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Old 03-10-2012, 01:04 PM
gdpawel gdpawel is offline
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Default Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing

Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing

Marco Gerlinger, M.D., Andrew J. Rowan, B.Sc., Stuart Horswell, M.Math., James Larkin, M.D., Ph.D., David Endesfelder, Dip.Math., Eva Gronroos, Ph.D., Pierre Martinez, Ph.D., Nicholas Matthews, B.Sc., Aengus Stewart, M.Sc., Patrick Tarpey, Ph.D., Ignacio Varela, Ph.D., Benjamin Phillimore, B.Sc., Sharmin Begum, M.Sc., Neil Q. McDonald, Ph.D., Adam Butler, B.Sc., David Jones, M.Sc., Keiran Raine, M.Sc., Calli Latimer, B.Sc., Claudio R. Santos, Ph.D., Mahrokh Nohadani, H.N.C., Aron C. Eklund, Ph.D., Bradley Spencer-Dene, Ph.D., Graham Clark, B.Sc., Lisa Pickering, M.D., Ph.D., Gordon Stamp, M.D., Martin Gore, M.D., Ph.D., Zoltan Szallasi, M.D., Julian Downward, Ph.D., P. Andrew Futreal, Ph.D., and Charles Swanton, M.D., Ph.D.

BACKGROUND

Intratumor heterogeneity may foster tumor evolution and adaptation and hinder personalized-medicine strategies that depend on results from single tumor-biopsy samples.

METHODS

To examine intratumor heterogeneity, we performed exome sequencing, chromosome aberration analysis, and ploidy profiling on multiple spatially separated samples obtained from primary renal carcinomas and associated metastatic sites. We characterized the consequences of intratumor heterogeneity using immunohistochemical analysis, mutation functional analysis, and profiling of messenger RNA expression.

RESULTS

Phylogenetic reconstruction revealed branched evolutionary tumor growth, with 63 to 69% of all somatic mutations not detectable across every tumor region. Intratumor heterogeneity was observed for a mutation within an autoinhibitory domain of the mammalian target of rapamycin (mTOR) kinase, correlating with S6 and 4EBP phosphorylation in vivo and constitutive activation of mTOR kinase activity in vitro. Mutational intratumor heterogeneity was seen for multiple tumor-suppressor genes converging on loss of function; SETD2, PTEN, and KDM5C underwent multiple distinct and spatially separated inactivating mutations within a single tumor, suggesting convergent phenotypic evolution. Gene-expression signatures of good and poor prognosis were detected in different regions of the same tumor. Allelic composition and ploidy profiling analysis revealed extensive intratumor heterogeneity, with 26 of 30 tumor samples from four tumors harboring divergent allelic-imbalance profiles and with ploidy heterogeneity in two of four tumors.

CONCLUSIONS

Intratumor heterogeneity can lead to underestimation of the tumor genomics landscape portrayed from single tumor-biopsy samples and may present major challenges to personalized-medicine and biomarker development. Intratumor heterogeneity, associated with heterogeneous protein function, may foster tumor adaptation and therapeutic failure through Darwinian selection (Funded by the Medical Research Council and others).

Supported by grants from the Medical Research Council, Cancer Research UK, the Royal Marsden Hospital Renal Research Fund, Novartis, EU Framework 7 Personalized RNA Interference to Enhance the Delivery of Individualized Cytotoxic and Targeted Therapeutics (PREDICT), and the Wellcome Trust (to Dr. Futreal).

N Engl J Med 2012; 366:883-892March 8, 2012

[url]http://www.nejm.org/doi/full/10.1056/NEJMoa1113205

According to an article, "Genetic heterogeneity and cancer drug resistance," by Nicholas C. Turner and Professor Jorge S. Reis-Filho, in The Lancet Oncology, Volume 13, Issue 4, Pages e178 - e185, April 2012:

Despite the success of targeted therapies in the treatment of cancer, the development of resistance limits the ability to translate this method into a curative treatment. The mechanisms of resistance have traditionally been thought of as intrinsic (ie, present at baseline) or acquired (ie, developed after initial response). Recent evidence has challenged the notion of acquired resistance. Although cancers are traditionally thought to be clonal, there is now evidence of intra-tumor genetic heterogeneity in most cancers. The clinical pattern of acquired resistance in many circumstances represents outgrowth of resistant clones that might have originally been present in the primary cancer at low frequency but that have expanded under the selective pressure imposed by targeted therapies. We describe the potential role of clonal heterogeneity in resistance to targeted therapy, discuss genetic instability as one of its causes, and detail approaches to tackle intra-tumor heterogeneity in the clinic.

