{"title":"Heterogeneity analysis and prognostic model construction of HPV negative oral squamous cell carcinoma T cells using ScRNA-seq and bulk-RNA analysis","authors":"Chunyan Li, Zengbo Lv, Chongxin Li, Shixuan Yang, Feineng Liu, Tengfei Zhang, Lin Wang, Wen Zhang, Ruoyu Deng, Guoyu Xu, Huan Luo, Yinhong Zhao, Jialing Lv, Chao Zhang","doi":"10.1007/s10142-024-01525-6","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>T cells are involved in every stage of tumor development and significantly influence the tumor microenvironment (TME). Our objective was to assess T-cell marker gene expression profiles, develop a predictive risk model for human papilloma virus (HPV)-negative oral squamous cell carcinoma (OSCC) utilizing these genes, and examine the correlation between the risk score and the immunotherapy response.</p><h3>Methods</h3><p>We acquired scRNA-seq data for HPV-negative OSCC from the GEO datasets. We performed cell‒cell communication, trajectory, and pathway enrichment analyses of T-cell-associated genes. In addition, we constructed and validated a T-cell-associated gene prognostic model for HPV-negative OSCC patients using TCGA and GEO data and assessed the immune infiltration status of HPV-negative OSCC patients .qRT-PCR was used to detect the expression level of prognosis-related genes in different risk groups.</p><h3>Results</h3><p>ScRNA-seq was conducted on 28,000 cells derived from 14 HPV-negative OSCC samples and 6 normal samples. We identified 4,635 T cells from these cells and identified 774 differentially expressed genes(DEGs) associated with T cells across five distinct T-cell subtypes. Through the integration of bulk-RNAseq data, we established a prognostic model based on DEGs related to T cells. By separating patients into high-risk and low-risk groups according to these prognostic related genes, we can accurately predict their survival rates and the immune infiltration status of the TME.qRT-PCR results showed that compared with the patients of low risk group, the expression of PMEPA1, SH2D2A, SMS and PRDX4 were significantly up-regulated in high risk group.</p><h3>Conclusion</h3><p>This study provides a resource for understanding the heterogeneity of T cells in HPV-negative OSCC patients and associated prognostic risk models. It provides new insights for predicting survival and level of immune infiltration in patients with HPV-negative OSCC.</p></div>","PeriodicalId":574,"journal":{"name":"Functional & Integrative Genomics","volume":"25 1","pages":""},"PeriodicalIF":3.9000,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11759468/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Functional & Integrative Genomics","FirstCategoryId":"99","ListUrlMain":"https://link.springer.com/article/10.1007/s10142-024-01525-6","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
引用次数: 0
Abstract
Background
T cells are involved in every stage of tumor development and significantly influence the tumor microenvironment (TME). Our objective was to assess T-cell marker gene expression profiles, develop a predictive risk model for human papilloma virus (HPV)-negative oral squamous cell carcinoma (OSCC) utilizing these genes, and examine the correlation between the risk score and the immunotherapy response.
Methods
We acquired scRNA-seq data for HPV-negative OSCC from the GEO datasets. We performed cell‒cell communication, trajectory, and pathway enrichment analyses of T-cell-associated genes. In addition, we constructed and validated a T-cell-associated gene prognostic model for HPV-negative OSCC patients using TCGA and GEO data and assessed the immune infiltration status of HPV-negative OSCC patients .qRT-PCR was used to detect the expression level of prognosis-related genes in different risk groups.
Results
ScRNA-seq was conducted on 28,000 cells derived from 14 HPV-negative OSCC samples and 6 normal samples. We identified 4,635 T cells from these cells and identified 774 differentially expressed genes(DEGs) associated with T cells across five distinct T-cell subtypes. Through the integration of bulk-RNAseq data, we established a prognostic model based on DEGs related to T cells. By separating patients into high-risk and low-risk groups according to these prognostic related genes, we can accurately predict their survival rates and the immune infiltration status of the TME.qRT-PCR results showed that compared with the patients of low risk group, the expression of PMEPA1, SH2D2A, SMS and PRDX4 were significantly up-regulated in high risk group.
Conclusion
This study provides a resource for understanding the heterogeneity of T cells in HPV-negative OSCC patients and associated prognostic risk models. It provides new insights for predicting survival and level of immune infiltration in patients with HPV-negative OSCC.
期刊介绍:
Functional & Integrative Genomics is devoted to large-scale studies of genomes and their functions, including systems analyses of biological processes. The journal will provide the research community an integrated platform where researchers can share, review and discuss their findings on important biological questions that will ultimately enable us to answer the fundamental question: How do genomes work?