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Old 11-20-2011, 10:42 PM   #1
gdpawel
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Breast Cancer Genetic Profiling Has Not Achieved Personalized Medicine Yet

Although ten years of genetic profiling has had an enormous impact on the understanding of breast cancer, progress on individualizing therapy has been rather limited, researchers from the UK and USA reported in The Lancet this week. Specifically, the authors refer to the prognostic and predictive factors associated with personalized medicine, even though genetic profiling offers enormous potential for better prediction of outcomes and optimizing individual patients' treatments.

At this moment there are no commercially available molecular tests that can predict benefit from a specific therapeutic agent, despite of many prognostic and predictive signatures having been developed. Scientists are still unable to accurately determine prognosis or chemotherapy success in some disease subsets, such as ER-negative and triple negative disease.

Jorge Reis-Filho from The Breakthrough Breast Cancer Research Centre at The Institute of Cancer Research in London, UK and Lajos Pusztai from the MD Anderson Cancer Center in Texas, USA, set out to determine what progress, if any, had been made over the last ten years regarding microarray analysis (expression profiling) of breast cancers.

Treatment decisions have usually been based on several clinical factors, such as tumor size and its location, estrogen receptor (ER) status, and whether the cancer has spread to lymph nodes or distant sites in the body.

The researchers explain: "With these approaches, about 60% of all patients with early-stage breast cancer still receive adjuvant chemotherapy, of which only a small proportion, 2-15% of patients, will ultimately derive benefit, while all remain at risk of toxic side-effects."

In addition to information provided by clinicopathological features, the introduction of first generation prognostic gene signatures has offered clinically useful prognostics.

At present, several genomic tests are being used in women with ER-positive disease to help determine the likelihood of cancer recurrence, and which patients' outcome has been sufficiently successful in order to deem chemotherapy unnecessary.

However, the researchers comment: "Increasingly clear is that the prognostic information offered by these [first generation prognostic] signatures in addition to the information provided by semi-quantitaive analysis of ER, PR, HER2, and Ki67 is limited...and the continued importance of standardized histo-pathological analysis of tumors should be emphasized."

Using gene signatures to predict which patients may benefit from specific therapies has been less successful, and even though scientists have developed many predictive signatures, some have been based on unreliable data; their usefulness in patients continues to be controversial.

This could be due to the fact that resistance to chemotherapy is a complex mechanism, as it can be caused by changes in just one or a small number of genes? The likelihood of diverse and often subtle changes resulting in resistance to chemotherapy being reliably identified by standard gene expression profiling is extremely small.

In a concluding statement the researchers say: "The theoretical knowledge and logistical lessons learned from gene expression profiling studies, however, will prove useful for research aiming to develop the next generation of prognostic and predictive biomarkers."

References: Prof Jorge S Reis-Filho FRCPath and Prof Lajos Pusztai MD "Gene expression profiling in breast cancer: classification, prognostication, and prediction" The Lancet, Volume 378, Issue 9805, Pages 1812 - 1823, 19 November 2011. doi:10.1016/S0140-6736(11)61539-0

http://www.thelancet.com/journals/la...539-0/abstract
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Old 11-26-2011, 09:32 PM   #2
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Cancers have a genomic signature unique to every patient

The interest in and the knowledge of gene expression profiling in cancer medicine has heighten since the completion of the human genome project. However, researchers have cautioned the science of gene expression profiling, in which scientists examine the genetic signature of a cell.

Medical research has focused on developing DNA (genomic) tests to identify various gene expressions, markers and mutations relevant to a person's cancer. The hope was that genetic information would enable researchers to better predict how an individual will respond to various treatment options.

However, when it comes to "predicting" the best treatment for the individual, unlocking the complexities of a person's DNA is not the answer, it is simply a starting point. In fact, a March 16, 2010 study in the Journal of the National Cancer Institute looked at the value of various gene tests and concluded none of the studies showed a clear usefulness.

Genomic tests provide lots of information about a patient's genes. But there are so many sequences in our DNA which influence disease, that attempting to unravel such complexity just produces more and more information without a particularly useful benefit. While genes may provide a recipe, they do not determine the end results and cannot predict how an individual will respond to a specific treatment.

Like the various influences on a flower seed that cause one blossom to turn out differently from another, there are biological processes in the body that affect the development of cancer in each patient and determine how that patient's cancer cells will uniquely react to treatment.

Despite its allure, the "genetic" path is not all that personalized. Treatment based on genetic testing is still a guessing game (trial-and-error). But a treatment regimen based on a "functional profile" - a real-time test of chemotherapy on the actual cancer tissue - can predict with accuracy an individual's response to chemotherapy.
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Old 01-06-2012, 07:27 PM   #3
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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.

http://www.translational-medicine.com/content/9/1/94
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Old 02-14-2012, 02:37 PM   #4
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Metabolic Profiles Are Essential For Personalizing Cancer Therapy

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

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

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

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

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

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

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

http://www.medicalnewstoday.com/releases/241306.php
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