Crocetto Felice, Musone Michele, Chianese Stefano, Conforti Paolo, Digitale Selvaggio Gaetano, Caputo Vincenzo Francesco, Falabella Roberto, Del Giudice Francesco, Giulioni Carlo, Cafarelli Angelo, Lucarelli Giuseppe, Busetto Gian Maria, Ferro Matteo, Barone Biagio, Zattoni Fabio, Terracciano Daniela
Department of Neurosciences, Sciences of Reproduction and Odontostomatology, University of Naples Federico II, Naples, Italy.
Urology Unit, San Carlo Hospital, Via Potito Petrone, Potenza, 85100, Italy.
J Liq Biopsy. 2025 Jun 16;9:100305. doi: 10.1016/j.jlb.2025.100305. eCollection 2025 Sep.
Prostate cancer (PCa) is one of the most prevalent malignancies in men, characterized by high clinical and molecular heterogeneity. Despite the widespread use of prostate-specific antigen (PSA) for diagnosis and monitoring, its limited specificity and sensitivity necessitate the development of more accurate biomarkers. This review provides a comprehensive overview of current and emerging diagnostic, prognostic, and predictive biomarkers in PCa, highlighting their clinical applications and future perspectives. PSA, though historically central in PCa screening, lacks tumor specificity, often leading to unnecessary biopsies or missed aggressive cancers. Recent blood-based biomarkers, such as the Prostate Health Index (PHI) and 4Kscore, improve specificity by integrating PSA isoforms or kallikrein protein levels with clinical parameters. Urine-based biomarkers like PCA3 and SelectMDx further enhance diagnostic precision, particularly in distinguishing high-grade tumors, and show potential in active surveillance settings. Prognostic markers such as Bcl-2, Ki-67, and EZH2, alongside genetic alterations like MCM7 and 8q gain, help stratify patients by tumor aggressiveness and risk of recurrence. Liquid biopsies, including circulating tumor DNA (ctDNA) and circulating tumor cells (CTCs), offer non-invasive alternatives for molecular profiling, especially in metastatic castration-resistant PCa (mCRPC), and can identify actionable alterations such as BRCA1/2 or ATM mutations. Emerging technologies such as machine learning and single-cell omics are reshaping biomarker discovery. Artificial intelligence-driven models, like the replication stress signature (RSS), show promise in predicting relapse and therapeutic response. Single-cell RNA sequencing and spatial transcriptomics have deepened our understanding of PCa heterogeneity, tumour microenvironment, and resistance mechanisms. Furthermore, novel biomarkers, including exosome RNAs and immune-related markers (PD-L1, SOX2, TcellinfGEP), offer insights into tumour progression and immunotherapeutic potential. The urinary and gut microbiomes are also being explored for their diagnostic and prognostic roles in PCa. In conclusion, integrating advanced molecular tools and biomarker-guided platforms into clinical practice can significantly enhance early detection, personalized treatment, and monitoring in prostate cancer, paving the way for precision oncology.
前列腺癌(PCa)是男性中最常见的恶性肿瘤之一,其特点是具有高度的临床和分子异质性。尽管前列腺特异性抗原(PSA)被广泛用于诊断和监测,但其有限的特异性和敏感性使得开发更准确的生物标志物成为必要。本综述全面概述了PCa中当前和新兴的诊断、预后和预测生物标志物,突出了它们的临床应用和未来前景。PSA虽然在历史上一直是PCa筛查的核心,但缺乏肿瘤特异性,常常导致不必要的活检或漏诊侵袭性癌症。最近基于血液的生物标志物,如前列腺健康指数(PHI)和4Kscore,通过将PSA异构体或激肽释放酶蛋白水平与临床参数相结合来提高特异性。基于尿液的生物标志物如PCA3和SelectMDx进一步提高了诊断精度,特别是在区分高级别肿瘤方面,并在主动监测环境中显示出潜力。预后标志物如Bcl-2、Ki-67和EZH2,以及像MCM7和8q增益这样的基因改变,有助于根据肿瘤侵袭性和复发风险对患者进行分层。液体活检,包括循环肿瘤DNA(ctDNA)和循环肿瘤细胞(CTC),为分子分析提供了非侵入性替代方法,特别是在转移性去势抵抗性PCa(mCRPC)中,并且可以识别可操作的改变,如BRCA1/2或ATM突变。机器学习和单细胞组学等新兴技术正在重塑生物标志物的发现。人工智能驱动的模型,如复制应激特征(RSS),在预测复发和治疗反应方面显示出前景。单细胞RNA测序和空间转录组学加深了我们对PCa异质性、肿瘤微环境和耐药机制的理解。此外,新型生物标志物,包括外泌体RNA和免疫相关标志物(PD-L1、SOX2、TcellinfGEP),为肿瘤进展和免疫治疗潜力提供了见解。尿液和肠道微生物群在PCa中的诊断和预后作用也正在被探索。总之,将先进的分子工具和生物标志物导向平台整合到临床实践中可以显著提高前列腺癌的早期检测、个性化治疗和监测,为精准肿瘤学铺平道路。