基于多数据库筛选胃癌的自噬相关基因及预后预测模型的建立

来源:用户上传      作者:罗志鹏 苗志国 金瑞日 魏海云

　　[摘要]目的通过多种癌症基因数据库构建胃癌自噬相关基因（ARGs）预后预测模型。方法从人类自噬数据库和GSEA分子特征数据库获得自噬基因，与GEO数据库得到的胃癌差异表达基因进行比对，从而筛选出胃癌ARGs。对胃癌ARGsM行富集分析及通路分析、多因素COX回归分析，筛选关键ARGs，应用R语言进行生存曲线分析、构建列线图及预测模型并对模型进行检验。结果从多种数据库下载得到胃癌差异表达基因和自噬基因，从中筛选出102个重合基因即胃癌ARGs，Lasso回归和COX多因素分析筛选最终得到2个关键ARGs，即DYNC1I1、RNASE1。基于两个基因建立1、3、5年生存期预测模型和诺莫列线图校正曲线，C值为0.68，提示该模型有相对较好的预测能力。结论本研究构建了基于DYNC1I1、RNASE1两个关键ARGs胃癌预后风险模型，该模型可有效预测胃癌患者预后。
　　[关键词]胃癌;自噬;癌症基因数据库;预后预测模型;列线图
　　[中图分类号]R735.2[文献标识码]A[文章编号]2095-0616（2022）13-0044-04
　　Establishment of autophagy related genes of gastric cancer and prognostic prediction model based on multi databases screening
　　LUO Zhipeng1MIAO Zhiguo1JIN Ruiri2WEI Haiyun1
　　1. Department of Abdominal Tumor Surgery，Jiangxi Cancer Hospital，Jiangxi，Nanchang 330029，China;2. Department of Gastroenterology，the First Affiliated Hospital of Nanchang University，Jiangxi，Nanchang 330006，China
　　[Abstract] Objective To establish the prognostic prediction model of autophagy related genes （ARGs）of gastric cancer through multi databases of cancer gene. Methods The autophagy genes obtained from human autophagy database and GSEA molecular characteristic database and the differentially expressed genes of gastric cancer obtained from GEO database were compared，so as to screen out ARGs of gastric cancer. Enrichment analysis，pathway analysis，and multivariate COX regression analysis were carried out to screen the key ARGs out of ARGs of gastric cancer. With R language，survival curve analysis was carried out，nomogram and prediction model were established，and the model was tested. Results The differentially expressed genes and autophagy genes of gastric cancer were downloaded from multi databases，and 102 coincident genes，namely ARGs of gastric cancer，were screened out. 2 key ARGs，namely DYNC1I1 and RNASE1，were finally obtained by Lasso regression and COX multivariate analysis screening. Based on the 2 genes，the prediction models of 1-，3- and 5-year survival and nomogram calibration curve were established. And the C value was 0.68，which indicated that the model had relatively good prediction ability. Conclusion Two key ARGs of gastric cancer prognosis risk models based on DYNC1I1 and RNASE1 are established，which can effectively predict the prognosis of patients with gastric cancer.
　　[Key words] Gastric cancer;Autophagy;Cancer gene database;Prognostic prediction model;Nomogram
　　胃癌是消化系统常见恶性肿瘤之一，首诊多为进展期，预后较差，且生存期短[1]。胃癌个体差异大，同一分期预后也不尽相同，目前临床常用的肿瘤标志物不能准确反映患者预后，寻找更多的生物标志物来协助预测胃癌患者预后具有重要意义。自噬是通过与溶酶体融合吞噬分解细胞质蛋白或细胞器，达到细胞代谢及更新细胞器的目的[2]，为体内重要的生物学过程，研究显示很多肿瘤的病理过程中都有自噬参与[3-4]。自噬还可能和肿瘤耐药有关[5]，因此进一步明确自噬在肿瘤中的作用对提高肿瘤的诊疗水平有较大的帮助。目前，基于自噬相关基因（autophagy relative genes，ARGs）构建的预后模型已经应用于多种癌症[6-7]，但关于胃癌ARGs预后模型仍较少。本研究通过多种数据库筛选得到胃癌ARGs，并应用COX及Lasso分析得到与胃癌患者预后相关的关键ARGs，建立预后预测模型，为胃癌患者提供新的预后预测方法。

nlc202208181413

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