ArticleOncotarget2018
Integrated landscape of copy number variation and RNA expression associated with nodal metastasis in invasive ductal breast carcinoma.
Article in Oncotarget, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed, 10 citations in OpenAlex.
- Multiple Testing of Mix-and-Match Feature Sets in Multi-Omics.Statistics in medicine · 2026Article
- Article
- Lipidomics investigations into the tissue phospholipidomic landscape of invasive ductal carcinoma of the breast.RSC advances · 2020Article
- Multi-omic signatures identify pan-cancer classes of tumors beyond tissue of origin.Scientific reports · 2020Article
- The genomic landscape of metastasis in treatment-naïve breast cancer models.PLoS genetics · 2020Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundLymph node metastasis (NM) in breast cancer is a clinical predictor of patient outcomes, but how its genetic underpinnings contribute to aggressive phenotypes is unclear. Our objective was to create the first landscape analysis of CNV-associated NM in ductal breast cancer. To assess the role of copy number variations (CNVs) in NM, we compared CNVs and/or associated mRNA expression in primary tumors of patients with NM to those without metastasis.
resultsWe found CNV loss in chromosomes 1, 3, 9, 18, and 19 and gains in chromosomes 5, 8, 12, 14, 16-17, and 20 that were associated with NM and replicated in both databases. In primary tumors, per-gene CNVs associated with NM were ten times more frequent than mRNA expression; however, there were few CNV-driven changes in mRNA expression that differed by nodal status. Overlapping regions of CNV changes and mRNA expression were evident for the
methodsData on CNV and mRNA expression from the TCGA and the METABRIC consortium of breast ductal carcinoma were utilized to identify CNV-based features associated with NM. Within each dataset, associations were compared across omic platforms to identify CNV-driven variations in gene expression. Only replications across both datasets were considered as determinants of NM.
conclusionsGains in
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Registered trials
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