Computational Drug Repurposing Across the Multiple Myeloma Spectrum: From MGUS to MM.

Abstract

Background/objectives: Multiple myeloma (MM) is a challenging, B cell malignancy characterised by the uncontrolled proliferation of plasma cells within the bone marrow. Despite significant advances in treatment options nowadays, MM remains an incurable malignancy, with the majority of patients succumbing to the disease. MM develops from a pre-malignant state known as monoclonal gammopathy of unknown significance (MGUS), which then has the potential to evolve either into smouldering (asymptomatic) multiple myeloma (SMM) or into MM. Since novel drug discovery takes years to reach the clinic, drug repurposing, which concerns the detection of existing drugs for a novel disease, can be applied.

Methods: To address this critical and still unmet medical need, we present a comprehensive signature-based drug-repurposing approach using all the publicly available bulk transcriptomics datasets on mGUS, sMM, and MM.

Results: Our study included an in-house scoring scheme approach enabling further filtering and prioritisation, resulting in 25 candidate repurposed drugs for mGUS, 23 for sMM, and 66 for MM. The corresponding gene targets and the related functional terms have been analysed, providing extra information for stage-specific underlying mechanisms in myeloma. Lastly, enabled by a specific computational workflow, we propose drug combinations between our top candidate repurposed drugs and FDA-approved drugs for MM.

Conclusions: Together, these results deliver a stage-specific, transparent resource for MM drug repurposing and combination design, intended to accelerate translation toward earlier disease intervention and improved patient outcomes.