Integration of scRNA-Seq and Bulk RNA-Seq to analyze the heterogeneity ofcolorectal cancer immune cells and establish a molecular risk model

Background:Colorectal cancer(CRC)is a highly heterogeneous malignant tumor that significantly impacts clinical diagnosis and treatment.Single-cell RNA sequencing is an innovative method for exploring tumor heterogeneity and understanding its role at cellular and genetic levels.Method:The colorectal cancer Single-cell RNA sequencing data were analysed on the immune.RNA-seq data in bulk form was utilized to assess the major genes of the immune cell subsets linked to CRC.We conducted an analysis of the abundance of immune cells in the microenvironment of CRC,and also performed weighted gene co-expression network analysis.Gene set enrichment analysis helped perform two analytical procedures of subtype groups.Furthermore,Least absolute shrinkage and selection operator regression was employed to analyse and screen for a gene signature.Finally,quantitative PCR Was performed to detect the expression levels of signature genes in CRC.Results:The Single-cell RNA sequencing(GSE146771)dataset was integrated to obtain 9 cell clusters.The Single-sample gene set enrichment analysis showed that the related gene expression of T-cell subsets of different functional statuses could vary greatly between patients with GSE146771.Immune cell analysis of TCGA-CRC indicated an improved overall survival rate for patients with elevated Th2 cell abundance.Five-gene signature(Risk Score=-0.205×CDC25C-0.231×GSTCD-0.010×KPNA2-0.002×KIF15-0.171×ORC1)was developed by weighted correlation network analysis,and lasso Cox regression.Then,the risk prediction efficacy of the signature was validated in four GSE datasets.Furthermore,the expression of five genes was reduced in CRC tissue by quantitative PCR.Conclusion:Five-gene signature based on CRC heterogeneity was developed as a prognosis predictor,which can serve as a potential treatment target.