Wu Huili, Zhao Xiao, Zhu Tingting, Rong Di, Wang Ying, Leng Diya, Wu Daming
Department of Endodontics, The Affiliated Stomatological Hospital of Nanjing Medical University, Nanjing, China.
Department of Oral and Maxillofacial Imaging, The Affiliated Stomatological Hospital of Nanjing Medical University, Nanjing, China.
Front Genet. 2022 Jul 11;13:856671. doi: 10.3389/fgene.2022.856671. eCollection 2022.
Here, we establish a prognostic signature based on glycosyltransferase-related genes (GTRGs) for head and neck squamous cell carcinoma (HNSCC) patients. The prognostic signature of GTRGs was constructed univariate and multivariate Cox analyses after obtaining the expression patterns of GTRGs from the TCGA. A nomogram based on the signature and clinical parameters was established to predict the survival of each HNSCC patient. Potential mechanisms were explored through gene set enrichment analysis (GSEA) and immune cell infiltration, immune checkpoints, immunotherapy, and tumor mutational burden (TMB) analyses. The expression differences and prognostic efficacy of the signature were verified through the gene expression omnibus (GEO) and several online databases. The prognostic signature was constructed based on five glycosyltransferases (PYGL, ALG3, EXT2, FUT2, and KDELC1) and validated in the GSE65858 dataset. The pathways enriched in the high- and low-risk groups were significantly different. The high-risk group had higher tumor purity; lower infiltration of immune cells, such as CD8 T cells and Tregs; higher cancer-associated fibroblast (CAF) infiltration; lower immune function; and lower checkpoint expression. The signature can also be applied to distinguish whether patients benefit from immunotherapy. In addition, the high-risk group had a higher TMB and more gene mutations, including those in TP53, CSMD1, CDKN2A, and MUC17. We propose a prognostic signature based on glycosyltransferases for HNSCC patients that may provide potential targets and biomarkers for the precise treatment of HNSCC.
在此,我们为头颈部鳞状细胞癌(HNSCC)患者建立了一种基于糖基转移酶相关基因(GTRGs)的预后特征。从TCGA获取GTRGs的表达模式后,通过单变量和多变量Cox分析构建了GTRGs的预后特征。建立了基于该特征和临床参数的列线图,以预测每位HNSCC患者的生存期。通过基因集富集分析(GSEA)以及免疫细胞浸润、免疫检查点、免疫治疗和肿瘤突变负荷(TMB)分析来探索潜在机制。通过基因表达综合数据库(GEO)和几个在线数据库验证了该特征的表达差异和预后疗效。基于五种糖基转移酶(PYGL、ALG3、EXT2、FUT2和KDELC1)构建了预后特征,并在GSE65858数据集中进行了验证。高风险组和低风险组中富集的通路存在显著差异。高风险组具有更高的肿瘤纯度;免疫细胞(如CD8 T细胞和调节性T细胞)浸润较低;癌症相关成纤维细胞(CAF)浸润较高;免疫功能较低;检查点表达较低。该特征还可用于区分患者是否能从免疫治疗中获益。此外,高风险组具有更高的TMB和更多的基因突变,包括TP53、CSMD1、CDKN2A和MUC17中的基因突变。我们为HNSCC患者提出了一种基于糖基转移酶的预后特征,可为HNSCC的精准治疗提供潜在靶点和生物标志物。