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Common profiles of Notch signaling differentiate disease-free survival in luminal type A and triple negative breast cancer

Overview of attention for article published in Oncotarget, November 2016
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Title
Common profiles of Notch signaling differentiate disease-free survival in luminal type A and triple negative breast cancer
Published in
Oncotarget, November 2016
DOI 10.18632/oncotarget.13451
Pubmed ID
Authors

Magdalena Orzechowska, Dorota Jędroszka, Andrzej K. Bednarek

Abstract

Breast cancer (BC) is characterized by high heterogeneity regarding its biology and clinical characteristics. The Notch pathway regulates such processes as organ modeling and epithelial-to-mesenchymal transition (EMT).The aim of the study was to determine the effect of differential expression of Notch members on disease-free survival (DFS) in luminal type A (lumA) and triple negative (TN) BC.The differential expression of 19 Notch members was examined in a TCGA BC cohort. DFS analysis was performed using the log-rank test (p<0.05). Biological differences between DFS groups were determined with Gene Set Enrichment Analysis (GSEA) (tTest, FDR<0.25). Common expression profiles according to Notch signaling were examined using ExpressCluster (K-means, mean centered, Euclidean distance metric).The overexpression of HES1, LFNG and PSEN1 was found to be favorable for DFS in lumA, and lowered expression favorable for DFS in TN.GSEA analysis showed that differential Notch signaling is associated with cell cycle, tissue architecture and remodeling. Particularly, targets of E2F, early stage S phase transcription factor, were upregulated in the lumA unfavorable group and the TN favorable group differentiated on a basis of HES1 and PSEN1 expression.Summarizing, our analysis show significance of Notch signaling in BRCA progression through triggering EMT. Moreover, identification of numerous genes which overexpression is associated with disease recurrence may serve as a source of potential targets for a new anticancer therapy.

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The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 22 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 18%
Student > Bachelor 4 18%
Student > Master 3 14%
Researcher 2 9%
Student > Doctoral Student 1 5%
Other 1 5%
Unknown 7 32%
Readers by discipline Count As %
Medicine and Dentistry 7 32%
Biochemistry, Genetics and Molecular Biology 3 14%
Agricultural and Biological Sciences 3 14%
Computer Science 1 5%
Mathematics 1 5%
Other 0 0%
Unknown 7 32%