# Defining the features of T cell response to tumor and self-antigens as predictors of response to checkpoint therapy > **NIH NIH R01** · BENAROYA RESEARCH INST AT VIRGINIA MASON · 2020 · $946,097 ## Abstract PROJECT SUMMARY/ABSTRACT Immune checkpoint inhibitor therapies have revolutionized the field of solid tumor oncology - in particular, they have played a substantial role in improving the survival of patients with advanced lung or bladder cancer. However, despite clinical successes, immune checkpoint inhibitors are not effective in all cases, and may be associated with serious immune-related adverse events. This application is in response to the National Cancer Institute’s Provocative Question #8: “What are the predictive biomarkers for the onset of immune-related adverse events (irAE) associated with checkpoint inhibition, and are they related to markers for efficacy?” The goal of the proposed studies is to identify T cell biomarkers that predict autoimmune-related irAE associated with ICI therapy. The central hypothesis for the proposed studies is that the frequency and phenotype of T cells specific for self-antigens predicts autoimmune irAE, which in turn predicts therapeutic efficacy in some patients. The following four Specific Aims will address this hypothesis. Aim 1 studies will determine how immune checkpoint inhibitor therapy alters the frequency and phenotype(s) of tumor- and autoantigen-specific T cells using an innovative approach to isolate antigen-specific T cells, and a longitudinal cohort of subjects before and after immune checkpoint inhibitor therapy. Aim 2 studies will use an innovative single cell RNA-sequencing approach to determine if expanded T cell clones arise with immune checkpoint inhibitor therapy, and whether these T cells have phenotypic or functional properties predictive of anti-tumor and autoimmune responses. Aim 3 studies will determine whether immune checkpoint inhibitor therapy alters the CD4 and CD8 T cell landscape in cancer making it similar to that seen in individuals with natural autoimmunity. Aim 4 studies will test the hypothesis that immune checkpoint inhibitor therapy releases quiescent autoreactive T cells from regulation, leading to increased frequency and activation distinct from the global T cell response. Together, these studies will systematically elucidate the relationship between tumor- and auto- immunity following immune checkpoint inhibitor therapy, and will provide insight into the potential of T cell biomarkers to predict clinical outcome. ## Key facts - **NIH application ID:** 9999523 - **Project number:** 5R01CA231226-02 - **Recipient organization:** BENAROYA RESEARCH INST AT VIRGINIA MASON - **Principal Investigator:** Jane Hoyt Buckner - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2020 - **Award amount:** $946,097 - **Award type:** 5 - **Project period:** 2019-09-01 → 2024-08-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/9999523 ## Citation > US National Institutes of Health, RePORTER application 9999523, Defining the features of T cell response to tumor and self-antigens as predictors of response to checkpoint therapy (5R01CA231226-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9999523. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*