Somatic Mutation Profiling and Associations With Prognosis and Trastuzumab Benefit in Early Breast Cancer

[url]http://www.medscape.com/viewarticle/808546

Note: Targeted "genotyping" cannot show any statistically significant associations with trastuzumab benefit.
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Old 03-10-2012, 01:07 PM
gdpawel gdpawel is offline
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Default Tumor's Genetic Identity Not Revealed By Single Biopsy

By Catharine Paddock PhD
Medical News Today

Taking one biopsy sample of a tumor may not be enough to reveal its full genetic identity, according to a breakthrough Cancer Research UK study published in the New England Journal of Medicine on Friday 8 March. The study is significant because it suggests relying on one sample could overlook important biomarkers that help make tailored treatments effective, explaining perhaps why personalized cancer therapy has been less successful than expected.

Professor Peter Johnson, chief clinician at Cancer Research UK said in a statement that the study highlights "important differences that exist within tumours and suggest a way to improve the success rate of personalised cancer medicines".

The lead author of the study is Professor Charles Swanton, who works at Cancer Research UK's London Research Institute and the UCL Cancer Institute. He and his colleagues analyzed the genetic variation among different regions of the same cancer tumor, using samples donated by patients with advanced kidney cancer.

This is the first time genome-wide analysis has been used for this.

Swanton told the press that scientists have known for a while that a tumor is a "patchwork" of faults, but this is the first time, thanks to cutting edge genomic sequencing technology, scientists have been able to map the genetic landscape of a tumor in such "exquisite detail".

For the study, he and his colleagues compared the genetic variations in samples taken from different regions of four separate kidney tumors. They also took samples from other organs the cancer had spread to.

They found that about two thirds of the genetic faults in a tumor were not repeated across other biopsy samples from the same tumor.

They uncovered 118 different mutations:

40 were "ubiquitous mutations", that is they were present in all the biopsy samples,

53 were "shared mutations", that is they were present in more than one, but not all of the samples, and

25 were "private mutations", that were only found in a single biopsy.

"This has revealed an extraordinary amount of diversity, with more differences between biopsies from the same tumour at the genetic level than there are similarities," said Swanton.

The patients who donated the samples used in the study were being treated at London's Royal Marsden Hospital under the supervision of co-author Dr James Larkin.

Larkin said the study has implications for personalized medicine, which tailors treatment for individual patients. The results show there are significant molecular differences across the various parts of a tumor, and also reveals differences between primary tumors and cancer cells that have spread to other sites.

He said such findings could be "relevant to how we treat kidney cancer with drugs because the molecular changes that drive the growth of the cancer once it has spread may be different from those that drive the growth of the primary tumour."

The researchers also analyzed the location of the shared mutations in relation to the whole tumor. From this they traced the origin of particular subtypes of cancer cells, to identify key driver mutations to make a "map" of how the gene variations in the tumor may have evolved.

Swanton said this is the first time they have been able to use the pattern of genetic faults in a tumor to find the origins of certain cancer cell populations. He said it was like Charles Darwin's "tree of life" that shows how different species are related.

The key is to find the mutations in the "trunk" of the tree, because these are the common ones, as opposed to those in the remote branches, which may only be present in a minority of cancer cells.

Such an approach may "also explain why surgery to remove the primary kidney tumour can improve survival, by decreasing the likelihood that resistant cells will be present that could go on to re-grow the tumour after treatment," said Swanton.

Johnson said under Cancer Research UK's Genomics Initiative they are going to see if the same results occur with larger groups of patients. The Initiative is a series of groundbreaking projects where scientists will use the latest high-tech gene sequencing machines to track down the genetic faults driving different types of cancer.

The study was funded by Cancer Research UK, the Medical Research Council and the Wellcome Trust.

References:

"Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing"; Marco Gerlinger, Andrew J. Rowan, Stuart Horswell, James Larkin, and others; N Engl J Med 2012, 366:883-892; published online 8 March 2012; DOI: 10.1056/NEJMoa1113205
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Old 03-15-2012, 01:39 AM
gdpawel gdpawel is offline
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Default The Unfulfilled Promise of Genomic Analysis

Dr. Robert Nagourney
Medical and Laboratory Director
Rational Therapeutics, Inc.
Long Beach, California

In the March 8 issue of the New England Journal of Medicine, investigators from London, England, reported disturbing news regarding the predictive validity and clinical applicability of human tumor genomic analysis for the selection of chemotherapeutic agents.

