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

Yuqi Luo; Xuesong Deng; Weihua Liao; Yiwen Huang; Caijie Lu

doi:10.3389/fgene.2023.1109683

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

Front Genet. 2023 Mar 30:14:1109683. doi: 10.3389/fgene.2023.1109683. eCollection 2023.

Authors

Yuqi Luo¹, Xuesong Deng², Weihua Liao³, Yiwen Huang⁴, Caijie Lu¹

Affiliations

¹ Department of Gastrointestinal and Hepatobiliary Surgery, Shenzhen Longhua District Central Hospital, Shenzhen, Guangdong, China.
² Department of Hepatobiliary Surgery, Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University, Shenzhen, Guangdong, China.
³ Department of Radiology, Guangzhou Nansha District Maternal and Child Health Hospital, Guangzhou, Guangdong, China.
⁴ Department of Emergency, Nansha Hospital, Guangzhou First People's Hospital, Guangzhou, Guangdong, China.

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.

Keywords: autophagy related genes; colorectal cancer; drug sensitivity; immune infiltration; prognostic prediction; single-cell sequencing.

Grants and funding

This study was supported by the Medical Science and Technology Project of Shenzhen Longhua District (No. 2022049), the Guangzhou Medical and Health Scientific Research Project (No. 20211A010004), the Science and Technology Planning Project of Guangzhou ((No. 202102080680 and 202201020509) and the Science and Technology Planning Project of Nansha District (No. 2021MS004).