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19 April 2024 |
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Article overview
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Signaling Network Assessment of Mutations and Copy Number Variations Predicts Breast Cancer Subtype-specific Drug Targets | | Naif Zaman
; Lei Li
; Maria Jaramillo
; Zhanpeng Sun
; Chabane Tibiche
; Myriam Banville
; Catherine Collins
; Mark Trifiro
; Miltiadis Paliouras
; Andre Nantel
; Maureen OConnor-McCourt
; Edwin Wang
; | | Date: |
10 Sep 2014 | | Abstract: | Individual cancer cells carry a bewildering number of distinct genomic
alterations i.e., copy number variations and mutations, making it a challenge
to uncover genomic-driven mechanisms governing tumorigenesis. Here we performed
exome-sequencing on several breast cancer cell lines which represent two
subtypes, luminal and basal. We integrated this sequencing data, and functional
RNAi screening data (i.e., for identifying genes which are essential for cell
proliferation and survival), onto a human signaling network. Two
subtype-specific networks were identified, which potentially represent
core-signaling mechanisms underlying tumorigenesis. Within both networks, we
found that genes were differentially affected in different cell lines; i.e., in
some cell lines a gene was identified through RNAi screening whereas in others
it was genomically altered. Interestingly, we found that highly connected
network genes could be used to correctly classify breast tumors into subtypes
based on genomic alterations. Further, the networks effectively predicted
subtype-specific drug targets, which were experimentally validated. | | Source: | arXiv, 1409.3261 | | Services: | Forum | Review | PDF | Favorites | |
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