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Old 09-04-2011, 11:20 PM
gdpawel gdpawel is offline
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Default Personalized Cancer Cytometrics More Accurate than Molecular Gene Testing

Personalized Cancer Cytometrics More Accurate than Molecular Gene Testing

Clinical Trial Finds Personalized Cancer Cytometrics More Accurate than Molecular Gene Testing

In the first head-to-head clinical trial comparing gene expression patterns with Personalized Cancer Cytometric testing (also known as “functional tumor cell profiling” or “chemosensitivity testing”), Personalized Cancer Cytometrics was found to be substantially more accurate.

In a clinical trial involving ovarian cancer patients, patterns of gene expression identified through molecular gene testing were compared with results of Personalized Cancer Cytometric testing (in which whole, living cancer cells are exposed to candidate chemotherapyterm drugs). Four different genes were included in the molecular part of the study. The four genes were selected as those which researchers believe to have the greatest likelihood of accurately predicting individual patient response to specific anti-cancer drugs.

Study Results:

For two of the genes studied, there was no significant correlation between gene expression pattern and patient response. In other words, results for these genes were found to be meaningless. For the third gene studied, there was a 75% correlation between expression and patient response. This means that the gene was 75% accurate when it came to identifying an active drug for that patient. For the fourth gene studied, the accuracy in identifying an active drug was only 25%. In marked contrast, Personalized Cancer Cytometric testing was found by the researchers to be 90% accurate in identifying active drugs for ovarian cancer patients in this study.

Discussion:

Molecular testing – that is, testing for gene expression patterns – is widely studied and heavily promoted as a method to identify effective chemotherapy drugs for individual cancer patients. However, most studies of molecular testing carried-out to date show only modest correlation or no correlation between test results and actual patient response. In other words, much work remains to be done before molecular gene testing can be regarded as an accurate tool for chemotherapy selection. And yet in this, first ever, head-to-head study of test accuracy, Personalized Cancer Cytometrics was found to be highly accurate when it came to identifying effective drugs.

Comparing this study with previous studies:

Although this was the first head-to-head trial, the accuracy levels found in this trial for Personalized Cancer Cytometric testing are strikingly consistent with those documented in dozens of previous studies, published by respected cancer researchers around the world. In those studies, as in this one, extremely high levels of correlation (in other words, high levels of test accuracy) were found for Personalized Cancer Cytometrics.

Arienti et al. Peritoneal carcinomatosis from ovarian cancer: chemosensitivity test and tissue markers as predictors of response to chemotherapy. Journal of Translational Medicine 2011, 9:94.

[url]http://www.translational-medicine.com/content/9/1/94
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Old 09-09-2011, 03:21 PM
gdpawel gdpawel is offline
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Default Chemosensitivity test and tissue markers as predictors of response to chemotherapy

Peritoneal carcinomatosis from ovarian cancer: chemosensitivity test and tissue markers as predictors of response to chemotherapy

Chiara Arienti (1), Anna Tesei (1), Giorgio M Verdecchia (2), Massimo Framarini (2), Salvatore Virzì (3), Antonio Grassi (3), Emanuela Scarpi (1), Livia Turci (1), Rosella Silvestrini (1), Dino Amadori (1) and Wainer Zoli (1)

Author Affiliations

(1) Biosciences Laboratory, Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (I.R.S.T.), Meldola, Italy

(2) Department of Surgery and Advanced Cancer Therapies, Morgagni-Pierantoni Hospital, Forlì, Italy

(3) Department of Surgery, Bentivoglio Hospital, Bologna, Italy

Abstract

Background:

Platinum-based regimens are the treatments of choice in ovarian cancer, which remains the leading cause of death from gynecological malignancies in the Western world. The aim of the present study was to compare the advantages and limits of a conventional chemosensitivity test with those of new biomolecular markers in predicting response to platinum regimens in a series of patients with peritoneal carcinomatosis from ovarian cancer.

Methods:

Fresh surgical biopsy specimens were obtained from 30 patients with primary or recurrent peritoneal carcinomatosis from ovarian cancer. ERCC1, GSTP1, MGMT, XPD, and BRCA1 gene expression levels were determined by Real-Time RT-PCR. An in vitro chemosensitivity test was used to define a sensitivity or resistance profile to the drugs used to treat each patient.

