Genomic profiling of breast cancer by microarray-based technology and bioinformatics

Cancer is a genetic disease that arises when a cell acquires unlimited growth potential through a series of mutational events, which target genes essential for normal cell control and maintenance. Breast cancer is one of the most frequent malignancies in women worldwide, and it is characterized by heterogeneous tumor biology, histological subtypes, variable prognosis and variable responsiveness to treatment. Breast tumors frequently harbor a vast amount of genetic alterations including point mutations, structural rearrangements, and gain or loss of genetic material. These genetic alterations are believed to be hallmarks of gene deregulation and genome instability. In breast cancer, patterns of DNA copy number alterations have been shown to be specific for subtypes of breast cancer. Furthermore, recurrent alterations can point towards genes important in breast cancer carcinogenesis and may disclose potentially novel therapeutic targets, as exemplified by the HER2 oncogene. In the current thesis, microarray platforms and data analysis algorithms have been developed for investigation of DNA copy number alterations in breast cancer. Microarray platforms based on comparative genomic hybridization (aCGH) were developed for both genome-wide and focused delineation of complex genomic aberrations in breast cancer cells. Findings from data analysis of breast cancer cells motivated further investigation of a crucial step in low-level aCGH data analysis, normalization, resulting in a normalization strategy specifically for aCGH data. These methods were combined to characterize genomic aberrations in breast tumors harboring amplification of the HER2 oncogene, pinpointing significant aberrations including both known and potentially novel therapeutic targets. Moreover, using a bottom-up discovery strategy, analysis of global gene expression profiles from 58 HER2-amplified tumors revealed three subgroups of HER2+ tumors with different clinical characteristics and outcomes. A HER2-derived prognostic predictor was constructed based on analysis of genes differentially expressed among the three subgroups. Validation of the predictor in independent breast cancer data sets proved the prognostic association in HER2-amplified breast cancer, as well as other clinically challenging breast cancer subgroups. Together, the results shed further light on the genomically complex and heterogeneous nature of HER2-amplified breast cancer that may have therapeutic implications