Prostate cancer (PC) remains a major cause of cancer deaths in men. The serum biomarker prostate-specific antigen (PSA) lacks specificity in distinguishing clinically significant PC (sPC) from insignificant PC (isPC), leading to overdiagnosis and overtreatment. Although magnetic resonance imaging (MRI) improves detection, it is expensive, is time-consuming, and may involve inter-reader discrepancies. Recently, metabolomics, which has a high analytical sensitivity and broad molecular-feature coverage, has emerged as a promising tool to risk-stratify PC. This review examined studies of blood and urine metabolomics for sPC biomarker identification. Significant metabolite changes in sPC patients often involved fatty acid metabolism, sphingolipid metabolism, glycolysis, the citric acid cycle, purine/pyrimidine metabolism, and tyrosine/phenylalanine metabolism. Specifically, more than one study reported increased lactate and phenylalanine levels, along with decreased tyrosine, xanthine, and histidine levels, in sPC patients. Several metabolic panels outperformed serum PSA in predicting sPC, particularly when combined with clinical factors. Among these, two urine-based tests may have higher accuracy in predicting sPC than most current commercially available assays. However, direct comparison between studies may be inappropriate due to methodological heterogeneity, the variability in biospecimen types, inconsistent use of digital rectal examinations, and different sPC definitions and predictive endpoints. Most relevant studies were of small sample size or lacked external validation. Despite these challenges, metabolomics-based liquid biopsies show strong potential for improving sPC detection. Future research should focus on protocol standardization, MRI integration, absolute metabolite quantification, and validation in large and independent cohorts to enhance model credibility.
前列腺癌（PC）仍是导致男性癌症死亡的主要原因。血清生物标志物前列腺特异性抗原（PSA）在区分临床显著性前列腺癌（sPC）与非显著性前列腺癌（isPC）方面缺乏特异性，导致过度诊断与过度治疗。尽管磁共振成像（MRI）提高了检测能力，但其成本高昂、耗时较长且可能存在阅片者间差异。近年来，代谢组学凭借其高分析灵敏度和广泛的分子特征覆盖范围，已成为风险分层前列腺癌的有力工具。本综述系统考察了血液和尿液代谢组学在sPC生物标志物识别方面的研究。sPC患者显著的代谢物变化常涉及脂肪酸代谢、鞘脂代谢、糖酵解、柠檬酸循环、嘌呤/嘧啶代谢以及酪氨酸/苯丙氨酸代谢通路。具体而言，多项研究报道sPC患者体内乳酸和苯丙氨酸水平升高，同时酪氨酸、黄嘌呤和组氨酸水平降低。多种代谢组合物在预测sPC方面表现优于血清PSA，尤其在与临床因素结合时。其中两项基于尿液的检测方法在预测sPC方面可能比当前多数商业化检测具有更高准确性。然而，由于研究方法异质性、生物样本类型差异、直肠指检应用不一致以及sPC定义和预测终点的不同，研究间直接比较可能存在局限。多数相关研究样本量较小或缺乏外部验证。尽管面临这些挑战，基于代谢组学的液体活检在改善sPC检测方面展现出巨大潜力。未来研究应聚焦于方案标准化、MRI技术整合、代谢物绝对定量以及在大规模独立队列中的验证，以提升模型的可信度。
Metabolomics-Based Liquid Biopsy for Predicting Clinically Significant Prostate Cancer
肿瘤(癌症)患者之家