基于TCGA数据库构建喉鳞状细胞癌免疫相关基因预后模型及筛选靶向分子药物

doi:10.6040/j.issn.1673-3770.0.2021.471

摘要/Abstract

摘要： 目的基于综合生物信息学分析,构建喉鳞状细胞癌(LSCC)预后模型,并筛选出LSCC的靶向分子药物。方法从TCGA数据库下载123个LSCC和正常对照样本的基因表达矩阵及患者临床信息,进行综合生物信息学分析,包括加权基因共表达网络分析(WGCNA),预后相关的免疫基因(PI-genes)的鉴定,LSCC预后模型的构建及其差异基因分析、生存分析、风险分析、独立预后分析和ROC曲线绘制,以及LSCC潜在靶向药物的筛选。结果对1 352个免疫相关mRNAs(I-mRNAs)和各临床性状构建了加权基因共表达网络,找到了2个与LSCC患者生存状态最相关的模块(棕色和红色模块)。然后鉴定了26个PI-genes,构建了基于8个候选PI-genes(CPI-genes)(KC877982.1、AC017100.1、AATBC、LINC02031、ULBP1、SEMA6C、NRTN和CALCB)的LSCC预后模型。通过后续分析可知,该预后模型可预测高、低风险组患者的生存及风险预后,并验证了预后模型的独立预测能力及预测准确性。最后鉴定了5个LSCC的潜在靶向药物(Rilmenidine、Hycanthone、Anisomycin、Megestrol和AR-A014418)。结论构建了基于8个CPI-genes 的LSCC预后模型,筛选了5个潜在的靶向分子药物,有望对LSCC的预后预测及精准治疗提供新思路。

Abstract: Objective To construct a prognostic model of laryngeal squamous cell carcinoma(LSCC)and screen for targeted molecular drugs for LSCC based on a comprehensive bioinformatics analysis. Methods The gene expression matrix and patient clinical information for 123 LSCC and normal control samples were downloaded from the TCGA database and a comprehensive bioinformatics analysis was performed. The analyses included weighted gene co-expression network analysis(WGCNA); identification of prognostic immune genes(PI-genes); construction of an LSCC prognostic model; differential gene, survival, risk, and independent prognostic analyses; ROC curve drawing, and screening for potential LSCC target drugs. Results A weighted gene co-expression network of 1 352 immune-associated mRNAs(I-mRNAs)and clinical traits was constructed, and two modules(brown and red)that were the most correlated with the survival status of patients with LSCC were identified. Then, 26 PI-genes were identified and a prognostic model for LSCC was constructed based on 8 candidate PI-genes(CPI-genes)(KC877982.1, AC017100.1, AATBC, LINC02031, ULBP1, SEMA6C, NRTN, and CALCB). Subsequent analyses indicated that our prognostic model could predict the survival and risk prognosis of patients in the high- and low-risk groups and verified the independent predictive ability and accuracy of the prognostic model. Finally, five potential targets of LSCC(rilmenidine, hycanthone, anisomycin, megestrol, and AR-A014418)were identified. Conclusion Eight CPI-genes based on the prognostic model of LSCC were constructed, and five potential targeted molecular drugs were screened. This is expected to provide a new direction for prognosis prediction and precise treatment of LSCC.

Key words: Laryngeal squamous cell carcinoma, Immune-associated genes, Prognostic model, Targeted drugs, Bioinformatics analysis

中图分类号:

R739.65

张永红,张辉,王彩华,杨欣欣,吴允刚,赵玉凤,庞太忠,李晓瑜. 基于TCGA数据库构建喉鳞状细胞癌免疫相关基因预后模型及筛选靶向分子药物[J]. 山东大学耳鼻喉眼学报, 2023, 37(5): 54-62.

ZHANG Yonghong, ZHANG Hui, WANG Caihua, YANG Xinxin, WU Yungang, ZHAO Yufeng, PANG Taizhong, LI Xiaoyu. Construction of an immune-associated gene prognostic model and screening of targeted molecular drugs for laryngeal squamous cell carcinoma based on the TCGA database[J]. Journal of Otolaryngology and Ophthalmology of Shandong University, 2023, 37(5): 54-62.

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