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Rosetta, Sheba Medical Center Partner on Study of MicroRNA Signature for Bristol-Myers' Opdivo

NEW YORK (GenomeWeb) – Rosetta Genomics announced today that it has partnered with Israel's Sheba Medical Center at Tel HaShomer to identify a microRNA-based signature that can predict lung cancer patient response to Bristol-Myers Squibb's immunotherapy Opdivo (nivolumab).

Opdivo is a monoclonal antibody-based checkpoint inhibitor that is approved in the US for a number of cancer indications including as a second-line treatment for non-small cell lung cancer (NSCLC). This past summer, Bristol-Myers Squibb disclosed that the drug failed as a first-line NSCLC therapy in a phase III clinical study. The pharma giant employed a PD-L1 test to stratify patients in studies, but it didn't segment the population as stringently as it should have, according to industry observers, choosing to go after a broader population: first-line advanced NSCLC patients who had PD-L1 expression in 5 percent or more of their tumor cells.

Under the terms of their collaboration, Rosetta and Sheba will use the company's proprietary microarray technology and qRT-PCR platform to identify miRNAs associated with Opdivo response in whole blood, peripheral blood mononuclear cells, and serum samples collected from lung cancer patients.

The primary endpoint of the study is the prediction of objective response rate as measured by tumor radiologic response to the immunotherapy, Rosetta said. The secondary endpoint is prediction of survival benefit from treatment.

"We have conducted early clinical research that has demonstrated microRNAs' potential as predictive biomarkers in immuno-oncology," Rosetta CSO Dganit Bar said in a statement. "Our goals for this collaboration with Sheba Medical dovetail with earlier work we conducted in partnership with large pharmaceutical companies that focused on establishing biomarkers to identify responders to certain immuno-oncology drugs."

Rosetta President and CEO Kenneth Berlin added that development of an Opdivo miRNA biomarker signature "fits well with our comprehensive lung-specific menu that assists in diagnosis, prognosis, and prediction to therapy for lung cancer patients."