Integrated single-cell sequencing and transcriptome sequencing to reveal a 9-gene prognostic signature of immune cells in colorectal cancer

Abstract

Background and purpose: Colorectal carcinoma (CRC) is a common malignant tumor with incidence and mortality rates second only to gastric cancer and esophageal cancer among digestive system malignancies. Increasing evidence suggests that immune cells play a significant role in the occurrence and development of CRC. The aim of this study was to construct a prognostic model related to immune cell-associated genes to predict the prognosis of CRC patients and enable precise management. Methods: Single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (RNA-seq) data, along with clinical information for colorectal cancer, were downloaded from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Differential genes of immune cell subtypes were extracted, and genes related to prognosis were screened in TCGA data using Cox regression and LASSO regression, with external validation using GSE39582 and GSE41258. The prognostic model was used to analyze chemotherapy drug sensitivity, assess immunotherapy efficacy, analyze pathways related to risk scores, and perform clinical correlation analysis. Finally, the expression levels of model genes were validated in 10 fresh frozen CRC tissues with post-operative pathological examination and cell lines using real-time fluorescence quantitative polymerase chain reaction (RTFQ-PCR) and immunohistochemistry. All samples were approved by the Fudan University Shanghai Cancer Center Ethics Committee (No. 050432-4-2108*). Results: We defined 16 cell clusters based on the scRNA-seq dataset (GSE161277) and labeled these clusters as different cell types using the R package celldex. Differential analysis of immune cell subtypes yielded 374 differentially expressed genes. Using univariate Cox and LASSO analyses, we constructed a 9-gene risk prognostic model in CRC. This risk model exhibited reliable prognostic prediction performance and played an important role in predicting anti-tumor drug sensitivity, immunotherapy efficacy, potential molecular mechanisms, and clinical characteristics. Patients with high-risk scores had a lower probability of benefiting from immunotherapy. Conclusion: We constructed a 9-gene risk prognostic model based on the heterogeneity of immune cells in the CRC tumor microenvironment, which predicted the survival and treatment outcomes of CRC patients.

Keywords

• |colorectal carcinoma|prognostic model|cancer immunity and immunotherapy|drug screening|scrna-seq