancies of human biology are beyond the ken of genomics.

As we enter the era of personalized medicine, it is time to take a fresh look at how we evaluate treatments for cancer patients. More emphasis is needed actually matching treatment to the patient (not statistical guesstimates).

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.

In this new era of pharmacogenomics, genetic and phenotypic analysis, prognostic molecular marker testing, and cell function analysis all share a role in the development of "personalized" patient care.

Literature Citation:

BMJ 2007;334(suppl 1):s18 (6 January), doi:10.1136/bmj.39034.719942.94
Functional profiling with cell culture-based assays for kinase and anti-angiogenic agents Eur J Clin Invest 37 (suppl. 1):60, 2007
Functional Profiling of Human Tumors in Primary Culture: A Platform for Drug Discovery and Therapy Selection (AACR: Apr 2008-AB-1546)

[url]http://hopepracticedhere.wordpress.com/2012/05/02/persistence-over-acceptance/

Companion Diagnostics

[url]http://cancerfocus.org/forum/showthread.php?t=3038
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Old 02-14-2012, 09:55 PM
gdpawel gdpawel is offline
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Default The Molecular Origins of Lung Cancer

Dr. Robert Nagourney, of Rational Therapeutics, attended the AACR-IASLC Joint Conference on Molecular Origins of Lung Cancer; Biology, Therapy and Personalized Medicine held in San Diego in January.

This symposium organized by David Carbone and Roy Herbst, brought together a broad spectrum of sophisticated scientists and international investigators, as well as community members and fundraising organizations who had the opportunity to present a special session on patient advocacy.

The meeting began with a keynote address examining microRNAs and lung cancer presented by Frank Slack from Yale University. He examined the growing recognition that lung cancer arises not only from gene mutations but also from small fragments of RNA that can up- or down-regulate normal genes in abnormal ways. This was the topic of discussion for many subsequent presentations.

Dr. Nagourney is generally underwhelmed by genomic analyses for drug selection and the prediction of cancer response. The fact that normal genes can function abnormally under the control of these small RNA sequences is just one more example of the genotype–phenotype dichotomy that cannot be adequately examined on static contemporary genomic platforms.

Many presentations examined the molecular biology of lung cancer with important distinctions being drawn between adenocarcinoma and squamous cell carcinomas. While adenocarcinomas reveal a growing number of targets – EGFR, ALK, ROS, RAS, and others – all the subject of small molecule inhibitors; squamous cell carcinomas provide fewer opportunities for the use of these classes of drugs.

One of the interesting discussions was the frequent mutation of LKB1 in lung cancers. Work going back several years by John Minna, a pioneer in this field, identified changes in this metabolic regulator as a common finding in lung malignancies.

Additional presentations examined chemoprevention, molecular pathology, new mechanisms to categorize lung cancer subtypes, and a very interesting discussion of field cancerization.

In a particularly interesting analysis, Ignacio Wistuba from M.D. Anderson, showed that molecular changes in the surface epithelium of the lung bronchioles recapitulated the molecular biology of the final tumor in a step-wise manner, inversely related to the distance to the tumor. That is, starting at the main bronchi, one or two mutational changes were detected.

Moving closer to the site of the tumor, additional mutations were accumulated. Finally arriving at the site of the established malignancy, all of the constituent mutations associated with this particular cancer became manifest; a saltatory slide into cancer presumably associated with exposure to carcinogens.

Among the other exciting presentations were updates on redox-based approaches to cancer presented by Kenneth Tew and Garth Powis.

Jeff Engelman presented an update on a new class of agents that target the RAS pathway. This is ongoing work that he and his group have reported on over the last several years.

At Rational Therapeutics, Dr. Nagourney has been engaged in related work using an MEK/ERK inhibitor similar to the compound that Dr. Englemen reported on at this meeting. It is exciting indeed to see early clinical results with this class of compounds, for Nagourney has identified many patients who might benefit from this pathways’ inhibition.

He waits with great anticipation for FDA approval of these compounds so that his patients currently being identified as candidates in the laboratory may soon receive these treatments.

Dr. Nagourney suggests, where genomic signatures provide useful insights for drug selection, as they do in APL (ATRA, Arsenic trioxide), NSCLC (EGFR, ROS1, ALK), CML (Imatinib, Dasatanib) then they should be used.

