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索拉非尼耐药的肝癌患者来源异种移植瘤的磷酸化蛋白质组学分析揭示了潜在的治疗策略。

Phosphoproteomics profiling of sorafenib-resistant hepatocellular carcinoma patient-derived xenografts reveals potential therapeutic strategies.

作者信息

Li Feng, Hu Bo, Zhang Lei, Liu Yang, Wang Jun, Wu Changqing, Wu Suiyi, Zhang Ying, Yang Xinrong, Lu Haojie

机构信息

Liver Cancer Institute and Institutes of Biomedical Sciences, Zhongshan Hospital, Fudan University, Shanghai, P.R. China.

Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, P.R. China.

出版信息

iScience. 2024 Dec 20;28(1):111657. doi: 10.1016/j.isci.2024.111657. eCollection 2025 Jan 17.

Abstract

Hepatocellular carcinoma (HCC) is the most common form of primary liver cancer with poor prognosis. Sorafenib, a first-line treatment for advanced HCC, has shown limited clinical benefits due to the onset of drug resistance. Thus, it is imperative to comprehend the mechanisms underlying sorafenib resistance and explore strategies to overcome or delay it. Here, we established HCC patient-derived xenograft (PDX) models with acquired resistance to sorafenib and performed comprehensive proteomic and phosphoproteomic analyses on these models. The active cell cycle pathway along with the active cyclin-dependent kinase CDK1 and DNA-dependent protein kinase PRKDC was identified through KEGG pathway enrichment and kinase substrate enrichment analyses. Upon investigating the potential of combining sorafenib with putative kinase inhibitors, we found that the combination displays synergistic anti-proliferative effects in the sorafenib-resistant liver cancer cell line, thus providing a proof of concept for phosphoproteomic-guided design of precision medicine.

摘要

肝细胞癌(HCC)是原发性肝癌最常见的形式,预后较差。索拉非尼是晚期HCC的一线治疗药物,但由于耐药性的出现,其临床疗效有限。因此,必须了解索拉非尼耐药的潜在机制,并探索克服或延缓耐药的策略。在此,我们建立了对索拉非尼产生获得性耐药的HCC患者来源异种移植(PDX)模型,并对这些模型进行了全面的蛋白质组学和磷酸化蛋白质组学分析。通过KEGG通路富集分析和激酶底物富集分析,确定了活跃的细胞周期通路以及活跃的细胞周期蛋白依赖性激酶CDK1和DNA依赖性蛋白激酶PRKDC。在研究索拉非尼与推定的激酶抑制剂联合使用的潜力时,我们发现这种联合在索拉非尼耐药的肝癌细胞系中显示出协同的抗增殖作用,从而为磷酸化蛋白质组学指导的精准医学设计提供了概念验证。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a43/11780156/cf6350974313/fx1.jpg

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