Results:

MGMT and XPD expression was directly and significantly related to resistance to platinum-containing treatment (p = 0.036 and p = 0.043, respectively). Significant predictivity in terms of sensitivity and resistance was observed for MGMT expression (75.0% and 72.5%, respectively; p = 0.03), while high predictivity of resistance (90.9%) but very low predictivity of sensitivity (37.5%) (p = 0.06) were observed for XPD. The best overall and significant predictivity was observed for chemosensitivity test results (85.7% sensitivity and 91.3% resistance; p = 0.0003).

Conclusions:

The in vitro assay showed a consistency with results observed in vivo in 27 out of the 30 patients analyzed. Sensitivity and resistance profiles of different drugs used in vivo would therefore seem to be better defined by the in vitro chemosensitivity test than by expression levels of markers.

Journal of Translational Medicine 2011, 9:94 doi:10.1186/1479-5876-9-94

The different genes that were studied in the molecular part of the above study were ERCC1, GSTP1, MGMT, XPD and BRCA1. These are putative drug resistance genes. ERCC and XPD are response elements for CDDP repair. BRCA1 is also a response element for DNA damage and part of FANC gene family (a genomic fidelity function).

GSTP1 is a detoxifying enzyme associated with thiol conjugation (alkylator resistance) while MGMT is the specific enzyme associated with the removal of temozolomide residues from DNA base pairs.

What the investigators did was to examine the (Caris) "Target Now" types of targets and compare clinical responses against the results with functional analyses, establishing that when one measures the biology of the disease it provides a more robust prediction of response. The "driver" term is less operative as these genes are not causative of the disease but causative of drug resistance.

Caris Lifesciences is a private company which does so-called “molecular” profiling, based on immunohistochemistry, FISH, RT-PCR, and molecular microarrays.
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Last edited by gdpawel : 03-01-2013 at 12:20 PM. Reason: additional info
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Old 09-22-2011, 12:20 AM
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Default Research in Combining Targeted Agents Faces Numerous Challenges

By Margot J. Fromer
ASCO Post
September 1, 2011, Volume 2, Issue 13

If the clinical trials endeavor in oncology is falling short of its goals and if targeted agents have not kept their promise, can a new approach to drug development provide a solution?

Very possibly, said John Hohneker, MD, Chair of the Workshop Planning Committee for the conference, “Facilitating Collaborations to Develop Combination Investigational Cancer Therapies,” held in Washington in mid-June and sponsored by the Institute of Medicine (IOM) National Cancer Policy Forum. He is also Senior Vice President and Global Head of Development, Integrated Hospital Care, Novartis.

Dr. Hohneker said that the purpose of the workshop was to talk about the many barriers to this new approach to cancer treatment. “Combining investigational products early in their development is thought to be a promising strategy, especially when they target multiple pathways (or more than one step in a pathway), thus conferring greater benefit than therapy directed at a single target.”

Unfulfilled Promise

Jane Perlmutter, PhD, founder of the Gemini Group, a consulting company, added, “The problem with the way cancer research is conducted is that the biology of the disease is so complicated that, although technology keeps advancing, personalized medicine is still mostly only a promise.”

Targeted agents for cancer haven’t panned out to the extent hoped. Although a few might work sometimes or for a short time, the effects have not been significant or durable. And many are more toxic than expected. “Their regulation is confusing and/or interpreted too conservatively, and despite the great need, there is limited incentive for pharmaceutical companies to collaborate with each other,” said Dr. Perlmutter.

Advances in genomics and cell biology have paved the way for increasingly sophisticated targeted therapies, but 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.

The traditional path to drug development, even targeted therapy, has been one at a time. Sometimes a new drug is added to a standard regimen and then compared to the standard alone, but regardless of how or with what it is used, it has to work on its own.

Cooperative Development

This system is no longer completely viable in cancer and needs to be modernized. A new approach would provide the flexibility to evaluate combination regimens in a single development program that can screen all tumors for their pathway dependencies, resulting in efficacy based on screening results and experience with patterns of resistance.

However, despite the potential benefits of such a scheme, uncertainty and risk abound. First, it is usually impossible to characterize the effects of the individual components. Second, combinations would probably yield considerably less information about safety and efficacy than would have been available had they been developed individually. Third, patients and physicians must not only be informed of more-than-usual risk, they must be willing to accept it. Fourth, there should be a compelling biologic rationale for their use and substantial reasons why the agents cannot be developed individually.

