AI-derived five-gene signature predicts risk in multiple myeloma under bortezomib-based therapy.

ABSTRACT: Multiple myeloma (MM) is a plasma cell malignancy characterized by clonal expansion within the bone marrow (BM) and remains largely incurable despite recent therapeutic advances. While prognostic indicators have predominantly focused on tumor-intrinsic features, the BM tumor microenvironment (TME) plays a critical role in disease progression and therapeutic resistance. Here, we present a robust prognostic model derived from transcriptomic profiling of the CD138-negative BM fraction, enabling precise risk stratification of patients undergoing bortezomib-based induction therapy. Using bioinformatic deconvolution and a custom immune-stromal signature matrix, we identified gene expression patterns representative of the MM TME. Through rigorous feature selection and elastic-net penalized Cox re

SUBMITTER: Gargano G 

PROVIDER: S-EPMC12783152 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature