High-resolution aCGH and expression profiling identifies a novel genomic subtype of ER negative breast cancer.
BACKGROUND
The characterization of copy number alteration patterns in breast cancer requires high-resolution genome-wide profiling of a large panel of tumor specimens. To date, most genome-wide array comparative genomic hybridization studies have used tumor panels of relatively large tumor size and high Nottingham Prognostic Index (NPI) that are not as representative of breast cancer demographics.


RESULTS
We performed an oligo-array-based high-resolution analysis of copy number alterations in 171 primary breast tumors of relatively small size and low NPI, which was therefore more representative of breast cancer demographics. Hierarchical clustering over the common regions of alteration identified a novel subtype of high-grade estrogen receptor (ER)-negative breast cancer, characterized by a low genomic instability index. We were able to validate the existence of this genomic subtype in one external breast cancer cohort. Using matched array expression data we also identified the genomic regions showing the strongest coordinate expression changes ('hotspots'). We show that several of these hotspots are located in the phosphatome, kinome and chromatinome, and harbor members of the 122-breast cancer CAN-list. Furthermore, we identify frequently amplified hotspots on 8q22.3 (EDD1, WDSOF1), 8q24.11-13 (THRAP6, DCC1, SQLE, SPG8) and 11q14.1 (NDUFC2, ALG8, USP35) associated with significantly worse prognosis. Amplification of any of these regions identified 37 samples with significantly worse overall survival (hazard ratio (HR) = 2.3 (1.3-1.4) p = 0.003) and time to distant metastasis (HR = 2.6 (1.4-5.1) p = 0.004) independently of NPI.


CONCLUSIONS
We present strong evidence for the existence of a novel subtype of high-grade ER-negative tumors that is characterized by a low genomic instability index. We also provide a genome-wide list of common copy number alteration regions in breast cancer that show strong coordinate aberrant expression, and further identify novel frequently amplified regions that correlate with poor prognosis. Many of the genes associated with these regions represent likely novel oncogenes or tumor suppressors.
Chin
Suet F
SF
Breast Cancer Functional Genomics, Cancer Research UK Cambridge Research Institute and Department of Oncology University of Cambridge, Li Ka-Shing Centre, Robinson Way, Cambridge CB2 0RE, UK. sc10021@cam.ac.uk
Teschendorff
Andrew E
AE
Marioni
John C
JC
Wang
Yanzhong
Y
Barbosa-Morais
Nuno L
NL
Thorne
Natalie P
NP
Costa
Jose L
JL
Pinder
Sarah E
SE
van de Wiel
Mark A
MA
Green
Andrew R
AR
Ellis
Ian O
IO
Porter
Peggy L
PL
Tavaré
Simon
S
Brenton
James D
JD
Ylstra
Bauke
B
Caldas
Carlos
C
D001943:Breast Neoplasms / Q000145:classification / Q000235:genetics*; D002880:Chromosomes, Human, Pair 11 / Q000235:genetics*; D002898:Chromosomes, Human, Pair 8 / Q000235:genetics*; D005260:Female; D018628:Gene Dosage / Q000235:genetics*; D020869:Gene Expression Profiling / Q000379:methods*; D015972:Gene Expression Regulation, Neoplastic; D042822:Genomic Instability; D023281:Genomics / Q000379:methods; D006801:Humans; D009693:Nucleic Acid Hybridization / Q000379:methods*; D009857:Oncogenes / Q000235:genetics*; D011960:Receptors, Estrogen / Q000378:metabolism
D011960:Receptors, Estrogen