ArticleNature genetics2016
Regulators of genetic risk of breast cancer identified by integrative network analysis.
Article in Nature genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 136 papers, 1 of them a synthesis that pooled it.
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Who cites it
136 citing papers in PubMed, 1 synthesis or guideline pooled it, 202 citations in OpenAlex.
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- Mixed-model and transcriptome-wide association analyses identify transcription factors and genes associated with colorectal cancer susceptibility.Nature communications · 2026Article
- Immune - cell death index in hepatocellular carcinoma: a multi-omics and machine learning study for prognosis and immunotherapy prediction.Frontiers in immunology · 2026Article
- Systematic profiling reveals distinct senescence signatures and regulators across human brain cell types.Nature communications · 2025Article
- Reconstruction of the transcriptional regulatory networks in the kidney of desert-adapted species.Communications biology · 2025Article
- Proteogenomic profiling of soft tissue leiomyosarcoma reveals distinct molecular subtypes with divergent outcomes and therapeutic vulnerabilities.bioRxiv : the preprint server for biology · 2025Article
- Dysregulated mitochondrial energy metabolism drives the progression of mucosal field effects to invasive bladder cancer.The Journal of pathology · 2025Article
- DNA methylation mediates the immunosuppressive tumour microenvironment in metastatic endometrial clear cell carcinoma.EBioMedicine · 2025Article
- Melanocortin System Activates Carotid Body Arterial Chemoreceptors in Hypertension.Circulation research · 2025Article
- PIT-1/SF-1-positive pituitary tumors in patients with acromegaly: transcriptomic perspective.Acta neuropathologica communications · 2025Article
- Article
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Corrections and comments
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Authors and funding
10 authors at 3 institutions in 3 countries.
Funding
Abstract
Genetic risk for breast cancer is conferred by a combination of multiple variants of small effect. To better understand how risk loci might combine, we examined whether risk-associated genes share regulatory mechanisms. We created a breast cancer gene regulatory network comprising transcription factors and groups of putative target genes (regulons) and asked whether specific regulons are enriched for genes associated with risk loci via expression quantitative trait loci (eQTLs). We identified 36 overlapping regulons that were enriched for risk loci and formed a distinct cluster within the network, suggesting shared biology. The risk transcription factors driving these regulons are frequently mutated in cancer and lie in two opposing subgroups, which relate to estrogen receptor (ER)(+) luminal A or luminal B and ER(-) basal-like cancers and to different luminal epithelial cell populations in the adult mammary gland. Our network approach provides a foundation for determining the regulatory circuits governing breast cancer, to identify targets for intervention, and is transferable to other disease settings.
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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.