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利用二次表型优化平台(QPOP)优化多发性骨髓瘤的药物组合。

Optimizing drug combinations against multiple myeloma using a quadratic phenotypic optimization platform (QPOP).

机构信息

Cancer Science Institute of Singapore, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117599, Singapore.

Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore.

出版信息

Sci Transl Med. 2018 Aug 8;10(453). doi: 10.1126/scitranslmed.aan0941.

DOI:10.1126/scitranslmed.aan0941
PMID:30089632
Abstract

Multiple myeloma is an incurable hematological malignancy that relies on drug combinations for first and secondary lines of treatment. The inclusion of proteasome inhibitors, such as bortezomib, into these combination regimens has improved median survival. Resistance to bortezomib, however, is a common occurrence that ultimately contributes to treatment failure, and there remains a need to identify improved drug combinations. We developed the quadratic phenotypic optimization platform (QPOP) to optimize treatment combinations selected from a candidate pool of 114 approved drugs. QPOP uses quadratic surfaces to model the biological effects of drug combinations to identify effective drug combinations without reference to molecular mechanisms or predetermined drug synergy data. Applying QPOP to bortezomib-resistant multiple myeloma cell lines determined the drug combinations that collectively optimized treatment efficacy. We found that these combinations acted by reversing the DNA methylation and tumor suppressor silencing that often occur after acquired bortezomib resistance in multiple myeloma. Successive application of QPOP on a xenograft mouse model further optimized the dosages of each drug within a given combination while minimizing overall toxicity in vivo, and application of QPOP to ex vivo multiple myeloma patient samples optimized drug combinations in patient-specific contexts.

摘要

多发性骨髓瘤是一种不可治愈的血液恶性肿瘤,依赖于药物联合治疗作为一线和二线治疗方案。蛋白酶体抑制剂(如硼替佐米)的加入改善了这些联合方案的中位生存期。然而,硼替佐米耐药是一种常见现象,最终导致治疗失败,因此仍然需要确定改进的药物联合方案。我们开发了二次表型优化平台(QPOP),以优化从 114 种已批准药物的候选药物库中选择的治疗组合。QPOP 使用二次曲面来模拟药物组合的生物学效应,以确定有效的药物组合,而无需参考分子机制或预先确定的药物协同数据。将 QPOP 应用于硼替佐米耐药多发性骨髓瘤细胞系,确定了共同优化治疗效果的药物组合。我们发现,这些组合通过逆转多发性骨髓瘤获得性硼替佐米耐药后经常发生的 DNA 甲基化和肿瘤抑制基因沉默来发挥作用。在异种移植小鼠模型上连续应用 QPOP 进一步优化了给定组合中每种药物的剂量,同时最大限度地减少了体内的整体毒性,并且将 QPOP 应用于体外多发性骨髓瘤患者样本优化了患者特定背景下的药物组合。

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