Telomerase-Associated Genes as Prognostic Markers in High-Grade Serous Ovarian Cancer

BACKGROUND High-grade serous ovarian cancer (HGSOC) is an aggressive malignancy with poor prognosis. This study investigates telomerase-associated genes (TAGs) and their cellular interactions in HGSOC to identify novel prognostic markers. MATERIAL AND METHODS Single-cell RNA sequencing and bulk RNA sequencing data were obtained from the Gene Expression Omnibus and the Cancer Genome Atlas databases. We performed cell type identification, pseudotime trajectory analysis, and CellChat analysis for intercellular communication. A prognostic model was developed using the intersection of TAGs and HGSOC differentially expressed genes (DEGs) through univariate Cox and least absolute shrinkage and selection operator analyses. Survival prognosis, immune infiltration, and drug sensitivity analyses were conducted. RESULTS Thirty cell clusters, 12 cell types, and 2089 TAGs were identified. Pseudotime trajectory analysis suggested 3 distinct cell states during HGSOC progression. CellChat analysis indicated intercellular communication via NAMPT-INSR and SPP1 (ITGAV+ITGB1) signaling pathways. In total, 1204 DEGs were identified between the transcriptomically inferred telomerase-active and -inactive cell populations, along with 1925 DEGs between HGSOC and normal tissue samples. Intersection of these gene sets yielded 768 key TAGs. The prognostic risk model categorized patients into high-risk and low-risk groups, with significant survival differences. Immune infiltration analysis displayed differential abundance of 12 immune cell types between the groups. Drug sensitivity analysis suggested a potential association between the low-risk group and increased sensitivity to certain therapeutic agents. Mutations in TP53 and TTN were frequently observed across both risk groups. CONCLUSIONS This study generates the hypothesis that TAGs are linked to HGSOC progression and yields a candidate prognostic model.