Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY.
Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY.
JCO Precis Oncol. 2022 Jun;6:e2200147. doi: 10.1200/PO.22.00147.
Selinexor is the first selective inhibitor of nuclear export to be approved for the treatment of relapsed or refractory multiple myeloma (MM). Currently, there are no known genomic biomarkers or assays to help select MM patients at higher likelihood of response to selinexor. Here, we aimed to characterize the transcriptomic correlates of response to selinexor-based therapy.
We performed RNA sequencing on CD138+ cells from the bone marrow of 100 patients with MM who participated in the BOSTON study, followed by differential gene expression and pathway analysis. Using the differentially expressed genes, we used cox proportional hazard models to identify a gene signature predictive of response to selinexor, followed by validation in external cohorts.
The three-gene signature predicts response to selinexor-based therapy in patients with MM in the BOSTON cohort. Then, we validated this gene signature in 64 patients from the STORM cohort of triple-class refractory MM and additionally in an external cohort of 35 patients treated in a real-world setting outside of clinical trials. We found that the signature tracks with both depth and duration of response, and it also validates in a different tumor type using a cohort of pretreatment tumors from patients with recurrent glioblastoma. Furthermore, the genes involved in the signature, WNT10A, DUSP1, and ETV7, reveal a potential mechanism through upregulated interferon-mediated apoptotic signaling that may prime tumors to respond to selinexor-based therapy.
In this study, we present a present a novel, three-gene expression signature that predicts selinexor response in MM. This signature has important clinical relevance as it could identify patients with cancer who are most likely to benefit from treatment with selinexor-based therapy.
Selinexor 是首个被批准用于治疗复发或难治性多发性骨髓瘤（MM）的核输出选择性抑制剂。目前，尚无已知的基因组生物标志物或检测方法来帮助选择对 selinexor 反应可能性更高的 MM 患者。在这里，我们旨在描述基于 selinexor 治疗的反应的转录组相关性。
我们对参与 BOSTON 研究的 100 名 MM 患者的骨髓 CD138+细胞进行了 RNA 测序，随后进行了差异基因表达和通路分析。使用差异表达基因，我们使用 cox 比例风险模型来识别预测对 selinexor 反应的基因特征，然后在外部队列中进行验证。
该三基因特征可预测 BOSTON 队列中 MM 患者对 selinexor 为基础的治疗的反应。然后，我们在 64 名来自三重耐药 MM 的 STORM 队列的患者和在临床试验之外的真实世界环境中治疗的 35 名患者的外部队列中验证了该基因特征。我们发现该特征与深度和反应持续时间相关，并且在使用来自复发性胶质母细胞瘤患者的预处理肿瘤的队列中也得到验证。此外，该特征中涉及的基因 WNT10A、DUSP1 和 ETV7，揭示了一种潜在的机制，即通过上调干扰素介导的凋亡信号，使肿瘤对基于 selinexor 的治疗产生反应。
在这项研究中，我们提出了一种新的三基因表达特征，可预测 MM 中的 selinexor 反应。该特征具有重要的临床相关性，因为它可以识别出最有可能从 selinexor 为基础的治疗中受益的癌症患者。
