PDF(Pubmed)
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.
摘要：
前列腺癌（PCa）是男性泌尿系统最常见的恶性肿瘤。线粒体自噬,作为一种自噬，可以去除细胞中受损的线粒体。线粒体自噬相关基因（MRGs）已被证明在PCa的发育中起关键作用。为此,基于对PCa样本及其对照的RNA-seq和scRNA-seq数据的综合分析，本文鉴定了PCa亚型并构建了预后模型.在本文中,我们从基因表达Omnibus(GEO)和TCGA数据库下载了scRNA-seq和RNA-seq数据。基于R包“Seurat”来处理scRNA-seq数据，总共鉴定了五种细胞类型。基于R包“AUCell”并使用MRG和每个细胞群体之间的交集基因对每个细胞群体进行评分。然后将B细胞群鉴定为高得分的细胞群。RNA-seq数据中的差异表达基因基于R包“limma”进行鉴定，并与先前相交的基因相交。然后，基于单变量Cox回归分析和Lasso-Cox回归分析，筛选预后基因，并构建了风险模型(由ADH5、CAT、BCAT2,DCXR,OGT,和FUS）。该模型在内部和外部测试集上进行了验证。独立预后分析确定年龄，N级,和风险评分作为独立的预后因素。本文的风险模型和预后基因可为开发PCa的新治疗靶点提供参考。
