Screening Genes Associated With Prognosis For Colon Adenocarcinoma Based On Immunization Scores And Matrix Scores

Objective:Colorectal cancer（colorectal cancer,CRC）is one of the fastest-growing malignant tumors,and the mortality rate ranks third in the world.Colon adenocarcinoma（COAD）is one of the multiple pathological types of CRC.The early diagnosis and treatment of colorectal cancer have improved,but 50%of patients still die from recurrence or distant metastasis of the disease.In this study,through bioinformatics research and analysis,the tumor microenvironment（Tumor Microenvironment,TME）-related genes related to the prognosis of COAD patients were screened,so that the prognosis evaluation of COAD patients has more reference basis.Methods:Download COAD patient gene expression data and clinical related data from The Cancer Genome Atlas（TCGA）,and use the ESTIMATE algorithm to apply the downloaded gene expression data to calculate the matrix and immune scores,according to the median of the immune/matrix scores divide COAD patients into high and low groups.Differential expression analysis was performed on samples with immune score and matrix score（FDR<0.05,|log₂FC|>1）,and the shared differentially expressed genes with immune score and matrix score were identified.By using the"cluster Profiler"R package to perform functional and pathway enrichment analysis on shared differential genes,the analysis shows that differential genes are closely related to TME.The potential prognostic value of differential genes is further explored,and the differential genes and overall survival（OS）of COAD patients are established as a Cox regression model for survival analysis.The"Survival"R package was used to perform Kaplan–Meier survival analysis,and the"survival ROC"R package was used to perform a time-varying Receiver Operating Characteristic（ROC）curve to evaluate the predictive accuracy of the prognostic risk scoring model.In addition,we are also exploring the correlation between differential genes and immune infiltrating cells.We use the TIMER（Tumor Immune Estimation Resource）website（tumor infiltrating immune cell component analysis software）to calculate the relationship between the expression of genes and immune cell infiltration.Correlation coefficient,extract correlation coefficient and p-value,use"corrplot"R package to draw correlation heat map.Results:1.There are 445 cases in the TCGA database for further analysis.According to the ESTIMATE algorithm,the matrix score ranges from-2174.75 to 5,128.50,and the immune score ranges from-831.00 to 6,078.48.2.Based on the median immunity/matrix score as the grouping criteria,differential expression analysis（FDR<0.05,|log₂FC|>1）was performed,and 1461 shared differential genes with immune score and matrix score were identified.Among the differentially expressed genes of the immune score,1719 up-regulated genes and 148down-regulated genes were identified.In the differentially expressed genes of the matrix score,2281 up-regulated genes and 75 down-regulated genes were identified.3.By using the"cluster Profiler"R package to perform function and pathway enrichment analysis on 1461 shared differential genes with immune score and matrix score,the analysis shows that differential genes are closely related to TME.4.We performed a single-factor Cox regression model analysis on the 1461 differential genes of COAD patients from the TCGA database.The analysis showed that 33 differential genes were significantly related to the patient’s OS,and then a multivariate Cox analysis was performed,showing a total of 7 differences Genes are significantly related to OS,risk score=0.147×Exp _LEP-0.315×Exp _CD1B+0.232×Exp _IRX4+0.174×Exp _NR5A1+0.157×Exp CT45A1+0.173×Exp SNCB+0.079×Exp HOXC85.According to the median risk score of 0.874,COAD patients were divided into high and low risk groups.Kaplan-Meier survival analysis was performed using the "Survival"R package.KM analysis showed that the OS of the high-risk group was significantly lower than that of the low-risk group（P<0.05）.The 5-year survival rate of the high-risk group and the low-risk group were 44.3%,respectively.And 80.2%（P=0.000）.The predictive ability of the model was evaluated by calculating the area under the ROC curve（AUC）,and the AUC value for predicting the 5-year survival period was 0.733,indicating that the model has a good predictive effect.The 7-gene joint risk model obtained by further verification,according to the ratio of 3:1,the COAD patients were randomly divided into training set and verification set for verification and analysis,and the AUC values of the two data sets（training set:0.727,verification set:0.782）All indicate that our risk assessment model can be used as an effective marker model for predicting the prognosis of COAD.6.Immune cell infiltration is usually associated with differential gene expression.IRX4,NR5A1 and CT45A1 have very limited association with immune cell infiltration;CD1B has a strong correlation with all immune cells except CD8⁺T cells and B cells;LEP has a slightly higher correlation with macrophages,neutrophils,and dendritic cells;SNCB has a slightly higher correlation with neutrophils and dendritic cells;HOXC8 has a slightly higher correlation with CD8⁺T cells,neutrophils,and dendrites The correlation between shape cells is slightly higher.Conclusion:In this study,based on immune score and matrix score,7 gene combination markers of LEP,CD1B,IRX4,NR5A1,CT45A1,SNCB,and HOXC8were established,which can be used for prognostic evaluation of COAD patients.