Dr. Peng Jiang of NCI’s Center for Cancer Research Cancer Data Science Lab and his postdocs have developed an open-source computational tool called the tumor-resilient T cell (Tres) model. Tres analyzes gene activity in T cells to assess how those cells are likely to fare in an immunosuppressive environment.

In an article in May’s issue of Nature Medicine, developers of the tool stated that this measure of T cell resilience predicts if cancer immunotherapy will be effective for the treatment of an individual patient.

Usages for this tool include:

• querying for positive or negative markers of tumor-resilient T cells in genes,
• predicting gene expression profiles of T cells or T-cell enriched samples and their resilience in solid tumors,
• prioritizing gene set input and markers of tumor-resilient T cells for follow-ups, and
• evaluating whether an input gene signature can predict T cell clinical efficacies in immune checkpoint blockade and adoptive cell therapy.

Read the full article in Nature Medicine.