However, in those diseases where we haven't the luxury of known targets or established pathways, i.e. most human malignancies, then more global assessments of human tumor biology should, indeed must, be used if we are to meet the need of our patients.

Primary culture analyses provide a window onto human tumor biology. They are vehicles for therapy improvement and conduits for drug discovery.
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Old 02-17-2012, 12:47 AM
gdpawel gdpawel is offline
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Default Genotype does not equal Phenotype

Much cell-based assay work focuses on tumor cell testing, with exciting results. Some small, private labs have commercialized cell-based assays to predict response to cancer treatment. These methods have become routine enablers for personalized medicine.

They distinguish between a disease phenotype from what may be numerous genotypes. With gene-based assays already in use (e.g., the breast cancer drug Herceptin and the her2neu gene), genes often provide an incomplete picture of response to a drug. The complexities and redundancies of human biology are beyond the ken of genomics.

These private labs have developed cell-based assays that predict which chemotherapy drugs or combinations will work on a specific patient’s tumor. Its diagnostic product uses tissue obtained from biopsy or surgery, and cultured to maintain as faithfully as possible the cancer cell's native "niche" and physiologic state within the tumor.

These cultures are then treated with various chemotherapy agents and combinations to see which drugs work best. Published data from clinical studies suggest a high degree of correlation between assay results and response to chemotherapy.

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 (biological activity) 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.

Then further analyses revealed evidence that the technologies for the prediction of response in individual patients could not be reproduced. The NCI 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. 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.

The particular sequence of DNA that an organism possess (genotype) does not determine what bodily or behaviorial form (phenotype) the organism will finally display. Among other things, environmental influences can cause the suppression of some gene functions and the activation of others. Out knowledge of genomic complexity tells us that genes and parts of genes interact with other genes, as do their protein products, and the whole system is constantly being affected by internal and external environmental factors.

The gene may not be central to the phenotype at all, or at least it shares the spotlight with other influences. Environmental tissue and cytoplasmic factors clearly dominate the phenotypic expression processes, which may in turn, be affected by a variety of unpredictable protein-interaction events. This view is not shared by all molecular biologists, who disagree about the precise roles of genes and other factors, but it signals many scientists discomfort with a strictly deterministic view of the role of genes in an organism’s functioning.

Until such time as cancer patients are selected for therapies predicated upon their own unique biology, we will confront one targeted drug after another. Our solution to this problem has been to investigate the targeting agents in each individual patient’s tissue culture, alone and in combination with other drugs, to gauge the likelihood that the targeting will favorably influence each patient’s outcome. Functional profiling results to date in patients with a multitude type of cancers suggest this to be a highly productive direction.

[url]http://jnci.oxfordjournals.org/content/102/7/NP.1.full

Multiple mutations and cancer

[url]http://www.ncbi.nlm.nih.gov/pmc/articles/PMC298677/
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Old 02-17-2012, 12:48 AM
gdpawel gdpawel is offline
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Default Phenotype Analysis

There have been attempts to develop molecular-based tests to examine a broader range of chemotherapeutic drugs. New technologies for measuring the expression (biological activity) of literally hundreds to thousands of genes as part of a single test. There are two main technologies involved: RT-PCR (reverse transcription polymerase chain reaction) and DNA microarray.

The Microarray (gene chips) is a device that measures differences in gene sequence, gene expression or protein expression in biological samples. Microarrays may be used to compare gene or protein expression under different conditions, such as cells found in cancer.

Hence the headlong rush to develop tests to identify molecular predisposing mechansims whose presence still does not guarantee that a 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 agents of the same class.

Genetic profiles are able to help doctors determine which patients will probably develop cancer, and those who will most likely relapse. However, it cannot be suitable for specific treatments for "individual" patients. The NCI has concluded (J Natl Cancer Inst. March 16, 2010), it cannot determine treatment plans for patients. It cannot test sensitivity to any of the targeted therapies. It just tests for "theoretical" candidates for targeted therapy.

Some molecular tests do utilize living cells, but generally of individual cancer cells in suspension, sometimes derived from tumors and sometimes derived from circulating tumor cells. This was tried with the human clonogenic assay, which had been discredited long ago. Traditionally, in-vitro (in lab) "cell-lines" have been studied in 2 dimensions (2D) which has inherent limitations iin applicability to real life 3D in-vivo (in body) states. Recently, other researchers have pointed to the limitations of 2D "cell-line" study and chemotherapy to more correctly reflect the human body.

