Department of Otolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, China.
Eur Arch Otorhinolaryngol. 2021 Sep;278(9):3523-3531. doi: 10.1007/s00405-021-06717-5. Epub 2021 Mar 8.
The aim of the study is to identify a reliable gene panel to predict the prognosis of HNSCC patients by integrated genomic analysis.
Co-expression gene networks were constructed by WGCNA using GSE113282 gene expression profile. The biological functional investigation was performed by GO and KEGG function enrichment analysis. The hub gene module was screened by PPI. The prognostic gene panel was established by Lasso regression analysis, and further progression-free survival (PFS) analysis was validated by Kaplan-Meier survival analysis using GSE102995 data.
We identified 195 genes associated with the overall survival (OS) status (correlation coefficients: - 0.42, and p value: 2e-05) by WGCNA. These genes were enriched in immune-related cytokines and pathways analyzed by GO and KEGG. Among the 195 genes, the module (42 genes) with the highest score was screened by PPI. A novel seven-gene predictive panel (CD19, CD40LG, CD5, CXCR6, FPR2, NCAM1, and SELL) was established by Lasso regression analysis, and the area under ROC curve (AUC) for 3-year OS status was 0.8298 and 0.7571, respectively, in the training set and the test set. The PFS time of the low-risk patients was significantly longer than the high-risk patients (p < 0.0001; log-rank test) by further validation using GSE102995 data.
The seven-gene panel may serve as a reliable predictive tool for HNSCC patients treated with platinum-based radio (chemo) therapy, and may be potential therapeutic targets for HNSCC patients.
本研究旨在通过综合基因组分析，确定一个可靠的基因谱，以预测头颈部鳞状细胞癌（HNSCC）患者的预后。
利用 WGCNA 构建共表达基因网络，使用 GSE113282 基因表达谱进行分析。通过 GO 和 KEGG 功能富集分析进行生物功能研究。通过 PPI 筛选枢纽基因模块。通过 Lasso 回归分析建立预后基因谱，并使用 GSE102995 数据进行 Kaplan-Meier 生存分析进行进一步的无进展生存期（PFS）分析验证。
我们通过 WGCNA 确定了 195 个与总生存期（OS）状态相关的基因（相关系数：-0.42，p 值：2e-05）。这些基因在 GO 和 KEGG 分析中富集于免疫相关细胞因子和途径。在 195 个基因中，通过 PPI 筛选出得分最高的模块（42 个基因）。通过 Lasso 回归分析建立了一个新的七基因预测谱（CD19、CD40LG、CD5、CXCR6、FPR2、NCAM1 和 SELL），在训练集和测试集中，3 年 OS 状态的 AUC 分别为 0.8298 和 0.7571。通过进一步使用 GSE102995 数据进行验证，低风险患者的 PFS 时间明显长于高风险患者（p<0.0001；log-rank 检验）。
该七基因谱可作为接受铂类放射（化疗）治疗的 HNSCC 患者的可靠预测工具，可能成为 HNSCC 患者的潜在治疗靶点。
