Evidence map›Paper›PMID 38443358›Full record

ArticleBlood cancer journal2024

Enhancing prognostic power in multiple myeloma using a plasma cell signature derived from single-cell RNA sequencing.

Jian-Rong Li, Shahram Arsang-Jang, Yan Cheng, Fumou Sun, Anita D'Souza, Binod Dhakal, Parameswaran Hari, Quillan Huang, Paul Auer, Yong Li and 6 more

Open access · goldAbstract read
In one paragraph

Article in Blood cancer journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.3field-weighted citation impact, top 13% 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

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Trial
  2. Review
  3. Review
  4. Review
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

16 authors at 3 institutions in 1 country.

Jian-Rong LiDepartment of Medicine, Baylor College of Medicine, Houston, TX, USA.
Shahram Arsang-JangDivision of Hematology Oncology, Department of Medicine, Medical College of Wisconsin, Milwaukee, WI, USA.
Yan ChengMyeloma Center, Winthrop P. Rockefeller Cancer Institute, Department of Internal Medicine, University of Arkansas for Medical Sciences, Little Rock, AR, USA.ORCID 0000-0001-7877-9622
Fumou SunMyeloma Center, Winthrop P. Rockefeller Cancer Institute, Department of Internal Medicine, University of Arkansas for Medical Sciences, Little Rock, AR, USA.ORCID 0000-0003-2034-3492
Anita D'SouzaDivision of Hematology Oncology, Department of Medicine, Medical College of Wisconsin, Milwaukee, WI, USA.ORCID 0000-0002-1092-5643
Binod DhakalDivision of Hematology Oncology, Department of Medicine, Medical College of Wisconsin, Milwaukee, WI, USA.ORCID 0000-0002-4377-9742
Parameswaran HariDivision of Hematology Oncology, Department of Medicine, Medical College of Wisconsin, Milwaukee, WI, USA.ORCID 0000-0002-8800-297X
Quillan HuangDepartment of Hematology/Oncology, Baylor College of Medicine, Houston, TX, USA.
Paul AuerDivision of Biostatistics, Institute for Health & Equity, and Cancer Center, Medical College of Wisconsin, Milwaukee, WI, USA.
Yong LiDepartment of Medicine, Baylor College of Medicine, Houston, TX, USA.ORCID 0000-0001-8838-1714
Raul UrrutiaLinda T. and John A. Mellowes Center for Genomic Sciences and Precision Medicine, Medical College of Wisconsin, Milwaukee, WI, USA.
Fenghuang ZhanMyeloma Center, Winthrop P. Rockefeller Cancer Institute, Department of Internal Medicine, University of Arkansas for Medical Sciences, Little Rock, AR, USA.ORCID 0000-0001-5417-2973
John D ShaughnessyMyeloma Center, Winthrop P. Rockefeller Cancer Institute, Department of Internal Medicine, University of Arkansas for Medical Sciences, Little Rock, AR, USA.
Siegfried JanzDivision of Hematology Oncology, Department of Medicine, Medical College of Wisconsin, Milwaukee, WI, USA.ORCID 0000-0002-2229-5511
Jing Dong *Division of Hematology Oncology, Department of Medicine, Medical College of Wisconsin, Milwaukee, WI, USA. jidong@mcw.edu.ORCID 0000-0001-9856-5963
Chao Cheng *Department of Medicine, Baylor College of Medicine, Houston, TX, USA. chao.cheng@bcm.edu.ORCID 0000-0002-5002-3417
Medical College of Wisconsin · USBaylor College of Medicine · USWinthrop Rockefeller Foundation · US

Funding

Defining genetic pathways of plasma-cell neoplasiaR01CA151354 · NCI · UNIVERSITY OF IOWA · PI JANZ, SIEGFRIED · 2010 to 2022
$3.9M
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
An innovative integrated computational framework using gene signatures for patient stratificationR01CA269764 · NCI · BAYLOR COLLEGE OF MEDICINE · PI CHAO CHENG · 2023 to 2026
$1.8M
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
Prognostic implications of mitochondrial inheritance in myelodysplastic syndromes after stem-cell transplantationK01HL164972 · NHLBI · MEDICAL COLLEGE OF WISCONSIN · PI Jing Dong · 2023 to 2026
$697k
High Memory High-Performance Computer Cluster for Biomedical ResearchS10OD032185 · OD · BAYLOR COLLEGE OF MEDICINE · PI HILSENBECK, SUSAN G. · 2022 to 2022
$596k
Automated Dynamic Lists for Efficient Electronic Health Record ManagementR41CA180190 · NCI · CLINACUITY,INC. · PI MEYSTRE, STEPHANE · 2013 to 2014
$422k
NCI NIH HHS R01 CA151354NCI NIH HHS R01 CA236814NCI NIH HHS R01 CA269764NCI NIH HHS R41 CA180190NCI NIH HHS R42 CA180190NHLBI NIH HHS K01 HL164972NIH HHS S10 OD032185
6 · The paper itself

Abstract

Multiple myeloma (MM) is a heterogenous plasma cell malignancy, for which the established prognostic models exhibit limitations in capturing the full spectrum of outcome variability. Leveraging single-cell RNA-sequencing data, we developed a novel plasma cell gene signature. We evaluated and validated the associations of the resulting plasma cell malignancy (PBM) score with disease state, progression and clinical outcomes using data from five independent myeloma studies consisting of 2115 samples (1978 MM, 65 monoclonal gammopathy of undetermined significance, 35 smoldering MM, and 37 healthy controls). Overall, a higher PBM score was significantly associated with a more advanced stage within the spectrum of plasma cell dyscrasias (all p < 0.05) and a shorter overall survival in MM (hazard ratio, HR = 1.72; p < 0.001). Notably, the prognostic effect of the PBM score was independent of the International Staging System (ISS) and Revised ISS (R-ISS). The downstream analysis further linked higher PBM scores with the presence of cytogenetic abnormalities, TP53 mutations, and compositional changes in the myeloma tumor immune microenvironment. Our integrated analyses suggest the PBM score may provide an opportunity for refining risk stratification and guide decisions on therapeutic approaches to MM.

Indexed as

Multiple MyelomaParaproteinemiasHumansPlasma CellsPrognosisSequence Analysis, RNATumor Microenvironment

Identifiers

PMID38443358
PMCPMC10915134
OpenAlexW4392514003

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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.