All DNA or RNA-type tests are based on "population" research (not individuals). They base their predictions on the fact that a higher percentage of people with similar genetic profiles or specific mutations may tend to respond better to certain drugs. This is not really "personalized" medicine, but a refinement of statistical data.

The cell "function" method 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.

Cancer is already in 3D conformation. Cell-based functional profiling cultures "fresh" live tumor cells in 3D conformation and profiles the function of cancer cells (is the whole cell being killed regardless of the targeted mechanism or pathway). It distinguishes between susceptibility of cancer cells to different drugs in the same class and the susceptibility to combinations. In other words, which combinations are best and in what sequence would they be most effective.

The key to understanding the genome is understanding how cells work. The ultimate driver is a "functional" assay (is the cell being killed regardless of the mechanism) as opposed to a "target" assay (does the cell express a particular target that the drug is supposed to be attacking). While a "target" assay tells you whether or not to give "one" drug, a "functional" assay can find other compounds and combinations and can recommend them from the one assay.

The core of the functional assay 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 therapeutic targets, but these targets require the determination of cellular endpoints.

Cell-based functional assays are 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 assay.

The reason for at least a "tru-cut" biopsied tumor specimen is that "real life" 3D analysis makes functional profiling indicative of what will happen in the body. It tests fresh "live" cells in their 3 dimensional (3D), floating clusters (iin their natural state). Upgrading clinical therapy by using drug sensitivity assays measuring cell-death of 3 dimenionsl microclusters of live "fresh" tumor cells can improve the conventional situation by allowing more drugs to be considered.
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Old 02-17-2012, 12:52 AM
gdpawel gdpawel is offline
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Default

The whole concept of using molecular signatures of any kind to do anything beyond the most straightforward of cases is flawed. The simple answer is that cancer isn’t simple. Cancer dynamics are not linear. Cancer biology does not conform to the dictates of molecular biologists. We are confronted with 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, it will be years, perhaps decades, before these profiles can approximate the vagaries of human cancer.

In recent years, personalized care has come to be considered synonymous with genomic profiling. While breakthroughs in human genomics is applauded, there is no molecular platform that can match patients to treatments. The objective response rate of just 10 percent, almost all in breast and ovarian cancer patients in one study (Von Hoff J Clin Oncol 2010 Nov 20:28(33): 4877-83), suggests that cancer biology is demonstrably more complex than an enumeration of its constituent DNA base pairs.

The endpoints (point of termination) of molecular profiling (genotyping analysis) are gene expression, examining a single process (pathway) within the cell or a relatively small number of processes (pathways) to test for "theoretical" candidates for targeted therapy.

The endpoints of functional profiling (phenotyping analysis) are expression of cell-death, both tumor cell death and tumor associated endothelial (capillary) cell-death (tumor and vascular death), and examines not only for the presence of the molecular profile but also for their functionality, for their interaction with other genes, proteins and other processes occuring within the cell, and for their "actual" response to anti-cancer drugs (not theoretical susceptibility).

Phenotype (functional profiling) analyses, which measure biological signals rather than DNA indicators, continues to provide clinically validated information and plays an important role in cancer drug selection. The data that support phenotype analyses is demonstrably greater and more compelling than any data currently generated from genotype analyses. Functional profiling remains the most validated technique for selecting effective therapies for cancer patients.

We don't know how to handle one gene, never mind 20,000 genes. To put this in context, two percent of the human genome that codes for known proteins (the part that everyone currently studies) represents only 1/20 of the whole story.

A more highly productive direction would be to investigate the targeting agents in each individual patient's tissue culture, alone and in combination with other drugs, to guage the likelihood that the targeting will favorably influence each patient's outcome.

The need for phenotype analyses has never been greater. As systems biologists point out, complexity is the hallmark of biological existence. Any attempts to oversimplify phenomena that cannot be simplified, have, and will continue to lead us in the wrong direction.

