Signaling network assessment of mutations and copy number variations predict breast cancer subtype-specific drug targets.
Individual cancer cells carry a bewildering number of distinct genomic alterations (e.g., 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 that represent two subtypes, luminal and basal. We integrated these sequencing data and functional RNAi screening data (for the identification of genes that are essential for cell proliferation and survival) onto a human signaling network. Two subtype-specific networks that potentially represent core-signaling mechanisms underlying tumorigenesis were identified. 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 on the basis of genomic alterations. Further, the networks effectively predicted subtype-specific drug targets, which were experimentally validated.
National Research Council Canada, Montreal, QC H4P 2R2, Canada; Department of Anatomy and Cell Biology, McGill University, Montreal, QC H3A 2B2, Canada; Center for Bioinformatics, McGill University, Montreal, QC H3G 0B1, Canada.
Naif
N
Zaman
Lei
L
Li
Maria Luz
ML
Jaramillo
Zhanpeng
Z
Sun
Chabane
C
Tibiche
Myriam
M
Banville
Catherine
C
Collins
Mark
M
Trifiro
Miltiadis
M
Paliouras
Andre
A
Nantel
Maureen
M
O'Connor-McCourt
Edwin
E
Wang
D001943:Breast Neoplasms / Q000188:drug therapy / Q000235:genetics* / Q000378:metabolism / Q000473:pathology; D045744:Cell Line, Tumor; D056915:DNA Copy Number Variations; D059472:Exome; D005260:Female; D006801:Humans; D058990:Molecular Targeted Therapy; D009154:Mutation; D015398:Signal Transduction