As part of an ongoing clinical trial in patients with metastatic renal cell carcinoma (the E-PREDICT) these investigators had the opportunity to conduct biopsies upon metastatic lesions and then compare their genomic profiles with those of the primary tumors. Their findings are highly instructive, though not terribly unexpected. Using exon-capture they identified numerous mutations, insertions and deletions. Sanger sequencing was used to validate mutations. When they compared biopsy specimens taken from the kidney they found significant heterogeneity from one region to the next.

Similar degrees of heterogeneity were observed when they compared these primary lesions with the metastatic sites of spread. The investigators inferred a branched evolution where tumors evolved into clones, some spreading to distant sites, while others manifested different features within the primary tumor themselves. Interestingly, when primary sites were matched with metastases that arose from that site, there was greater consanguinity between the primary and met than between one primary site and another primary site in the same kidney. Another way of looking at this is that your grandchildren look more like you, than your neighbor.

Tracking additional mutations, these investigators found unexpected changes that involved histone methyltransferase, histone d-methyltransferase and the phosphatase and tensin homolog (PTEN). These findings were perhaps among the most interesting of the entire paper for they support the principal of phenotypic convergence, whereby similar genomic changes arise by Darwinian selection. This, despite the observed phenotypes arising from precursors with different genomic heritages. This fundamental observation suggests that cancers do not arise from genetic mutation, but instead select advantageous mutations for their survival and success.

The accompanying editorial by Dr. Dan Longo makes several points worth noting. First he states that “DNA is not the whole story.” This should be familiar to those who follow my blogs, as I have said the same on many occasions. In his discussion, Dr Longo then references Albert Einstein, who said “Things should be made as simple as possible, but not simpler.” Touché.

I appreciate and applaud Dr. Longo’s comments for they echo our sentiments completely. This article is only the most recent example of a growing litany of observations that call into question molecular biologist’s preternatural fixation on genomic analyses. Human biology is not simple and malignantly transformed cells more complex still. Investigators who insist upon using genomic platforms to force disorderly cells into artificially ordered sub-categories, have once again been forced to admit that these oversimplifications fail to provide the needed insights for the advancement of cancer therapeutics. Those laboratories and corporations that offer “high price” genomic analyses for the selection of chemotherapy drugs should read this and related articles carefully as these reports portend a troubling future for their current business model.

All laboratory platforms are subject to “sampling errors”. That is, the tissue procured may not be reflective of the overall biology of the disease. This however is compounded by laboratory platforms that use FNA’s to measure genes or other “analytes” that are not functional parameters of the disease process, in all its complexity. These are instead mere reflections of the disease process, as it were, a veneer of information gleaned from the most superficial surface.

To address smapling errors, we prefer large specimens which are assessed in their native state, not propagated or sub=cultured (thereby avoiding addtional artifacts). These are preferably obtained from metastatic sites, which often reflect greater degeees of resistance over the tumor primaries, giving us the best “shot” at both. We know from extensive clinical experience that many (most) patients that have responses to systemic therapy, have overall improvement with only a minority having true “mixed” responses. We also know that the tumors and their metastatic lesions share biologic similarities that provide useful insights into the tumor’s relative sensitivity to drugs. Even still, the subsequent re-growth of tumors, may reflect clonal expansion resulting from the elimination of the more sensitive tumors and emergence of a new dominant clone. To address this, we will often re-biopsy and re-dedicate our efforts to controlling the second or subsequent clones.

All of these theoretical issues are hurdles to be overcome. They contribute to the fact that, although our lab analyses consistently double objective response rates, they are not perfect predictors. It is extremely important to remember that all the medical oncologists in practice today confront all of these same issues (heterogeneity, clonal divergence, differeing biology from primary to met, etc) yet they select drugs and combinations with absolutely no guidance whatsover!

[url]http://robertanagourney.wordpress.com/2012/03/12/the-unfulfilled-promise-of-genomic-analysis/#respond
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Old 03-15-2012, 01:50 AM
gdpawel gdpawel is offline
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Default Intratumor Heterogeneity and Branched Evolution

This "intratumor heterogeneity" issue is not a new revelation to cell function analysis. As you can see, searching for these genetic predispositions, it is like searching for a needle in a haystack. 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.

Testing of one sample of the tumor may well not render an accurate environment, unless you are recognizing the interplay between cells, stroma, vascular elements, cytokines, macrophages, lymphocytes and other environmental factors. The human tumor primary culture microspheroid contains all of these elements. Studying cancer response to drugs within this microenvironment would provide clinically relevant predictions to cancer patients. It is the capacity to study human tumor microenvironments that distinguishes it from other platforms in the field.

