Concurrent Gene Signatures for Han Chinese Breast Cancers

Chi-Cheng Huang,Ching-Shui Huang,Eric Y Chuang,Chi-Jung Huang,Jaan-Yeh Jeng,Shih-Hsin Tu,Liang-Chuan Lai,Heng-Hui Lien,Ying Xu

doi:10.1371/journal.pone.0076421

Abstract

The interplay between copy number variation (CNV) and differential gene expression may be able to shed light on molecular process underlying breast cancer and lead to the discovery of cancer-related genes. In the current study, genes concurrently identified in array comparative genomic hybridization (CGH) and gene expression microarrays were used to derive gene signatures for Han Chinese breast cancers.We performed 23 array CGHs and 81 gene expression microarrays in breast cancer samples from Taiwanese women. Genes with coherent patterns of both CNV and differential gene expression were identified from the 21 samples assayed using both platforms. We used these genes to derive signatures associated with clinical ER and HER2 status and disease-free survival.Distributions of signature genes were strongly associated with chromosomal location: chromosome 16 for ER and 17 for HER2. A breast cancer risk predictive model was built based on the first supervised principal component from 16 genes (RCAN3, MCOLN2, DENND2D, RWDD3, ZMYM6, CAPZA1, GPR18, WARS2, TRIM45, SCRN1, CSNK1E, HBXIP, CSDE1, MRPL20, IKZF1, and COL20A1), and distinct survival patterns were observed between the high- and low-risk groups from the combined dataset of 408 microarrays. The risk score was significantly higher in breast cancer patients with recurrence, metastasis, or mortality than in relapse-free individuals (0.241 versus 0, P<0.001). The concurrent gene risk predictive model remained discriminative across distinct clinical ER and HER2 statuses in subgroup analysis. Prognostic comparisons with published gene expression signatures showed a better discerning ability of concurrent genes, many of which were rarely identifiable if expression data were pre-selected by phenotype correlations or variability of individual genes.We conclude that parallel analysis of CGH and microarray data, in conjunction with known gene expression patterns, can be used to identify biomarkers with prognostic values in breast cancer.

Highlights

Breast cancer is a heterogeneous disease in terms of molecular taxonomy
Analysis of array comparative genomic hybridization (CGH) A total of 83 incidental breast cancer samples were recruited in a consecutive manner between January 2007 and December 2010
In the current study we found that breast cancer was heterogeneous in both gene expression and copy number variation (CNV)

Summary

Introduction

Microarray experiments in the past decade have revealed distinct molecular subtypes based on gene expression patterns, most of which are associated with clinical phenotypes or predictions of treatment response or survival [1,2,3,4,5,6,7,8,9,10]. In contrast to gene expression signatures, the clinical significance of genomic aberrations in breast tumors, such as amplifications and deletions, remains undefined. Chromosomal comparative genomic hybridization (CGH) is a technique designed to assess genomic aberrations in tumor and cultured cells; the complexity of genomic variations as well as resolution limitations have impeded widespread application of this technique to breast cancer. Recently has microarray-based CGH (array CGH), with either a BAC clone or oligonucleotide for hybridization, allowed the direct evaluation of the chromosomal instability of solid tumors [12,13,14]

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Discussion

Conclusion