丝氨酸蛋白酶抑制剂(SERPIN)家族相关基因在结肠腺癌中预后模型的建立及应用OACSTPCD

To construct a prognostic model of serine protease inhibitor(SERPIN)family-related genes in colon adenocarcinoma(COAD)was constructed by applying bioinformatics methods.Transcriptomic and clinical data of colon adenocarcinoma(COAD)were downloaded from the TCGA database and GEO database,and consistent clustering analysis of COAD patients was performed based on the expression of SERPINs family genes in the data;the data was randomly and equally divided into training set(Train)and validation set(Test).Based on the differential genes of the two subtypes,the COX regression and Lasso regression were used to construct a prognostic model using the Train set.The samples were divided into two groups of high and low risk according to the median risk score of the model,and survival curves were drawn for patients in the high and low risk groups;the predictive ability of the model was evaluated by ROC curves;the model was validated using the data from the Test group.Column line plots were constructed to assess the consistency between the predicted and actual values of patient survival rates.The ESTIMATE algorithm and CIBERSORT algorithms were utilized to assess the correlation between risk scores and tumor microenvironment(TME)as well as immune infiltration.The results showed that two subtypes were identified based on 34 SERPIN genes,and 436 prognosis-related staging differences were screened based on two subtypes.11 prognosis-related genes were identified through Lasso regression to participate in the construction of the risk model,and the high and low risk groups distinguished by model scores had significant survival differences.In addition,the column line graphs could accurately predict 1-year,3-year,and 5-year survival rates.Tumor microenvironment analysis and immune infiltration analysis showed poor immune activity in patients in the high-risk score group.In addition,the risk score model constructed by SERPIN family-related genes can predict the prognosis of COAD,which is beneficial to further guide the clinical diagnosis and treatment of COAD and improve the survival rate of patients.