Evidence map›Paper›PMID 31101498›Full record

ArticleMolecular cell2019

Analysis of the Human Kinome and Phosphatome by Mass Cytometry Reveals Overexpression-Induced Effects on Cancer-Related Signaling.

Xiao-Kang Lun, Damian Szklarczyk, Attila Gábor, Nadine Dobberstein, Vito Riccardo Tomaso Zanotelli, Julio Saez-Rodriguez, Christian von Mering, Bernd Bodenmiller

Open access · bronzeAbstract read
In one paragraph

Article in Molecular cell, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
2.9field-weighted citation impact, top 8% 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

30 citing papers in PubMed, 56 citations in OpenAlex.

  1. Article
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  9. Review
  10. Article
  11. Emerging Roles of YES1 in Cancer: The Putative Target in Drug Resistance.International journal of molecular sciences · 2024
    Review
  12. Review
  13. Review
  14. Article
  15. Review
  16. ANPELA: Significantly Enhanced Quantification Tool for Cytometry-Based Single-Cell Proteomics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023
    Article
  17. Article
  18. The Intriguing Landscape of Single-Cell Protein Analysis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022
    Review
  19. Article
  20. 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

8 authors at 3 institutions in 3 countries.

Xiao-Kang LunInstitute of Molecular Life Sciences, University of Zürich, 8057 Zürich, Switzerland; Molecular Life Sciences PhD Program, Life Science Zürich Graduate School, ETH Zürich and University of Zürich, 8057 Zürich, Switzerland.
Damian SzklarczykInstitute of Molecular Life Sciences, University of Zürich, 8057 Zürich, Switzerland.
Attila GáborJoint Research Centre for Computational Biomedicine, Faculty of Medicine, RWTH Aachen University, 52074 Aachen, Germany.
Nadine DobbersteinInstitute of Molecular Life Sciences, University of Zürich, 8057 Zürich, Switzerland.
Vito Riccardo Tomaso ZanotelliInstitute of Molecular Life Sciences, University of Zürich, 8057 Zürich, Switzerland; Systems Biology PhD Program, Life Science Zürich Graduate School, ETH Zürich and University of Zürich, 8057 Zürich, Switzerland.
Julio Saez-RodriguezJoint Research Centre for Computational Biomedicine, Faculty of Medicine, RWTH Aachen University, 52074 Aachen, Germany; European Bioinformatics Institute, European Molecular Biology Laboratory (EMBL-EBI), Hinxton, CB10 1SD Cambridge, UK; Institute for Computational Biomedicine, Faculty of Medicine, Heidelberg University, BIOQUANT, 69120 Heidelberg, Germany.
Christian von MeringInstitute of Molecular Life Sciences, University of Zürich, 8057 Zürich, Switzerland.
Bernd BodenmillerInstitute of Molecular Life Sciences, University of Zürich, 8057 Zürich, Switzerland. Electronic address: bernd.bodenmiller@imls.uzh.ch.
University of Zurich · CHEuropean Bioinformatics Institute · GBJoint Research Centre · DE

Funding

Single-Cell Analyses of Human Islets in T1D Using Highly Multiplexed ImagingUC4DK108132 · NIDDK · UNIVERSITY OF FLORIDA · PI ATKINSON, MARK A., BODENMILLER, BERND · 2015 to 2015
$3.6M
European Research Council 336921NIDDK NIH HHS UC4 DK108132
6 · The paper itself

Abstract

Kinase and phosphatase overexpression drives tumorigenesis and drug resistance. We previously developed a mass-cytometry-based single-cell proteomics approach that enables quantitative assessment of overexpression effects on cell signaling. Here, we applied this approach in a human kinome- and phosphatome-wide study to assess how 649 individually overexpressed proteins modulated cancer-related signaling in HEK293T cells in an abundance-dependent manner. Based on these data, we expanded the functional classification of human kinases and phosphatases and showed that the overexpression effects include non-catalytic roles. We detected 208 previously unreported signaling relationships. The signaling dynamics analysis indicated that the overexpression of ERK-specific phosphatases sustains proliferative signaling. This suggests a phosphatase-driven mechanism of cancer progression. Moreover, our analysis revealed a drug-resistant mechanism through which overexpression of tyrosine kinases, including SRC, FES, YES1, and BLK, induced MEK-independent ERK activation in melanoma A375 cells. These proteins could predict drug sensitivity to BRAF-MEK concurrent inhibition in cells carrying BRAF mutations.

Indexed as

CarcinogenesisCell ProliferationDrug Resistance, NeoplasmGene Expression Regulation, NeoplasticHEK293 CellsHumansMelanomaMutationPhosphoric Monoester HydrolasesPhosphorylationPhosphotransferasesProtein Kinase InhibitorsProteomicsProto-Oncogene Proteins B-rafSignal TransductionBRAF protein, humanPhosphoric Monoester HydrolasesPhosphotransferasesProtein Kinase InhibitorsProto-Oncogene Proteins B-rafBP-R(2) analysiscancer signaling networksdrug resistancefunctional classificationhuman kinome and phosphatomemass cytometryoverexpression effectssignaling dynamicssignaling relationshipssingle-cell proteomics

Identifiers

PMID31101498
PMCPMC6561723
OpenAlexW2946532031

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.