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.

Objective: To understand the immune characteristics of the ovarian cancer (OC) microenvironment and explore the differences of immune-related molecules and cells to establish an effective risk model and identify the molecules that significantly affected the immune response of OC, to help guide the diagnosis.Methods: First, we calculate the TMEscore which reflects the immune microenvironment, and then analyze the molecular differences between patients with different immune characteristics, and determine the prognostic genes. Then, the risk model was established by least absolute shrinkage and selection operator (LASSO) analysis and combined with clinical data into a nomogram for diagnosis and prediction. Subsequently, the potential gene CLEC5A influencing the immune response of OC was identified from the prognostic genes by integrative immune-stromal analysis. The genomic alteration was explored based on copy number variant (CNV) and somatic mutation data.Results: TMEscore was a prognostic indicator of OC. The prognosis of patients with high TMEscore was better. The risk model based on immune characteristics was a reliable index to predict the prognosis of patients, and the nomogram could comprehensively evaluate the prognosis of patients. Besides, CLEC5A was closely related to the abundance of immune cells, immune response, and the expression of immune checkpoints in the OC microenvironment. OC cells with high expression of CLEC5A increased the polarization of M2 macrophages. CLEC5A expression was significantly associated with TTN and CDK12 mutations and affected the copy number of tumor progression and immune-related genes.Conclusion: The study of immune characteristics in the OC microenvironment and the risk model can reveal the factors affecting the prognosis and guide the clinical hierarchical treatment. CLEC5A can be used as a potential key gene affecting the immune microenvironment remodeling of OC, which provides a new perspective for improving the effect of OC immunotherapy.

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.

Ovarian cancer (OC) is the most lethal gynecological malignancy, in which chemoresistance is a crucial factor leading to the poor prognosis. Recently, immunotherapy has brought new light for the treatment of solid tumors. Hence, as a kind of immunologically active cancer, it is reasonably necessary to explore the potential mechanism between immune characteristics and cisplatin resistance in OC. Our study focused on the important role of cisplatin resistance-related lncRNAs on mediating the OC tumor immune microenvironment (TIME) using an integrative analysis based on the Cancer Genome Atlas (TCGA) database. First, the cisplatin resistance-related differentially expressed lncRNAs (DELs) and mRNAs (DEMs) were preliminarily screened to construct a DEL–DEM co-expression network. Next, the protein–protein interaction (PPI) network and pivot analysis were performed to reveal the relevance of these lncRNAs with tumor immune response. Second, the novel lncRNA CTD-2288O8.1 was identified as a key gene for the OC cisplatin resistance formation by qRT-PCR and survival analysis. Gain- and loss-of-function assays (Cell Counting Kit-8 (CCK-8) assay, wound-healing scratch assay, transwell assay, and colony formation assay) further verified the activity of CTD-2288O8.1 in OC progression as well. Third, gene set enrichment analysis (GSEA) was applied along with the correlation analyses of CTD-2288O8.1 with ImmuneScore, tumor-infiltrating immune cells (TICs), and immune inhibitory checkpoint molecules, illustrating that CTD-2288O8.1 was strongly associated with the TIME and has the potential to predict the effect of OC immunotherapy. In addition, basic experiments demonstrated that the expression of CTD-2288O8.1 impacted the EGFR/AKT signal pathway activity of OC tumor cells. Of greater significance, it promoted the M2 polarization of macrophage, which is a type of the most important components of the TIME in solid tumor. Taking together, our study revealed cisplatin resistance-related lncRNAs closely linked with tumor immunity in OC, underscoring the potential mechanism of the TIME in conferring cisplatin resistance, which provided the research basis for further clinical treatment. CTD-2288O8.1 was identified to mediate cisplatin resistance and affect the response of immunotherapy, which could serve as a promising biomarker for guiding clinical treatment and improving prognosis in OC.