Immune checkpoint blockade (ICB) therapies?including ipilimumab (IPI; developed against cytotoxic T lymphocyte-antigen 4), nivolumab (NIVO; anti-programmed death 1 antibody) and their combination (IPI/NIVO)?have demonstrated durable survival benefits in melanoma. Despite high response rates, >50% of patients do not respond to these treatments. In addition, patients often develop immune-related adverse events with severe morbidity, substantially reducing quality of life. Efforts to identify biomarkers of ICB outcomes have mainly centered on the tumor microenvironment because anti-tumor T cell immunity is the primary target of ICB, the focus has been predominantly on tumor T-cell infiltration. While promising tumor-based surrogates of ICB have been proposed, none of these markers alone or in combination fully explains variability in ICB outcome. Hence, there is a continuing need to identify more powerful biomarkers of ICB outcomes that would also serve as potential novel targets for more effective and less toxic treatments. We propose a novel hypothesis that ICB outcomes are strongly impacted by host immunity, shown in recent reports to be influenced by underlying inherited factors. It was demonstrated that phenotypic variation in T-cell subsets, including CD8+ T cells, is attributed to germline genetic variation. In a recent study, we showed that this inherited component maps to the non-coding regulatory genome, impacting transcriptional regulation of T-cell differentiation and function. Based on these data, we hypothesize that circulating CD8+ T cells, a primary target of NIVO and IPI/NIVO therapies, are controlled by germline genetic variation in the CD8+ non-coding regulatory genome (regulome), and that this genetic variability modulates ICB efficacy and toxicity. The goal of the proposed study is to discover inherited signatures of the CD8+ T cell regulome that predict ICB efficacy and toxicity. Using samples from 600 melanoma patients from a clinical trial of NIVO and IPI/NIVO, we will perform a comprehensive analysis of whole-genome sequencing (WGS) and a whole-transcriptome analysis on peripheral blood pre-treatment CD8+ T cells to identify non-coding transcriptome signatures that predict ICB efficacy (Aim 1). We will use the genetic information from WGS to comprehensively assess open chromatin states in pre-treatment CD8+ T cells from the same 600 patients to identify epigenetic signatures controlled by inherited genetic variation, predicting ICB response and immune-related toxicity (Aim 2). Our preliminary data have revealed novel genomic imprints in the non-coding regulome that predict ICB response with high clinical accuracy, thus substantially supporting our hypotheses and design. For the first time, our study will elucidate the effect of inherited anti-tumor host immunity on ICB outcomes. As we suggest, besides imminent applicability to personalized prediction of ICB treatment benefits, the integration of genomic information from both aims will reveal novel transcriptional networks in CD8+ T cells that potentially affect ICB resistance. These may eventually serve as novel targets for improved ICB therapies in melanoma and other cancers.

Public Health Relevance

A substantial number of patients do not benefit from the promising new immune checkpoint blocking therapies that stimulate the immune system to target melanoma. In our study, we propose to discover the factors that influence response to these novel therapies, providing an opportunity to significantly improve treatment outcomes for patients with metastatic melanoma. ! !

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA227505-03
Application #
9994845
Study Section
Special Emphasis Panel (ZCA1)
Project Start
2018-08-01
Project End
2023-07-31
Budget Start
2020-08-01
Budget End
2021-07-31
Support Year
3
Fiscal Year
2020
Total Cost
Indirect Cost
Name
New York University
Department
Dermatology
Type
Schools of Medicine
DUNS #
121911077
City
New York
State
NY
Country
United States
Zip Code
10016