Hepatocellular carcinoma (HCC) represents a global health challenge, and ranks among one of the most prevalent and deadliest cancers worldwide. Therapeutic advances have expanded the treatment armamentarium for patients with advanced HCC, but obstacles remain. Precision oncology, which aims to match specific therapies to patients who have tumours with particular features, holds great promise. However, its implementation has been hindered by the existence of numerous ‘HCC influencers’ that contribute to the high inter-patient heterogeneity. HCC influencers include tumour-related characteristics, such as genetic alterations, immune infiltration, stromal composition and aetiology, and patient-specific factors, such as sex, age, germline variants and the microbiome. This Review delves into the intricate world of HCC, describing the most innovative model systems that can be harnessed to identify precision and/or personalized therapies. We provide examples of how different models have been used to nominate candidate biomarkers, their limitations and strategies to optimize such models. We also highlight the importance of reproducing distinct HCC influencers in a flexible and modular way, with the aim of dissecting their relative contribution to therapy response. Next-generation HCC models will pave the way for faster discovery of precision therapies for patients with advanced HCC.

肝细胞癌 （HCC） 是一项全球性的健康挑战，是全球最普遍和最致命的癌症之一。治疗进展扩大了晚期 HCC 患者的治疗武器库，但仍然存在障碍。精准肿瘤学旨在为具有特定特征的肿瘤患者匹配特定疗法，前景广阔。然而，由于存在许多“HCC 影响因素”，导致患者间的高度异质性，其实施受到了阻碍。HCC 影响因素包括肿瘤相关特征，例如遗传改变、免疫浸润、基质组成和病因，以及患者特异性因素，例如性别、年龄、种系变异和微生物组。本综述深入探讨了 HCC 的错综复杂世界，描述了可用于识别精准和/或个性化疗法的最具创新性的模型系统。我们提供了如何使用不同模型来提名候选生物标志物、它们的局限性以及优化此类模型的策略的示例。我们还强调了以灵活和模块化的方式复制不同 HCC 影响因素的重要性，目的是剖析它们对治疗反应的相对贡献。下一代 HCC 模型将为更快地发现晚期 HCC 患者的精准疗法铺平道路。