Gene Expression Profiling after Radiation-Induced DNA Damage Is Strongly Predictive of BRCA1 Mutation Carrier Status Zsofia Kote-Jarai, 1 Richard D. Williams, 2 Nicola Cattini, 3 Maria Copeland, 1 Ian Giddings, 3 Richard Wooster, 3 Robert H. tePoele, 5 Paul Workman, 5 Barry Gusterson, 6 John Peacock, 4 Gerald Gui, 7 Colin Campbell, 8 and Ros Eeles 1,7 1 Translational Cancer Genetics, 2 Paediatric Oncology, 3 Molecular Carcinogenesis, and 4 Academic Unit of Radiotherapy, The Institute of Cancer Research, Sutton, Surrey; 5 Cancer Research UK Centre for Cancer Therapeutics, Sutton, Surrey; 6 Division of Gene Regulation and Molecular Pathology, University of Glasgow, Glasgow; 7 Royal Marsden NHS Trust, London; and 8 Computational Intelligence Unit, Bristol University, Bristol, United Kingdom ABSTRACT Purpose: The impact of the presence of a germ-line BRCA1 mutation on gene expression in normal breast fibro- blasts after radiation-induced DNA damage has been inves- tigated. Experimental Design: High-density cDNA microarray technology was used to identify differential responses to DNA damage in fibroblasts from nine heterozygous BRCA1 mutation carriers compared with five control samples with- out personal or family history of any cancer. Fibroblast cultures were irradiated, and their expression profile was compared using intensity ratios of the cDNA microarrays representing 5603 IMAGE clones. Results: Class comparison and class prediction analysis has shown that BRCA1 mutation carriers can be distin- guished from controls with high probability (85%). Sig- nificance analysis of microarrays and the support vector machine classifier identified gene sets that discriminate the samples according to their mutation status. These include genes already known to interact with BRCA1 such as CDKN1B, ATR, and RAD51. Conclusions: The results of this initial study suggest that normal cells from heterozygous BRCA1 mutation car- riers display a different gene expression profile from con- trols in response to DNA damage. Adaptations of this pilot result to other cell types could result in the development of a functional assay for BRCA1 mutation status. INTRODUCTION It is estimated that 5–10% of breast cancer patients develop the disease because of the presence of a mutation in a breast cancer predisposition gene (1). A significant proportion of this population (just under a half) has a mutation in one of the known breast cancer predisposition genes, BRCA1 or BRCA2. Besides the obviously disease-causing deleterious mutations, very often small alterations caused by a single base change (missense mutations) are found in these genes. Their functional effects are usually unknown and so they are termed variants of uncertain significance. Some of these variants of uncertain significance could also have a role in breast cancer predisposition, but it is not currently possible to establish their disease-causing effect. The available diagnostic tests for mutation analysis of BRCA1/2 are time and labor intensive, expensive, and none of them allow the identification of all types of mutation. Our aim in this preliminary study was to investigate if gene expression profiling could be used to distinguish between heterozygous BRCA1 mutation carriers and control samples from reduction mammo- plasties with a very low chance of the presence of a BRCA1 mutation. If this were possible, then this would have the poten- tial to develop a method to identify the presence of a BRCA1 defect. The BRCA1 gene encodes a large nuclear protein (220 kDa) that has multiple possible functions, including DNA dam- age signaling, DNA repair, growth inhibition, and transcription regulation (2, 3). The involvement of BRCA1 in transcriptional regulation has been revealed in several studies showing direct interaction with other transcriptional activators and repressors such as STAT1, MYC, TP53, ZBRK1, and CDKN1B (4) It appears that BRCA1 is phosphorylated as a response to various DNA damaging agents by kinases such as CHEK2, ATM, and ATR, and this phosphorylation results in changes in its protein- protein interactions, which then can lead to regulatory changes in the expression of various target genes (5). Microarray studies have been shown to be of great value in understanding the molecular biology of many diseases, and they have been successfully used to classify various tumors based on their clinical phenotype or genetic background (reviewed in Ref. 6). This approach has enabled classification of tumors and division into prognostic groups on the basis of their global patterns of gene expression. One of the first of these studies classified myeloid and lymphoblastic leukemias using a class discovery procedure (7) demonstrating the feasibility of this technique. Similarly, it has been shown that breast epithelial cell lines have an expression profile that is distinct from breast tumors and that breast tumor samples can be divided into Received 7/22/03; revised 10/6/03; accepted 10/13/03. Grant support: B. G. was funded by Breakthrough Breast Cancer. Tissue collection was partly funded by a grant from the United States Department of Defense. This work also had support from Cancer Re- search United Kingdom and The Institute of Cancer Research. The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact. Supplementary data available at http://www.icr.ac.uk/array/array.html. Requests for reprints: Zsofia Kote-Jarai, Translational Cancer Genet- ics, The Institute of Cancer Research, Sutton, Surrey, United Kingdom. Phone: 0208-661-3897; Fax: 0208-770-1489; E-mail:Zsofia.Kote- Jarai@icr.ac.uk. 958 Vol. 10, 958 –963, February 1, 2004 Clinical Cancer Research Downloaded from http://aacrjournals.org/clincancerres/article-pdf/10/3/958/1955377/zdf00304000958.pdf by guest on 16 June 2022