This systematic review evaluates the prognostic utility of quantitative mass spectrometry-based proteomics or metabolomics in multiple myeloma cohorts. The analysis included 19 studies after screening 1,077 records, comparing MS-based biomarkers against ISS/R-ISS staging or traditional monitoring techniques. The review focuses on overall survival, progression-free survival, hazard ratios, and minimal residual disease sensitivity thresholds.
The authors synthesize that specific MS-derived signatures, such as microenvironmental proteins and dysregulated lipid metabolites, were consistently associated with progression-free survival and overall survival. These biomarkers retained independent prognostic significance in multivariate models adjusted for R-ISS. Regarding minimal residual disease detection, the review notes sensitivity up to 1,000-fold higher than traditional immunofixation electrophoresis, identifying biochemical relapse 2–11 months earlier than conventional methods.
Concordance with bone marrow-based assays, including NGS/NGF, was reported as high. However, the authors acknowledge that standardization of bioinformatics pipelines and MS methodologies is the final barrier to implementing MS-guided treatment adjustments in routine clinical practice. No safety data, adverse events, or discontinuations were reported in the included studies. The review does not establish causality and highlights that further standardization is required before widespread clinical adoption.
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IntroductionCurrent multiple myeloma (MM) risk stratification, anchored on the Revised International Staging System (R-ISS), provides a static snapshot of disease but fails to capture its dynamic biological evolution, functional tumor-microenvironment crosstalk, and real-time treatment response. Mass spectrometry (MS)-based proteomic and metabolomic profiling has emerged as a high-sensitivity tool for both novel biomarker discovery and minimal residual disease (MRD) monitoring. This systematic review evaluates the independent prognostic value and clinical utility of quantitative MS-based proteomics and metabolomics compared to standard-of-care risk models and traditional disease monitoring techniques.MethodsFollowing PRISMA 2020 guidelines, a systematic search of PubMed, Embase, and Web of Science was conducted. Inclusion required quantitative MS-based proteomics or metabolomics in MM cohorts with outcomes compared to ISS/R-ISS or traditional MRD detection methods. Data analysis was performed with a focus on overall survival (OS), progression-free survival (PFS), hazard ratios (HR), and MRD sensitivity thresholds.ResultsFrom 1,077 records, 19 studies met the inclusion criteria. Eleven discovery-focused studies identified specific MS-derived signatures, such as microenvironmental proteins (e.g., MTA2, CD44) and dysregulated lipid metabolites (e.g., acylcarnitines, LysoPE) that were consistently associated with PFS and OS. Crucially, MS-based biomarkers retained independent prognostic significance in multivariate models adjusted for R-ISS. Furthermore, 8 studies tackling blood-based MS-MRD detection demonstrated up to 1,000-fold higher sensitivity than traditional immunofixation electrophoresis, identified biochemical relapse 2–11 months earlier, and achieved high concordance with bone marrow-based assays (NGS/NGF).ConclusionIn conclusion, quantitative MS profiling provides a high-resolution molecular lens that significantly refines MM risk stratification beyond static staging. By enabling non-invasive, longitudinal MRD monitoring with superior lead times, MS integration facilitates a shift from reactive to proactive intervention. Standardization of bioinformatics pipelines and MS methodologies is now the final barrier to implementing MS-guided treatment adjustments in routine clinical practice.