Evidence map›Paper›PMID 29204123›Full record

ArticleFrontiers in physiology2017

Network Modularity in Breast Cancer Molecular Subtypes.

Sergio Antonio Alcalá-Corona, Guillermo de Anda-Jáuregui, Jesús Espinal-Enríquez, Enrique Hernández-Lemus

Abstract read
In one paragraph

Article in Frontiers in physiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 1 pooled it
–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

24 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Contrast-enhanced mammography based quantitative and qualitative feature analysis across different breast cancer molecular subtypes.Cancer imaging : the official publication of the International Cancer Imaging Society · 2026
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  15. Modularity in Biological Networks.Frontiers in genetics · 2021
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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

4 authors.

Sergio Antonio Alcalá-CoronaComputational Genomics, National Institute of Genomic Medicine, México City, Mexico.
Guillermo de Anda-JáureguiComputational Genomics, National Institute of Genomic Medicine, México City, Mexico.
Jesús Espinal-EnríquezComputational Genomics, National Institute of Genomic Medicine, México City, Mexico.
Enrique Hernández-LemusComputational Genomics, National Institute of Genomic Medicine, México City, Mexico.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer is a heterogeneous and complex disease, a clear manifestation of this is its classification into different molecular subtypes. On the other hand, gene transcriptional networks may exhibit different modular structures that can be related to known biological processes. Thus, modular structures in transcriptional networks may be seen as manifestations of regulatory structures that tightly controls biological processes. In this work, we identify modular structures on gene transcriptional networks previously inferred from microarray data of molecular subtypes of breast cancer: luminal A, luminal B, basal, and HER2-enriched. We analyzed the modules (communities) found in each network to identify particular biological functions (described in the Gene Ontology database) associated to them. We further explored these modules and their associated functions to identify common and unique features that could allow a better level of description of breast cancer, particularly in the basal-like subtype, the most aggressive and poor prognosis manifestation. Our findings related to the immune system and a decrease in cell death-related processes in basal subtype could help to understand it and design strategies for its treatment.

Indexed as

breast cancer subtypescommunity structureFunctional modulesgene regulatory networks (GRN)network modularitypathway enrichment analysis

Identifiers

PMID29204123
PMCPMC5699328

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.