通过精神分裂症差异基因建立针对结肠癌的预后分析及预测模型

A Prognosis Analysis and Prediction Model for Colon Cancer Based on Differential Genes of Schizophrenia

目的 本研究旨在探索精神分裂症与结肠癌之间差异基因的相关性,以及这些差异基因对结肠癌发生发展的影响,并建立结肠癌预后生存的风险评估模型。方法 从基因表达综合数据库(GEO)中选取精神分裂症(SCZ)数据集,并从TCGA数据库获得结肠癌(COAD)相关基因。对SCZ数据集进行Limma分析,鉴定差异表达基因(DEG)。通过机器学习鉴定最小绝对收缩和选择运算符(Lasso-Cox)回归用于识别与COAD生存预后相关的候选基因,并最终得到4个风险相关基因用于建立COAD的风险模型。绘制ROC曲线和Kaplan-Meier(KM)分析曲线用于评估模型的诊断效果和预后生存能力。然后建构预后模型并验证其预测性能。最后我们对这4个基因进行GSVA富集分析和免疫浸润分析以探讨其与COAD预后相关的可能机制。结果 通过筛选,我们找到了4个与COAD预后相关的候选基因(ATP6V1B1、C1orf61、CCKBR、CRHR1),并构建了预测模型(C-index为:0.750)(AUC 1年0.84,AUC 3年0.80,AUC 5年0.80)(KM中P=2.3×10-10)。这些基因显示出较高的诊断和预测价值。此外,这4个基因与免疫细胞浸润有较强的关系,可能是导致COAD预后差异的原因。结论 本研究成功建构了一个包含4个候选基因的预后模型,具有较高的诊断和预测价值。这些基因可能与免疫细胞浸润有关,为揭示COAD的预后差异提供了新的视角。

Objective This study aims to explore the correlation between different genes between schizophrenia and colon cancer,as well as the impact of these differential genes on the development of colon cancer,and to establish a risk assessment model of prognosis of colon cancer.Methods We extracted schizophrenia(SCZ)data sets from gene expression comprehensive database(GEO),and obtained colon cancer-related genes from the TCGA database.Limma analysis was performed on the SCZ dataset to identify the differential expression gene(DEG).The minimum absolute shrinkage and selection of the operator(Lasso-Cox)regression through machine learning was conducted to identify candidate genes related to the prognosis of Coad,and obtained 4 risk-related genes used to establish a COAD risk model.Receiver operation characteristic curve(ROC CURVE)and Kaplan-Meier(KM Analysis)curve were drawn for assessing the diagnostic effect and prognosis of the model.We then constructed a prognostic model and verified its predictive performance.Finally,we conducted GSVA enrichment analysis and immune infiltration analysis of these four genes to explore the possibility of the prognosis related to Coad.Results By screening steps,we found 4 candidate genes related to the prognosis of COAD(ATP6V1B1,C1ORF61,CCKBR,CRHR1),and constructed the predictive model(C-Index to 0.750)(AUC1 year 0.84,AUC3 year 0.80,AUC5 year 0.80)(P=2.3×10^(-10)).These genes showed a high diagnosis and predictive value.In addition,these four genes had a strong relationship with the infiltration of immune cells,which might be the cause of the prognostic difference.Conclusion This study has successfully constructed a prognostic model containing 4 candidate genes,with a high diagnosis and predictive value.These genes may be related to the infiltration of immune cells,which can provide a novel perspective for revealing the prognostic differences of Coad.