Establishing and validating a prognostic model for colorectal cancer patients by integrating data from single-cell RNA sequencing and bulk RNA sequencing

作者：Qiujin Huang, Dengwei You, Zhi Huang, Zhaohui Yin, Xuya Zhao · 发表于：Research Square · 年份：2024 · DOI：10.21203/rs.3.rs-3787497/v1 · 研究领域：Cancer Immunotherapy and Biomarkers、Ferroptosis and cancer prognosis、Genetic factors in colorectal cancer

Abstract Background Colorectal adenocarcinoma (COAD) is a major global cause of mortality. While conventional RNA sequencing (RNA-seq) has been used to study its prognostic indicators, it lacks precision in identifying cellular alterations. This study aimed to develop a predictive framework for COAD by integrating scRNA-seq with conventional RNA-seq. Methods This study acquired primary RNA sequencing data from The Cancer Genome Atlas (TCGA) database and single-cell RNA sequencing data on colorectal adenocarcinoma (COAD) from the Gene Expression Omnibus (GEO) database. The t-SNE method reduced dimensionality and identified clusters. Additionally, Weighted Gene Correlation Network Analysis (WGCNA) identified crucial modules and genes with differential expression (DEGs). Cox regression analysis was utilized to construct the prognostic model and explore mutation profiles and immune statuses across different risk groups. Results Integration of scRNA-seq data from four samples revealed 15 distinct clusters covering 8 cell types. Differential analysis identified important cell types, including B cells (Naïve and Plasma cells), Endothelial cells, Epithelial cells, Monocytes, Natural Killer (NK) cells, Smooth muscle cells, and T cells (CD8+). Subsequently, a prognostic model was built using 28 genes showing differential expression, with four DEGs displaying a significant correlation with higher risk scores, poorer survival outcomes, and increased APC mutation rates. Various prognostic...