Next-Generation Biomarkers in Multiple Myeloma: Advancing Diagnosis, Risk Stratification, and Precision Therapy Beyond Current Guidelines

TL;DR

This paper reviews new biomarkers for multiple myeloma that could improve diagnosis, treatment decisions, and patient outcomes beyond current standards.

Contribution

The paper identifies novel biomarker categories with translational potential for advancing precision therapy in multiple myeloma.

Findings

Biomarkers like ctDNA methylome and single-cell multiomics show promise for risk stratification and early progression detection.

Proteomics of surface antigens and PET/CT radiomics may guide therapy selection and identify new targets.

Current diagnostic and therapeutic models can be enhanced by integrating advanced biomarker platforms.

Abstract

Multiple myeloma (MM) is an oncohematological neoplasm characterized by the abnormal proliferation of neoplastic plasma cells in the bone marrow and the excessive secretion of monoclonal antibodies into the bloodstream. Approximately 3 to 5% of patients present with a variant form of the disease where there is no secretion of monoclonal proteins, characterizing the non-secretory MM picture. It exhibits a highly complex and heterogeneous genetic signature, allowing the disease to be classified into premalignant entities and symptomatic forms. In this context, an integrative narrative review was conducted, encompassing genomic, epigenomic, proteomic, metabolomic, and radiomic biomarkers described in the literature between 2018 and 2025. Emphasis was placed on their translational potential, current limitations in clinical practice, and gaps within recent recommendations. Several categories of biomarkers, particularly ctDNA methylome, single-cell multiomics, proteomics of surface antigens, functional ex vivo assays, and PET/CT radiomics, demonstrate strong potential for enhancing risk stratification, detecting early progression, guiding therapy selection, and identifying novel therapeutic targets. These applications extend beyond existing guideline frameworks. Thus, integrating advanced biomarker platforms can overcome limitations of current diagnostic and therapeutic models and enhance precision strategies across plasma cell disorders.

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