Evidence map›Paper›PMID 37217482›Full record

ArticleBlood cancer journal2023

Mass Cytometry reveals unique phenotypic patterns associated with subclonal diversity and outcomes in multiple myeloma.

Linda B Baughn, Erik Jessen, Neeraj Sharma, Hongwei Tang, James B Smadbeck, Mark D Long, Kathryn Pearce, Matthew Smith, Surendra Dasari, Zohar Sachs and 8 more

Open access · goldAbstract read
In one paragraph

Article in Blood cancer journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.3field-weighted citation impact, top 11% 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

5 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Review
  5. 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

18 authors at 8 institutions in 2 countries.

Linda B BaughnDivision of Laboratory Genetics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA. baughn.linda@mayo.edu.ORCID 0000-0001-5229-4897
Erik JessenDivision of Computational Biology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
Neeraj SharmaDivision of Laboratory Genetics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA.ORCID 0000-0002-8229-3083
Hongwei TangDivision of Laboratory Genetics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA.
James B SmadbeckDivision of Computational Biology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
Mark D LongDepartment of Biostatistics and Bioinformatics, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA.
Kathryn PearceDivision of Laboratory Genetics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA.
Matthew SmithDivision of Hematology, Department of Internal Medicine, Mayo Clinic, Rochester, MN, USA.
Surendra DasariDivision of Computational Biology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
Zohar SachsDivision of Hematology, Oncology, and Transplantation, Department of Medicine and Masonic Cancer Center, University of Minnesota, Minneapolis, MN, USA.ORCID 0000-0001-9386-4163
Michael A LindenDepartment of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA.
Joselle CookDivision of Hematology, Department of Internal Medicine, Mayo Clinic, Rochester, MN, USA.ORCID 0000-0001-5335-9533
A Keith StewartPrincess Margaret Cancer Centre, Toronto, ON, Canada.
Marta ChesiDivision of Hematology, Department of Internal Medicine, Mayo Clinic, Scottsdale, AZ, USA.ORCID 0000-0002-4024-8225
Amit MitraDepartment of Drug Discovery and Development, Auburn University, Auburn, AL, USA.ORCID 0000-0003-4046-7070
P Leif BergsagelDivision of Hematology, Department of Internal Medicine, Mayo Clinic, Scottsdale, AZ, USA.ORCID 0000-0003-1523-7388
Brian Van NessDepartment of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, MN, USA.ORCID 0000-0003-4985-2274
Shaji K KumarDivision of Hematology, Department of Internal Medicine, Mayo Clinic, Rochester, MN, USA.ORCID 0000-0001-5392-9284
Mayo Clinic in Arizona · USMayo Clinic · USMayo Clinic in Florida · USUniversity of Minnesota · USAuburn University · USPrincess Margaret Cancer Centre · CARoswell Park Comprehensive Cancer Center · USUniversity of Minnesota Medical Center · US

Funding

Project 4: Targeting Resistance to T-Cell Directed Therapy in Multiple MyelomaP50CA186781 · NCI · MAYO CLINIC ARIZONA · PI Yi Lin · 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 CA224018
6 · The paper itself

Abstract

Multiple myeloma (MM) remains an incurable plasma cell (PC) malignancy. Although it is known that MM tumor cells display extensive intratumoral genetic heterogeneity, an integrated map of the tumor proteomic landscape has not been comprehensively evaluated. We evaluated 49 primary tumor samples from newly diagnosed or relapsed/refractory MM patients by mass cytometry (CyTOF) using 34 antibody targets to characterize the integrated landscape of single-cell cell surface and intracellular signaling proteins. We identified 13 phenotypic meta-clusters across all samples. The abundance of each phenotypic meta-cluster was compared to patient age, sex, treatment response, tumor genetic abnormalities and overall survival. Relative abundance of several of these phenotypic meta-clusters were associated with disease subtypes and clinical behavior. Increased abundance of phenotypic meta-cluster 1, characterized by elevated CD45 and reduced BCL-2 expression, was significantly associated with a favorable treatment response and improved overall survival independent of tumor genetic abnormalities or patient demographic variables. We validated this association using an unrelated gene expression dataset. This study represents the first, large-scale, single-cell protein atlas of primary MM tumors and demonstrates that subclonal protein profiling may be an important determinant of clinical behavior and outcome.

Indexed as

Multiple MyelomaHumansPlasma CellsProteomics

Identifiers

PMID37217482
PMCPMC10203138
OpenAlexW4377287471

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.