Prognostic value of autophagy-related genes based on single-cell RNA-sequencing in colorectal cancer

Abstract

Background: Colorectal cancer (CRC) is the second most common cancer in China. Autophagy plays an important role in the initiation and development of CRC. Here, we assessed the prognostic value and potential functions of autophagy-related genes (ARGs) using integrated analysis using single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) and RNA sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA).Methods: We analyzed GEO-scRNA-seq data from GEO using various single-cell technologies, including cell clustering, and identification of differentially expressed genes (DEGs) in different cell types. Additionally, we performed gene set variation analysis (GSVA). The differentially expressed ARGs among different cell types and those between CRC and normal tissues were identified using TCGA-RNA-seq data, and the hub ARGs were screened. Finally, a prognostic model based on the hub ARGs was constructed and validated, and patients with CRC in TCGA datasets were divided into high- and low-risk groups based on their risk-score, and immune cells infiltration and drug sensitivity analyses between the two groups were performed.Results: We obtained single-cell expression profiles of 16,270 cells, and clustered them into seven types of cells. GSVA revealed that the DEGs among the seven types of cells were enriched in many signaling pathways associated with cancer development. We screened 55 differentially expressed ARGs, and identified 11 hub ARGs. Our prognostic model revealed that the 11 hub ARGs including CTSB, ITGA6, and S100A8, had a good predictive ability. Moreover, the immune cell infiltrations in CRC tissues were different between the two groups, and the hub ARGs were significantly correlated with the enrichment of immune cell infiltration. The drug sensitivity analysis revealed that the patients in the two risk groups had difference in their response to anti-cancer drugs.Conclusion: We developed a novel prognostic 11-hub ARG risk model, and these hubs may act as potential therapeutic targets for CRC.

Integrative analysis reveals a four-gene signature for predicting survival and immunotherapy response in colon cancer patients using bulk and single-cell RNA-seq data

“…scRNA-seq, an innovative methodology, allows us to precisely distinguish different cell types within tissues, providing a powerful tool to understand the complex mix of cell populations when comparing, for instance, tumor and normal tissues (18,20). Additionally, scRNA-seq has the potential to uncover crucial hub genes related to tumor initiation and cancer advancement, which could be instrumental in shaping personalized therapies for CC patients (21)(22)(23)(24)(25)(26)36).…”

“…Recent advances in scRNA-seq help categorize colorectal cancer cells, explore gene differences, and distinguish between primary tumors and metastases (18)(19)(20). A few studies have effectively combined scRNA-seq and bulkRNA-seq data to establish and validate prognostic signatures in CC (21)(22)(23)(24)(25)(26), such as identifying genes related to membrane tension and aging-related or autophagy-related genes (21)(22)(23).…”

Unveiling the role of GAS41 in cancer progression

“…Colorectal cancer (CRC) ranks as the second most common cancer in women and the third most common cancer in men [ 97 ]. Globally, approximately 10% of cancer cases and cancer-related deaths can be attributed to CRC [ 98 ].…”