Jiwei Sun1,2,3, Fengyuan Guo1,2,3, Qingming Tang1,2,3, Guangjin Chen1,2,3, Jinfeng Peng1,2,3, Yufeng Shen1,2,3, Junyuan Zhang1,2,3, Jingqiong Hu4, Cheng Yang1,2,3. 1. Department of Stomatology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology Wuhan 430022, Hubei, China. 2. School of Stomatology, Tongji Medical College, Huazhong University of Science and Technology Wuhan 430022, Hubei, China. 3. Hubei Province Key Laboratory of Oral and Maxillofacial Development and Regeneration Wuhan 430022, Hubei, China. 4. Stem Cell Center, Union Hospital, Huazhong University of Science and Technology Wuhan 430022, Hubei, China.
Abstract
BACKGROUND: Tongue squamous cell carcinoma (TSCC) is one of the most common oral cancers. Immune activity is significantly related to the initiation and progression of TSCC. Systemic analysis of the immunogenomic landscape and identification of crucial immune-related genes (IRGs) would help understanding of TSCC. Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) provide multiple TSCC cases for use in an integrated immunogenomic study. METHODS: Immune landscape of TSCC was depicted by expression microarray data from GSE13601 and GSE34105. Univariate Cox analysis, in combination with survival analysis, was applied to select candidate IRGs with significant survival value. Survival predicting models were constructed by multivariate Cox regression and logistic regression analysis. Unsupervised clustering analysis was used to construct an immune gene panel based on prognostic IRGs to distinguish TSCC subgroups with different prognostic outcomes. Finally, IHC staining was performed to validate the clinical value of this immune-gene panel. RESULTS: Differentially expressed IRGs were identified in two TSCC microarray datasets. Functional enrichment analysis revealed that ontology terms associated with variations in T cell function, were highly enriched. Infiltration status of activated CD8+ T cells, central memory CD4+ T cells and type 17 T helper cells, had great prognostic value for TSCC progression. Unsupervised clustering analysis was further performed to classify TSCC patients into three subgroups. CTSG, CXCL13, and VEGFA were finally combined together to form an immune-gene panel, todistinguish different TSCC subgroups. IHC staining of TSCC sections further validated the clinical efficiency of the immune-gene panel consisting of prognostic IRGs to distinguish TSCC patients. CONCLUSION: VEGFA, CXCL13, and CTSG, correlated with T cell infiltration and prognostic outcome. They were screened to form an immune-gene panel to identify TSCC subgroups with different prognostic outcomes. Clinical IHC further validated the efficacy of this immune-gene panel to evaluate aggressiveness of TSCC development. AJTR
BACKGROUND: Tongue squamous cell carcinoma (TSCC) is one of the most common oral cancers. Immune activity is significantly related to the initiation and progression of TSCC. Systemic analysis of the immunogenomic landscape and identification of crucial immune-related genes (IRGs) would help understanding of TSCC. Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) provide multiple TSCC cases for use in an integrated immunogenomic study. METHODS: Immune landscape of TSCC was depicted by expression microarray data from GSE13601 and GSE34105. Univariate Cox analysis, in combination with survival analysis, was applied to select candidate IRGs with significant survival value. Survival predicting models were constructed by multivariate Cox regression and logistic regression analysis. Unsupervised clustering analysis was used to construct an immune gene panel based on prognostic IRGs to distinguish TSCC subgroups with different prognostic outcomes. Finally, IHC staining was performed to validate the clinical value of this immune-gene panel. RESULTS: Differentially expressed IRGs were identified in two TSCC microarray datasets. Functional enrichment analysis revealed that ontology terms associated with variations in T cell function, were highly enriched. Infiltration status of activated CD8+ T cells, central memory CD4+ T cells and type 17 T helper cells, had great prognostic value for TSCC progression. Unsupervised clustering analysis was further performed to classify TSCC patients into three subgroups. CTSG, CXCL13, and VEGFA were finally combined together to form an immune-gene panel, todistinguish different TSCC subgroups. IHC staining of TSCC sections further validated the clinical efficiency of the immune-gene panel consisting of prognostic IRGs to distinguish TSCC patients. CONCLUSION: VEGFA, CXCL13, and CTSG, correlated with T cell infiltration and prognostic outcome. They were screened to form an immune-gene panel to identify TSCC subgroups with different prognostic outcomes. Clinical IHC further validated the efficacy of this immune-gene panel to evaluate aggressiveness of TSCC development. AJTR
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