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Old 11-04-2012, 02:53 PM
gdpawel gdpawel is offline
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Default New Clinical Study Shows Test That Doubles Chemotherapy Response Rate

Using only FDA-approved, standard lung cancer drugs available to all oncologists, a process of laboratory selection provided a 64.5 percent response rate - more than double the national average of 30 percent (p = 0.00015), well established in medical literature. More importantly, the median overall survival of 21.3 months was nearly two-fold longer than the best results of 13.5 months reported for non-assay based standard treatments. Strikingly, among the stage IV (metastatic) patients, there are several who remain alive approaching eight years since diagnosis.

According to a Phase II clinical trial conducted by investigators at Rational Therapeutics and the Memorial Care Todd Cancer Institute, Long Beach, CA, and published in the October issue of Anticancer Research, functional cytometric profiling of programmed cell death doubles the response rate and improves time-to-progression and survival in patients with advanced lung cancer. According to Dr. Robert A. Nagourney, lead investigator, this study confirms the ability of a laboratory test to accurately predict drug activity for individual cancer patients.

The article, titled "Functional Profiling to Select Chemotherapy in Untreated, Advanced or Metastatic Non-Small Cell Lung Cancer," describes results achieved in patients who received first-line chemotherapy based on their phenotype analysis. Functional profiling provides a window into the dynamic process by which human tumor cells respond to therapy. By capturing cells within their natural microenvironment, human biology is recreated in the laboratory. Statistical analyses enable researchers to establish “levels” of certainty. Reported as “p-values,” these metrics offer the reader levels of statistical significance indicating that a given finding is not simply the result of chance. A p-value equal to 0.1 (1 in 10) means that the findings are 90 percent likely to be true with a 10 percent error. A p-value of 0.05 (1 in 20) tells the reader that the findings are 95 percent likely to be true. While a p-value equal to 0.01 (1 in 100) tells the reader that the results are 99 percent likely to be true. For an example in real time, this paper is reporting in lung cancer literature that doubled the response rate for metastatic disease compared with the national standard. The results achieved statistical significance where p = 0.00015. That is to say, that there is only 15 chances out of 100,000 that this finding is the result of chance. The biomarker-based paradigm will require us to consider the level of evidence necessary to declare true activity. Daniel J. Sargent, PhD, Professor of Cancer Research at the Mayo Clinic, tells us that it may become impossible to perform traditional trials with requirements to achieve a P-value less than 0.05, high statistical power, and an OS advantage. When the patient population becomes small, we’re going to have to consider either other endpoints or other statistical philosophies. Should we use a Bayesian strategy, in which we borrow information from other clinical trials to help make decisions? Or do we loosen the P-value requirements, that a P-value of less than 0.1 or 0.2, for example, be considered a sufficient level of evidence for activity? These are active areas of research that need to be fully considered as we enter this era of truly personalized therapy with patient populations that are becoming smaller and smaller. I do know that the Bayesian method is no stranger to the functional profiling platform. It’s what gives credit to the accuracy of the assay tests.

The absolute predictive accuracy of cell culture assay tests varies according to the overall response rate in the patient population, in accordance with Bayesian principles. The actual performance of assays in each type of tumor precisely match predictions made from Bayes’ Theorem. Bayes’ Theorem is a tool for assessing how probable evidence makes some hypothesis. It is a powerful theorem of probability calculus which is used as a tool for measuring propensities in nature rather than the strength of evidence (Solving a Problem in the Doctrine of Changes). Sources: Anticancer Research October 2012 vol. 32 no. 10; 4454-4460 Daniel J. Sargent, PhD, is the Ralph S. and Beverly E. Caulkins Professor of Cancer Research at the Mayo Clinic Cancer Center in Rochester, Minnesota, and Group Statistician for the Alliance for Clinical Trials in Oncology. "Commentary on clinical endpoints, validation of surrogate endpoints and biomarkers in oncology clinical trials."

[url]http://ar.iiarjournals.org/content/32/10/4453.abstract?sid=eb8c3504-bee5-4756-a1a8-1ae7c0d554dc
[url]http://www.rationaltherapeutics.com/downloads/pdfs/Functional-Profiling-To-Select-Chemotherapy.pdf
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Last edited by gdpawel : 01-13-2014 at 05:42 PM. Reason: additional info
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Old 11-04-2012, 03:15 PM
gdpawel gdpawel is offline
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Default Functional Profiling to Select Chemotherapy in Untreated Advanced or Metastatic NSCLC

Functional Profiling to Select Chemotherapy in Untreated, Advanced or Metastatic Non-Small Cell Lung Cancer

Robert A. Nagourney 1,2, Jonathan B. Blitzer 1, Robert L. Shuman 1, Thomas J. Asciuto 1, Eknath A. Deo 1, Marylyn Paulsen 1, Robert L. Newcomb 3, Steve S. Evans 2

1. Memorial Medical Center of Long Beach, Todd Cancer Institute, Long Beach, CA
2. Rational Therapeutics, Long Beach, CA
3. Institute for Clinical & Translational Science, University of California, Irvine, CA

Abtract

Background Aim:

To assess the impact of drug selection upon the treatment of advanced and metastatic non-small cell lung cancer (NSCLC), we applied a functional platform that measures drug induced cell death in human tumor primary-culture micro-spheroids isolated from surgical specimens.