They have observed some degree of "genetic drift" where mets tend to be somewhat more resistant to drugs than primaries. Over the years, they have often encouraged physicians to provide nodal, pleural or distant site biopsies to give the "best shot" at the "most defended" of the tumor elements when metastatic disease is found.

The tumor of origin (as in the NEJM study as well) and the associated mets tend to retain consanguinity. That is, the carcinogenic processes that underlie the two populations are related. This is the reason they do not see "mixed responses" (one place in the body getting better and another place in the body getting worse), but instead, generally see response or non-responses.

Heterogeneity likely underlies the recurrences that are seen in almost all patients. This is why they try to re-biopsy and re-evaluate when recurrences are observed. Heterogeneity remains a theoretical issue no matter what platform one uses. Why complicate this fact by using a less biologically relevant method like genomics that only scratches the surface of the tumor biology?

Human beings are demonstrably more than the sum of their genes. Cancer biology and the study of cancer therapy are many things, but simple is not one of them. Complex problems require solutions that incorporate all of their complexities, however uncomfortable this may be for genomic investigators.

Contrary to analyte-based genomic and proteomic methodologies that yield static measures of gene or protein expression, functional profiling provides a window on the complexity of cellular biology in real-time, gauging tumor cell response to chemotherapies in a laboratory platform.

By examining drug induced cell death, functional analyses measure the cumulative result of all of a cell's mechanisms of resistance and response acting in concert. Thus, functional profiling most closely approximates the cancer phenotype.

Insights gained can determine which drugs, signal transduction inhibitors, or growth factor inhibitors induce programmed cell death in individual patients' tumors. Functional profiling is the most clinically validated technique available today to predict patient response to drugs and targeted agents.

Epigentics may have important implications for the treatment of cancer. The cell-based functional profiling platform has the capacity to measure genetic and epigenetic events as a functional, real-time adjunct to static genomic and proteomic platforms.

By examining small clusters of cancer cells (microspheroids or microclusters) in their native state, it can provide a snapshot of the response of tumor cells to drugs, combinations and targeted therapies.

The proteomic platform does not clarify how the response to targeted drugs compares with that to chemotherapy, combinations, or other targeted therapies. There is a challenge to identify which patients the targeted treatment will be effective.

The analysis is unique in that each microspheroid examined contains all the complex elements of tumor biosystems found in the human body and have a major impact on clinical response. Cell function analysis is a conduit that connects novel drugs to clinicians and patients in need.

Clinical application of functional profiling in advanced NSCLC and colorectal cancers ASCO Meeting Abstracts 26: 13547 R. A. Nagourney, J. Blitzer, D. McConnell, R. Shuman, S. Grant, K. Azaren, I. Shbeeb, T. Ascuito, B. Sommers, and M. Paulsen

Functional profiling in stage IV colorectal cancer: A phase II trial of individualized therapy ASCO Meeting Abstracts 27: e15124. J. B. Blitzer, I. Shbeeb, A. Neoman, K. Azaren, M. Paulsen, S. Evans, and R. Nagourney

Functional profiling in stage IV NSCLC: A phase II trial of individualized therapy ASCO Meeting Abstracts 27: e19079. R. A. Nagourney, J. Blitzer, E. Deo, R. Nandan, R. Schuman, T. Asciuto, D. Mc Connell, M. Paulsen, and S. Evans
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Old 03-15-2012, 01:51 AM
gdpawel gdpawel is offline
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Default Personalized Approach to Cancer Care

There are many challenges in personalized cancer medicine. It means being able to take the tumor specimen at the time of diagnosis, and perform a series of assays that provides the clinician with a definable list of prognostic markers and therapeutic targets.

The British study used various methods: immunohistochemical (IHC) analysis, mutation functional analysis (that is not cell function analysis) and profiling of mRNA expression. Looking for genetic predispositions is like searching for a needle in a haystack. Or you can look for drugs that are sensitive to killing cancer cells.

Theoretical analysis is based on population research. They base their predictions on the fact that a higher percentage of patients with similar genetic profiles or specific mutations may tend to respond better to certain drugs. This is really a refinement of statistical data.

The British study used "target" assays; does the cell express a particular target that a drug is supposed to be attacking. The particular sequence of DNA that an organism possesses (genotype) does not determine what bodily or behaviorial form (phenotype) the organism will finally display.

