Evidence map›Paper›PMID 34683129›Full record

ArticleJournal of personalized medicine2021

RNA-Sequencing-Based Transcriptomic Score with Prognostic and Theranostic Values in Multiple Myeloma.

Elina Alaterre, Veronika Vikova, Alboukadel Kassambara, Angélique Bruyer, Nicolas Robert, Guilhem Requirand, Caroline Bret, Charles Herbaux, Laure Vincent, Guillaume Cartron and 2 more

Open access · goldAbstract read
In one paragraph

Article in Journal of personalized medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.2field-weighted citation impact, top 21% 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

9 citing papers in PubMed, 12 citations in OpenAlex.

  1. Review
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  5. Oncoimmunology · 2024
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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

12 authors at 3 institutions in 3 countries.

Elina AlaterreInstitute of Human Genetics, UMR 9002 CNRS-UM, 34395 Montpellier, France.
Veronika VikovaInstitute of Human Genetics, UMR 9002 CNRS-UM, 34395 Montpellier, France.
Alboukadel KassambaraInstitute of Human Genetics, UMR 9002 CNRS-UM, 34395 Montpellier, France.
Angélique BruyerInstitute of Human Genetics, UMR 9002 CNRS-UM, 34395 Montpellier, France.
Nicolas RobertDepartment of Biological Hematology, CHU Montpellier, 34395 Montpellier, France.
Guilhem RequirandDepartment of Biological Hematology, CHU Montpellier, 34395 Montpellier, France.
Caroline BretInstitute of Human Genetics, UMR 9002 CNRS-UM, 34395 Montpellier, France.
Charles HerbauxInstitute of Human Genetics, UMR 9002 CNRS-UM, 34395 Montpellier, France.ORCID 0000-0003-4910-476X
Laure VincentDepartment of Clinical Hematology, CHU Montpellier, 34395 Montpellier, France.ORCID 0000-0001-5904-1286
Guillaume CartronUFR de Médecine, University of Montpellier, 34003 Montpellier, France.
Olivier ElementoCaryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY 10021, USA.
Jérôme MoreauxInstitute of Human Genetics, UMR 9002 CNRS-UM, 34395 Montpellier, France.ORCID 0000-0002-5717-3207
Centre National de la Recherche Scientifique · FRCentre Hospitalier Universitaire de Montpellier · FRCornell University · US

Funding

Agence Nationale de la Recherche ANR-18-CE15-0010-01Agence Nationale de la Recherche TIE-Skip; 2017-CE15-002401French National Cancer Institute PLBIO18-362 PIT-MMFrench National Cancer Institute PLBIO19-098 INCA_13832
6 · The paper itself

Abstract

Multiple myeloma (MM) is the second most frequent hematological cancer and is characterized by the clonal proliferation of malignant plasma cells. Genome-wide expression profiling (GEP) analysis with DNA microarrays has emerged as a powerful tool for biomedical research, generating a huge amount of data. Microarray analyses have improved our understanding of MM disease and have led to important clinical applications. In MM, GEP has been used to stratify patients, define risk, identify therapeutic targets, predict treatment response, and understand drug resistance. In this study, we built a gene risk score for 267 genes using RNA-seq data that demonstrated a prognostic value in two independent cohorts (n = 674 and n = 76) of newly diagnosed MM patients treated with high-dose Melphalan and autologous stem cell transplantation. High-risk patients were associated with the expression of genes involved in several major pathways implicated in MM pathophysiology, including interferon response, cell proliferation, hypoxia, IL-6 signaling pathway, stem cell genes, MYC, and epigenetic deregulation. The RNA-seq-based risk score was correlated with specific MM somatic mutation profiles and responses to targeted treatment including EZH2, MELK, TOPK/PBK, and Aurora kinase inhibitors, outlining potential utility for precision medicine strategies in MM.

Indexed as

gene expression profilingmultiple myelomaprecision medicinerisk stratification

Identifiers

PMID34683129
PMCPMC8541503
OpenAlexW3202447953

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.