Patients and Methods:

At diagnosis, microspheroids isolated by mechanical and enzymatic disaggregation were examined for drug-induced cell-death by morphology and staining characteristics. Drugs were administered using standard protocols. Thirty-one patients, who received at least one cycle of therapy, were evaluable. All patients signed informed consent.

Results:

Twenty of 31 patients responded (64.5%). 1 completely and 19 partially, providing a two-fold improvement over historical control of 30% (p=0.00015), a median time to progression of 8.5 months and a median overall survival of 21.3 months.

Conclusion:

This functional platform is feasible and provides a favorable objective response rate, time to progression and survival in advanced, metastatic, untreated NSCLC, and warrants further evaluation.

Source: Anticaner Research October 2012 vol. 32 no. 10; 4454-4460

Using only FDA-approved, standard lung cancer drugs available to all oncologists, this process of laboratory selection provided a 64.5 percent response rate – more than double the national average of 30 percent (p = 0.00015), well established in the literature. More importantly, the median overall survival of 21.3 months was nearly two-fold longer than the best results of 13.5 months reported for non-assay based standard treatments. Strikingly, among the Stage IV (metastatic) patients, there are several who remain alive approaching eight years since diagnosis.

Standard treatment protocols, administered in accordance with published results in thoracic oncology literature, included: Carboplatin & Paclitaxel (Taxol); Cisplatin & Navelbine (vinorelbine); Cisplatin & Gemzar (gemcitabine); Carboplatin & Gemzar; Carboplatin & Alimta (pemetrexed); Tarceva (erlotinib); Tarceva & Avastin (bevacizumab); Carboplatin & Taxol & Avastin; Cisplatin & Navelbine & Avastin; Taxol; Docetaxel (Taxotere); Navelbine; Taxotere & Gemzar; Campto (Irinotecan); Campto & Cisplatin.

To date, they are tracking a 100% response rate to Tarceva in the select populations; even patients who have not been found to carry recognized mutations.

Assay Results and Bayes' Theorem

[url]http://cancerfocus.org/forum/showthread.php?t=3754

[url]http://www.rationaltherapeutics.com/downloads/pdfs/EVAPCD.pdf

Translational science: past, present, and future

[url]http://www.biotechniques.com/multimedia/archive/00003/BTN_A_000112749_O_3671a.pdf
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Last edited by gdpawel : 02-26-2013 at 11:18 AM. Reason: added url address
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Old 11-27-2012, 10:01 AM
gdpawel gdpawel is offline
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Default Systems Biology Comes of Age: Metastatic Lung Cancer in the Crosshairs

Robert A. Nagourney, M.D.

Cancer therapists have long sought mechanisms to match patients to available therapies. Current fashion revolves around DNA mutations, gene copy and rearrangements to select drugs. While every cancer patient may be as unique as their fingerprints, all of the fingerprints on file with the federal AFIS (automated fingerprint identification system) database don’t add up to a hill of genes (pun intended), if you can’t connect them to the criminal.

To continue the analogy, it doesn’t matter why the individual chose a life of crime, his upbringing, childhood traumas or personal tragedies. What matters is that you capture him in the flesh and incarcerate him (or her, to be politically correct).

The term we apply to the study of cancer, as a biological phenomenon is “systems biology.” This discipline strikes fear into the heart of molecular biologists, for it complicates their tidy algorithms and undermines the artificial linearity of their cancer pathways. We frequently allude to the catchphrase, genotype ≠ phenotype, yet it is the cancer phenotype that we must confront if we are to cure this disease.

Using a systems biology approach, we applied the ex-vivo analysis of programmed cell death (functional profiling) to the study of previously untreated patients with non-small cell lung cancer. Tissue aggregates isolated from their surgical specimens were studied in their native state against drugs and signal transduction inhibitors. This methodology captures all of the interacting “systems,” as they respond to cytotoxic agents and growth factor withdrawal. The trial was powered to achieve a two-fold improvement in response.

At interim analysis, we had more than accomplished our goal. The results speak for themselves.

First: a two-fold improvement in clinical response – from the national average of 30 percent we achieved 64.5 percent (p – 0.00015).

Second: The median time to progression was improved from 6.4 to 8.5 months.

Third: And most importantly the median overall survival was improved from an average of 10 – 12 months to 21.3 months, a near doubling.

These results, from a prospective clinical trial in which previously untreated lung cancer patients were provided assay directed therapy, reflects the first real time application of systems biology to chemotherapeutics. The closest comparison for improved clinical outcome with chemotherapeutic drugs chosen from among all active agents by a molecular platform in a prospective clinical trial is . . . Oh, that’s right there isn’t any.

[url]http://www.rationaltherapeutics.com/the-science/published-reports.aspx

Systems Biology Is The Future Of Medical Research

[url]http://cancerfocus.org/forum/showthread.php?t=3473
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