On November 6, 2019 Cofactor Genomics, leaders in RNA-based technologies and diagnostics, reported they will provide early access to a new feature in their Predictive Immune Modeling platform which enables cell-state characterization within FFPE tissue samples (Press release, Cofactor Genomics, NOV 6, 2019, View Source [SID1234550450]). Measuring cell-states, such as T cell exhaustion, has been cited as integral to improving the accuracy of patient selection for immune checkpoint inhibitors. The field has previously failed to reach consensus on a short list of individual analytes that effectively characterize exhaustion using incumbent technologies, leading Cofactor to address this challenge using multidimensional biomarker models.
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Cofactor is offering access to the technology through the "Functional to FFPE" Early Access Grant Program, which will support solid tumor or engineered cell therapy exploratory studies, with up to $100,000 in reagents, sequencing, and analysis support covered by the company.
Cofactor’s platform is underpinned by the industry’s first database of Health Expression Models, built using machine learning to identify multidimensional gene expression patterns that enable highly-sensitive characterization of cell types in heterogenous tissue or cell samples. With this new feature, the database has been expanded to include validated models for unstimulated T cells, activated T cells, and exhausted T cells.
The presence of terminally exhausted T cells has been shown to negatively predict success with anti-PD-1 checkpoint inhibitor therapies. As a result, the ability to detect cell state – such as exhaustion – has garnered significant interest, but has proved difficult with clinical archives. Previously, only viable tissue and laborious functional assays were able to generate difficult-to-interpret rough approximations of cell state.
"The ability of RNA-based models to accurately characterize these important cell states in FFPE tissue samples is exactly the reason why Cofactor has invested in Predictive Immune Modeling. No other technology – genomic or proteomic – has been able to accomplish this in FFPE," stated Cofactor’s Chief Scientific Officer Jon Armstrong. "We have to move beyond just detecting cells, and better characterize how those cells are influenced by their microenvironment."
In addition to today’s announcement, Cofactor will be presenting early results using these new cell state models, sharing data from collaborative studies via poster presentations, and releasing other product updates this month at the Annual Meetings for the Association for Molecular Pathology (Booth #2319) and Society for Immunotherapy of Cancer (SITC) (Free SITC Whitepaper) (Booth #535).