Integrating single-cell RNA-sequencing and bulk RNA-sequencing data to explore the role of mitophagy-related genes in prostate cancer

Abstract

Prostate cancer (PCa) is the most common malignancy of the male urinary system. Mitophagy, as a type of autophagy, can remove damaged mitochondria in cells. Mitophagy-related genes (MRGs) have been shown to play critical roles in the development of PCa. To this end, based on the comprehensive analysis of RNA-seq and scRNA-seq data of PCa samples and their controls, this paper identified PCa subtypes and constructed a prognostic model. In this paper, we downloaded scRNA-seq and RNA-seq data from Gene Expression Omnibus (GEO) and TCGA database. Based on the R package “Seurat” to process the scRNA-seq data, a total of five cell types were identified. Each cell population was scored based on the R package “AUCell” and using the intersection genes between MRGs and each cell population. The B cell population was then identified as a high-scoring cell population. Differentially expressed genes in RNA-seq data were identified based on the R package “limma” and intersected with previously intersected genes. Then, based on univariate Cox regression analysis and Lasso-Cox regression analysis, the prognostic genes were screened, and the risk model was constructed (composed of ADH5, CAT, BCAT2, DCXR, OGT, and FUS). The model is validated on internal and external test sets. Independent prognostic analysis identified age, N stage, and risk score as independent prognostic factors. This paper's risk models and prognostic genes can provide a reference for developing novel therapeutic targets for PCa.

Keywords

• Prostate cancer
• scRNA-seq
• RNA-seq
• Biomarkers
• Mitophagy-related genes
• Prognosis model