ArticleScientific reports2018
Breast cancer associated germline structural variants harboring small noncoding RNAs impact post-transcriptional gene regulation.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Polyamine metabolism related gene index prediction of prognosis and immunotherapy response in breast cancer.Frontiers in oncology · 2025Article
- BMI-CNV: a Bayesian framework for multiple genotyping platforms detection of copy number variants.Genetics · 2022Article
- Automated prediction of the clinical impact of structural copy number variations.Scientific reports · 2022Article
- DNA copy number variation: Main characteristics, evolutionary significance, and pathological aspects.Biomedical journal · 2021Review
- Non-Coding Variants in Cancer: Mechanistic Insights and Clinical Potential for Personalized Medicine.Non-coding RNA · 2021Review
- Biomarker-guided heterogeneity analysis of genetic regulations via multivariate sparse fusion.Statistics in medicine · 2021Article
- A HPV16-related prognostic indicator for head and neck squamous cell carcinoma.Annals of translational medicine · 2020Article
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Authors and funding
7 authors.
Funding
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Abstract
Copy Number Variants (CNVs) are a class of structural variations of DNA. Germline CNVs are known to confer disease susceptibility, but their role in breast cancer warrants further investigations. We hypothesized that breast cancer associated germline CNVs contribute to disease risk through gene dosage or other post-transcriptional regulatory mechanisms, possibly through tissue specific expression of CNV-embedded small-noncoding RNAs (CNV-sncRNAs). Our objectives are to identify breast cancer associated CNVs using a genome wide association study (GWAS), identify sncRNA genes embedded within CNVs, confirm breast tissue (tumor and normal) expression of the sncRNAs, correlate their expression with germline copy status and identify pathways influenced by the genes regulated by sncRNAs. We used an association study design and accessed germline CNV data generated on Affymetrix Human SNP 6.0 array in 686 (in-house data) and 495 (TCGA data) subjects served as discovery and validation cohorts. We identified 1812 breast cancer associated CNVs harboring miRNAs (n = 38), piRNAs (n = 9865), snoRNAs (n = 71) and tRNAs (n = 12) genes. A subset of CNV-sncRNAs expressed in breast tissue, also showed correlation with germline copy status. We identified targets potentially regulated by miRNAs and snoRNAs. In summary, we demonstrate the potential impact of embedded CNV-sncRNAs on expression and regulation of down-stream targets.
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