Defining tumor and blood-based immunogenomic signatures predicting response to immunotherapy in ovarian cancer

Icahn School Of Medicine At Mount Sinai, New York NY

Investigators

Abstract

The advent of immunotherapies (IO) such as immune checkpoint inhibitors (ICI) heralded a significant improvement in cancer patient survival, but the mechanisms underlying treatment response are still opaque. The level of tumor-infiltrating lymphocytes (TILs) has been suggested as one potential ICI response biomarker, signaling an active anti-tumor immune response. So-called “hot” tumors, those with many TILs, are more frequent in some cancers (e.g. melanoma) than others (e.g. ovarian cancer, OC). Strategies to recruit additional TILs and thereby make cold tumors hot are in development, including the use of oncolytic viruses (OVs). Refining IO outcome predictors, for both ICI and OV therapies, is an unmet clinical need. Expanding on my previous findings of a novel germline genomic biomarker of ICI resistance in the circulating CD8+ T cells of metastatic melanoma patients (H-MAX), I hypothesize that inherited immune biomarkers can be identified in other IO-treated cancers. Whether such markers are the same for “hot” tumors like melanoma, or differ for cold tumors such as OC, remains to be seen, as does their applicability to novel IO combinations such as those including OVs. Understanding the interplay between circulating and tumor-infiltrating immune cells and charting the dynamic post-treatment changes in the immune landscape may further illuminate the anti-tumor responses induced by IO therapies. This proposal aims to answer these questions using peripheral blood and tumor samples from IO clinical trials of ICI alone (NRG-GY003; NCT02498600) or in combination with OV (ONCOS-102; NCT02963831). Sequencing these samples, I will define the inherited and acquired mutational profiles of these patients (Aim 1.1), correlating these with their treatment outcomes. I will then assess their association with known (e.g. TILs) and novel (e.g. H-MAX) IO biomarkers in both OC and other cancers. Using high-resolution spatial profiling, I will then map the pre-treatment (NRG-GY003) and pre- and post-treatment (ONCOS-102) tumor immune landscape (Aim 1.2), correlating these profiles with IO response and the genomic signatures in Aim 1.1. Sequencing both tumor and peripheral blood TCRs from NRG-GY003, I will identify the baseline tumor-resident TCR sequences and, using post-treatment blood samples, map their expansion in the periphery following ICI treatment (Aim 2). I will conduct the same analysis in ONCOS-102, for which I also have post-treatment tumor samples, allowing me to correlate the changes in circulating TCR profiles with those in the tumor. I will also use ECCITE-seq, an emerging technology for obtaining single-cell proteomic, transcriptomic, and TCR data, to profile pre/post-treatment ONCOS-102 peripheral blood mononuclear cells. With this deep profiling, I will precisely define the cellular phenotypes and TCR repertoires of the reactive T-cell clones, charting their dynamic post-treatment evolution following combined OV and ICI treatment. Collectively, the results from this work may identify novel OC response biomarkers, potentially improving treatment stratification and pointing to mechanisms of IO response and resistance.