{"title":"CD8+ T细胞相关基因ALDH2在头颈部鳞状细胞癌中的治疗和预后作用","authors":"Hongmei Zhang, Zhaozheng Li, Yan Zheng","doi":"10.1177/11769351221139252","DOIUrl":null,"url":null,"abstract":"<p><p>Head and neck squamous cell carcinoma (HNSC) is a widely known malignancy which is usually diagnosed late and has a poor prognosis. This study focuses on finding a new gene linked with CD8+ <i>T</i> cell infiltration as a prognostic marker for patients with HNSC. Differential analysis of transcriptomic data was performed between HNSC and control tissues from TCGA and GEO database. The CD8+ <i>T</i> cell infiltration score was quantified using single-sample gene set enrichment analysis (ssGSEA). Weighted gene co-expression network analysis (WGCNA) algorithms were used to identify key modules associated with CD8+ <i>T</i> cell infiltration. Kaplan-Meier (K-M) survival analysis was used to compare overall survival (OS) between the 2 groups. Univariate and multivariate Cox analyses were used to assess independent prognostic markers. The results showed CD8+ <i>T</i> cell infiltration score was an independent favorable prognostic marker in HNSC. Differential analysis and WGCNA identified 93 differential gene related to high CD8+ <i>T</i> infiltration. Amog the 93 genes, ALDH2 was an independent favorable prognostic marker in HNSC. ALDH2 expression was found to be much lower in HNSC, and patients with low ALDH2 expression had higher T stage and N stage. The correlation analysis showed that ALDH2 was linked with immune cell infiltration in the tumor microenvironment of HNSC. Patients having increased expression of ALDH2 tend to be sensitive to immune checkpoint inhibitors (ICIs). In addition, we showed the relationship between ALDH2 expression and chemotherapeutic drug sensitivity. In conclusion, this study identified ALDH2 as a prognostic marker, associated with CD8+ <i>T</i> cell infiltration in HNSC.</p>","PeriodicalId":35418,"journal":{"name":"Cancer Informatics","volume":"21 ","pages":"11769351221139252"},"PeriodicalIF":2.4000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/0b/19/10.1177_11769351221139252.PMC9772952.pdf","citationCount":"1","resultStr":"{\"title\":\"Identifying the Therapeutic and Prognostic Role of the CD8+ T Cell-Related Gene ALDH2 in Head and Neck Squamous Cell Carcinoma.\",\"authors\":\"Hongmei Zhang, Zhaozheng Li, Yan Zheng\",\"doi\":\"10.1177/11769351221139252\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Head and neck squamous cell carcinoma (HNSC) is a widely known malignancy which is usually diagnosed late and has a poor prognosis. This study focuses on finding a new gene linked with CD8+ <i>T</i> cell infiltration as a prognostic marker for patients with HNSC. Differential analysis of transcriptomic data was performed between HNSC and control tissues from TCGA and GEO database. The CD8+ <i>T</i> cell infiltration score was quantified using single-sample gene set enrichment analysis (ssGSEA). Weighted gene co-expression network analysis (WGCNA) algorithms were used to identify key modules associated with CD8+ <i>T</i> cell infiltration. Kaplan-Meier (K-M) survival analysis was used to compare overall survival (OS) between the 2 groups. Univariate and multivariate Cox analyses were used to assess independent prognostic markers. The results showed CD8+ <i>T</i> cell infiltration score was an independent favorable prognostic marker in HNSC. Differential analysis and WGCNA identified 93 differential gene related to high CD8+ <i>T</i> infiltration. Amog the 93 genes, ALDH2 was an independent favorable prognostic marker in HNSC. ALDH2 expression was found to be much lower in HNSC, and patients with low ALDH2 expression had higher T stage and N stage. The correlation analysis showed that ALDH2 was linked with immune cell infiltration in the tumor microenvironment of HNSC. Patients having increased expression of ALDH2 tend to be sensitive to immune checkpoint inhibitors (ICIs). In addition, we showed the relationship between ALDH2 expression and chemotherapeutic drug sensitivity. In conclusion, this study identified ALDH2 as a prognostic marker, associated with CD8+ <i>T</i> cell infiltration in HNSC.</p>\",\"PeriodicalId\":35418,\"journal\":{\"name\":\"Cancer Informatics\",\"volume\":\"21 \",\"pages\":\"11769351221139252\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/0b/19/10.1177_11769351221139252.PMC9772952.pdf\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cancer Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/11769351221139252\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATHEMATICAL & COMPUTATIONAL BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/11769351221139252","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
Identifying the Therapeutic and Prognostic Role of the CD8+ T Cell-Related Gene ALDH2 in Head and Neck Squamous Cell Carcinoma.
Head and neck squamous cell carcinoma (HNSC) is a widely known malignancy which is usually diagnosed late and has a poor prognosis. This study focuses on finding a new gene linked with CD8+ T cell infiltration as a prognostic marker for patients with HNSC. Differential analysis of transcriptomic data was performed between HNSC and control tissues from TCGA and GEO database. The CD8+ T cell infiltration score was quantified using single-sample gene set enrichment analysis (ssGSEA). Weighted gene co-expression network analysis (WGCNA) algorithms were used to identify key modules associated with CD8+ T cell infiltration. Kaplan-Meier (K-M) survival analysis was used to compare overall survival (OS) between the 2 groups. Univariate and multivariate Cox analyses were used to assess independent prognostic markers. The results showed CD8+ T cell infiltration score was an independent favorable prognostic marker in HNSC. Differential analysis and WGCNA identified 93 differential gene related to high CD8+ T infiltration. Amog the 93 genes, ALDH2 was an independent favorable prognostic marker in HNSC. ALDH2 expression was found to be much lower in HNSC, and patients with low ALDH2 expression had higher T stage and N stage. The correlation analysis showed that ALDH2 was linked with immune cell infiltration in the tumor microenvironment of HNSC. Patients having increased expression of ALDH2 tend to be sensitive to immune checkpoint inhibitors (ICIs). In addition, we showed the relationship between ALDH2 expression and chemotherapeutic drug sensitivity. In conclusion, this study identified ALDH2 as a prognostic marker, associated with CD8+ T cell infiltration in HNSC.
期刊介绍:
The field of cancer research relies on advances in many other disciplines, including omics technology, mass spectrometry, radio imaging, computer science, and biostatistics. Cancer Informatics provides open access to peer-reviewed high-quality manuscripts reporting bioinformatics analysis of molecular genetics and/or clinical data pertaining to cancer, emphasizing the use of machine learning, artificial intelligence, statistical algorithms, advanced imaging techniques, data visualization, and high-throughput technologies. As the leading journal dedicated exclusively to the report of the use of computational methods in cancer research and practice, Cancer Informatics leverages methodological improvements in systems biology, genomics, proteomics, metabolomics, and molecular biochemistry into the fields of cancer detection, treatment, classification, risk-prediction, prevention, outcome, and modeling.