The Science Is Complex

James Doroshow, MD, Deputy Director for Clinical and Translational Research, NCI, discussed the scientific challenges facing development of combination targeted therapeutics:

The mechanisms of action for a growing number of targeted agents that are available for trials are not completely understood.

Lack of the right assays or imaging tools means inability to assess the target effect of many agents, and assays are not standardized.

Preclinical models to evaluate efficacy, dosing schedule effects, biomarker utility, and toxicity are not available for combination therapies.

Clinical trials methodology remains unclear with regard to numbers of patients, tumor biopsies, relevance of histologic homogeneity, and pharmacokinetic interactions.

Intellectual property and regulatory matters are daunting.

Dr. Doroshow also discussed mechanism of action (or mechanism of resistance) studies in early-phase trials. Problems include the evaluation of actual vs presumed sites of target engagement, evidence to support further development, demonstration of the relationship between dosing schedule and systemic exposure to target effects, and relevance of biomarkers.

“In addition, we need to investigate the molecular effects, toxicology, and other safety signals of combination agents in surrogate tissues,” said Dr. Doroshow. “This is a huge undertaking, and unfortunately it is not necessarily predictive of clinical benefit. That requires larger, later-stage trials.”

Michael T. Barrett, PhD, Associate Professor and Head of the Oncogenomics Laboratory, TGen, added that cancer is extremely genetically unstable, resulting in highly karyotypically and biologically individual malignancies. Thus, each patient’s cancer could require its own specific therapy. Even if this were possible and practical, the treatment could ultimately be thwarted by emergence of a resistant variant genetic subline.

Dr. Barrett also noted that each genome has unique sets of selected aberrations and mutations, of which multiple populations can be present at biopsy. These mutations can be asymmetric; they can progress and metastasize, and thus resist treatment. He warned that application of genomic tools to combination therapy has to be based on unbiased profiling of biopsies, as well as identification of therapeutic vulnerabilities in all patients.

Kurt Bachman, PhD, Head of Translational Medicine and Biology, GlaxoSmithKline, added, “The challenge is to identify the tumor types most likely to respond, to find biomarkers that predict a response, and to define the relationship of the predictors to the biology of the inhibitors.”

Disclosure: Dr. Hohneker is employed by and owns stock in Novartis. Dr. Barrett has a current research contract with AstraZeneca. Dr. Bachman is employed by GlaxoSmithKline. Dr. Perlmutter reported no potential conflicts of interest. Dr. Doroshow reported no potential conflicts of interest.
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  #4  
Old 09-26-2011, 01:29 AM
gdpawel gdpawel is offline
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Default Targeted Therapies for Cancer Confronts Hurdles

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. One of those clinicians, Dr. Robert Nagourney felt that there had been an epiphany.

The complexities and redundancies of human tumor biology had finally dawned on these investigators, who had previously clung unwaiveringly to their analyte-based molecular platforms.

The molecular biologists humbled by the manifest complexity of human tumor biology had finally recognized that they were outgunned and whole-cell experimental models had gained the hegemony they so rightly deserved.

Source: Dr. Robert A. Nagourney, medical director, Rational Therapeutics and instructor in Pharmacology at the University of California, Irvine School of Medicine.
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Last edited by gdpawel : 10-05-2011 at 09:43 AM. Reason: additional info
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Old 10-05-2011, 09:51 AM
gdpawel gdpawel is offline
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Default Genetic variations alone do not determine response to chemotherapy

Dr. R. Stephanie Huang
University of Chicago Department of Medicine

As a pharmacist, Dr. R. Stephanie Huang’s main concern is how drugs affect patients. Currently, Dr. Huang is exploring how genetics determine why some people respond to certain types of chemotherapy while others do not. For example, one-quarter of women with ovarian cancer develop a platinum resistant cancer. The reason that some people, or some tumors, are resistant to platinum therapies may have its roots in genetics. This area of personalized medicine is expanding as genetic sequencing technology becomes faster and cheaper.

When studying the effect of genetics on anti-cancer treatments, two types of genetic variations need to be considered. The first, germline variations, encompass a person’s genetic code including any heritable mutations. The second, somatic variations, are mutations that are not heritable, such as genetic changes caused by exposure to chemicals. Dr. Huang’s research is focusing on the germline genetic variations, since these may predispose an individual to various treatment-related toxicities. Furthermore, since all cancer cells derive from normal cells, certain germline variations could be linked to both the likelihood of developing ovarian cancer and response to treatments.

