结直肠癌坏死性凋亡相关lncRNA预后风险模型构建

Construction of a Prognostic Risk Model for Necroptosis-associated LncRNA in Colorectal Cancer

目的基于生物信息学和机器学习算法,筛选并构建结直肠癌坏死性凋亡相关lncRNA预后风险模型,分析模型在结直肠癌患者预后评估及抗癌药物敏感性的预测价值。方法TCGA数据库下载结直肠癌样本的RNA-seq数据和临床信息,使用差异分析及Spearman相关分析获取坏死性凋亡相关lncRNA;单因素Cox、多因素Cox回归分析方法构建最优模型,并评估模型的独立预后价值;使用pRRophetic包分析模型在抗癌治疗药物应用中指导价值;结合临床信息构建列线图评估列线图的临床应用价值。结果预后模型共纳入7个lncRNA,模型的风险评分可以作为结直肠癌的独立预后因子,高风险组的患者均表现为较差的生存率,对7种抗癌药物敏感性低,对6种抗癌药物敏感性高。依据模型构建的列线图具有较精准的生存预测价值。结论坏死性凋亡相关lncRNA预后风险模型为结直肠癌的独立预后因子,可有效预测结直肠癌患者的生存预后,并可作为抗癌药物选择的重要指标。

Objective Based on bioinformatics and machine learning methods,we screened and constructed a prognostic risk model for necroptosis-related lncRNA in colorectal cancer,and analyzed the predictive value of the model in prognostic assessment and anticancer drug sensitivity in CRC patients. Methods RNA-seq data and clinical information of colorectal cancer samples were downloaded from TCGA database,and necroptosisrelated lncRNAs were obtained using difference analysis and Spearman correlation methods. Univariate Cox,machine learning and multivariate Cox regression analysis methods were used to construct the optimal model.And then the independent prognostic value of the model was evaluated. The application value of the model in drug sensitivity analysis of anticancer therapeutics was analyzed using the p RRophetic package. Finally,the nomogram was constructed by combining clinical information and risk scores,and the clinical application value of the nomogram was evaluated. Results A total of 7 lncRNAs were included in the prognostic model,and the risk score of the model could be used as an independent prognostic factor. Patients in the high-risk group all showed poor survival,and had low sensitivity to 7 anticancer drugs and high sensitivity to 6 anticancer drugs.Nomogram had a more accurate survival prediction value. Conclusion The prognostic risk model of necroptosisassociated lncRNA is an independent prognostic factor for colorectal cancer,which can effectively predict the survival prognosis of patients with colorectal cancer and can be used as an important indicator for anti-cancer drug selection.