Enhancing staging in multiple myeloma using an m6A regulatory gene-pairing model.

Abstract

Multiple myeloma (MM) is characterized by clonal plasma cell proliferation in the bone marrow, challenging prognosis prediction. We developed a gene-pairing prognostic risk model using m6A regulatory genes and a nested LASSO method. A cutoff of - 0.133 categorized MM samples into high-risk and low-risk groups. The model showed strong prognostic performance in 2088 newly diagnosed MM samples and predicted response to combination therapy (daratumumab, carfilzomib, lenalidomide, and dexamethasone) in patients who failed or relapsed from bortezomib-containing regimens, with an AUC of 0.9. It distinguished between smoldering MM and MM (cutoff: - 0.45) and between MM and plasma cell leukemia (cutoff: 0.0857). Single-cell analysis revealed higher risk scores at relapse. Combining MM cell lines and sample data, we identified potential drugs and targets (ADAT2 and NUP153) effective against high-risk MM. Integrating the m6A risk model with the International Staging System (ISS) enhanced stratification accuracy. These insights support precision treatment of MM.