Testing of one sample of the tumor may well not render an accurate environment, unless you are recognizing the interplay between cells, stroma, vascular elements, cytokines, macrophages, lymphocytes and other environmental factors. The human tumor primary culture microspheroid contains all of these elements.

Studying cancer response to drugs within this microenvironment would provide clinically relevant predictions to cancer patients. It is the capacity to study human tumor microenvironments that distinguishes it from other platforms in the field.

The vision is that modern sequencing technology, proteomic technology, has the ability to determine all of the oncogenic vulnerabilities, or all the genes and pathways that are driving the tumor, identify those in a single or a limited number of assays, and provide an interpretable and actionable list of variables for the clinician.

However, one of challenges is that many in the field felt that the ability to read out every single base in our 3 billion-based comparison, to do a complete sequencing of a cancer genome would be the test that would need to be done, or that should be done, to provide all of the answers.

What has been learned is that that is naïve and not true. The idea that sequencing a cancer genome alone will provide enough information for the clinician is clearly misguided and not sufficient.

Those in the basic science field need to integrate that sort of information with other information, such as gene expression, protein analyses, functional profiling and other types of analyses. It is going to be a bit more complicated than many were hoping.
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Old 03-24-2012, 04:11 PM
gdpawel gdpawel is offline
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Default Cancer is Heterogeneous

All cancers, in general, are heterogeneous. That is why the use of human tumor primary culture analyses (functional profiling) are so instructive and should be incorporated into clinical trials for targeted agents.

The mindset of medicine is to think it's great science to identify the best treatment to give to the average patient is through prospective, randomized trials. We have produced an entire generation of investigators in clinical oncology who believe that the only valid form of clinical research is to perfrom well-designed, prospective randomized trials in which patients are randomized to receive one empiric drug combination versus another empiric drug combination. Do cancer cells like Coke or Pepsi.

All the rigorous clinical trials identified are the best treatments for the average patient. But cancer is not an average disease. Cancer is far more heterogeneous in response to various individual drugs than are bacterial infections. The tumors of different patients have different responses to chemotherapy. It requires individualized treatment based on testing the individual properties of each patient's cancer.

There are hundreds of different therapeutic drug regimens which any one or in combination can help cancer patients. The system is overloaded with drugs and underloaded with wisdom and expertise for using them. We are getting an expanding list of treatments which are partially effective in a minority of patients, ineffective in a majority, remarkably effective in a few, while being enormously expensive. The fastest way to improve things is to match treatment to the patient.

One of the main problems in providing effective chemotherapy is the situation that every patient is unique. Tumors grow and spread in different ways and their response to treatment depends on these characteristics. The amount of chemotherapy that each patient can tolerate varies considerably from patient to patient. Therapeutic protocols currently in use are limited in their effectiveness because they are based on the results of clinical trials conducted on a general patient population, yet no two patients are alike.

Clinical trials test the efficacy, not the accuracy of a drug. Efficacy means producing a desired effect, like tumor shrinkage. Single arm clinical trials provide the tumor response evidence that is the basis for approving new cancer drugs. Metastasis is an organism-wide phenomenon that may involve dozens of processes. It's hard to do replicable experiements when there are so many variables. So, instead, researchers opt for more straightforward experiments that generate plenty of reproducible results (like tumor shrinkage).

Tumor shrinkage should not be the criteria for approving cancer drugs. A patient responds to therapy when their tumor shrinks, but apparently this has nothing to do with survival. A tumor responds, that is, shrinks a little, then quickly grows and spreads. The cancer comes back with a vengeance and the cancer patient is given a death sentence.

There are tens of thousands of scientists pushing a goal of finding the tiniest improvements in treatment rather than genuine breakthroughs, that fosters redundant problems and rewards academic achievement and publication above all else. The randomized, controlled clinical trial may likely remain the standard for evidence of clinical decision-making in cancer medicine, however, systems biology is clearly useful. Even with the importance of clinical trials, it is crucial to work on reducing their inherent limitations, including uncertain generalizations, and to expand the use of the randomized clinical trial paradigm to areas beyond proving biological activity, like diagnostic testing.

As the number of possible treatment options supported by completed randomized clinical trials increases, the scientific literature becomes increasingly vague for guiding physicians. Almost any combination therapy is acceptable in the treatment of cancer these days. Physicians are confronted on nearly a daily basis by decisions that have not been addressed by randomized clinical trial evaluation. Their decisions are made according to experience, new basic science insights, bias or personal preference, philosophical beliefs, etc.

