Published OnlineFirst January 12, 2010; DOI: 10.1158/1078-0432.CCR-09-0709 Clinical Imaging, Diagnosis, Prognosis Cancer Research Integration of DNA Copy Number Alterations and Prognostic Gene Expression Signatures in Breast Cancer Patients Hugo M. Horlings1, Carmen Lai2,6, Dimitry S.A. Nuyten3, Hans Halfwerk1, Petra Kristel1, Erik van Beers1, Simon A. Joosse1, Christiaan Klijn2, Petra M. Nederlof4, Marcel J.T. Reinders6, Lodewyk F.A. Wessels2,6, and Marc J. van de Vijver5 Abstract Purpose: Several prognostic gene expression profiles have been identified in breast cancer. In spite of this progress in prognostic classification, the underlying mechanisms that drive these gene expression pat- terns remain unknown. Specific genomic alterations, such as copy number alterations, are an important factor in tumor development and progression and are also associated with changes in gene expression. Experimental Design: We carried out array comparative genomic hybridization in 68 human breast carcinomas for which gene expression and clinical data were available. We used a two-class supervised algorithm, Supervised Identification of Regions of Aberration in aCGH data sets, for the identification of regions of chromosomal alterations that are associated with specific sample labeling. Using gene expres- sion data from the same tumors, we identified genes in the altered regions for which the expression level is significantly correlated with the copy number and validated our results in public available data sets. Results: Specific chromosomal aberrations are related to clinicopathologic characteristics and prognos- tic gene expression signatures. The previously identified poor prognosis, 70-gene expression signature is associated with the gain of 3q26.33-27.1, 8q22.1-24.21, and 17q24.3-25.1; the 70-gene good prognosis profile is associated with the loss at 16q12.1-13 and 16q22.1-24.1; basal-like tumors are associated with the gain of 6p12.3-23, 8q24.21-22, and 10p12.33-14 and losses at 4p15.31, 5q12.3-13.1, 5q33.1, 10q23.33, 12q13.13-3, 15q15.1, and 15q21.1; HER2+ breast show amplification at 17q11.1-12 and 17q21.31-23.2 (including HER2 gene). Conclusions: There is a strong correlation between the different gene expression signatures and under- lying genomic changes. These findings help to establish a link between genomic changes and gene expres- sion signatures, enabling a better understanding of the tumor biology that causes poor prognosis. Clin Cancer Res; 16(2); 651–63. ©2010 AACR. In recent years, high-throughput technologies such as the “molecular subtypes” (3–5), the “wound response signa- gene expression profiling using microarray analysis have ture” (6), the chromosomal instability signature (7), and improved the possibilities to assess the risk of developing the genomic grade index (GGI; ref. 8). These signatures are distant metastases in individual breast cancer patients. Gene independently derived prognostic factors and show a partial expression profiling studies have identified various prognos- agreement in the identification of patients at increased tic gene expression signatures in breast cancer: a 70-gene risk of developing distant metastases (9). prognosis signature (1), a 76-gene prognosis signature (2), Differences in gene expression between breast tumor samples can be considered to be the result of genetic Authors' Affiliations: 1Division of Experimental Therapy, 2Bioinformatics (10, 11) and/or epigenetic changes (12). Association be- and Statistics, Department of Molecular Biology, Divisions of 3Radiation tween copy number change and gene expression levels Oncology, and 4Diagnostic Oncology, The Netherlands Cancer Institute; has been shown, and ∼12% of gene expression variation and 5Department of Pathology, Academic Medical Center, Amsterdam, the Netherlands; and 6Faculty of Electrical Engineering Mathematics can be explained by differences in DNA copy number and Computer Science, Delft University of Technology, Delft, the (10). Regulators of molecular processes may be targeted Netherlands by these alterations, and the expression changes are mostly Note: Supplementary data for this article are available at Clinical Cancer the result of downstream targets of these regulators react- Research Online (http://clincancerres.aacrjournals.org/). ing to the changes. By combining gene expression and H.M. Horlings and C. Lai contributed equally to this work. copy number data, these interactions can be revealed Corresponding Author: Marc J. van de Vijver, Department of Pathology, Academic Medical Center, Meibergdreef 9, 1105 AZ, Amsterdam, the and therefore better pinpoint the involved processes. Netherlands. Phone: 31-020-566-4100; Fax: 31-020-566-9523; E-mail: Several studies have correlated DNA copy number [email