Evidence map›Paper›PMID 32631905›Full record

ArticleCancer research2020

Aquaporin-7 Regulates the Response to Cellular Stress in Breast Cancer.

Chen Dai, Verodia Charlestin, Man Wang, Zachary T Walker, Maria Cristina Miranda-Vergara, Beth A Facchine, Junmin Wu, William J Kaliney, Norman J Dovichi, Jun Li and 1 more

Abstract read
In one paragraph

Article in Cancer research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
–field-weighted citation impact
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

31 citing papers in PubMed.

  1. Review
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  11. Article
  12. Review
  13. Molecular basis for human aquaporin inhibition.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  14. Article
  15. Review
  16. Aquaporins in sepsis- an update.Frontiers in immunology · 2024
    Review
  17. Review
  18. Article
  19. Aquaporins in Tumor.Advances in experimental medicine and biology · 2023
    Article
  20. 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

11 authors.

Chen Dai *Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana.
Verodia Charlestin *Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana.ORCID 0000-0003-4357-2909
Man WangDepartment of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana.
Zachary T WalkerDepartment of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana.
Maria Cristina Miranda-VergaraDepartment of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana.
Beth A FacchineDepartment of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana.
Junmin WuDepartment of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana.
William J KalineyHarper Cancer Research Institute, South Bend, Indiana.ORCID 0000-0002-4785-1633
Norman J DovichiDepartment of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana.
Jun LiHarper Cancer Research Institute, South Bend, Indiana.
Laurie E LittlepageDepartment of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana. laurie.littlepage@nd.edu.ORCID 0000-0002-0839-8274

Funding

Chemistry-Biochemistry-Biology Training Program at Notre DameT32GM075762 · NIGMS · UNIVERSITY OF NOTRE DAME · PI CHANG, MAYLAND F, MOBASHERY, SHAHRIAR · 2007 to 2021
$3.7M
Technology for single cell proteomics and its application to the analysis of single Xenopus blastomeresR01GM096767 · NIGMS · UNIVERSITY OF NOTRE DAME · PI DOVICHI, NORMAN J · 2011 to 2019
$2.5M
Advances in bioanalysisR35GM136334 · NIGMS · UNIVERSITY OF NOTRE DAME · PI DOVICHI, NORMAN J · 2020 to 2024
$2.0M
Online Raman Diagnostics of OncometabolitesR33CA206922 · NCI · UNIVERSITY OF NOTRE DAME · PI SCHULTZ, ZACHARY · 2016 to 2018
$1.0M
NCI NIH HHS R33 CA206922NIGMS NIH HHS R01 GM096767NIGMS NIH HHS R35 GM136334NIGMS NIH HHS T32 GM075762
6 · The paper itself

Abstract

The complex yet interrelated connections between cancer metabolism, gene expression, and oncogenic driver genes have the potential to identify novel biomarkers and drug targets with prognostic and therapeutic value. Here we effectively integrated metabolomics and gene expression data from breast cancer mouse models through a novel unbiased correlation-based network analysis. This approach identified 35 metabolite and 34 gene hubs with the most network correlations. These hubs have prognostic value and are likely integral to tumor metabolism and breast cancer. The gene hub Aquaporin-7 (

Indexed as

AdipocytesAnimalsAquaporinsBreast NeoplasmsCarbohydrate MetabolismCell MovementFemaleGene Expression Regulation, NeoplasticGlycolipidsGlycolysisHumansInositolLipidsLung NeoplasmsMammary Glands, AnimalNitric OxideAQP7 protein, humanAqp7 protein, mouseAquaporinsGlcNalpha1-6-myo-inositol-1-HPO4-sn-1, 2-dipalmitoylglycerolGlycolipidsInositolLipidsNitric Oxide

Identifiers

PMID32631905
PMCPMC7899076

What OpenQuestion holds

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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.