Crucial breakthroughs in the treatment of cancer could be achieved by harnessing systems biology. One of the hallmarks of cancer is the complex interaction of genes, networks and cells in order to initiate and maintain a cancerous state. This inherent complexity constantly challenges our ability to develop effective and specific treatments. A systems biology approach towards the understanding and treatment of cancer examines the many components of the disease simultaneously.

Systems Biology in Cancer Drug Selection: [url]http://cancerfocus.org/forum/showthread.php?t=3473
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Old 03-29-2012, 12:57 PM
gdpawel gdpawel is offline
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Default Personalized cancer treatment has a long way to go

Herman Kattlove, M.D.

Retired medical oncologist. For the last seven years before his retirement, he was a medical editor for the American Cancer Society where he helped develop much of the information about specific cancers that is posted on the website at [url]www.cancer.org

A few months ago I wrote about a new treatment for widespread melanoma that targeted a particular molecule that controlled that cancer’s growth. Shortly afterward, someone I know found out that the melanoma he thought he was cured of 20 years ago, had now come back in his liver as well as other places in his body.

It turned out that the melanoma had a genetic alteration that made it sensitive to this new treatment. He was started on the drug (don’t ask how much it costs) and saw his tumors shrink. He also started feeling better. Unfortunately, all this lasted just a few months. Soon the tumor was growing rapidly and he quickly succumbed.

What went wrong? The answer is something the experts call “genetic heterogeneity”. When his melanoma was biopsied, only a small bit was examined and that small bit turned up the mutation that could have been causing the tumor to grow. But there were also mutations that went undiscovered because the doctors were looking for just this one.

The bad news is that cancers survive and grow because they contain many mutations. Many of these can also cause the cancers to grow and spread apart from the ones that we can see in a small biopsy. Recently, investigators from Great Britain published an article in the New England Journal of Medicine (March 8, 2012) that showed that these cancers have many more mutations than can be assessed in a small biopsy specimen. They studied four patients who had biopsies to establish a diagnosis of kidney cancer. The patients eventually had their kidneys removed. The investigators examined different areas of the kidney tumor, looking for mutations. They also looked at specimens taken from metastases that had also been removed.

To no one’s surprise all these sites contained many different mutations than were seen in the original biopsy specimen. In an earlier article the main investigator likened this to Darwinian evolution. Just as new mutations can confer a survival advantage on different species, these mutations in the tumors allow them to survive and grow, even if drugs had suppressed one or more of the mutations – just like in my friend with melanoma.

A lot has been made of “targeted therapy” for cancer. But most of these new drugs work for just a short time. Patients may get a few extra months on average. Still, drug companies are putting a lot of time and money into developing these kinds of treatments for cancer. They seem to be very profitable and since most of the drug companies older “blockbuster” drugs have become generic, they see this as a major source of new income. My friend’s treatment cost $10,000 a month.

As I think about all this, it seems to me that all the money spent on these drugs by pharmaceutical manufacturers and patients must have a better use in bettering health than giving people a very few extra months of life.

[url]http://kattlovecancerblog.blogspot.com/2012/03/personalized-cancer-treatment-has-long.html
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Old 04-03-2012, 05:43 PM
gdpawel gdpawel is offline
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Default Gene Sequencing: Not Ready for Prime Time

Medscape Oncology

April 3, 2012 (Chicago, Illinois) — When it comes to predicting the risk for common diseases, including cancer, genome sequencing is not a magic bullet. It might be a valuable tool for people with a strong family history of a disease, but not for the vast majority of people, researchers report.

Genomic sequencing will never be a crystal ball that can reliably predict future health issues, explained researcher Bert Vogelstein, MD, Clayton Professor of Oncology and Pathology at the Johns Hopkins Kimmel Cancer Center in Baltimore, Maryland.

"It cannot substitute for conventional risk-management strategies, including routine check-ups and lifestyle optimization," he said at a press briefing here at the American Association for Cancer Research 103rd Annual Meeting.

Dr. Vogelstein was summarizing the results of a study presented at the meeting and simultaneously published online April 2 in Science Translational Medicine.

The researchers analyzed data collected from thousands of twin-pair groups on the incidence of 24 diseases, including cancer and autoimmune, cardiovascular, genitourinary, neurologic, and obesity-associated conditions. They used mathematical models to predict disease risk.

For the majority of tested individuals, the results would be negative for most diseases. In addition, the predictive value of these negative tests would generally be quite modest, because "the total risk for acquiring the disease in an individual testing negative would be similar to that of the general population," according to the researchers.