Dr. Larry Weisenthal, one of the pioneers of functional cytometric profiling analysis, has described the use of RT-PCR and DNA microarrays in personalized oncology as analogous to the introduction of the personal computer. Dazzling hardware in search of a killer application. This was wonderful technology and the geekiest of people bought them and played with them, but they really didn’t start to do anything for a mass market until the introduction of the first killer application, which was a spreadsheet program called Visicalc.

So what research scientists in universities and cancer centers have been doing for the past ten years is to try and figure out a way to use this dazzling technology to look for patterns of gene expression which correlate with and predict for the activity of anticancer drugs. Hundreds of millions of dollars have been spent on this effort. Objectively speaking, it’s like the emperor’s new clothes. So far, a qualified failure.

Academics are besides themselves over the promise of the new technology. It seems so cool that it simply must be good for something. How about in the area of identifying drugs which will work in individual patients? It has been a major bust by whatever standard you choose to apply. Objectively, if you compare and contrast the peer-reviewed medical literature supporting the use of functional cytometric profiling for personalizing drug selection versus the correspond literature supporting molecular profiling, the literature supporting functional profiling wins.

Sources:

JNCI J Natl Cancer Inst (2010) doi: 10.1093/jnci/djq306

J Thorac Cardiovasc Surg 2007;133:352-363. Chemotherapy Resistance and Oncogene Expression in NSCLC.

J Clin Onco, 2006 ASCO Annual Meeting Proceedings Part 1. Vol 24, No. 18S (June 20 Supplement), 2006: 17117. Genfitinib-induced cell death in short term fresh tumor cultures predicts for long term patient survival in previously-treated NSCLC.

Eur J Clin Invest, Volume 37(suppl. 1):60, April 2007. Functional profiling with cell culture-based assays for kinase inhibitors and anti-angiogenic agents.

Weisenthal Cancer Group, Huntington Beach, CA and Departments of Clinical Pharmacology and Oncology, Uppsala University, Uppsala, Sweden. Current Status of Cell Culture Drug Resistance Testing (CCDRT) May, 2002.

Journal of Clinical Oncology Reviews on Chemotherapy Sensitivity and Resistance Assays, September1,2004.
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Last edited by gdpawel : 12-28-2012 at 06:21 PM. Reason: additional info
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Old 02-17-2012, 12:53 AM
gdpawel gdpawel is offline
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Default What is Phenotype?

A phenotype is an organism's observable characteristics or traits: such as its morphology, development, biochemical or physiological properties, behavior, and products of behavior (such as a bird's nest). Phenotypes result from the expression of an organism's genes as well as the influence of environmental factors and the interactions between the two.

The genotype of an organism is the inherited instructions it carries within its genetic code. Not all organisms with the same genotype look or act the same way because appearance and behavior are modified by environmental and developmental conditions. Similarly, not all organisms that look alike necessarily have the same genotype.

This genotype-phenotype distinction was proposed by Wilhelm Johannsen in 1911 to make clear the difference between an organism's heredity and what that heredity produces. The distinction is similar to that proposed by August Weismann, who distinguished between germ plasm (heredity) and somatic cells (the body). The Genotype-Phenotype concept should not be confused with Francis Crick's central dogma of molecular biology which is a statement about the directionality of molecular sequential information flowing from DNA to protein (but which cannot become transferred from proteins).

Despite its seemingly straightforward definition, the concept of the phenotype has hidden subtleties. It may seem that anything dependent on the genotype is a phenotype, including molecules such as RNA and proteins. Most molecules and structures coded by the genetic material are not visible in the appearance of an organism, yet they are observable (for example by Western blotting) and are thus part of the phenotype.

Human blood groups are an example. It may also seem that this goes beyond the original intentions of the concept with its focus on the (living) organism in itself, meaning that the lowest level of biological organization compatible with the phenotype concept is at the cellular level.

Either way, the term phenotype includes traits or characteristics that can be made visible by some technical procedure. Another extension adds behavior to the phenotype, since behaviors are also observable characteristics. Indeed there is research into the clinical relevance of behavioral phenotypes as they pertain to a range of syndromes. Often, the term "phenotype" is incorrectly used as a shorthand to indicate phenotypical changes observed in mutated organisms (most often in connection with knockout mice).

References

Churchill F.B. 1974. William Johannsen and the genotype concept. Journal of the History of Biology 7, 5-30.

