Multiple myeloma (MM) is an incurable malignancy, and despite novel anti-myeloma drugs that increased survival, up to 30% of patients develop primary resistance, and many patients experience early relapse. This innovation deploys single‑cell analytical tools to identify molecular signatures of refractory or relapsed multiple myeloma malignancies. Identification of such biomarkers will facilitate patient stratification and improve prognostics and therapy individualization.
Multiple myeloma (MM) is a malignancy characterized by expansion of plasma cells in the bone marrow and subsequent overexpression of monoclonal antibodies that ultimately disrupt the function of major organs. To date, the disease is still incurable, with a life expectancy that has been recently increased to 7-8 years, thanks to newly introduced novel anti‑myeloma drugs. Nevertheless, up to 30% of patients develop primary treatment resistance, which is associated with reduced survival. Similarly, early relapse occurring within 12-24 months of autologous stem cell transplant, is closely linked with poor prognosis. These patient subpopulations are generally underrepresented in clinical trials and evidence-based treatment and management strategies are therefore wanting. Moreover, current molecular analysis technologies lack the depth and resolution necessary to profile the diversity of MM subtypes and their responses to both intrinsic and extrinsic factors dictating their course. Comprehensive analysis of the transcriptome and targetable resistance-driving pathways unique to these patients will likely propel discovery of agents particularly effective for relapsed/refractory MM.
This technology harnesses state-of-the-art single-cell technologies to profile the cellular and molecular signatures of primary refractory MM (PRMM) with the overall aim of identifying diagnostic and stratification biomarkers, as well as targetable pathways.
Using cell sorting and single-cell gene expression analyses techniques, the research team generated single-cell atlases of plasma cells longitudinally collected from newly diagnosed MM (NDMM) and PRMM patients undergoing MM treatment and from healthy volunteers. Comparative analyses identified novel gene modules differentially expressed in PRMM as compared to NDMM and healthy cells, which successfully predicted clinical responsiveness to specific MM drug combinations, as well as progression-free and overall survival. The identified gene expression signature became progressively more prevalent in patients on later lines of treatment. In-depth analysis of the genes upregulated in non-responders, suggested potentially targetable escape mechanisms. Specifically, Cyclophilin A (PPIA) upregulation was identified as a new mechanism that induces ultra-resistance MM in patients. A combined treatment of PPIA inhibitor and proteasome inhibitors (PI) had a synergistic effect that resulted in dramatically increased apoptosis of MM cells.
- Identification of early resistance mechanisms which can be leveraged for
- Risk stratification
- Identification of prognostic biomarkers
- Identification of therapeutic targets and treatments
- Prediction of therapeutic potential
Present results were derived from clinical samples of patients undergoing MM treatment within the framework of a clinical trial. Preliminary biomarkers identified PPRM-specific perturbations in mitochondrial stress genes, proteasome machinery and endoplasmic reticulum and unfolded protein response pathways. The team showed both in-vitro (on cell lines) and ex-vivo (on primary MM cells taken from refractory patient’s bone marrow) that PPIA inhibition using a chemical inhibitor (cyclosporine) or by gene knockout, sensitize MM cells to proteasome inhibitors (PI). Finally further clinical work is being performed on a small cohort, with initial positive results.