Abstract / Summary
Cellular senescence is a hallmark of cancer, and senescent cancer-associated fibroblasts (seneCAFs) contribute to tumor progression across multiple malignancies. However, how seneCAFs promote high-grade serous ovarian (HGSOC) remains unclear. We integrated public single-cell RNA sequencing (scRNA-seq), spatial transcriptomic data, and clinical specimens to characterize seneCAFs and define their transcriptomic signature. A prognostic model based on the seneCAFs signature was developed using least absolute shrinkage and selection operator (LASSO)-based machine learning to predict survival outcomes. Cell-cell communication analysis was performed to identify candidate seneCAFs-derived effectors. In vitro and in vivo functional assays were conducted to investigate the pro-tumorigenic role of seneCAFs and the regulatory mechanisms governing the expression of key effector. Furthermore, pan-cancer analysis was carried out to evaluate the prognostic value of the seneCAFs risk model and the candidate effector across multiple cancer types. CAFs in HGSOC exhibited elevated cellular senescence, and the seneCAFs-based risk model predicted poor survival. Among its prognostic genes, Tenascin-C (TNC) emerged as a key seneCAFs-secreted effector that signals to tumor cells. Functional assays confirmed that seneCAFs-derived TNC promoted HGSOC progression. Mechanistically, TNC activated SDC4-ERK signaling in tumor cells to induce epithelial-mesenchymal transition (EMT), while NF-κB activation in seneCAFs transcriptionally upregulated TNC expression. Pan-cancer analysis linked high seneCAFs risk score and TNC expression to worse overall survival. The seneCAFs transcriptomic signature and its risk model stratify HGSOC patients and predict worse clinical outcomes. Our study offers a novel insight about seneCAFs promote tumor progression and identifies TNC as a potential therapeutic target for HGSOC and other solid tumors.