Evidence map›Paper›PMID 41120896›Full record

ArticleClinical proteomics2025

Novel proteomic characterization of multiple myeloma bone marrow interstitial fluid links prognosis to coagulation pathways.

Sam Cutler, Amy M Trottier, Robert Liwski, Jason Quinn, Daniel Gaston, Randy Veinotte, Jackie St Pierre, Darrell White, Nicholas Forward, Alfredo De La Torre and 1 more

Abstract read
In one paragraph

Article in Clinical proteomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Sam CutlerFaculty of Medicine, Dalhousie University, Halifax, NS, Canada.
Amy M TrottierDepartment of Medicine, Division of Hematology and Hematologic Oncology, Dalhousie University, Halifax, NS, Canada.
Robert LiwskiDepartment of Pathology and Laboratory Medicine, Division of Hematopathology, Dalhousie University, Halifax, NS, Canada.
Jason QuinnDepartment of Pathology and Laboratory Medicine, Division of Hematopathology, Dalhousie University, Halifax, NS, Canada.
Daniel GastonDepartment of Pathology and Laboratory Medicine, Division of Hematopathology, Dalhousie University, Halifax, NS, Canada.
Randy VeinotteDepartment of Pathology and Laboratory Medicine, Division of Hematopathology, Nova Scotia Health Authority, NS, Halifax, Canada.
Jackie St PierreDepartment of Pathology and Laboratory Medicine, Division of Hematopathology, Nova Scotia Health Authority, NS, Halifax, Canada.
Darrell WhiteDepartment of Medicine, Division of Hematology and Hematologic Oncology, Dalhousie University, Halifax, NS, Canada.
Nicholas ForwardDepartment of Medicine, Division of Hematology and Hematologic Oncology, Dalhousie University, Halifax, NS, Canada.
Alfredo De La TorreDepartment of Medicine, Division of Hematology and Hematologic Oncology, Dalhousie University, Halifax, NS, Canada.
Manal ElnenaeiDepartment of Pathology and Laboratory Medicine, Division of Clinical Chemistry, Dalhousie University, Halifax, NS, Canada. manal.elnenaei@nshealth.ca.

Funding

Research Nova Scotia 1029591
6 · The paper itself

Abstract

backgroundMultiple myeloma (MM), the second most prevalent hematological malignancy, carries high morbidity with variability in clinical progression among patients. This necessitates accurate risk stratification for effective therapy and life planning. While extensively genomically and transcriptomically characterized, MM remains modestly studied from a proteomic perspective. As proteomics is a closer measure of phenotype than genomic and transcriptomic assessments, addressing this gap in the literature may yield new insights into disease biology and novel biomarkers.

methodsHerein, we applied a new sample preparation approach for mass-spectrometry based proteomics to bone marrow interstitial fluid (BMIF) from patients with MM or its precursors.

resultsWe achieved deep coverage of the proteome, identifying > 11,000 protein groups (PGs) across our cohort, with an average of ~ 8900 PGs per sample. Of these, 194 PGs were significantly associated with overall survival (OS). These survival-associated PGs were enriched for those involved in coagulation, and clustering newly diagnosed MM (NDMM) based on coagulation-related proteins revealed three distinct groups characterised by globally high, medium, and low intensity of coagulation-related proteins. The group with low intensity of coagulation-related PGs had significantly reduced OS (log-rank p = 0.00078). Clustering was independent of measured clinical covariates, including chemotherapeutic regimens used, Revised International Staging System (R-ISS stage), International Normalised Ratio (INR), and age, among others.

conclusionOur findings support the value of fluid-based proteomic assessment of MM and suggest that coagulation-related PGs could serve as valuable novel biomarkers for risk stratification in multiple myeloma, warranting further investigation into this area.

Indexed as

Coagulation ProteinsMultiple MyelomaPrognosisProteomic

Identifiers

PMID41120896
PMCPMC12542439

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.