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 safety, specificity and treatment efficacy for immunotherapy-treated cancer patients.

Public Health Relevance

Immunotherapies have revolutionized the treatment of cancer by improving survival benefit for patients in a number of cancer types, however, with increasingly complex treatment strategies being deployed in a variety of combinations, the risk for developing severe side-effects in the form of immunotoxicities is heightened. Through improved preclinical models, such as generating tumors in autoimmune-prone mice, we can better study the influence of immunotherapies on both tumor immunity and autoimmunity. This will address a growing need to provide accurate safety profiling and mechanistic interrogation of both combinatorial and single-agent therapies to determine optimal therapeutic regimens to improve cancer care with mimimal immune-related adverse-events.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Career Transition Award (K99)
Project #
1K99CA246061-01
Application #
9882145
Study Section
Special Emphasis Panel (ZCA1)
Program Officer
Radaev, Sergey
Project Start
2020-02-01
Project End
2022-01-31
Budget Start
2020-02-01
Budget End
2021-01-31
Support Year
1
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of California San Francisco
Department
Type
University-Wide
DUNS #
094878337
City
San Francisco
State
CA
Country
United States
Zip Code
94118