Frontiers in Immunology | |
CD4+ conventional T cells-related genes signature is a prognostic indicator for ovarian cancer | |
Immunology | |
Tian Hua1  Shao-teng Li2  Shu-bo Chen2  Deng-xiang Liu2  Xiao-chong Zhang2  Qun Zhao3  Peng Yan4  | |
[1] Department of Gynecology, Affiliated Xingtai People Hospital of Hebei Medical University, Xingtai, China;Department of Oncology, Affiliated Xingtai People Hospital of Hebei Medical University, Xingtai, China;Department of Oncology, Hebei Medical University, Fourth Hospital, Shijiazhuang, China;Hebei Key Laboratory of Precision Diagnosis and Comprehensive Treatment of Gastric Cancer, Shijiazhuang, China;Department of Oncology, The Second Affiliated Hospital Of Xingtai Medical College, Xingtai, China; | |
关键词: ovarian cancer; CD4+ conventional T cells; prognostic signature; tumor microenvironment; immunotherapy; | |
DOI : 10.3389/fimmu.2023.1151109 | |
received in 2023-01-25, accepted in 2023-03-16, 发布年份 2023 | |
来源: Frontiers | |
![]() |
【 摘 要 】
IntroductionIt is believed that ovarian cancer (OC) is the most deadly form of gynecological cancer despite its infrequent occurrence, which makes it one of the most salient public health concerns. Clinical and preclinical studies have revealed that intratumoral CD4+ T cells possess cytotoxic capabilities and were capable of directly killing cancer cells. This study aimed to identify the CD4+ conventional T cells-related genes (CD4TGs) with respect to the prognosis in OC.MethodsWe obtained the transcriptome and clinical data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. CD4TGs were first identified from single-cell datasets, then univariate Cox regression was used to screen prognosis-related genes, LASSO was conducted to remove genes with coefficient zero, and multivariate Cox regression was used to calculate riskscore and to construct the CD4TGs risk signature. Kaplan-Meier analysis, univariate Cox regression, multivariate Cox regression, time-dependent receiver operating characteristics (ROC), decision curve analysis (DCA), nomogram, and calibration were made to verify and evaluate the risk signature. Gene set enrichment analyses (GSEA) in risk groups were conducted to explore the tightly correlated pathways with the risk group. The role of riskscore has been further explored in the tumor microenvironment (TME), immunotherapy, and chemotherapy. A risk signature with 11 CD4TGs in OC was finally established in the TCGA database and furtherly validated in several GEO cohorts.ResultsHigh riskscore was significantly associated with a poorer prognosis and proven to be an independent prognostic biomarker by multivariate Cox regression. The 1-, 3-, and 5-year ROC values, DCA curve, nomogram, and calibration results confirmed the excellent prediction power of this model. Compared with the reported risk models, our model showed better performance. The patients were grouped into high-risk and low-risk subgroups according to the riskscore by the median value. The low-risk group patients tended to exhibit a higher immune infiltration, immune-related gene expression and were more sensitive to immunotherapy and chemotherapy.DiscussionCollectively, our findings of the prognostic value of CD4TGs in prognosis and immune response, provided valuable insights into the molecular mechanisms and clinical management of OC.
【 授权许可】
Unknown
Copyright © 2023 Hua, Liu, Zhang, Li, Yan, Zhao and Chen
【 预 览 】
Files | Size | Format | View |
---|---|---|---|
RO202310108586582ZK.pdf | 4794KB | ![]() |