Single‐cell transcriptomes reveal heterogeneity of high‐grade serous ovarian carcinoma

Abstract

Abstract Background High‐grade serous ovarian carcinoma (HGSOC) is the most common and aggressive histotype of epithelial ovarian cancer. The heterogeneity and molecular basis of this disease remain incompletely understood. Methods To address this question, we have performed a single‐cell transcriptomics analysis of matched primary and metastatic HGSOC samples. Results A total of 13 571 cells are categorized into six distinct cell types, including epithelial cells, fibroblast cells, T cells, B cells, macrophages, and endothelial cells. A subset of aggressive epithelial cells with hyperproliferative and drug‐resistant potentials is identified. Several new markers that are highly expressed in epithelial cells are characterized, and their roles in ovarian cancer cell growth and migration are further confirmed. Dysregulation of multiple signaling pathways, including the translational machinery, is associated with ovarian cancer metastasis through the trajectory analysis. Moreover, single‐cell regulatory network inference and clustering (SCENIC) analysis reveals the gene regulatory networks and suggests the JUN signaling pathway as a potential therapeutic target for treatment of ovarian cancer, which is validated using the JUN/AP‐1 inhibitor T‐5224. Finally, our study depicts the epithelial‐fibroblast cell communication atlas and identifies several important receptor‐ligand complexes in ovarian cancer development. Conclusions This study uncovers new molecular features and the potential therapeutic target of HGSOC, which would advance the understanding and treatment of the disease.

Keywords

• chemoresistance
• gene regulatory network
• intercellular communication
• metastasis
• single‐cell RNA‐seq