Several therapeutic agents have been approved for treating multiple myeloma (MM), a cancer of bone marrow resident plasma cells. Predictive biomarkers for drug response could help guide clinical strategies to optimize outcomes. Here, we present an integrated functional genomic analysis of tumor samples from MM patients that were assessed for their ex vivo drug sensitivity to 37 drugs, clinical variables, cytogenetics, mutational profiles, and transcriptomes. This analysis revealed a MM transcriptomic topology that generates “footprints” in association with ex vivo drug sensitivity that have both predictive and mechanistic applications. Validation of the transcriptomic footprints for the anti-CD38 monoclonal antibody daratumumab and the nuclear export inhibitor selinexor demonstrated that these footprints can accurately classify clinical responses. The analysis further revealed that daratumumab and selinexor have anti-correlated mechanisms of resistance, and treatment with a selinexor-based regimen immediately after a daratumumab-containing regimen was associated with improved survival in three independent clinical trials, supporting an evolutionary-based strategy involving sequential therapy. These findings suggest that this unique repository and computational framework can be leveraged to inform underlying biology and to identify therapeutic strategies to improve treatment of MM.

中文翻译：

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功能性转录组学景观为多发性骨髓瘤的治疗策略提供信息


几种治疗药物已被批准用于治疗多发性骨髓瘤 （MM），这是一种骨髓驻留浆细胞癌。药物反应的预测性生物标志物有助于指导临床策略以优化结果。在这里，我们提出了对 MM 患者肿瘤样本的综合功能基因组分析，这些样本评估了他们对 37 种药物、临床变量、细胞遗传学、突变谱和转录组的离体药物敏感性。该分析揭示了一种 MM 转录组拓扑结构，该拓扑结构产生与离体药物敏感性相关的“足迹”，具有预测和机制应用。对抗 CD38 单克隆抗体 daratumumab 和核输出抑制剂 selinexor 的转录组足迹的验证表明，这些足迹可以准确分类临床反应。分析进一步显示，daratumumab 和 selinexor 具有抗相关耐药机制，在含 daratumumab 的方案后立即使用基于塞利尼索的方案进行治疗与三项独立临床试验中的生存率提高相关，支持涉及序贯治疗的基于进化的策略。这些发现表明，可以利用这种独特的存储库和计算框架来告知基础生物学并确定改善 MM 治疗的治疗策略。