protected]. changes with the mRNA expression variation of individual doi: 10.1158/1078-0432.CCR-09-0709 genes (13–16) and, more recently, gene expression signa- ©2010 American Association for Cancer Research. tures (17–22). Adler et al. (23) showed that an activated www.aacrjournals.org 651 Downloaded from clincancerres.aacrjournals.org on September 30, 2021. © 2010 American Association for Cancer Research. Published OnlineFirst January 12, 2010; DOI: 10.1158/1078-0432.CCR-09-0709 Horlings et al. (CGH) arrays and matching gene expression array data Translational Relevance to identify dysregulated genes. DNA was extracted from 106 pretreatment fine-needle aspirations of stage II to III This study reports the specific chromosomal and re- breast cancers that received preoperative chemotherapy. gional aberrations related to clinical and pathologic A high number of molecular targets (HER-2, epidermal characteristics and prognostic gene expression signa- growth factor receptor, PTEN, VEGFA, AURKA, CHEK, tures. Using gene expression data (mRNA) from the AKT, and FGFR1) showed a significant correlation be- same tumors, we identified genes in the altered regions tween DNA copy number alterations and mRNA levels. for which the expression level is significantly correlated The region between 8q24.14 and 8q24.22 was gained in with the copy number. We found that gains and losses 58% of the tumors and the genomic region at 8p11 and varied between prognostic gene expression signatures 8p12 showed a high level of amplification in 10% of and clinical and pathologic features. For example, the the samples. The most striking finding was that triple- previously identified poor prognosis, 70-gene signa- negative tumors showed gain at 6p21, and Andre et ture is associated with gain of 3q26-27, 8q22-24, and al. (22) identified at least three (VEGFA, PTEN,and 17q24-25; the 70-gene good prognosis profile is asso- EGFR) genes that showed a high frequency of DNA copy ciated with loss at 16q11-24. These findings help to es- number alterations that was correlated with gene expres- tablish a link between genomic changes and gene sion. Even the VEGFA gene was gained in 34% of triple- expression signatures that determine tumor behavior negative tumors. in breast cancer, enabling a better understanding of We have previously developed an algorithm, Supervised the tumor biology that causes poor prognosis. These Identification of Regions of Aberration in aCGH data sets correlations will also help in the development of (SIRAC; ref. 25), to perform supervised identification of improved prognostic tests that may be used in genomic regions enriched for probes correlated with sam- patient-tailored therapy for breast cancer. ple labeling (25). Here, we analyzed DNA copy number changes within labeled data sets using SIRAC and integrated these findings with gene expression (mRNA) profiles in a wound response signature in breast carcinomas is strongly series of 68 primary breast carcinomas. These tumors were associated with the amplification of MYC (8q24) and CSN5 labeled based on well-known clinical and pathologic fea- (8q13), and in vitro experiments have shown that these tures and gene expression profiles. These included the 70- genes can induce the activated wound signature. Other gene prognosis signature (1), the wound signature (6), GGI prognostic signatures, including the basal-like (4) and 70- (8), and the breast cancer molecular subtypes (3–5). The gene (1) signatures, were not induced by MYC and CSN5 associations of these subclasses with specific DNA copy (23). Several additional specific associations have also been number changes and gene expression were investigated. reported: basal-like tumors were found to be associated with the amplification of 6p21-25 (17) and 10p14 (24); Materials and Methods luminal-type tumors have been found to be associated with several recurrent DNA copy number changes. Tumor samples. We selected 68 breast carcinomas, from Integration of DNA copy number alterations and gene the fresh-frozen tissue bank of the Netherlands Cancer expression profiling may also result in improved classifica- Institute/Antoni van Leeuwenhoek Hospital, for DNA iso- tion and prediction of prognosis in breast cancer. For ex- lation and DNA copy number analysis. These 68 tumors ample, Chin et al. (18) who found that the accuracy of risk were part of a series of breast tumor specimens of 295 stratification according to the outcome of breast cancer consecutive women with breast cancer. For each of the disease can be improved by combining analyses of gene 295 samples, gene expression (26) and clinicopathologic expression and DNA copy number. They measured both data (27) were previously available. Several studies have DNA copy number and gene