Evidence map›Paper›PMID 37386588›Full record

ArticleJournal of hematology & oncology2023

A gene signature can predict risk of MGUS progressing to multiple myeloma.

Fumou Sun, Yan Cheng, Jun Ying, David Mery, Samer Al Hadidi, Visanu Wanchai, Eric R Siegel, Hongwei Xu, Dongzheng Gai, Timothy Cody Ashby and 11 more

Open access · goldAbstract readLetter
In one paragraph

Article in Journal of hematology & oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
3.8field-weighted citation impact, top 6% of its field
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

11 citing papers in PubMed, 13 citations in OpenAlex.

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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

21 authors at 3 institutions in 1 country.

Fumou Sun *Myeloma Center, Department of Internal Medicine, Winthrop P. Rockefeller Cancer Institute, University of Arkansas for Medical Sciences, 4301 W. Markham St. Slot# 508, Little Rock, AR, 72205, USA.
Yan Cheng *Myeloma Center, Department of Internal Medicine, Winthrop P. Rockefeller Cancer Institute, University of Arkansas for Medical Sciences, 4301 W. Markham St. Slot# 508, Little Rock, AR, 72205, USA.
Jun YingDepartment of Biostatistics, University of Arkansas for Medical Sciences, Little Rock, AR, USA.
David MeryMyeloma Center, Department of Internal Medicine, Winthrop P. Rockefeller Cancer Institute, University of Arkansas for Medical Sciences, 4301 W. Markham St. Slot# 508, Little Rock, AR, 72205, USA.
Samer Al HadidiMyeloma Center, Department of Internal Medicine, Winthrop P. Rockefeller Cancer Institute, University of Arkansas for Medical Sciences, 4301 W. Markham St. Slot# 508, Little Rock, AR, 72205, USA.
Visanu WanchaiMyeloma Center, Department of Internal Medicine, Winthrop P. Rockefeller Cancer Institute, University of Arkansas for Medical Sciences, 4301 W. Markham St. Slot# 508, Little Rock, AR, 72205, USA.
Eric R SiegelDepartment of Biostatistics, University of Arkansas for Medical Sciences, Little Rock, AR, USA.
Hongwei XuMyeloma Center, Department of Internal Medicine, Winthrop P. Rockefeller Cancer Institute, University of Arkansas for Medical Sciences, 4301 W. Markham St. Slot# 508, Little Rock, AR, 72205, USA.
Dongzheng GaiMyeloma Center, Department of Internal Medicine, Winthrop P. Rockefeller Cancer Institute, University of Arkansas for Medical Sciences, 4301 W. Markham St. Slot# 508, Little Rock, AR, 72205, USA.
Timothy Cody AshbyDepartment of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, USA.
Clyde BaileyMyeloma Center, Department of Internal Medicine, Winthrop P. Rockefeller Cancer Institute, University of Arkansas for Medical Sciences, 4301 W. Markham St. Slot# 508, Little Rock, AR, 72205, USA.
Jin-Ran ChenArkansas Children's Nutrition Center, University of Arkansas for Medical Sciences, Little Rock, AR, USA.
Carolina SchinkeMyeloma Center, Department of Internal Medicine, Winthrop P. Rockefeller Cancer Institute, University of Arkansas for Medical Sciences, 4301 W. Markham St. Slot# 508, Little Rock, AR, 72205, USA.
Sharmilan ThanendrarajanMyeloma Center, Department of Internal Medicine, Winthrop P. Rockefeller Cancer Institute, University of Arkansas for Medical Sciences, 4301 W. Markham St. Slot# 508, Little Rock, AR, 72205, USA.
Maurizio ZangariMyeloma Center, Department of Internal Medicine, Winthrop P. Rockefeller Cancer Institute, University of Arkansas for Medical Sciences, 4301 W. Markham St. Slot# 508, Little Rock, AR, 72205, USA.
Siegfried JanzDivision of Hematology and Oncology, Department of Medicine, Medical College of Wisconsin, Milwaukee, WI, USA.
Bart BarlogieMyeloma Center, Department of Internal Medicine, Winthrop P. Rockefeller Cancer Institute, University of Arkansas for Medical Sciences, 4301 W. Markham St. Slot# 508, Little Rock, AR, 72205, USA.
Frits Van RheeMyeloma Center, Department of Internal Medicine, Winthrop P. Rockefeller Cancer Institute, University of Arkansas for Medical Sciences, 4301 W. Markham St. Slot# 508, Little Rock, AR, 72205, USA.
Guido TricotMyeloma Center, Department of Internal Medicine, Winthrop P. Rockefeller Cancer Institute, University of Arkansas for Medical Sciences, 4301 W. Markham St. Slot# 508, Little Rock, AR, 72205, USA.
John D ShaughnessyMyeloma Center, Department of Internal Medicine, Winthrop P. Rockefeller Cancer Institute, University of Arkansas for Medical Sciences, 4301 W. Markham St. Slot# 508, Little Rock, AR, 72205, USA. JDShaughnessy@uams.edu.
Fenghuang ZhanMyeloma Center, Department of Internal Medicine, Winthrop P. Rockefeller Cancer Institute, University of Arkansas for Medical Sciences, 4301 W. Markham St. Slot# 508, Little Rock, AR, 72205, USA. FZhan@uams.edu.
University of Arkansas for Medical Sciences · USWinthrop Rockefeller Foundation · USMedical College of Wisconsin · US

