High-resolution aCGH and expression profiling identifies a novel genomic subtype of ER negative breast cancer

Suet F Chin,John C Marioni,Yanzhong Wang,Carlos Caldas,Andrew R Green,James D Brenton,Natalie P Thorne,Mark A Van De Wiel,Ian O Ellis,Andrew E Teschendorff,Peggy L Porter,Simon Tavaré,Nuno L Barbosa-Morais,Bauke Ylstra,Sarah E Pinder,Jose L Costa

doi:10.1186/gb-2007-8-10-r215

Abstract

High resolution array-CGH and expression profiling identifies a novel genomic subtype of ER negative breast cancer, and provides a genome-wide list of common copy number alterations associated with aberrant expression and poor prognosis.

Highlights

The characterization of copy number alteration patterns in breast cancer requires high-resolution genome-wide profiling of a large panel of tumor specimens
Detailed clinical data of the breast cancer cohort profiled is available in Additional Data File 1, while the raw and normalized array comparative genomic hybridization (aCGH) data for tumors and cell lines is available from NCBI's Gene Expression Omnibus (GEO) [16,17,18] under the series accession number GSE8757
The choice of thresholds was further validated with the help of breast tumor cell lines with known gains and losses

Summary

Introduction

The characterization of copy number alteration patterns in breast cancer requires high-resolution genome-wide profiling of a large panel of tumor specimens. 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. A further important insight gained through array comparative genomic hybridization (aCGH) data has been the identification of clinically relevant tumor subclasses within specific tumor types (e.g. myelomas [3], glioblastomas [4], pancreatic adenocarcinomas [5], colorectal cancer [2], etc.), which often match those found from genome-wide gene expression studies. We asked whether the molecular taxonomy as well as the clinically relevant amplification and deregulation patterns could differ substantially if a tumor panel that is more representative of breast cancer demographics had been used To this end, we performed a high-resolution (

Objectives

Methods

Results

Discussion

Conclusion