A Prognosis Analysis and Prediction Model for Colon Cancer Based on Differential Genes of Schizophrenia
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.
SchizophreniaColon cancerMachine learningPrognostic model
万方数据
维普
