ArticleBritish journal of cancer2012
A network-based, integrative study to identify core biological pathways that drive breast cancer clinical subtypes.
Article in British journal of cancer, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
What it found
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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.
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Who cites it
33 citing papers in PubMed, 49 citations in OpenAlex.
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- Hip osteoarthritis: A novel network analysis of subchondral trabecular bone structures.PNAS nexus · 2022Article
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- Biomarker-guided heterogeneity analysis of genetic regulations via multivariate sparse fusion.Statistics in medicine · 2021Article
- Genetic co-expression networks contribute to creating predictive model and exploring novel biomarkers for the prognosis of breast cancer.Scientific reports · 2021Article
- Integrated Network Analysis Reveals FOXM1 and MYBL2 as Key Regulators of Cell Proliferation in Non-small Cell Lung Cancer.Frontiers in oncology · 2019Article
- Investigating MicroRNA and transcription factor co-regulatory networks in colorectal cancer.BMC bioinformatics · 2017Article
- HIT'nDRIVE: patient-specific multidriver gene prioritization for precision oncology.Genome research · 2017Article
- The Many-Faced Program of Epithelial-Mesenchymal Transition: A System Biology-Based View.Frontiers in oncology · 2017Review
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- Coexpression network analysis of the genes regulated by two types of resistance responses to powdery mildew in wheat.Scientific reports · 2016Article
- Identifying Cancer Subtypes from miRNA-TF-mRNA Regulatory Networks and Expression Data.PloS one · 2016Article
- Empirical inference of circuitry and plasticity in a kinase signaling network.Proceedings of the National Academy of Sciences of the United States of America · 2015Article
- Targeting ADAM-17 with an inhibitory monoclonal antibody has antitumour effects in triple-negative breast cancer cells.British journal of cancer · 2015Article
- Article
- Identification of Novel Breast Cancer Subtype-Specific Biomarkers by Integrating Genomics Analysis of DNA Copy Number Aberrations and miRNA-mRNA Dual Expression Profiling.BioMed research international · 2015Article
- Systems biology approaches for studying the pathogenesis of non-alcoholic fatty liver disease.World journal of gastroenterology · 2014Review
- Reproducible combinatorial regulatory networks elucidate novel oncogenic microRNAs in non-small cell lung cancer.RNA (New York, N.Y.) · 2014Article
Corrections and comments
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Authors and funding
14 authors at 4 institutions in 3 countries.
Funding
Abstract
backgroundThe rapid collection of diverse genome-scale data raises the urgent need to integrate and utilise these resources for biological discovery or biomedical applications. For example, diverse transcriptomic and gene copy number variation data are currently collected for various cancers, but relatively few current methods are capable to utilise the emerging information.
methodsWe developed and tested a data-integration method to identify gene networks that drive the biology of breast cancer clinical subtypes. The method simultaneously overlays gene expression and gene copy number data on protein-protein interaction, transcriptional-regulatory and signalling networks by identifying coincident genomic and transcriptional disturbances in local network neighborhoods.
resultsWe identified distinct driver-networks for each of the three common clinical breast cancer subtypes: oestrogen receptor (ER)+, human epidermal growth factor receptor 2 (HER2)+, and triple receptor-negative breast cancers (TNBC) from patient and cell line data sets. Driver-networks inferred from independent datasets were significantly reproducible. We also confirmed the functional relevance of a subset of randomly selected driver-network members for TNBC in gene knockdown experiments in vitro. We found that TNBC driver-network members genes have increased functional specificity to TNBC cell lines and higher functional sensitivity compared with genes selected by differential expression alone.
conclusionClinical subtype-specific driver-networks identified through data integration are reproducible and functionally important.
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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.