Conversely, in the best-case scenario, the results show that the majority of people tested might be alerted to a clinically meaningful risk for at least 1 disease with whole-genome sequencing.

"We stand on the verge of a revolution, and advances in technology and sequencing that have immense implications for many fields of science," said Dr. Vogelstein. "But, as we all know from the recent revolutions in the Middle East, we can't always predict the final outcomes of revolutions."

He added that in genetics, and specifically in personalized medicine, many of the predictions have been based on qualitative arguments and anecdotal reports.

Positive and Negative Tests

A positive test result should indicate that a person has at least a 10% risk for disease. "That means 1 in 10 would develop the disease from all factors combined," he explained.

The usefulness of a negative test result "is in the eye of the beholder," Dr. Vogelstein noted. To be medically useful, the risk would have to be much lower than in the general population.

As an example, Dr. Vogelstein explained that 2% of those taking the test would get positive results for ovarian cancer. "That is 1 in 50 women, and that is the maximum — the best-case scenario," he said. "That can be useful for those women so they can have closer surveillance."

On the flipside, the other 98% of women would get a negative test. "Unfortunately, the negative test is not that informative because it only shows that they have a risk that is slightly lower than the general population," Dr. Vogelstein said.

These results were similar for the other diseases that the researchers looked at, although there were a few "outliers," Dr. Vogelstein explained. "In theory, with coronary heart disease — at least in males — it might be possible that many individuals in the population would have a positive test; this might put them on the alert for heart disease."

Cancer risk is influenced by both environmental and stochastic factors, which further dilutes the ability of whole-genome sequencing to predict disease risk.

To illustrate the limits of genetic testing, Dr. Vogelstein noted that currently, men have a 45% lifetime risk for cancer and women have a 38% lifetime risk. Having a negative test result would lower the risk to 32% to 42% in men and 27% to 36% in women, which is only a slight difference from that of the general population.

Dr. Vogelstein emphasized that information about the genome will not change these estimates, which "are made under the assumption that we are omniscient and understand the effects of every variant and their interactions with one another."

Benefit Seen for Some Conditions

Dr. Vogelstein and his team derived their estimates from 53,666 monozygotic twin pairs and clinical data from registries all over the world. Their analyses suggest that for 23 of the 24 diseases studied, the majority of individuals will receive negative test results, which will probably not be very informative.

With a negative test result, they estimate that the risk of developing 19 of the 24 diseases would be 50% to 80% of that in the general population, at a minimum.

For 13 of 27 disease categories, the researchers note that the majority of patients who would ultimately develop these diseases would not test positive, even in the best-case scenario. For 4 of the disease categories — thyroid autoimmunity, type 1 diabetes, Alzheimer's disease, and coronary heart disease deaths in men — genetic testing might be able to identify more than three quarters of people who subsequently will develop the disease.

Not Ready for Prime Time

A panel of discussants agreed with Dr. Vogelstein's conclusions and pointed out the implications of the study.

Timothy Rebbeck, PhD, professor of epidemiology at the University of Pennsylvania Perelman School of Medicine in Philadelphia, and editor-in-chief of Cancer Epidemiology, Biomarkers & Prevention, noted that "we are going to have to reconsider the value of genetic information and rethink new models and when this information is valuable and when it may not be."

He added that "what we are learning" from this study and previous research is that genetics might not be "the magic cure-all" for all things.

Thomas Sellers, PhD, MPH, executive vice president and director at the H. Lee Moffitt Cancer Center & Research Institute in Tampa, Florida, agreed "with the primary conclusion of this report," adding that this is a very "provocative" study that puts very important issues into perspective.

"Genome sequencing is not going away; there are questions that we have to look at," he said.

The third discussant, Olufunmilayo I. Olopade, MD, professor of medicine and human genetics and director of the cancer risk clinic at the University of Chicago School of Medicine in Illinois, pointed out how many researchers said the same thing about BRCA testing.

"I remember the argument we had almost 20 years ago about BRCA testing," she said. "Some thought nothing good could come out of that research..., now it has been adopted," Dr. Olopade said. "Many women died from ovarian cancer, and we could have prevented it if we had known."

She emphasized that "we are now just beginning our understanding," and that to have an impact on prevention, "we need to have a more elaborate approach."

"I think that genome sequencing can improve public health, but we need to know how we are we going to do it," she said. "We are not there yet, it's not ready for prime time.

American Association for Cancer Research (AACR) 103rd Annual Meeting. Presented April 2, 2012.

