Genomic score testing is increasingly being integrated into the management of prostate cancer (PCa) to overcome the limitations of traditional clinical and pathological parameters. Genomic tools will represent essential components of precision medicine, supporting risk stratification, therapeutic decision-making, and personalized screening strategies. Genomic score tests can be broadly classified into two main categories: polygenic risk scores (PRSs) and tumor-derived genomic classifiers (GCs). While not yet standard in routine practice, several international guidelines recommend their selective use when results are likely to impact clinical management. PRSs estimate an individual’s susceptibility to PCa based on the cumulative effect of multiple low-penetrance germline genetic variants. These scores show promise in enhancing early detection strategies and identifying men at higher genetic risk who may benefit from tailored screening protocols. Tumor-based GCs assays provide prognostic information that complements conventional clinical and pathological parameters, and are used to guide treatment decisions, including eligibility for active surveillance (AS) or adjuvant therapy after treatment of the primary tumor. This review summarizes and analyzes the current evidence on genomic testing in PCa, with a focus on the available assays, their clinical applications, and their predictive and prognostic value across the disease spectrum. When integrated with clinical and pathological parameters, these tools have the potential to significantly enhance personalized care and should be increasingly considered in routine clinical practice.
基因组评分检测正日益被整合到前列腺癌(PCa)的管理中,以克服传统临床和病理参数的局限性。基因组工具将成为精准医学的重要组成部分,支持风险分层、治疗决策和个性化筛查策略。基因组评分检测可大致分为两大类:多基因风险评分(PRSs)和肿瘤来源的基因组分类器(GCs)。尽管尚未成为常规实践的标准,但多项国际指南建议在结果可能影响临床管理时选择性使用这些工具。PRSs基于多个低外显率种系遗传变异的累积效应,评估个体对前列腺癌的易感性。这些评分在增强早期检测策略以及识别可能受益于定制筛查方案的高遗传风险男性方面显示出潜力。基于肿瘤的GCs检测提供预后信息,补充传统的临床和病理参数,并用于指导治疗决策,包括主动监测(AS)的适用性以及原发肿瘤治疗后的辅助治疗。本综述总结并分析了当前关于前列腺癌基因组检测的证据,重点关注可用的检测方法、其临床应用以及在疾病谱系中的预测和预后价值。当与临床和病理参数结合时,这些工具有望显著提升个性化护理水平,并应越来越多地纳入常规临床实践中加以考虑。