Drivers of Progression, Resistance & High-Risk Disease
Defining drivers of relapse and resistance to improve outcomes in high-risk myeloma
Drivers of Progression, Resistance & High-Risk Disease Early relapse and drug resistance remain the main obstacles to long-term survival in myeloma. We have shown that chromosome 1q gain drives venetoclax failure, identified a three-gene expression signature that predicts selinexor benefit, and demonstrated that germline DNA-repair variants modify myeloma risk and treatment outcome. We are now assembling a single-cell atlas of more than 150 high-risk patients to chart tumor clones alongside their immune- and stroma-cell compartments, trace the signals that sustain aggressive disease, and derive combination therapies for testing.
Predictors of response to Venetoclax RNA-seq of relapsed patients identified a 6-gene score that stratifies venetoclax response and confirmed 1q-driven MCL1 expression as a resistance factor. CDK7 inhibition lowered MCL1 and restored venetoclax sensitivity in 1q-gain cell models, supporting a combination strategy.
A three-gene signature of response to Selinexor RNA-seq from 100 BOSTON-study samples yielded a WNT10A-DUSP1-ETV7 signature that predicts depth and duration of response to selinexor. The signature was validated in two independent myeloma cohorts and in glioblastoma, suggesting a shared interferon-mediated mechanism.
Germline predisposition to myeloma Germline exomes from 1,681 patients showed that 8–11 % carry pathogenic variants, mainly in DNA-repair genes; BRCA1/2 PGVs confer 4- to 7-fold higher myeloma risk. Carriers present younger and benefit more from high-dose melphalan, supporting genetic testing at diagnosis.
Ongoing projects
Single-cell Atlas of High-Risk Myeloma We are building a single-cell RNA atlas of high-risk myeloma to resolve intratumor heterogeneity, define the bone-marrow microenvironment features that mark aggressive disease, and map the communication between high-risk clones and their immune and stromal neighbors. By integrating these layers, we aim to uncover actionable signaling routes and propose combination therapies for patients who currently lack effective options.