Sci Transl Med. Published online April 2, 2012.

[url]http://stm.sciencemag.org/content/early/2012/04/02/scitranslmed.3003380
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Old 04-09-2012, 07:05 PM
gdpawel gdpawel is offline
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Default Laying The Foundation For Personalized Cancer Treatment Using DNA Sequencing?

A presentation at the American Association for Cancer Research meeting held in Chicago March 31 – April 4, 2012, one of the presenters at the melanoma session described whole genome sequencing on 24 human melanomas.

To their chagrin they found 24 completely different genomes. From the macroscopic to the most microscopic (single gene analysis) mankind in general and his tumors in particular, distinguish themselves for their unique attributes.

The assumption behind all these recent efforts has been the gene mutation theory of cancer. Mutated genes somehow either cause cancer directly or inactivate genes though to guard against cancer, the so-called oncogenes and tumor suppressor genes.

However, there is no functional proof that the gene mutation theory is correct. Only 1 to 2 percent of the genome consists of genes. DNA is not the whole story.

Cells speak to each other and the messages they send are interpreted via intracellular pathways. You wouldn't know this using genotype analysis. Phenotype analysis provides the window. It can test various cell-death signaling pathways downstream.

While most scientists use genotype platforms to detect mutations in these pathways that might result in response to chemicals, phenotype platforms have taken a different tack. By applying cell functional analysis, to measure the end result of pathway activation or deactivation, it can predict whether patients will "actually" respond, not theoretical susceptibility.

Even if cancers are from the same tissue, and are generated with the same carcinogen, they are never the same. There is always a cytogenetic and a biochemical individuality in every cancer.

The phenotype platform has the capacity to measure genetic and epigenetic events as a functional, real-time adjunct to static genotype platforms. The "key" to understanding the genome is understanding how cells work. The ultimate "driver" is functional profiling.
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Old 04-30-2012, 07:07 PM
gdpawel gdpawel is offline
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Default The Frustrating Reality - When a Tumor Sample isn't Sufficient for Testing

Dr. Robert Nagourney
Medical and Laboratory Director
Rational Therapeutics, Inc.
Long Beach, California

The principles underlying the Rational Therapeutics functional profiling platform reflect many years of development. Recognizing the importance of cell death measures — apoptotic and non-apoptotic — our laboratory dismissed growth-based assays. The closure of Oncotech, the principal purveyor of proliferation-based assays, illustrates the demise of a failed paradigm in the study and testing of human tumor biology. A second principal of our work is the need to examine all of the operative mechanisms of cell death (autophagic, necrotic, etc.). Laboratories that measure only one mechanism of cell death (e.g. caspase activation as a measure of apoptosis) miss important cell responses that are critical to the accurate prediction of clinical response. The third principle of our work is the maintenance of cells in their native state.

These fundamentals provide the basis of our many successes, but also a constraint. Because we do not propagate, subculture or expand tissues, we can only work with the amounts of tissue provided to us by our surgeons. While some labs propagate small biopsy samples into larger populations by growth to confluence, this introduces irreconcilable artifacts, which diminish the quality of sensitivity profiles. Avoiding this pitfall, however, demands that a tissue sample be large enough (typically 1cm) to provide an adequate number of cells for study without growth or propagation.

This is the reason our laboratory must request biopsies of adequate size. The old computer dictum of “garbage in, garbage out” is doubly true for small tissue samples. Those that contain too few tumor cells, are contaminated, fibrotic or inadequately processed will not serve the patients who are so desperately in need of therapy selection guidance. As a medical oncologist, I am deeply disappointed by every failed assay and I am more familiar than most with the implications of a patient requiring treatment predicated on little more than intuition or randomization.

We do everything within our power to provide results to our patients. This sometimes requires low yield samples be repeatedly processed. It may also set limitations on the size of the study or, in some circumstances, forces us to report a “no go” (characterized as an assay with insufficient cells or insufficient viability). Of course, it goes without saying that we would never charge a patient for a “no-go” assay beyond a minimal set up fee (if applicable). But, more to the point, we suffer the loss of an opportunity to aid a patient in need.

Cancer patients never undergo therapy without a tissue biopsy. Many have large-volume disease at presentation, so it is virtually always possible to obtain tissue for study if a dedicated team of physicians makes the effort to get it processed and submitted to our laboratory. The time and energy required to conduct an excisional biopsy pales in comparison to the time, energy and lost opportunities associated with months of ineffective, toxic therapy.
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