NEW YORK – Cofactor Genomics said Tuesday that it will partner with the University of California, San Diego, to continue to study the utility of its predictive immune modeling technology in personalizing immunotherapy treatment for head and neck cancers.
The company noted that improving therapy selection for this hard-to-treat tumor type has become especially important given the US Food and Drug Administration's recent approval of pembrolizumab (Merk's Keytruda) as a first-line option for recurrent and metastatic, squamous cell head and neck carcinoma.
In approving that indication last year, FDA also approved Agilent Technologies' Dako PD-L1 IHC 22C3 pharmDx assay as a companion diagnostic, but researchers have also been evaluating alternative biomarkers like tumor mutational burden for identifying which patients are more likely to respond to anti-PD-1/PD-L1 drugs like pembrolizumab. Cofactor believes its immune-focused approach could prove more effective than these other predictors.
The company's effort with UCSD is being led by Ezra Cohen, chief of the division of hematology‐oncology at the Moores Cancer Center.
"Predicting tumor response prior to treatment is a necessary part of the precision medicine challenge," Cohen said in a statement. "Cofactor is approaching diagnostic development in a number of ways that are unique. Integrating multiple immune signals into a single clinical decision simultaneously simplifies and expands how we leverage this information," he added.
The company's Predictive Immune Modeling approach involves immune-specific multidimensional biomarkers, which reflect distinct differences in gene expression profiles between the tumors of responders and non-responders to immunotherapy.
According to Cofactor, under the terms of the partnership, UCSD will provide a curated resource of patient specimens and clinical metadata. The company hopes to generate results that will expand on the clinical evidence presented earlier this year by Washington University physicians showing that its technology is superior to established PD-L1 IHC testing in predicting responders to immunotherapy.
Financial details of the collaboration were not disclosed.