Funding

Prevention of MGUS Progression to MM by Modulating the Bone Marrow MicroenvironmentU54CA272691 · NCI · CHILDREN'S MERCY HOSP (KANSAS CITY, MO) · PI Yong Li · 2023 to 2026
$6.1M
Towards a better understanding of the critical role and therapeutic potential of drug resistant genes in multiple myelomaR01CA236814 · NCI · UNIV OF ARKANSAS FOR MED SCIS · PI FENGHUANG ZHAN · 2020 to 2026
$2.5M
Automated Problem and Allergy Lists Enrichment Based on High Accuracy Information Extraction from the Electronic Health RecordR42CA180190 · NCI · CLINACUITY,INC. · PI MEYSTRE, STEPHANE · 2016 to 2017
$1.5M
Automated Dynamic Lists for Efficient Electronic Health Record ManagementR41CA180190 · NCI · CLINACUITY,INC. · PI MEYSTRE, STEPHANE · 2013 to 2014
$422k
NCI NIH HHS R01 CA236814NCI NIH HHS R41 CA180190NCI NIH HHS R42 CA180190NCI NIH HHS U54 CA272691NIH HHS 1R01CA236814-01A1
6 · The paper itself

Abstract

Multiple myeloma is preceded by monoclonal gammopathy of undetermined significance (MGUS). Serum markers are currently used to stratify MGUS patients into clinical risk groups. A molecular signature predicting MGUS progression has not been produced. We have explored the use of gene expression profiling to risk-stratify MGUS and developed an optimized signature based on large samples with long-term follow-up. Microarrays of plasma cell mRNA from 334 MGUS with stable disease and 40 MGUS that progressed to MM within 10 years, was used to define a molecular signature of MGUS risk. After a three-fold cross-validation analysis, the top thirty-six genes that appeared in each validation and maximized the concordance between risk score and MGUS progression were included in the gene signature (GS36). The GS36 accurately predicted MGUS progression (C-statistic is 0.928). An optimal cut-point for risk of progression by the GS36 score was found to be 0.7, which identified a subset of 61 patients with a 10-year progression probability of 54.1%. The remainder of the 313 patients had a probability of progression of only 2.2%. The sensitivity and specificity were 82.5% and 91.6%. Furthermore, combination of GS36, free light chain ratio and immunoparesis identified a subset of MGUS patients with 82.4% risk of progression to MM within 10 years. A gene expression signature combined with serum markers created a highly robust model for predicting risk of MGUS progression. These findings strongly support the inclusion of genomic analysis in the management of MGUS to identify patients who may benefit from more frequent monitoring.

Indexed as

Monoclonal Gammopathy of Undetermined SignificanceMultiple MyelomaGene Expression ProfilingGenomicsHumansPlasma CellsGene expression profilingGene signatureMonoclonal gammopathy of undetermined significance (MGUS)Multiple myelomaPrediction model

Identifiers

PMID37386588
PMCPMC10308756
OpenAlexW4382631517

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.