Abstract
Epithelial ovarian cancer has a low response rate to immunotherapy and a complex immune microenvironment that regulates its treatment outcomes. Understanding the immune microenvironment and its molecular basis is of great clinical significance in the effort to improve immunotherapy response and outcomes. To determine the characteristics of the immune microenvironment in ovarian cancer, we stratified ovarian cancer patients into three immune subtypes (C1, C2, and C3) using immune-related genes based on gene expression data from The Cancer Genome Atlas and found that these three subtypes had significant differences in immune characteristics and prognosis. Methylation and copy number variant analysis showed that the immune checkpoint genes that influenced immune response were significantly hypermethylated and highly deleted in the immunosuppressive C3 subtype, suggesting that epigenetic therapy may be able to reverse the efficacy of immunotherapy. In addition, the mutation frequencies of BRCA2 and CDK12 were significantly higher in the C2 subtype than in the other two subtypes, suggesting that mutation of DNA repair-related genes significantly affects the prognosis of ovarian cancer patients. Our study further elucidated the molecular characteristics of the immune microenvironment of ovarian cancer, which providing an effective hierarchical method for the immunotherapy of ovarian cancer patients, and has clinical relevance to the design of new immunotherapies and a reasonable combination strategies.
Highlights
Immunotherapy is an innovative treatment for cancer that has recently received a great deal of attention and has shown significant benefits in many types of cancer, but not ovarian cancer (OC) [1, 2]
The expression values of immune-related gene (IRG) were extracted from the The Cancer Genome Atlas (TCGA) dataset, and 798 IRGs were screened after removing genes with no or low expression
Using these prognosis-related genes, the optimal number of clusters obtained by the negative matrix factorization (NMF) algorithm was 3 (Figures S1A, B); the three resulting clusters were defined as C1 (n=97), C2 (n=90), and C3 (n=175), respectively (Figure 2A)
Summary
Immunotherapy is an innovative treatment for cancer that has recently received a great deal of attention and has shown significant benefits in many types of cancer, but not ovarian cancer (OC) [1, 2]. Positive responses to immunotherapy often rely on interactions of tumor cells with immune regulation within the tumor microenvironment (TME). Recent studies have shown that an immunosuppressive TME is a major obstacle to successful implementation of tumor immunotherapy in OC patients [7, 8].
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