Cherradi Sara, Roux Salomé, Dupuy Marie, Tabone-Eglinger Séverine, Tuaillon Edouard, Ziol Marianne, Assenat Eric, Duong Hong Tuan
PredictCan Biotechnologies SAS, Biopôle Euromédecine, Grabels, France.
Service d'Oncologie Médicale, Hôpital Saint Eloi, Centre Hospitalier Universitaire de Montpellier, Montpellier, France.
Sci Rep. 2025 Jan 7;15(1):1179. doi: 10.1038/s41598-024-84304-4.
Hepatocellular carcinoma (HCC) is the third most common cause of cancer-related death worldwide. Treating HCC is challenging because of the poor drug effectiveness and the lack of tools to predict patient responses. To resolve these issues, we established a patient-centric spheroid model using HepG2, TWNT-1, and THP-1 co-culture, that mimics HCC phenotype. We developed a target-independent cell killing (TICK) exclusion strategy to monitor the therapeutic response. We demonstrated that our model reproduced the Barcelona Clinic Liver Cancer (BCLC) molecular classification, displayed known alterations of epigenetic players, and responded to tyrosine kinase inhibitors (TKIs) such as sorafenib, cabozantinib, and lenvatinib in a patient-dependent manner. Importantly, we reported for the first time that our model correctly predicted 34 clinical outcomes to TKIs out of 37 case studies on 32 HCC patients confirming that patient-centric spheroids, combined with our TICK exclusion strategy, are valuable models for drug discovery and opening a near perspective to personalized care.
肝细胞癌(HCC)是全球癌症相关死亡的第三大常见原因。由于药物疗效不佳以及缺乏预测患者反应的工具,治疗HCC具有挑战性。为了解决这些问题,我们使用HepG2、TWNT-1和THP-1共培养建立了一个以患者为中心的球体模型,该模型模拟了HCC表型。我们开发了一种非靶向细胞杀伤(TICK)排除策略来监测治疗反应。我们证明,我们的模型重现了巴塞罗那临床肝癌(BCLC)分子分类,显示了表观遗传参与者的已知改变,并以患者依赖的方式对索拉非尼、卡博替尼和乐伐替尼等酪氨酸激酶抑制剂(TKIs)产生反应。重要的是,我们首次报告,在对32例HCC患者的37个案例研究中,我们的模型正确预测了34例TKI的临床结果,证实以患者为中心的球体与我们的TICK排除策略相结合,是药物发现的有价值模型,并为个性化医疗开辟了近景。