肿瘤分类在前列腺癌 (PCa) 治疗中发挥着关键作用。它可以在疾病诊断时尽早预测PCa的临床结果，然后指导治疗方案，例如主动监测、独立手术干预或手术辅以术后辅助治疗，从而避免病情恶化和过度治疗。基于临床病理特征的分类，如前列腺癌特异性抗原、格里森评分和TNM分期，仍然是主要的危险分层策略，并在标准化临床决策中发挥着重要作用。然而，越来越多的证据表明，孤立的临床病理学参数无法充分捕捉不同 PCa 患者之间表现出的异质性，例如那些具有相同格里森评分但预后不同的患者。作为一种补救措施，分子分类被引入。目前，分子研究已经揭示了与不同类型PCa相关的特征性基因组改变、表观遗传调节和肿瘤微环境，这为泌尿外科医生完善PCa分类提供了机会。在这种背景下，人们设计了许多宝贵的分子分类，采用不同的统计方法和算法方法，包括自组织图谱聚类、无监督聚类分析和多种多样的算法。有趣的是，分类器 PAM50 用于 2 期多中心开放标签试验 NRG-GU-006 进行进一步验证，这暗示了分子分类在临床应用的前景。因此，这篇综述检查了现有的分子分类，描绘了临床相关分子特征的普遍概况，并深入研究了八种标志性分子分类，剖析了它们的方法基础和临床实用性。

Tumour classifications play a pivotal role in prostate cancer (PCa) management. It can predict the clinical outcomes of PCa as early as the disease is diagnosed and then guide therapeutic schemes, such as active monitoring, standalone surgical intervention, or surgery supplemented with postoperative adjunctive therapy, thereby circumventing disease exacerbation and excessive treatment. Classifications based on clinicopathological features, such as prostate cancer-specific antigen, Gleason score, and TNM stage, are still the main risk stratification strategies and have played an essential role in standardized clinical decision-making. However, mounting evidence indicates that clinicopathological parameters in isolation fail to adequately capture the heterogeneity exhibited among distinct PCa patients, such as those sharing identical Gleason scores yet experiencing divergent prognoses. As a remedy, molecular classifications have been introduced. Currently, molecular studies have revealed the characteristic genomic alterations, epigenetic modulations, and tumour microenvironment associated with different types of PCa, which provide a chance for urologists to refine the PCa classification. In this context, numerous invaluable molecular classifications have been devised, employing disparate statistical methodologies and algorithmic approaches, encompassing self-organizing map clustering, unsupervised cluster analysis, and multifarious algorithms. Interestingly, the classifier PAM50 was used in a phase-2 multicentre open-label trial, NRG-GU-006, for further validation, which hints at the promise of molecular classification for clinical use. Consequently, this review examines the extant molecular classifications, delineates the prevailing panorama of clinically pertinent molecular signatures, and delves into eight emblematic molecular classifications, dissecting their methodological underpinnings and clinical utility.