Single-cell RNA sequencing in ovarian cancer: decoding the tumor microenvironment for personalized therapy.

Abstract

Ovarian cancer (OC) remains a leading cause of mortality among gynecological malignancies, largely due to profound inter- and intra-tumoral heterogeneity and the critical influence of the tumor microenvironment (TME). Comprising immune, stromal, endothelial, and extracellular matrix components, the TME orchestrates tumor progression, metastasis, and therapeutic resistance. Single-cell RNA sequencing (scRNA-seq) has revolutionized the study of OC by providing high-resolution insights into rare cellular subpopulations, dynamic transcriptional programs, and intercellular communication networks. These advances have facilitated the discovery of prognostic biomarkers, immune signatures, and novel therapeutic targets. Moreover, integration of scRNA-seq with spatial transcriptomics, multi-omics platforms, and artificial intelligence has expanded its potential to capture cellular complexity and refine patient stratification. Despite current challenges, including underrepresentation of specific cell types, technical variability, and high cost, scRNA-seq continues to drive progress in precision oncology. This review highlights recent applications of single-cell technologies in ovarian cancer, underscores their role in decoding TME biology, and explores future directions toward clinical translation and personalized therapeutic strategies.