Intratumor Heterogeneity and Branched Evolution

[gpawelski]

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

http://www.nejm.org/doi/full/10.1056/NEJMoa1113205

[gpawelski]

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

[gpawelski]

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!

“In the land of the blind, the one eyed-man is king.”

[gpawelski]

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

[gpawelski]

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.

[gpawelski]

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.

World renowned Oncologists are challenging the cancer industry to recognize a Chemo-Screening test (CSRA) that takes the "guesswork" out of drug selection. One of the reasons medical oncologists dont like in vitro chemosensitivity tests is that it may be in direct competition with the randomized controlled clinical trial paradigm.

http://vimeo.com/72389724

[gpawelski]

EGFR Mutation Heterogeneity and the Mixed Response to EGFR Tyrosine Kinase Inhibitors of Lung Adenocarcinomas

Zhi-Yong Chena, Wen-Zhao Zhonga, Xu-Chao Zhanga, Jian Sua, Xue-Ning Yanga, Zhi-Hong Chena, Jin-Ji Yanga, Qing Zhoua, Hong-Hong Yana, She-Juan Ana, Hua-Jun Chena, Ben-Yuan Jianga, Tony S. Mokb and Yi-Long Wua

a. Guangdong Lung Cancer Institute, Guangdong General Hospital, and Guangdong Academy of Medical Sciences, Guangzhou, China;

b. State Key Laboratory of Southern China, The Chinese University of Hong Kong, Sir YK Pau Cancer Center, Prince of Wales Hospital, Hong Kong, China

Correspondence:

Yi-Long Wu, M.D., Guangdong Lung Cancer Institute, Guangdong General Hospital and Guangdong Academy of Medical Sciences, Guangzhou, China. e-mail: syylwu@live.cn

Tony S. Mok, M.D., State Key Laboratory of Southern China, The Chinese University of Hong Kong, Sir YK Pau Cancer Center, Prince of Wales Hospital, Hong Kong, China. e-mail: tony@clo.cuhk.edu.hk

THE ONCOLOGIST Express on June 6, 2012.

Disclosures: Tony S. Mok: AstraZeneca, Roche, Eli Lilly, Merck Serono, AVEO, Pfizer, BI (C/A, H). The other authors indicated no financial relationships.

Abstract

Background:

Non-small cell lung cancer patients with epidermal growth factor receptor (EGFR) mutations have mixed responses to tyrosine kinase inhibitors (TKIs). Intertumor heterogeneity in EGFR mutations is one potential explanation for this phenomenon.

Methods:

We performed direct sequencing to identify EGFR mutations in 180 pairs of lung adenocarcinoma samples (from 3,071 patients). The high-resolution melting method was used in discordant cases to confirm EGFR mutation status. Matching samples were divided into four groups: primary lesions detected at different times, primary tumors with matched metastatic lymph nodes, multiple pulmonary nodules, and primary tumors with matched distant metastases. Multivariate analyses were performed to evaluate correlations between heterogeneity and patient characteristics.

Results:

In the study population, the discordance rate was 13.9% (25 of 180). The multiple pulmonary nodules group had the highest discordance rate of 24.4% (10 of 41; odds ratio for heterogeneity in primary lesions detected at different times, 6.37; 95% confidence interval, 1.71–23.72; p = .006). Discordance rates in the metachronous and synchronous settings were 15.7% (22 of 140) and 7.5% (three of 40), respectively. In the 34 patients who developed EGFR TKI resistance, 10 (29.4%) cases exhibited heterogeneity and five (14.7%) patients exhibited a mixed response to the drug. Three (8.8%) of the patients with a mixed response also exhibited discordant EGFR mutations.

Conclusions:

The overall discordance rate of EGFR mutation heterogeneity in Asian patients with pulmonary adenocarcinoma is relatively low, but the rate in patients with multiple pulmonary nodules is significantly higher. This observation may explain the mixed tumor response to EGFR TKIs.

http://theoncologist.alphamedpress.org/ ... 7/978.full

[gpawelski]

The phenomenon of “mixed responses” is certainly a recognized clinical occurrence. Most patients have responses that are reflected in most areas of the disease. That is, "mixed responses" are somewhat less common.

Clearly, some tumors progress in what would be described as a clonal evolution. The initiating clone, over time, may acquire new features, some of which could conceivably result in drug resistance.

While some clonal variation could be anticipated, it cannot possibly be better to "guess" what drug might work as opposed to getting a reasonable approximation of the tumor biology by sampling a portion of the disease.

Testing 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 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.

Some references to work on the type of functional profiling platform:

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

It's a theoretical but overrated problem. The same problem applies to ER, Her2, EGFR mutations, KRAS, OncotypeDx. Even worse for trying to do studies on individual cells, e.g. as from circulating tumor cells. Less of a problem for cell function analysis, since they are sampling a much bigger mass of cells and are homogenizing the mass (actually homogenizing the distribution of microclusters).

It's analogous to the Gallup poll. You are projecting the behavior of a national electorate, based on a sample of 1,500 voters, who may or may not be representative of the whole. Rasmussen and Gallup have the same sized sample, but select different people for their polling ("likely voters" vs "all voters"), so their projections often disagree.

It is one of the reasons why (1) "resistance" predictions tend to be more accurate than "sensitive" predictions (if the cancer is resistant anywhere, it pretty much doesn't matter), if you use the "resistant" drug, the patient will have progressive disease and (2) the tests are more analogous to using the barometric pressure to predict for rain than they are analogous to a serum sodium level; i.e. the predictions are useful (assay "sensitive" drugs being seven times more likely to work than assay "resistant" drugs), but they aren't perfect (i.e. 100%), no diagnostic test in medicine is.

[gpawelski]

The problem with all of this is that gene and protein testing (genotype analysis) are indirect approaches to "chemotherapy selection" which examine a single process within the cell or a relatively small number of processes. The aim is to determine only if there is evidence of a theoretical predisposition to drug susceptibility. In this regard, genomic testing is a "static profiling" approach.

In contrast, a "functional profiling" approach (phenotype analysis) involves real-time assessment of living cancer and endothelial cell behaviors in the presence or absence of anti-cancer or anti-angiogenic drugs. This method accounts not only for the existence of genes and proteins but also for their functionality and for their interaction with other genes, other proteins, and other processes occurring within the cell.

What is an excellent feature of this protocol for cancer patients is "real-time" reporting of patient outcomes by the patients' doctors as they become available. This is in sharp contrast to a traditional clinical trial, where outcomes take years to accumulate in large cancer trials.

This represents a potential landmark change in approach to personalized cancer treatment. The kind which has the potential to change the tide of cancer treatment. One which being the ability to direct cancer treatments to personal tumors rather than groups of patients' tumors. This has the potential to bring about "cutting edge" personalized cancer treatment proposals.

If by picture you mean an "updated" one, yes, someone had told me the other picture was eerily similar to another person's picture on the board. Time to change it. That other picture was from when I started to get involved with this cancer research stuff, 17 years ago. I've aged a little!