ArticleOncology research2023
System analysis based on the T cell exhaustion‑related genes identifies CD38 as a novel therapy target for ovarian cancer.
Article in Oncology research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 7 citations in OpenAlex.
- CD38 contributes to tumor progression and tumor microenvironment reshaping in epithelial ovarian cancer.Translational oncology · 2025Article
- Bioinformation study of immune microenvironment characteristics of disulfidptosis-related subtypes in ovarian cancer and prognostic model construction.Discover oncology · 2025Article
- Deciphering T-cell exhaustion in the tumor microenvironment: paving the way for innovative solid tumor therapies.Frontiers in immunology · 2025Review
- Exploring the role of ADAMTSL2 across multiple cancer types: A pan-cancer analysis and validated in colorectal cancer.Discover oncology · 2024Article
- Editorial: Transcriptome analysis in tumor microenvironment and tumor heterogeneity.Oncology research · 2023Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ovarian cancer (OV) is highly heterogeneous tumor with a very poor prognosis. Studies increasingly show that T cell exhaustion is prognostically relevant in OV. The aim of this study was to dissect the heterogeneity of T cell subclusters in OV through single cell transcriptomic analysis. The single RNA-sequencing (scRNA-seq) data of five OV patients were analyzed, and six major cell clusters were identified after threshold screening. Further clustering of T cell-associated clusters revealed four subtypes. Pathways related to oxidative phosphorylation, G2M checkpoint, JAK-STAT and MAPK signaling were significantly activated, while the p53 pathway was inhibited in the CD8+ exhausted T cells. The standard marker genes of CD8+ T cell exhaustion were screened to develop a T-cell related gene score (TRS) based on random forest plots in TCGA cohort. The patients with low TRS have better prognosis compared to the patients with high TRS in both TCGA and GEO. In addition, most genes included in the TRS showed significant differences in expression levels between the high- and low-risk groups. Immune cell infiltration was analyzed using the MCPcounter and xCell algorithms, which revealed significant differences between the two risk groups, indicating that the different prognoses may stem from the respective immune landscapes. In addition, CD38 knockdown in OV cell lines increased apoptosis and inhibited invasion
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