ArticleFrontiers in physiology2018
The Hierarchical Modular Structure of HER2+ Breast Cancer Network.
Article in Frontiers in physiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it, 27 citations in OpenAlex.
- Unveiling the Link Between Inflammation and Adaptive Immunity in Breast Cancer.Frontiers in immunology · 2019Pooled it
- Pseudogene Coexpression Networks Reveal a Robust Prognostic Signature for Pediatric B-ALL Survival.Cancer research communications · 2026Article
- Potential Drug Synergy Through the ERBB2 Pathway in HER2+ Breast Tumors.International journal of molecular sciences · 2024Article
- The network structure of hematopoietic cancers.Scientific reports · 2023Article
- Detecting Human Epidermal Growth Factor Receptor 2 (HER2) Amplification: Proof of Concept of an Alternative Approach.Cureus · 2023Article
- Pseudogenes in Cancer: State of the Art.Cancers · 2023Review
- Review
- Molecular Subtyping of Cancer Based on Robust Graph Neural Network and Multi-Omics Data Integration.Frontiers in genetics · 2022Article
- k-core genes underpin structural features of breast cancer.Scientific reports · 2021Article
- A Transcriptome Community-and-Module Approach of the Human Mesoconnectome.Entropy (Basel, Switzerland) · 2021Article
- Highly connected, non-redundant microRNA functional control in breast cancer molecular subtypes.Interface focus · 2021Article
- Modularity in Biological Networks.Frontiers in genetics · 2021Review
- Loss of Long Distance Co-Expression in Lung Cancer.Frontiers in genetics · 2021Article
- Luminal A Breast Cancer Co-expression Network: Structural and Functional Alterations.Frontiers in genetics · 2021Article
- Gene Co-Expression in Breast Cancer: A Matter of Distance.Frontiers in oncology · 2021Article
- Structure of communities in semantic networks of biomedical research on disparities in health and sexismBiomedica : revista del Instituto Nacional de Salud · 2020Review
- Gene Expression and Co-expression Networks Are Strongly Altered Through Stages in Clear Cell Renal Carcinoma.Frontiers in genetics · 2020Article
- Comorbidity Networks in Cardiovascular Diseases.Frontiers in physiology · 2020Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
HER2-enriched breast cancer is a complex disease characterized by the overexpression of the ERBB2 amplicon. While the effects of this genomic aberration on the pathology have been studied, genome-wide deregulation patterns in this subtype of cancer are also observed. A novel approach to the study of this malignant neoplasy is the use of transcriptional networks. These networks generally exhibit modular structures, which in turn may be associated to biological processes. This modular regulation of biological functions may also exhibit a hierarchical structure, with deeper levels of modular organization accounting for more specific functional regulation. In this work, we identified the most probable (maximum likelihood) model of the hierarchical modular structure of the HER2-enriched transcriptional network as reconstructed from gene expression data, and analyzed the statistical associations of modules and submodules to biological functions. We found modular structures, independent from direct ERBB2 amplicon regulation, involved in different biological functions such as signaling, immunity, and cellular morphology. Higher resolution submodules were identified in more specific functions, such as micro-RNA regulation and the activation of viral-like immune response. We propose the approach presented here as one that may help to unveil mechanisms involved in the development of the pathology.
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Registered trials
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.