Tumour Microenvironment-Based Molecular Profiling Reveals Ideal Candidates for High-Grade Serous Ovarian Cancer Immunotherapy

Abstract

Background: Due to limited immunological profiles of high-grade serous ovarian cancer (HGS-OvCa), we aimed to characterise its molecular features to determine whether a specific subset that can respond to immunotherapy exists. Methods: A training cohort of 418 HGS-OvCa samples from TCGA was analysed by consensus non-negative matrix factorization. We correlated the expression patterns with the presence of immune cell infiltrates, immune regulatory molecules and other genomic or epigenetic features. Two independent cohorts containing 482 HGS-OvCa samples and in vitro experiments were used for validation. Findings: We identified immune and normal groups where the former was enriched in signatures that reflect immune cells, infiltration, and PD-1 signalling (all, P<0·001), and presented with a lower burden of chromosomal aberrations but significantly increased neoantigens, tumour mutation burden, and microsatellite instability (all, P<0·05); this group was further refined into two microenvironment-based subtypes characterized by either immunoactivation or carcinoma-associated fibroblasts (CAFs) and distinct prognosis. The CAFs-immune subtype was enriched for factors that mediate immunosuppression and promote tumour progression, including highly expressed stromal signature, TGF-β signalling, epithelial-mesenchymal transition, and tumour-associated M2-polarized macrophages (all, P<0·001). The robustness of these immune-specific subtypes were verified in validation cohorts, and in vitro experiments indicated the activated-immune subtype can benefit from anti-PD1 antibody therapy (P<0·05). Interpretation: Our findings revealed two distinct immune subtypes with different responses to immunotherapy and indicate some HGS-OvCas may be susceptible to immunotherapies or combination therapies. Funding Statement: This work was supported by the Fundamental Research Funds for the Central Universities grants of China (Grant No. 2632018FY04); the “Double First-Class” University project (CPU2018GY09); the National Natural Science Foundation of China (81973145). Declaration of Interests: The authors declare no conflict of interest. Ethics Approval Statement: Not required.