Evidence map›Paper›PMID 28176486›Full record

ArticleProteomics2017

Integrated analysis of proteome, phosphotyrosine-proteome, tyrosine-kinome, and tyrosine-phosphatome in acute myeloid leukemia.

Jiefei Tong, Mohamed Helmy, Florence M G Cavalli, Lily Jin, Jonathan St-Germain, Robert Karisch, Paul Taylor, Mark D Minden, Michael D Taylor, Benjamin G Neel and 2 more

Open access · greenAbstract read
In one paragraph

Article in Proteomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.2field-weighted citation impact, top 12% 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

10 citing papers in PubMed, 25 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Multimerin-1 and cancer: a review.Bioscience reports · 2022
    Review
  5. Review
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
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 5 institutions in 3 countries.

Jiefei TongProgram in Cell Biology, Hospital for Sick Children, Toronto, Canada.
Mohamed HelmyThe Donnelly Centre, University of Toronto, Toronto, Canada.
Florence M G CavalliPeter Gilgan Centre for Research and Learning, Hospital For Sick Children, Toronto, Canada.
Lily JinProgram in Cell Biology, Hospital for Sick Children, Toronto, Canada.
Jonathan St-GermainPrincess Margaret Cancer Centre, University of Toronto, Toronto, Canada.
Robert KarischPrincess Margaret Cancer Centre, University of Toronto, Toronto, Canada.
Paul TaylorProgram in Cell Biology, Hospital for Sick Children, Toronto, Canada.
Mark D MindenPrincess Margaret Cancer Centre, University of Toronto, Toronto, Canada.
Michael D TaylorPeter Gilgan Centre for Research and Learning, Hospital For Sick Children, Toronto, Canada.
Benjamin G NeelPrincess Margaret Cancer Centre, University of Toronto, Toronto, Canada.
Gary D BaderThe Donnelly Centre, University of Toronto, Toronto, Canada.
Michael F MoranProgram in Cell Biology, Hospital for Sick Children, Toronto, Canada.
Hospital for Sick Children · CAUniversity of Toronto · CABrain Tumour Research · GBDonnelly College · USPrincess Margaret Cancer Centre · CA

Funding

TR&D 3 - Network Guided Machine LearningP41GM103504 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI IDEKER, TREY · 2012 to 2024
$17.3M
Pathway Commons: Research Resource for Biological PathwaysU41HG006623 · NHGRI · SLOAN-KETTERING INST CAN RESEARCH · PI SANDER, CHRIS · 2012 to 2017
$5.7M
Cytoscape: A Modeling Platform for Biomolecular NetworksR01GM070743 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI IDEKER, TREY · 2004 to 2016
$5.7M
Pathway Commons: Research Resource for Biological PathwaysP41HG004118 · NHGRI · SLOAN-KETTERING INST CAN RESEARCH · PI SANDER, CHRIS · 2008 to 2011
$3.8M
Cytoscape: A Modeling Platform for Biomolecular NetworksR01HG009979 · NHGRI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI IDEKER, TREY · 2017 to 2021
$3.5M
Canadian Institutes for Health ResearchNHGRI NIH HHS P41 HG004118NHGRI NIH HHS R01 HG009979NHGRI NIH HHS U41 HG006623NIGMS NIH HHS P41 GM103504NIGMS NIH HHS R01 GM070743
6 · The paper itself

Abstract

Reversible protein-tyrosine phosphorylation is catalyzed by the antagonistic actions of protein-tyrosine kinases (PTKs) and phosphatases (PTPs), and represents a major form of cell regulation. Acute myeloid leukemia (AML) is an aggressive hematological malignancy that results from the acquisition of multiple genetic alterations, which in some instances are associated with deregulated protein-phosphotyrosine (pY) mediated signaling networks. However, although individual PTKs and PTPs have been linked to AML and other malignancies, analysis of protein-pY networks as a function of activated PTKs and PTPs has not been done. In this study, MS was used to characterize AML proteomes, and phospho-proteome-subsets including pY proteins, PTKs, and PTPs. AML proteomes resolved into two groups related to high or low degrees of maturation according to French-American-British classification, and reflecting differential expression of cell surface antigens. AML pY proteomes reflect canonical, spatially organized signaling networks, unrelated to maturation, with heterogeneous expression of activated receptor and nonreceptor PTKs. We present the first integrated analysis of the pY-proteome, activated PTKs, and PTPs. Every PTP and most PTKs have both positive and negative associations with the pY-proteome. pY proteins resolve into groups with shared PTK and PTP correlations. These findings highlight the importance of pY turnover and the PTP phosphatome in shaping the pY-proteome in AML.

Indexed as

HumansLeukemia, Myeloid, AcutePhosphorylationPhosphotyrosineProtein KinasesProteomeProteomicsSignal TransductionPhosphotyrosineProtein KinasesProteomeAMLKinomeProteomePTPomepYome

Identifiers

PMID28176486
PMCPMC5500908
OpenAlexW2587171772

What OpenQuestion holds

Textmetadata
LicenceTDM
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.