Integrating TCGA and single-cell sequencing data for colorectal cancer: a 10-gene prognostic risk assessment model.

ABSTRACT: Colorectal cancer represents a significant health threat, yet a standardized method for early clinical assessment and prognosis remains elusive. This study sought to address this gap by using the Seurat package to analyze a single-cell sequencing dataset (GSE178318) of colorectal cancer, thereby identifying distinctive marker genes characterizing various cell subpopulations. Through CIBERSORT analysis of colorectal cancer data within The Cancer Genome Atlas (TCGA) database, significant differences existed in both cell subpopulations and prognostic values. Employing WGCNA, we pinpointed modules exhibiting strong correlations with these subpopulations, subsequently utilizing the survival package coxph to isolate genes within these modules. Further stratification of TCGA dataset based on thes

SUBMITTER: Lu D 

PROVIDER: S-EPMC10499771 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature