Integrated immunogenomic analyses of high-grade serous ovarian cancer reveal vulnerability to combination immunotherapy

Abstract

AbstractBackgroundHigh-grade serous ovarian cancer (HGSOC) remains the most lethal gynecologic malignancy despite new therapeutic concepts, including poly-ADP-ribose polymerase inhibitors (PARPis) and antiangiogenic therapy. The efficacy of immunotherapies is modest, but clinical trials investigating the potential of combination immunotherapy with PARPis are underway. Homologous recombination repair deficiency (HRD) or BRCAness and the composition of the tumor microenvironment appear to play a critical role in determining the therapeutic response.MethodsWe conducted comprehensive immunogenomic analyses of HGSOC using data from several patient cohorts, including a new cohort from the Medical University of Innsbruck (MUI). Machine learning methods were used to develop a classification model for BRCAness from gene expression data. Integrated analysis of bulk and single-cell RNA sequencing data was used to delineate the tumor immune microenvironment and was validated by immunohistochemistry. The impact of PARPi andBRCA1mutations on the activation of immune-related pathways was studiedin vitrousing ovarian cancer cell lines, RNA sequencing, and immunofluorescence analysis.ResultsWe identified a predictive 24-gene signature to determine BRCAness. Comprehensive analysis of the tumor microenvironment allowed us to identify patient samples with BRCAness and high immune infiltration. Further characterization of these samples revealed increased infiltration of immunosuppressive cells, including tumor-associated macrophages (TAMs) expressingTREM2,C1QA,andLILRB4,as identified by further analysis of single-cell RNA sequencing data and gene expression analysis of samples from patients receiving combination therapy with PARPi and anti-PD-1. PARPi activated the cGAS-STING signaling pathway and the downstream innate immune response in a similar manner to HGSOC patients with BRCAness status. We have developed a web application (https://ovrseq.icbi.at) and an associated R package OvRSeq, which allow for comprehensive characterization of ovarian cancer patient samples and assessment of a vulnerability score that enables stratification of patients to predict response to the mentioned combination immunotherapy.ConclusionsGenomic instability in HGSOC affects the tumor immune environment, and TAMs play a crucial role in modulating the immune response. Based on various datasets, we have developed a diagnostic application that uses RNA sequencing data not only to comprehensively characterize HGSOC but also to predict vulnerability and response to combination immunotherapy.