Functional profiling using EVA/PCD doubles response rate and improves survival in NSCLC patients

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Rational TherapeuticsOct 8 2012

Functional profiling using ex-vivo analysis of programmed cell death (EVA/PCD^®) doubles the response rate and improves time-to-progression and survival in patients with advanced lung cancer, according to a Phase II clinical trial conducted by investigators at Rational Therapeutics (http://www.rational-t.com) and the MemorialCare Todd Cancer Institute (Long Beach, CA) and published in the October issue of Anticancer Research.

"Medical oncologists have long pursued methods that can match patients to available therapies," said Dr. Robert Nagourney, lead investigator. "This study confirms the ability of a laboratory test to accurately predict drug activity for individual patients."

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.

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 individual ex-vivo analysis.

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.

"These results suggest that laboratory selection of chemotherapy can change the natural history of this lethal disease," said Dr. Nagourney. "What makes the EVA/PCD approach unique is its capacity to capture human tissues in their native state, recreating conditions found in the human body."

Attempts to use gene profiling in this disease resulted in failure and controversy ("How Bright Promise In Cancer Testing Fell Apart." - Gina Kolata, New York Times, July 7, 2011). Contrary to gene-based methods, functional platforms capture the systems biology of human tumors in real-time providing therapeutic insights that translate directly into improved clinical outcomes.

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Rational Therapeutics

Posted in: Device / Technology News | Medical Condition News | Pharmaceutical News

Tags: Assay, B Cell, Cancer, Cell, Cell Death, Chemotherapy, Clinical Trial, Drugs, Ex Vivo, Gene, Laboratory, Lung Cancer, Lungs, Non-Small Cell Lung Cancer, Programmed Cell Death, Research, Small Cell Lung Cancer, T-Cell, Therapeutics, Tumor

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“p-values”

Gregory Pawelski says:

October 17, 2012 at 1:15 AM

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.

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. To wit, 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, they are reporting a paper 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.

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