Evidence map›Paper›PMID 30607001›Full record

ArticleBlood cancer journal2019

Molecular signatures of multiple myeloma progression through single cell RNA-Seq.

Jin Sung Jang, Ying Li, Amit Kumar Mitra, Lintao Bi, Alexej Abyzov, Andre J van Wijnen, Linda B Baughn, Brian Van Ness, Vincent Rajkumar, Shaji Kumar and 1 more

Open access · goldAbstract read
In one paragraph

Article in Blood cancer journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers.

0numbers the graph read from it
0cells of the map it votes in
65citing papers in PubMed
12.8field-weighted citation impact, top 1% 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

65 citing papers in PubMed, 104 citations in OpenAlex.

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  19. Mitochondrial dysfunction and drug targets in multiple myeloma.Journal of cancer research and clinical oncology · 2023
    Review
  20. Review

5 more citing papers are in PubMed but not listed here.

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 at 5 institutions in 1 country.

Jin Sung JangGenome Analysis Core, Medical Genome Facility, Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA.
Ying LiDivision of Bioinformatics and Biostatistics, Department of Health Science Research, Mayo Clinic, Rochester, MN, USA.
Amit Kumar MitraDepartment of Drug Discovery and Development, Harrison School of Pharmacy, Auburn University, Auburn, AL, USA.
Lintao BiDivision of Hematology, Department of Internal Medicine, Mayo Clinic, Rochester, MN, USA.
Alexej AbyzovDivision of Bioinformatics and Biostatistics, Department of Health Science Research, Mayo Clinic, Rochester, MN, USA.
Andre J van WijnenDepartment of Orthopedic Surgery, Mayo Clinic, Rochester, MN, USA.ORCID http://orcid.org/0000-0002-4458-0946
Linda B BaughnDepartment of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA.
Brian Van NessDepartment of Genetics, Cell Biology & Development, University of Minnesota, Minneapolis, MN, USA.
Vincent RajkumarDivision of Hematology, Department of Internal Medicine, Mayo Clinic, Rochester, MN, USA.ORCID http://orcid.org/0000-0002-5862-1833
Shaji KumarDivision of Hematology, Department of Internal Medicine, Mayo Clinic, Rochester, MN, USA. Kumar.Shaji@mayo.edu.ORCID http://orcid.org/0000-0001-5392-9284
Jin JenGenome Analysis Core, Medical Genome Facility, Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA. jen.jin@mayo.edu.
Mayo Clinic in Arizona · USMayo Clinic · USMayo Clinic in Florida · USAuburn University · USUniversity of Minnesota · US

Funding

Project 4: Targeting Resistance to T-Cell Directed Therapy in Multiple MyelomaP50CA186781 · NCI · MAYO CLINIC ARIZONA · PI Rafael Fonseca · 2015 to 2026
$25.5M
Project 3 - Modeling Proteasome Inhibitor Response and Resistance in Cell Lines and Patient Samples with Single Cell Analysis of SubpopulationsU54CA224018 · NCI · MAYO CLINIC ARIZONA · PI BERGSAGEL, PETER LEIF · 2017 to 2021
$6.0M
NCI NIH HHS P50 CA186781NCI NIH HHS U54 CA224018U.S. Department of Health & Human Services | National Institutes of Health (NIH) U54CA224018
6 · The paper itself

Abstract

We used single cell RNA-Seq to examine molecular heterogeneity in multiple myeloma (MM) in 597 CD138 positive cells from bone marrow aspirates of 15 patients at different stages of disease progression. 790 genes were selected by coefficient of variation (CV) method and organized cells into four groups (L1-L4) using unsupervised clustering. Plasma cells from each patient clustered into at least two groups based on gene expression signature. The L1 group contained cells from all MGUS patients having the lowest expression of genes involved in the oxidative phosphorylation, Myc targets, and mTORC1 signaling pathways (p < 1.2 × 10

Indexed as

TranscriptomeBiopsyBone MarrowComputational BiologyDisease ProgressionGene Expression ProfilingHigh-Throughput Nucleotide SequencingHumansKaplan-Meier EstimateMultiple MyelomaPrognosisSequence Analysis, RNASingle-Cell AnalysisWorkflow

Identifiers

PMID30607001
PMCPMC6318319
OpenAlexW2908343344

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.