Evidence map›Paper›PMID 28691706›Full record

ArticleNature communications2017

Crosstalk and the evolvability of intracellular communication.

Michael A Rowland, Joseph M Greenbaum, Eric J Deeds

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
2.0field-weighted citation impact, top 13% 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

22 citing papers in PubMed, 41 citations in OpenAlex.

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  7. Signaling pathways and their potential therapeutic utility in esophageal squamous cell carcinoma.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2022
    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

3 authors at 3 institutions in 1 country.

Michael A RowlandUS Army Engineer Research and Development Center, 3909 Halls Ferry Road, Vicksburg, Mississippi 39180, USA.
Joseph M GreenbaumUniversity of Kansas, 2030 Becker Dr Lawrence, Kansas 66047, USA.
Eric J DeedsUniversity of Kansas, 2030 Becker Dr Lawrence, Kansas 66047, USA.
Oak Ridge Institute for Science and EducationSanta Fe Institute · USUniversity of Kansas · US

Funding

MBRS IMSD PROGRAM AT THE UNIVERSITY OF KANSASR25GM062232 · NIGMS · UNIVERSITY OF KANSAS LAWRENCE · PI CARTWRIGHT, PAULYN, HANSON, PAUL R. · 2001 to 2018
$6.9M
NIGMS NIH HHS R25 GM062232
6 · The paper itself

Abstract

Metazoan signalling networks are complex, with extensive crosstalk between pathways. It is unclear what pressures drove the evolution of this architecture. We explore the hypothesis that crosstalk allows different cell types, each expressing a specific subset of signalling proteins, to activate different outputs when faced with the same inputs, responding differently to the same environment. We find that the pressure to generate diversity leads to the evolution of networks with extensive crosstalk. Using available data, we find that human tissues exhibit higher levels of diversity between cell types than networks with random expression patterns or networks with no crosstalk. We also find that crosstalk and differential expression can influence drug activity: no protein has the same impact on two tissues when inhibited. In addition to providing a possible explanation for the evolution of crosstalk, our work indicates that consideration of cellular context will likely be crucial for targeting signalling networks.

Indexed as

Evolution, MolecularModels, GeneticReceptor Cross-TalkHumansSignal Transduction

Identifiers

PMID28691706
PMCPMC5508131
OpenAlexW2736039324

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.