前列腺癌（PCa）是发达国家男性中最常见和第二致命的癌症类型，是一种高度异质性的疾病。PCa的异质性、治疗耐药性、干细胞特性以及致命性进展已被归因于谱系可塑性，谱系可塑性是指肿瘤细胞在微环境压力下通过在发育细胞状态之间切换而发生表型变化的能力。有待阐明的是如何识别谱系可塑性的测量方法，如何将其用于预临床和临床研究，以及如何对患者进行分类并指导治疗策略。最近的研究强调了下一代测序技术在识别与谱系可塑性相关的潜在生物标志物方面的关键作用。在这里，我们回顾了已经在PCa中描述的基因组、转录组和表观遗传事件，并强调那些对谱系可塑性具有重要意义的事件。我们进一步关注这些事件在PCa研究中的相关性以及在PCa患者分类中的好处。最后，我们探讨了如何利用生物信息学分析来基于大规模组学分析和算法来确定谱系可塑性，并对上游和下游事件进行阐明的方法。最重要的是，一个综合的多组学方法可能很快可以用于识别谱系可塑性特征，从而革新PCa患者的分子分类。

Prostate cancer (PCa), the most frequent and second most lethal cancer type in men in developed countries, is a highly heterogeneous disease. PCa heterogeneity, therapy resistance, stemness, and lethal progression have been attributed to lineage plasticity, which refers to the ability of neoplastic cells to undergo phenotypic changes under microenvironmental pressures by switching between developmental cell states. What remains to be elucidated is how to identify measurements of lineage plasticity, how to implement them to inform preclinical and clinical research, and, further, how to classify patients and inform therapeutic strategies in the clinic. Recent research has highlighted the crucial role of next-generation sequencing technologies in identifying potential biomarkers associated with lineage plasticity. Here, we review the genomic, transcriptomic, and epigenetic events that have been described in PCa and highlight those with significance for lineage plasticity. We further focus on their relevance in PCa research and their benefits in PCa patient classification. Finally, we explore ways in which bioinformatic analyses can be used to determine lineage plasticity based on large omics analyses and algorithms that can shed light on upstream and downstream events. Most importantly, an integrated multiomics approach may soon allow for the identification of a lineage plasticity signature, which would revolutionize the molecular classification of PCa patients.