“One challenge is to differentiate between what we know and what we can do about it. I’m working to make genetics useful in terms of making fully informed decision about what works for each patient,” says Dr. Huang.

Dr. Huang recently published a paper looking for differences among individuals in their normal DNA code, known as germline genetic variations, that predicted platinum sensitivity in women with ovarian cancer. To do this, she utilized hundreds of cell lines (specific cells bred in a laboratory and able to duplicate indefinitely so that they can be used for research purposes) evaluated by the International HapMap Consortium. This international collaboration is aimed at obtaining all common genetic variations in the world’s human populations and making them publicly available for research. Each of the cell lines is derived from an individual’s blood; information about their ethnicity is captured as well.

The cell lines were treated in her lab with various chemotherapeutic agents to determine each individual’s sensitivity to drugs. Dr. Huang then did genetic analyses between each person’s genomic code and his or her sensitivity to the drug. Her goal was to identify germline genetic variations that could be used to predict chemotherapy response. These cell-based findings were then evaluated in 400 women with ovarian cancer who had undergone the related drug treatment. She found that there may be some genetic variations that affect overall survival, progression free survival or response to chemotherapy. Unfortunately, the data was not able to be validated in a larger scale analysis, but leaves the door open for continued research.

The Huang lab is also examining the differences in germline variations and somatic mutations to see which of those are cancer-related. To do so, Dr. Huang and her collaborators are utilizing data from the Cancer Genome Atlas (TCGA).

TCGA is a multi-year, multi-cancer study funded by the National Cancer Institute to understand the genetics of certain cancers, including ovarian. Preliminary ovarian cancer results were released earlier this year, showing that there are multiple genetic mutations in each case of ovarian cancer, and that each tumor may contain a unique combination of mutations. This poses a significant challenge for individualized ovarian cancer management.

Dr. Huang is working with a team to use TCGA’s information in her research. She is looking at the difference between a person’s genetic code and that of their tumor to establish links between germline genetic variation and somatic mutations in the tumor. Then she can determine genome markers. For example, we know that germline mutations in the BRCA mutations increase a woman’s risk for breast and ovarian cancer. Those women are also more responsive to certain drugs, like PARP inhibitors.

There may be other genetic markers that will help providers understand a woman’s sensitivity to drugs. In the future, each woman may receive a personalized cocktail of drugs intended to target her tumor’s specific mix of genetic mutations. Researchers like Dr. Huang are trying to determine which genetic variations respond best to a particular treatment.

In order to validate any treatment protocols, researchers would need to find the exact genetic variation as well as understand the patient’s overall genetic makeup. Then researchers would collect the patient’s blood, establish cell lines and link the patient’s treatment, outcome, genetics and tumor genetics to determine which treatments will work best. Currently, Dr. Huang is doing this for toxicity to chemotherapy in head, neck and ovarian tumors, and is seeing some patterns.

“The technology in genomic sequencing is fairly mature, but it’s going to get faster and cheaper,” says Dr. Huang. “We will soon have the ability to look at every individual’s genome. Our challenge is to translate scientific discovery into implementation, which takes a lot of data, and a lot of patient participation.” As this field evolves, so might treatment options for women with ovarian cancer.

Source: Ovarian Cancer National Alliance Periodical of Progress Volume 5 October 2011

[url]http://www.tealjournal.org/2011/10/lab-tour-how-genetics-could-transform-ovarian-cancer-treatment/

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 10-12-2011, 11:46 AM
gdpawel gdpawel is offline
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Default

In the end, the genetic variations alone could not determine response to chemotherapy, overall survival and progressive-free survival.

"The cell lines were treated in her lab with various chemotherapeutic agents to determine each individual’s sensitivity to drugs. Dr. Huang then did genetic analyses between each person’s genomic code and his or her sensitivity to the drug. Her goal was to identify germline genetic variations that could be used to predict chemotherapy response. These cell-based findings were then evaluated in 400 women with ovarian cancer who had undergone the related drug treatment. She found that there may be some genetic variations that affect overall survival, progression free survival or response to chemotherapy. Unfortunately, the data was not able to be validated in a larger scale analysis, but leaves the door open for continued research."

