Hua Bao, Yang Qing, Song Shangqing, Li Wenfeng, Xu Bin, Gu Yufei
Department of Urology, School of Medicine, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University, Shanghai, China.
Front Genet. 2025 Jul 17;16:1592779. doi: 10.3389/fgene.2025.1592779. eCollection 2025.
Prostate cancer (PCa), a highly heterogeneous cancer with a complex molecular pathogenesis, is a leading cause of cancer-related mortality among men globally. The present study presents a lipid metabolism-based risk model for PCa and explores the role of succinyl-CoA ligase GDP-forming subunit beta (SUCLG2), a potential marker and therapeutic target in PCa involved in lipid metabolism and cancer progression, from the perspective of developing effective diagnostic and therapeutic strategies.
High-throughput RNA sequencing and single-cell RNA sequencing were used to investigate the expression and functional relevance of SUCLG2 in PCa. We analyzed 497 PCa samples from The Cancer Genome Atlas and conducted a comprehensive bioinformatics analysis, including univariate Cox proportional hazards regression, least absolute shrinkage and selection operator regression, and gene set enrichment analysis. Furthermore, quantitative real-time polymerase chain reaction and immunofluorescence assays were performed to validate SUCLG2 expression in clinical samples and the prostate carcinoma epithelial cell line 22Rv1.
Our findings revealed that lipid metabolism-related genes, including SUCLG2, have significant prognostic value, based on a 16-gene risk model constructed that accurately predicted PCa prognosis. In particular, SUCLG2 was significantly enriched in luminal and basal/intermediate cell subsets, highlighting its potential role in tumor progression and therapy resistance. Drug sensitivity analysis indicated that SUCLG2 expression is correlated with the efficacy of several chemotherapeutic agents, based on which strategies for personalized therapy in PCa treatment could be devised.
SUCLG2 plays a pivotal role in the metabolic reprogramming of PCa, thus offering new insights into its progression and potential therapeutic targets. Our study underscores the importance of metabolic pathways in PCa pathogenesis and paves the way for the development of targeted therapies, thus contributing to personalized medicine in PCa management.
前列腺癌（PCa）是一种具有高度异质性且分子发病机制复杂的癌症，是全球男性癌症相关死亡的主要原因。本研究提出了一种基于脂质代谢的PCa风险模型，并从制定有效的诊断和治疗策略的角度，探讨了琥珀酰辅酶A连接酶GDP形成亚基β（SUCLG2）作为PCa中参与脂质代谢和癌症进展的潜在标志物及治疗靶点的作用。
采用高通量RNA测序和单细胞RNA测序来研究SUCLG2在PCa中的表达及功能相关性。我们分析了来自癌症基因组图谱的497份PCa样本，并进行了全面的生物信息学分析，包括单变量Cox比例风险回归、最小绝对收缩和选择算子回归以及基因集富集分析。此外，还进行了定量实时聚合酶链反应和免疫荧光检测，以验证SUCLG2在临床样本和前列腺癌上皮细胞系22Rv1中的表达。
我们的研究结果表明，基于构建的能准确预测PCa预后的16基因风险模型，包括SUCLG2在内的脂质代谢相关基因具有显著的预后价值。特别是，SUCLG2在管腔和基底/中间细胞亚群中显著富集，突出了其在肿瘤进展和治疗耐药中的潜在作用。药物敏感性分析表明，SUCLG2的表达与几种化疗药物的疗效相关，据此可制定PCa治疗中的个性化治疗策略。
SUCLG2在PCa的代谢重编程中起关键作用，从而为其进展和潜在治疗靶点提供了新的见解。我们的研究强调了代谢途径在PCa发病机制中的重要性，并为靶向治疗的发展铺平了道路，从而有助于PCa管理中的个性化医疗。
