BeyondSpring (NASDAQ: BYSI) will present novel data relevant to predictive biomarkers for patient selection for its lead asset, Plinabulin, at the 2019 American Association for Cancer Research (AACR) annual meeting in Atlanta on April 1.
In this study, BeyondSpring generated neural and logistic regression algorithms that utilized Affymetrix array-based mRNA measurements to predict the ability of Plinabulin to dramatically reduce the number of live breast, lung, prostate, ovarian and CNS cancer cells in vitro.
The methods and predictive gene mRNAs discovered will be utilized to introduce a similar exploratory approach into Plinabulin clinical trials.
“There is an enormous need to predict, with confidence, an individual cancer patient’s likelihood of response to therapies being considered,” Dr. James Tonra, SVP of preclinical development for BeyondSpring, said in a statement.
“Yet patient selection strategies, beyond cancer type and line of therapy, are the exception rather than the rule,” he added. “This nonclinical effort was undertaken to significantly advance the concept of patient selection, and we are very pleased with the ability of our algorithms to accurately and confidently predict potent Plinabulin anti-cancer effects.”
Plinabulin is already in global Phase 3 trials for non-small cell lung cancer. Dr. Ramon Mohanlal, EVP for R&D and CMO for BeyondSpring, said this “new discovery opens up the potential of developing multiple indications for Plinabulin using this biomarker-based approach to patient selection for increased efficacy.”
Gene expression profiles at baseline that are predictive of outcomes are achievable and will allow BeyondSpring to identify the right chemotherapies and cancer types for this approach through relatively small, early proof-of-concept trials, he added.