Dr. Huang used cell-based findings to test effectiveness against tumors (now why would a researcher do that unless she believed they were accurate) but then could not correlate that to genetic profile? Other than that she used cell-lines instead of using fresh cells, this looks very much like the same results that happen in 2 large trials that found no association between the CYP2D6 genotype and the effectiveness of tamoxifen in preventing breast cancer recurrence (CYP2D6 polymorphism and the outcome of tamoxifen therapy), presented at the 33rd Annual San Antonio Breast Cancer Symposium (SABCS): Abstracts S1-7 and S1-8, December 9, 2010.

Genotype (germline variations) does not equal phenotype. Genes do not operate alone within the cell but in an intricate network of interactions. 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. Our 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.

[url]http://www.ncbi.nlm.nih.gov/pubmedhealth/PMH0048548/
[url]http://www.mayomedicallaboratories.com/test-catalog/Clinical+and+Interpretive/83180
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Last edited by gdpawel : 07-31-2013 at 09:39 AM. Reason: additional info
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Old 11-17-2011, 05:34 PM
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Default Advantages of Cancer Cytometric Profiling vs Molecular Gene Testing

By Larry Weisenthal, M.D., PhD.
Weisenthal Cancer Group

Molecular gene testing attempts to link surrogate gene expression to a theoretical potential for drug activity. It is nearly the opposite of "whole cell" cytometric profiling, in which living cancer cells obtained from each patient are exposed to dozens of candidate chemotherapy drugs and the actual cell killing ability of each drug is precisely measured.

In gene testing, patients’ cells are never exposed to chemotherapy drugs. Instead, gene testing looks only for an assumed predisposition - and then only for a very small number of largely non-specific drugs. It relies upon a relatively small number of gene patterns (only a few of these have been discovered to date) to predict for the behavior of an entire population of cancer cells. This does not take into consideration whether or not the genes truly are relevant, if they are active, or, even more basically, if a chemotherapy drug will ever find its way into the interior of the cancer cell. Nor does it account for the thousands - perhaps millions - of known and unknown protein interactions occurring within a cancer cell, or for the signaling between cancer cells, which profoundly affect susceptibility to chemotherapy drugs.

In addition, testing for activity among different drugs in the same class is not possible in gene testing. This is important because different drugs within the same class of drugs often exert vastly different anti-tumor effects. Neither can gene testing predict for activity of drug combinations. Since most chemotherapy today is administered in combination, this is a serious drawback. Equally disadvantageous is the inability of gene testing to reliably predict for activity in the important new anti-vascular drugs, which work by cutting off the blood supply to tumor cells.

In contrast, cytometric profiling has been proven in numerous studies, involving thousands of cancer patients, to discriminate and accurately measure differing activity - for each patient - among individual drugs in the same class, including the newer “targeted” agents. It does so by measuring the net effect of all cellular gene and protein interactions - those that are known and those that are as yet unknown - in the actual presence of the broadest possible range of potentially active chemotherapy drugs.

Cytometric profiling also has the proven ability to identify synergy which can occur in rational drug combinations. Drugs which are not active as single agents sometimes become extremely effective when combined with certain other agents. Cytometric profiling can pinpoint these drug combinations - gene testing cannot. Further, Weisenthal Cancer Group applies the only technology capable of assessing the effectiveness of new anti-vascular agents (such as Avastin and others) in mixed-cell micro-clusters. No gene test can do this. This critically-important anti-vascular drug profiling technology was originated by Larry Weisenthal and is exclusive to Weisenthal Cancer Group.

In the only head-to-head study (above) of gene testing (molecular profiling) versus cytometric profiling to date, cytometric profiling was found to be highly relevant - 90% concordance with treatment outcome - while gene testing was found to be considerably less relevant (0%, 25%, or 75%, depending upon which genes were studied). This rigorous, independently-conducted study was published in a peer-reviewed medical journal (Journal of Translational Medicine 2011, 9:94 doi:10.1186/1479-5876-9-94).

Assay Results and Bayes' Theorem

[url]http://cancerfocus.org/forum/showthread.php?t=3721
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Old 12-21-2012, 01:08 AM
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Default A Personalized Approach to Cancer Care?

John Maris, Chief of the Division of Oncology at the Children's Hospital in Philadelphia, in speaking to Medscape Oncology, stated that there are many challenges in personalized cancer medicine.

In cancer, personalized cancer medicine 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 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, and other types of analyses. It is going to be a bit more complicated than many were hoping.

[url]http://www.medscape.com/viewarticle/755803
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