Abstract
Ovarian cancer (OC) is one of the most malignant tumors whose mortality rate ranks first in gynecological tumors. Although immunotherapy sheds new light on clinical treatments, the low response still restricts its clinical use because of the unique characteristics of OC such as immunosuppressive microenvironment and unstable genomes. Further exploration on determining an efficient biomarker to predict the immunotherapy response of OC patients is of vital importance. In this study, integrative analyses were performed systematically using transcriptome profiles and somatic mutation data from The Cancer Genome Atlas (TCGA) based on the immune microenvironment and genomic instability of OC patients. Firstly, intersection analysis was conducted to identify immune-related differentially expressed genes (DEGs) and genomic instability-related DEGs. Secondly, Apolipoprotein B MRNA Editing Enzyme Catalytic Subunit 3A (APOBEC3A) was recognized as a protective factor for OC, which was also verified through basic experiments such as quantitative reverse transcription PCR (RT-qPCR), immunohistochemistry (IHC), Cell Counting Kit-8 (CCK-8), and transwell assays. Thirdly, the correlation analyses of APOBEC3A expression with tumor-infiltrating immune cells (TICs), inhibitory checkpoint molecules (ICPs), Immunophenoscores (IPS), and response to anti-PD-L1 immunotherapy were further applied along with single-sample GSEA (ssGSEA), demonstrating APOBEC3A as a promising biomarker to forecast the immunotherapy response of OC patients. Last, the relationship between APOBEC3A expression with tumor mutation burden (TMB), DNA damage response (DDR) genes, and m6A-related regulators was also analyzed along with the experimental verification of immunofluorescence (IF) and RT-qPCR, comprehensively confirming the intimate association of APOBEC3A with genomic instability in OC. In conclusion, APOBEC3A was identified as a protective signature and a promising prognostic biomarker for forecasting the survival and immunotherapy effect of OC patients, which might accelerate the clinical application and improve immunotherapy effect.