The development of a predicti on model for ovarian cancer patients based on the monocyte/macrophage cell marker genes identified by the scRNA-seq data

Ovarian cancer is the leading cause of mortality among gynecological malignancies worldwide, accounting for approximately 140,000 deaths annually. Tumor heterogeneity represents a key feature of ovarian cancer. With the rapid development of molecular technologies, including deep sequencing, RNA sequencing, epigenomics, and proteomics, the complexity of intratumoral heterogeneity has become increasingly well understood. We conducted a comprehensive analysis of single-cell RNA sequencing (scRNA-seq) data of ovarian cancer (OC) obtained from the GEO database to precisely identify Monocyte/Macrophage cell marker genes. Subsequently, using the TCGA database as the training cohort, survival analysis, univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO) regression analysis, and multivariate Cox regression analysis were performed to construct a prognostic model based on Monocyte/Macrophage cell marker genes. The predictive performance of the prognostic model was further validated in the TCGA test cohort. A total of 108 Monocyte/Macrophage cell marker genes were identified through scRNA-seq analysis. Among them, the nine most predictive genes were selected to construct a prognostic model using the TCGA dataset. A risk score was calculated based on the expression levels of these nine genes, which stratified patients into high-risk and low-risk groups. Survival analysis demonstrated that patients in the high-risk group had significantly poorer overall survival (OS) than those in the low-risk group in both the training cohort and the test set. Multivariate analysis further confirmed that the risk score served as an independent prognostic factor. Ultimately, we successfully established and validated a predictive risk model for ovarian cancer, and the expression of the selected genes was further validated by immunohistochemistry (IHC) in 44 ovarian cancer patients. This study highlights the potential significance of these genes in evaluating patient prognosis and may contribute to the development of targeted or personalized therapeutic strategies for ovarian cancer. The nine Monocyte/Macrophage cell marker genes identified through scRNA-seq analysis may serve as potential biomarkers for predicting the prognosis of OC patients. These findings provide a new perspective for therapeutic strategies and may contribute to improving clinical outcomes in ovarian cancer patients.