Evidence map›Paper›PMID 25961905›Full record

ArticlePLoS computational biology2015

Extensive decoupling of metabolic genes in cancer.

Ed Reznik, Chris Sander

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
1.8field-weighted citation impact, top 17% 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

24 citing papers in PubMed, 44 citations in OpenAlex.

  1. Article
  2. Article
  3. Gene regulatory networks in disease and ageing.Nature reviews. Nephrology · 2024
    Review
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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

2 authors at 1 institution in 1 country.

Ed ReznikComputational Biology Program, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America.
Chris SanderComputational Biology Program, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America.
Memorial Sloan Kettering Cancer Center · US

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
TR&D 3 - Network Guided Machine LearningP41GM103504 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI IDEKER, TREY · 2012 to 2024
$17.3M
MSKCC Center for Translational Cancer Genomic AnalysisU24CA143840 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI LADANYI, MARC, SANDER, CHRIS · 2009 to 2016
$11.5M
Pathway Commons: Research Resource for Biological PathwaysU41HG006623 · NHGRI · SLOAN-KETTERING INST CAN RESEARCH · PI SANDER, CHRIS · 2012 to 2017
$5.7M
NCI NIH HHS P30 CA008748NCI NIH HHS U24 CA143840NHGRI NIH HHS U41 HG006623NIGMS NIH HHS P41 GM103504
6 · The paper itself

Abstract

Tumorigenesis requires the re-organization of metabolism to support malignant proliferation. We examine how the altered metabolism of cancer cells is reflected in the rewiring of co-expression patterns among metabolic genes. Focusing on breast and clear-cell kidney tumors, we report the existence of key metabolic genes which act as hubs of differential co-expression, showing significantly different co-regulation patterns between normal and tumor states. We compare our findings to those from classical differential expression analysis, and counterintuitively observe that the extent of a gene's differential co-expression only weakly correlates with its differential expression, suggesting that the two measures probe different features of metabolism. Focusing on this discrepancy, we use changes in co-expression patterns to highlight the apparent loss of regulation by the transcription factor HNF4A in clear cell renal cell carcinoma, despite no differential expression of HNF4A. Finally, we aggregate the results of differential co-expression analysis into a Pan-Cancer analysis across seven distinct cancer types to identify pairs of metabolic genes which may be recurrently dysregulated. Among our results is a cluster of four genes, all components of the mitochondrial electron transport chain, which show significant loss of co-expression in tumor tissue, pointing to potential mitochondrial dysfunction in these tumor types.

Indexed as

Breast NeoplasmsCarcinoma, Renal CellCell Transformation, NeoplasticComputational BiologyElectron TransportFemaleGene Expression ProfilingGenes, MitochondrialHumansKidney NeoplasmsMetabolic Networks and PathwaysModels, BiologicalMultigene FamilyNeoplasms

Identifiers

PMID25961905
PMCPMC4427321
OpenAlexW2113532366

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.