Aix Marseille Université, Centre National de la Recherche Scientifique (CNRS), Institut National de la Santé et de la Recherche Médicale (INSERM), Institut Paoli Calmettes, Centre de Recherche en Cancérologie de Marseille (CRCM), Marseille, France.
Aix Marseille Université, CNRS, UMR 7051, INP, Inst Neurophysiopathol, Marseille, France.
EBioMedicine. 2023 Sep;95:104752. doi: 10.1016/j.ebiom.2023.104752. Epub 2023 Aug 10.
Pharmacological synergisms are an attractive anticancer strategy. However, with more than 5000 approved-drugs and compounds in clinical development, identifying synergistic treatments represents a major challenge.
High-throughput screening was combined with target deconvolution and functional genomics to reveal targetable vulnerabilities in glioblastoma. The role of the top gene hit was investigated by RNA interference, transcriptomics and immunohistochemistry in glioblastoma patient samples. Drug combination screen using a custom-made library of 88 compounds in association with six inhibitors of the identified glioblastoma vulnerabilities was performed to unveil pharmacological synergisms. Glioblastoma 3D spheroid, organotypic ex vivo and syngeneic orthotopic mouse models were used to validate synergistic treatments.
Nine targetable vulnerabilities were identified in glioblastoma and the top gene hit RRM1 was validated as an independent prognostic factor. The associations of CHK1/MEK and AURKA/BET inhibitors were identified as the most potent amongst 528 tested pairwise drug combinations and their efficacy was validated in 3D spheroid models. The high synergism of AURKA/BET dual inhibition was confirmed in ex vivo and in vivo glioblastoma models, without detectable toxicity.
Our work provides strong pre-clinical evidence of the efficacy of AURKA/BET inhibitor combination in glioblastoma and opens new therapeutic avenues for this unmet medical need. Besides, we established the proof-of-concept of a stepwise approach aiming at exploiting drug poly-pharmacology to unveil druggable cancer vulnerabilities and to fast-track the identification of synergistic combinations against refractory cancers.
This study was funded by institutional grants and charities.
药物协同作用是一种有吸引力的抗癌策略。然而，在超过 5000 种已批准的药物和化合物正在临床开发中，确定协同治疗方法是一项重大挑战。
采用高通量筛选与靶标去卷积和功能基因组学相结合的方法，揭示胶质母细胞瘤的可靶向脆弱性。通过 RNA 干扰、转录组学和免疫组织化学方法在胶质母细胞瘤患者样本中研究了顶级基因靶点的作用。使用包含 88 种化合物的定制文库与六种鉴定出的胶质母细胞瘤脆弱性抑制剂联合进行药物组合筛选，以揭示药物协同作用。使用胶质母细胞瘤 3D 球体、器官型体外和同源原位小鼠模型验证协同治疗。
在胶质母细胞瘤中确定了 9 种可靶向的脆弱性，顶级基因靶点 RRM1 被验证为独立的预后因素。CHK1/MEK 和 AURKA/BET 抑制剂的关联被鉴定为 528 种测试的两两药物组合中最有效的组合，其在 3D 球体模型中的疗效得到了验证。AURKA/BET 双重抑制的高协同作用在体外和体内胶质母细胞瘤模型中得到了证实，且没有可检测到的毒性。
我们的工作为 AURKA/BET 抑制剂联合治疗胶质母细胞瘤的有效性提供了强有力的临床前证据，并为这一未满足的医疗需求开辟了新的治疗途径。此外，我们建立了一种逐步方法的概念验证，旨在利用药物多药理学揭示可治疗的癌症脆弱性，并快速确定针对难治性癌症的协同组合。
本研究由机构拨款和慈善机构资助。