Johannsen W. 1911. The genotype conception of heredity. American Naturalist 45, 129-159

O'Brien, Gregory; Yule, William, eds (1995). Behavioural Phenotypes. Clinics in Developmental Medicine No.138.

O'Brien, Gregory, ed (2002). Behavioural Phenotypes in Clinical Practice.

Crusio WE (May 2002). "'My mouse has no phenotype'". Genes, Brain and Behavior 1 (2): 71.
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Old 02-27-2012, 05:43 PM
gdpawel gdpawel is offline
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Default Driver Mutations and Passenger Mutations on the road to cancer

Scientists at the Wellcome Trust Sanger Institute, where one-third of the human genome was sequenced, have pioneered decoding the sequence of cancer genomes. They have carried out the broadest survey yet of the human genome in cancer by sequencing more than 250 million letters of DNA code, covering more than 500 genes and 200 cancers.

The survey, published in Nature, shows that the number of mutated genes that drive development of cancer is greater than previously thought. Significantly, as well as driver mutations for cancer, each cell type carries many more passenger mutations that have hitchhiked along for the ride. The study showed that a challenge for cancer biologists will be to distinguish the drivers from the larger number of passengers.

"The human genome is a vast place and this, our first deep systematic exploration in cancer, has thrown up many surprises", said Professor Mike Stratton, co-leader of the Cancer Genome Project at the Sanger Institute. "We have found a much larger number of mutated driver genes produced by a wider range of forces than we expected."

All cancers are believed to be due to mutations, abnormalities in genes. The availability of the human genome sequence has opened the door to analyzing hundreds to thousands of genes, which will ultimately allow us to acquire a complete catalogue of the mutations in individual cancers.

The team studied more than 500 genes of a type called kinases, some of which have been previously implicated in causing cancers. One example is the BRAF gene: the 2002 pilot phase of the team's work showed that BRAF was mutated in more than 60% of cases of malignant melanoma. That observation has driven discovery of new drugs to treat melanoma. The study was much broader and included breast, lung, colorectal and stomach cancers, which are the most common cancer types.

The new research showed that mutations in cancers can be divided into drivers or passengers. Driver mutations are the ones that cause cancer cells to grow, whereas passengers are co-travellers that make no contribution to cancer development. The team identified possible driver mutations in 120 genes, most of which had not been seen before.

"It turns out that most mutations in cancers are passengers," explained Dr Andy Futreal, co-leader of the Cancer Genome Project. "However, buried among them are much larger numbers of driver mutations than was previously anticipated. This suggests that many more genes contribute to cancer development than was thought."

Our understanding of the roles of kinase proteins sheds light on some of the mutations. Kinases can act as a series of relays, switching on and off in our cells, to control cell behaviour, such as cell division.

Dr Futreal explains: "For example, we found that a group of kinases involved in the Fibroblast Growth Factor Receptor signalling pathway was hit much more than we expected, particularly in colorectal cancers."

The team also found that the mutations carry important coded messages within them. The type of mutation found varies markedly between individual cancers, reflecting the processes that generated the mutations, some of which were active decades before the cancer showed itself.

Patterns of mutations are an archaeological record written into the DNA of each cancer telling us about the factors that caused the cancer in the first place, which were often active many decades previously. Some of the patterns can be deciphered, such as the signatures of damage from ultraviolet radiation (sunlight) or cancer-causing chemicals in tobacco, but others are currently cryptic and will require decoding in the future.

"This study vindicates all of the effort that went into the Human Genome Project," commented Dr Mark Walport, Director of the Wellcome Trust. "Understanding the mutations that cause cancer is crucial in order to develop accurately targeted treatments."

This research shows cancers in a different light and highlights many different insights into how cancers develop. The challenge will be distinguishing the drivers from the passengers.

In some cases this is straightforward. For many others, it appears, scientists will have to analyse much larger numbers of each cancer type. New, faster DNA sequencing technologies will play an important part in achieving the scale of study needed.

"The time is right to apply the powerful tools of genomics to obtain a comprehensive view of what goes wrong at the DNA level in cancer," said Francis S. Collins, MD, PhD, director of the National Human Genome Research Institute at the National Institutes of Health. "The important and interesting data on protein kinases in this report by Professor Stratton, Dr Futreal and colleagues further encourages the conclusion that a full assault on the cancer genome will yield many opportunities to revolutionize diagnosis and treatment."
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