A Novel Four Mitochondrial Respiration-Related Signature for Predicting Biochemical Recurrence of Prostate Cancer

• Published in: Journal of clinical medicine 2023-01, Vol.12 (2), p.654
• Main Authors: Xia, Zhongyou, Liu, Haolin, Fan, Shicheng, Tu, Hongtao, Jiang, Yongming, Wang, Hai, Gu, Peng, Liu, Xiaodong
• Format: Article
• Language: English
• Subjects: Cancer therapies; Clinical medicine; Datasets; Genes; Genomes; Medical prognosis; Metabolism; Metastasis; Mitochondrial DNA; Nomograms; Prostate cancer; Radiation therapy; Respiration
• ISSN: 2077-0383; 2077-0383
• DOI: 10.3390/jcm12020654

The biochemical recurrence (BCR) of patients with prostate cancer (PCa) after radical prostatectomy is high, and mitochondrial respiration is reported to be associated with the metabolism in PCa development. This study aimed to establish a mitochondrial respiratory gene-based risk model to predict the BCR of PCa. RNA sequencing data of PCa were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and mitochondrial respiratory-related genes (MRGs) were sourced via GeneCards. The differentially expressed mitochondrial respiratory and BCR-related genes (DE-MR-BCRGs) were acquired through overlapping BCR-related differentially expressed genes (BCR-DEGs) and differentially expressed MRGs (DE-MRGs) between PCa samples and controls. Further, univariate Cox, least absolute shrinkage and selection operator (LASSO), and multivariate Cox analyses were performed to construct a DE-MRGs-based risk model. Then, a nomogram was established by analyzing the independent prognostic factor of five clinical features and risk scores. Moreover, Gene Set Enrichment Analysis (GSEA), tumor microenvironment, and drug susceptibility analyses were employed between high- and low-risk groups of PCa patients with BCR. Finally, qRT-PCR was utilized to validate the expression of prognostic genes. We identified 11 DE-MR-BCRGs by overlapping 132 DE-MRGs and 13 BCR-DEGs and constructed a risk model consisting of 4 genes ( , , , and ). Furthermore, we established an accurate nomogram, including a risk score and a Gleason score, for the BCR prediction of PCa patients. The GSEA result suggested the risk model was related to the PPAR signaling pathway, the cholesterol catabolic process, the organic hydroxy compound biosynthetic process, the small molecule catabolic process, and the steroid catabolic process. Simultaneously, we found six immune cell types relevant to the risk model: resting memory CD4+ T cells, monocytes, resting mast cells, activated memory CD4+ T cells, regulatory T cells (Tregs), and macrophages M2. Moreover, the risk model could affect the IC50 of 12 cancer drugs, including Lapatinib, Bicalutamide, and Embelin. Finally, qRT-PCR showed that , , and were highly expressed in PCa, while was downregulated in PCa. Collectively, a mitochondrial respiratory gene-based nomogram including four genes and one clinical feature was established for BCR prediction in patients with PCa, which could provide novel strategies for further studies.