Abstract

To determine whether genes associated with the tumor microenvironment can serve as markers for diagnosing and monitoring ovarian cancer progression was analyzed, using the clinical data of 169 ovarian cancer individuals from the cancer genome atlas database. We conducted univariate Cox regression analysis using 760 tumor microenvironment-related gene expression values as continuous variables to conduct differential analysis, generate risk score model and verify diagnostic model; tumor microenvironment differential gene function enrollment was carried. Univariate Cox regression analysis estimated the differential analysis, generated risk score calculation and diagnostic model verification and develop TME differential gene function enrollment. The ovarian cancer patients in our hospital from January 2020 to January 2023 were tested for potential selected genes as diagnostic markers. The expression of tumor microenvironment was closely related to the development and diagnosis of ovarian cancer. The optimal number of differential genes was 15, among which the genes of branched chain amino acid aminotransferase and enhancer of zeste homolog 2 were significant. These genes were enriched in the extracellular matrix organization and extracellular matrix receiver interaction pathway. The two genes, branched chain amino acid aminotransferase and enhancer of zeste homolog 2 were utilized as clinical markers to predict ovarian cancer patients at different stages, and the accuracy rate met the standard. Tumor microenvironment related genes can serve as effective clinical markers for the diagnosis and progression of ovarian cancer.