Cargando…
Integrated landscape of copy number variation and RNA expression associated with nodal metastasis in invasive ductal breast carcinoma
BACKGROUND: Lymph 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...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals LLC
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6305147/ https://www.ncbi.nlm.nih.gov/pubmed/30627325 http://dx.doi.org/10.18632/oncotarget.26386 |
Sumario: | BACKGROUND: Lymph 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. RESULTS: We 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 CTAGE5 gene. In 8q12, 11q13-14, 20q1, and 17q14-24 regions, there were gene-specific gains in CNV-driven mRNA expression associated with NM. METHODS: Data 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. CONCLUSIONS: Gains in CTAGE5, NDUFC2, EIF4EBP1, and PSCA genes and their expression may aid in early diagnosis of metastatic breast carcinoma and have potential as therapeutic targets. |
---|