# Developing strategies to inhibit cancer immunotherapy-induced immune-related adverse events without impeding anti-tumor immunity > **NIH NIH R00** · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · 2024 · $249,000 ## Abstract Project Summary/Abstract Tumors elicit a range of suppressive mechanisms in order to evade the immune system. Many of these are targetable as evidenced by the great success of cancer immunotherapies that boost a patient's own immune response towards cancer. Often, targets for cancer immunotherapies represent pathways that at homeostasis protect against activation of an immune response towards self, limiting the development of autoimmune disease. Cancer patients treated with immune-potentiating therapies are exposed to significant risk of developing immune-related adverse events (irAEs). These irAEs have been reported in nearly every organ system, and in many cases represent non-resolving autoimmune side-effects that pose a significant impact due to their potential morbidity, mortality and associated healthcare costs. With a growing number of immunotherapies reaching clinical utility and increasing combination studies that may initiate more frequent and severe irAEs, understanding which therapeutic approaches provide improved tumor control with minimal side-effects is essential. In this study, by generating transplantable, syngeneic tumor cell lines in autoimmune- prone NOD mice, which develop autoimmune pathologies in response to cancer immunotherapies, we may begin to assess the interplay between irAEs and anti-tumor immunity. In-depth profiling of genetic, epigenetic and cellular mechanisms that separate anti-tumor immunity versus autoimmunity in response to cancer immunotherapies will be defined to better engineer therapeutic strategies that enhance the immune response towards tumor with limited impact towards self. Using NOD tumors resistant to clinically-approved cancer immunotherapies such as anti-PD-1 and anti-CTLA-4, combination therapeutic strategies that reinvigorate immune activation in the tumor microenvironment will be identified and the associated risk for precipitating irAEs determined. Together, these preclinical models provide a platform to assess safety profiles for cancer immunotherapies, identifying mechanisms to inhibit or avoid irAEs while preserving anti-tumor immunity. This research will be performed amongst world-class scientists and facilities at the University of California, San Francisco, this environment will foster expert training in the analysis of high-dimensional datasets generated from CyTOF and 10X single-cell RNA and TCR sequencing, an essential skill for delineating the complex mechanisms contributing to immune-mediated disease. Both my mentorship committee, led by Dr. Jeffrey Bluestone and expert collaborators will allow me to fulfil these research goals. Following, I will transition to an independent position establishing a research program that integrates the effect of multiple environmental factors, including microbiome, diet, age and stress, alongside autoimmune and anti-tumor immune responses to cancer immunotherapy using the NOD tumor models that have been developed, with the ultimate aim to improve saf... ## Key facts - **NIH application ID:** 10755293 - **Project number:** 5R00CA246061-05 - **Recipient organization:** UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH - **Principal Investigator:** Arabella Young - **Activity code:** R00 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $249,000 - **Award type:** 5 - **Project period:** 2020-02-01 → 2025-11-30 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10755293 ## Citation > US National Institutes of Health, RePORTER application 10755293, Developing strategies to inhibit cancer immunotherapy-induced immune-related adverse events without impeding anti-tumor immunity (5R00CA246061-05). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10755293. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*