Abstract
Given the increasing clinical importance of microarray expression classification of breast tumours and the different biology it may reveal [1], identifying an associated SNP profile may be of considerable value for pharmacogenetics, early diagnostics and cancer prevention. Studying the promoter composition of the genes that strongly predict the patient subgroups, we observed clear separation of the gene clusters based solely on their promoter composition, making feasible the hypothesis that SNPs in the regulatory regions of genes that create or abrogate transcription binding sites have the potential to influence the expression profiles. Morley and colleagues [2] reported linkage analysis of expression levels of 3554 genes and 2500 SNPs in 14 CEPH families (retrieved online [3]), and found significant evidence for the existence of regulation hot spots, suggesting both cis and trans regulatory effects. We report similar observations from a study with a different design, performing actual genotyping of 49 unrelated breast cancer patients, whose tumours have previously been analysed by genome-wide expression microarrays leading to a robust tumour classification with strong prognostic impact [4]. These patients were a part of a pharmacogenetic study of 193 patients who had received radiation therapy or chemotherapy. A high-throughput solid-phase, array-based method using primer extension chemistry has been used to perform the genotyping (GenomeLab™ SNPstream genotyping system; Beckman Coulter, Fullerton, CA, USA). A total of 583 SNPs in 203 selected genes (1–19 SNPs/gene) were genotyped and tumour genome-wide expression was studied in 49 patients. Association in both cis and trans was detected for SNPs in 42 genes. SNP–expression associations with the top 0.25% best P values (9.81 × 10 -6 <P < 0.001) revealed regulatory SNPs in 115 genes in trans. The subsets of transcripts that were observed to have significantly many associations in common with a set of SNPs were further analysed using the gene ontology (GO) annotations. The GO terms of the unselected mRNA transcripts found associated to the SNPs in the selected candidate genes were often similar, suggesting that the observed associations are within the same functional pathway. Taken together these data suggest that the observed SNP–expression associations do exist and are observable even in a small set of unrelated individuals. A given expression profile of the tumour may be potentially associated and predicted by the genotype of the patient.
Highlights
Endocrine therapy for breast cancer is a major modality for the treatment of breast cancer, producing response rates between 30% and 40% of unselected patients with the minimum of toxicity
We have shown that overexpression of TGF-β1 in mammary epithelial cells suppresses the development of carcinomas and that expression of a dominant negative type II TGF-β receptor (DNIIR) in mammary epithelial cells under control of the MMTV promoter/enhancer increases the incidence of erbB2 in carcinomas accompanied by Tgfbr2fspKO fibroblasts
The present article reviews results from neoadjuvant studies in which endocrine therapy was given to patients whose primary breast cancer was still within the breast so that changes in tumour volume could be used to assess clinical response and so that sequential biopsies could be taken for molecular analyses designed to identify predictive markers
Summary
Endocrine therapy for breast cancer is a major modality for the treatment of breast cancer, producing response rates between 30% and 40% of unselected patients with the minimum of toxicity. Several human genetic diseases are known to be or suspected to be due to defects in DNA repair or cell cycle control Some of these patients are radiation sensitive and/or predisposed for cancer as a cause of mutations in genes involved in these cellular pathways. Microarray-based comparative genomic hybridization (arrayCGH) allows the construction of high-resolution genome-wide maps of copy number alterations, and statistical software packages are available for exploring and analysing array-CGH data (see, for example, [2,3]), facilitating the delineation of the boundaries of CNAs in individual tumors and thereby localizing and identifying potential oncogenes and tumor suppressor genes. The aim of this study was to evaluate the prognostic value of gene expression-based classification as well as established prognostic markers, including mutation status of the TP53 gene, in a group of breast cancer patients with long-term (>10 years) fol The aim of this study was to compare MR spectroscopic findings from breast cancer tissue with histological grading of tumor and patient lymph node status
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