A Three-Gene Signature Predicts Response to Selinexor in Multiple Myeloma

Author:

Restrepo Paula12ORCID,Bhalla Sherry12,Ghodke-Puranik Yogita1,Aleman Adolfo13ORCID,Leshchenko Violetta1ORCID,Melnekoff David T.134,Agte Sarita1,Jiang Joy3ORCID,Madduri Deepu15,Richter Joshua1ORCID,Richard Shambavi1,Chari Ajai1ORCID,Cho Hearn Jay16ORCID,Jagannath Sundar1ORCID,Walker Christopher J.7,Landesman Yosef7,Laganà Alessandro124,Parekh Samir1ORCID

Affiliation:

1. Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY

2. Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY

3. Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, NY

4. Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY

5. Janssen Pharmaceutical Research and Development, Raritan, NJ

6. Multiple Myeloma Research Foundation, Norwalk, CT

7. Karyopharm Therapeutics, Newton, MA

Abstract

PURPOSE 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. METHODS 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. RESULTS 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. CONCLUSION 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.

Publisher

American Society of Clinical Oncology (ASCO)

Subject

Cancer Research,Oncology

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