CD4+ T cells infiltrate the tumor microenvironment, but their role in high-grade serous ovarian cancer (HGSOC) progression remains unclear. Cell death-associated genes critically impact HGSOC advancement. We integrated single-cell and spatial transcriptomics to analyze CD4+ T cell heterogeneity and identify cell death-associated genes. Key candidates were experimentally validated via qPCR and Western blotting in independent HGSOC cohorts. Furthermore, a T cell–tumor cell co-culture system was employed for functional validation of candidate gene effects on tumor behavior. To comprehensively characterize the heterogeneity of CD4+ T cells in HGSOC, we performed an integrated analysis including inferCNV, pseudotime trajectory, SCENIC transcription regulatory networks, and hdWGCNA. This multi-omics approach defined distinct CD4+ T cell subgroups and identified key regulons. Notably, a co-expression network module derived from hdWGCNA was leveraged to construct a prognostic model, which demonstrated significant predictive power for patient survival. Spatial transcriptomic analysis identified co-localized niches of IL7R+CD4+ T cells and Tregs, exhibiting highly concordant gene expression with scRNA-seq data. Orthogonal validation confirmed significant dysregulation of MAL (p < 0.001) and ANXA1 (p < 0.001) in HGSOC. Critically, in vitro co-culture experiments demonstrated that silencing MAL in T cells significantly suppressed ovarian cancer cell proliferation, migration, and invasion, highlighting its functional role in modulating the tumor microenvironment. Our findings elucidate mechanisms of cell death-associated genes in CD4+ T cell subgroups, with experimentally grounded biomarkers offering therapeutic options for HGSOC.
Wu et al. (Tue,) studied this question.