Evidence map›Paper›PMID 24940735›Full record

ArticlePloS one2014

Gene expression correlations in human cancer cell lines define molecular interaction networks for epithelial phenotype.

Kurt W Kohn, Barry M Zeeberg, William C Reinhold, Yves Pommier

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
67citing papers in PubMed, 2 pooled it
4.0field-weighted citation impact, top 5% 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

67 citing papers in PubMed, 2 syntheses or guidelines pooled it, 108 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
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  5. A Novel Anti-Cadherin-17 Monoclonal Antibody, CaAntibodies (Basel, Switzerland) · 2026
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  19. GRHL2-controlled gene expression networks in luminal breast cancer.Cell communication and signaling : CCS · 2023
    Article
  20. Article

7 more citing papers are in PubMed but not listed here.

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

4 authors at 2 institutions in 1 country.

Kurt W KohnLaboratory of Molecular Pharmacology, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, United States of America.
Barry M ZeebergLaboratory of Molecular Pharmacology, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, United States of America.
William C ReinholdLaboratory of Molecular Pharmacology, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, United States of America.
Yves PommierLaboratory of Molecular Pharmacology, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, United States of America.
Center for Cancer Research · USNational Cancer Institute · US

Funding

Investigating Regulatory Networks that Control Cell Proliferation and ApoptosisZIABC006192 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI KOHN, KURT · 2009 to 2014
$3.8M
6 · The paper itself

Abstract

Using gene expression data to enhance our knowledge of control networks relevant to cancer biology and therapy is a challenging but urgent task. Based on the premise that genes that are expressed together in a variety of cell types are likely to functions together, we derived mutually correlated genes that function together in various processes in epithelial-like tumor cells. Expression-correlated genes were derived from data for the NCI-60 human tumor cell lines, as well as data from the Broad Institute's CCLE cell lines. NCI-60 cell lines that selectively expressed a mutually correlated subset of tight junction genes served as a signature for epithelial-like cancer cells. Those signature cell lines served as a seed to derive other correlated genes, many of which had various other epithelial-related functions. Literature survey yielded molecular interaction and function information about those genes, from which molecular interaction maps were assembled. Many of the genes had epithelial functions unrelated to tight junctions, demonstrating that new function categories were elicited. The most highly correlated genes were implicated in the following epithelial functions: interactions at tight junctions (CLDN7, CLDN4, CLDN3, MARVELD3, MARVELD2, TJP3, CGN, CRB3, LLGL2, EPCAM, LNX1); interactions at adherens junctions (CDH1, ADAP1, CAMSAP3); interactions at desmosomes (PPL, PKP3, JUP); transcription regulation of cell-cell junction complexes (GRHL1 and 2); epithelial RNA splicing regulators (ESRP1 and 2); epithelial vesicle traffic (RAB25, EPN3, GRHL2, EHF, ADAP1, MYO5B); epithelial Ca(+2) signaling (ATP2C2, S100A14, BSPRY); terminal differentiation of epithelial cells (OVOL1 and 2, ST14, PRSS8, SPINT1 and 2); maintenance of apico-basal polarity (RAB25, LLGL2, EPN3). The findings provide a foundation for future studies to elucidate the functions of regulatory networks specific to epithelial-like cancer cells and to probe for anti-cancer drug targets.

Indexed as

TranscriptomeAlternative SplicingBiological TransportCalcium SignalingCell Adhesion MoleculesCell DifferentiationCell Line, TumorCell PolarityEpithelial CellsHumansIntercellular JunctionsPhenotypeProtein Interaction MapsCell Adhesion Molecules

Identifiers

PMID24940735
PMCPMC4062414
OpenAlexW2084766332

What OpenQuestion holds

Textmetadata
LicenceCC0
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.