ArticlePLoS genetics2017
Pathway-based discovery of genetic interactions in breast cancer.
Article in PLoS genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
What it found
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Who cites it
23 citing papers in PubMed, 69 citations in OpenAlex.
- Article
- The Paul Fearn Award for Excellence in Data Sharing in Cancer Control and Population Sciences.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2026Article
- A global genetic interaction map of a human cell reveals conserved principles of genetic networks.bioRxiv : the preprint server for biology · 2025Article
- BridGE: a pathway-based analysis tool for detecting genetic interactions from GWAS.Nature protocols · 2024Review
- Mechanism of ferroptosis in breast cancer and research progress of natural compounds regulating ferroptosis.Journal of cellular and molecular medicine · 2024Review
- Multi-scale systems genomics analysis predicts pathways, cell types, and drug targets involved in normative variation in peri-adolescent human cognition.Cerebral cortex (New York, N.Y. : 1991) · 2023Article
- From bugs to bedside: functional annotation of human genetic variation for neurological disorders using invertebrate models.Human molecular genetics · 2022Article
- Article
- Theranostic Interpolation of Genomic Instability in Breast Cancer.International journal of molecular sciences · 2022Review
- Review
- Environmental robustness of the global yeast genetic interaction network.Science (New York, N.Y.) · 2021Article
- Trigenic Synthetic Genetic Array (τ-SGA) Technique for Complex Interaction Analysis.Methods in molecular biology (Clifton, N.J.) · 2021Article
- Systematic analysis of bypass suppression of essential genes.Molecular systems biology · 2020Article
- Drug mechanism-of-action discovery through the integration of pharmacological and CRISPR screens.Molecular systems biology · 2020Article
- Review
- High-Resolution Regulatory Maps Connect Vascular Risk Variants to Disease-Related Pathways.Circulation. Genomic and precision medicine · 2019Article
- Genetic interaction networks in cancer cells.Current opinion in genetics & development · 2019Review
- Integrating genetic and protein-protein interaction networks maps a functional wiring diagram of a cell.Current opinion in microbiology · 2018Review
- Synthetic Lethal Networks for Precision Oncology: Promises and Pitfalls.Journal of molecular biology · 2018Review
- Complex Haplotypes ofG3 (Bethesda, Md.) · 2018Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
Abstract
Breast cancer is the second largest cause of cancer death among U.S. women and the leading cause of cancer death among women worldwide. Genome-wide association studies (GWAS) have identified several genetic variants associated with susceptibility to breast cancer, but these still explain less than half of the estimated genetic contribution to the disease. Combinations of variants (i.e. genetic interactions) may play an important role in breast cancer susceptibility. However, due to a lack of statistical power, the current tests for genetic interactions from GWAS data mainly leverage prior knowledge to focus on small sets of genes or SNPs that are known to have an association with breast cancer. Thus, many genetic interactions, particularly among novel variants, remain understudied. Reverse-genetic interaction screens in model organisms have shown that genetic interactions frequently cluster into highly structured motifs, where members of the same pathway share similar patterns of genetic interactions. Based on this key observation, we recently developed a method called BridGE to search for such structured motifs in genetic networks derived from GWAS studies and identify pathway-level genetic interactions in human populations. We applied BridGE to six independent breast cancer cohorts and identified significant pathway-level interactions in five cohorts. Joint analysis across all five cohorts revealed a high confidence consensus set of genetic interactions with support in multiple cohorts. The discovered interactions implicated the glutathione conjugation, vitamin D receptor, purine metabolism, mitotic prometaphase, and steroid hormone biosynthesis pathways as major modifiers of breast cancer risk. Notably, while many of the pathways identified by BridGE show clear relevance to breast cancer, variants in these pathways had not been previously discovered by traditional single variant association tests, or single pathway enrichment analysis that does not consider SNP-SNP interactions.
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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.