{"title":"整合单细胞RNA-Seq和大容量RNA-Seq,构建与γδT细胞相关的新型人乳头状瘤病毒感染宫颈癌预后特征。","authors":"Xiaochuan Wang, Yichao Jin, Liangheng Xu, Sizhen Tao, Yifei Wu, Chunping Ao","doi":"10.1177/10732748241274228","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Gamma delta (γδ) T cells play dual roles in human tumors, with both antitumor and tumor-promoting functions. However, the role of γδT cells in HPV-infected cervical cancer is still undetermined. Therefore, we aimed to identify γδT cell-related prognostic signatures in the cervical tumor microenvironment.</p><p><strong>Methods: </strong>Single-cell RNA-sequencing (scRNA-seq) data, bulk RNA-seq data, and corresponding clinical information of cervical cancer patients were obtained from the TCGA and GEO databases. The Seurat R package was used for single-cell analysis, and machine learning algorithms were used to screen and construct a γδT cell-related prognostic signature. Real-time quantitative PCR (RT-qPCR) was performed to detect the expression of prognostic signature genes.</p><p><strong>Results: </strong>Single-cell analysis indicated distinct populations of γδT cells between HPV-positive (HPV+) and HPV-negative (HPV-) cervical cancers. A trajectory analysis indicated γδT cells clustered into differential clusters with the pseudotime. High-dimensional Weighted Gene Co-expression Network Analysis (hdWGCNA) identified the key γδT cell-related gene modules. Bulk RNA-seq analysis also demonstrated the heterogeneity of immune cells, and the γδT-score was positively associated with inflammatory response and negatively associated with MYC stemness. Eight γδT cell-related hub genes (GTRGs), including ITGAE, IKZF3, LSP1, NEDD9, CLEC2D, RBPJ, TRBC2, and OXNAD1, were selected and validated as a prognostic signature for cervical cancer.</p><p><strong>Conclusion: </strong>We identified γδT cell-related prognostic signatures that can be considered independent factors for survival prediction in cervical cancer.</p>","PeriodicalId":49093,"journal":{"name":"Cancer Control","volume":null,"pages":null},"PeriodicalIF":2.5000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11363054/pdf/","citationCount":"0","resultStr":"{\"title\":\"Integrating Single-Cell RNA-Seq and Bulk RNA-Seq to Construct a Novel γδT Cell-Related Prognostic Signature for Human Papillomavirus-Infected Cervical Cancer.\",\"authors\":\"Xiaochuan Wang, Yichao Jin, Liangheng Xu, Sizhen Tao, Yifei Wu, Chunping Ao\",\"doi\":\"10.1177/10732748241274228\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Gamma delta (γδ) T cells play dual roles in human tumors, with both antitumor and tumor-promoting functions. However, the role of γδT cells in HPV-infected cervical cancer is still undetermined. Therefore, we aimed to identify γδT cell-related prognostic signatures in the cervical tumor microenvironment.</p><p><strong>Methods: </strong>Single-cell RNA-sequencing (scRNA-seq) data, bulk RNA-seq data, and corresponding clinical information of cervical cancer patients were obtained from the TCGA and GEO databases. The Seurat R package was used for single-cell analysis, and machine learning algorithms were used to screen and construct a γδT cell-related prognostic signature. Real-time quantitative PCR (RT-qPCR) was performed to detect the expression of prognostic signature genes.</p><p><strong>Results: </strong>Single-cell analysis indicated distinct populations of γδT cells between HPV-positive (HPV+) and HPV-negative (HPV-) cervical cancers. A trajectory analysis indicated γδT cells clustered into differential clusters with the pseudotime. High-dimensional Weighted Gene Co-expression Network Analysis (hdWGCNA) identified the key γδT cell-related gene modules. Bulk RNA-seq analysis also demonstrated the heterogeneity of immune cells, and the γδT-score was positively associated with inflammatory response and negatively associated with MYC stemness. Eight γδT cell-related hub genes (GTRGs), including ITGAE, IKZF3, LSP1, NEDD9, CLEC2D, RBPJ, TRBC2, and OXNAD1, were selected and validated as a prognostic signature for cervical cancer.</p><p><strong>Conclusion: </strong>We identified γδT cell-related prognostic signatures that can be considered independent factors for survival prediction in cervical cancer.</p>\",\"PeriodicalId\":49093,\"journal\":{\"name\":\"Cancer Control\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2024-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11363054/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cancer Control\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1177/10732748241274228\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Control","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/10732748241274228","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ONCOLOGY","Score":null,"Total":0}
Integrating Single-Cell RNA-Seq and Bulk RNA-Seq to Construct a Novel γδT Cell-Related Prognostic Signature for Human Papillomavirus-Infected Cervical Cancer.
Background: Gamma delta (γδ) T cells play dual roles in human tumors, with both antitumor and tumor-promoting functions. However, the role of γδT cells in HPV-infected cervical cancer is still undetermined. Therefore, we aimed to identify γδT cell-related prognostic signatures in the cervical tumor microenvironment.
Methods: Single-cell RNA-sequencing (scRNA-seq) data, bulk RNA-seq data, and corresponding clinical information of cervical cancer patients were obtained from the TCGA and GEO databases. The Seurat R package was used for single-cell analysis, and machine learning algorithms were used to screen and construct a γδT cell-related prognostic signature. Real-time quantitative PCR (RT-qPCR) was performed to detect the expression of prognostic signature genes.
Results: Single-cell analysis indicated distinct populations of γδT cells between HPV-positive (HPV+) and HPV-negative (HPV-) cervical cancers. A trajectory analysis indicated γδT cells clustered into differential clusters with the pseudotime. High-dimensional Weighted Gene Co-expression Network Analysis (hdWGCNA) identified the key γδT cell-related gene modules. Bulk RNA-seq analysis also demonstrated the heterogeneity of immune cells, and the γδT-score was positively associated with inflammatory response and negatively associated with MYC stemness. Eight γδT cell-related hub genes (GTRGs), including ITGAE, IKZF3, LSP1, NEDD9, CLEC2D, RBPJ, TRBC2, and OXNAD1, were selected and validated as a prognostic signature for cervical cancer.
Conclusion: We identified γδT cell-related prognostic signatures that can be considered independent factors for survival prediction in cervical cancer.
期刊介绍:
Cancer Control is a JCR-ranked, peer-reviewed open access journal whose mission is to advance the prevention, detection, diagnosis, treatment, and palliative care of cancer by enabling researchers, doctors, policymakers, and other healthcare professionals to freely share research along the cancer control continuum. Our vision is a world where gold-standard cancer care is the norm, not the exception.