IntroductionBreast cancer is a profoundly heterogeneous disease with respect to biologic and clinical behavior. Gene-expression profiling has been used to dissect this complexity and to stratify tumors into intrinsic gene-expression subtypes, associated with distinct biology, patient outcome, and genomic alterations. Additionally, breast tumors occurring in individuals with germline BRCA1 or BRCA2 mutations typically fall into distinct subtypes.MethodsWe applied global DNA copy number and gene-expression profiling in 359 breast tumors. All tumors were classified according to intrinsic gene-expression subtypes and included cases from genetically predisposed women. The Genomic Identification of Significant Targets in Cancer (GISTIC) algorithm was used to identify significant DNA copy-number aberrations and genomic subgroups of breast cancer.ResultsWe identified 31 genomic regions that were highly amplified in > 1% of the 359 breast tumors. Several amplicons were found to co-occur, the 8p12 and 11q13.3 regions being the most frequent combination besides amplicons on the same chromosomal arm. Unsupervised hierarchical clustering with 133 significant GISTIC regions revealed six genomic subtypes, termed 17q12, basal-complex, luminal-simple, luminal-complex, amplifier, and mixed subtypes. Four of them had striking similarity to intrinsic gene-expression subtypes and showed associations to conventional tumor biomarkers and clinical outcome. However, luminal A-classified tumors were distributed in two main genomic subtypes, luminal-simple and luminal-complex, the former group having a better prognosis, whereas the latter group included also luminal B and the majority of BRCA2-mutated tumors. The basal-complex subtype displayed extensive genomic homogeneity and harbored the majority of BRCA1-mutated tumors. The 17q12 subtype comprised mostly HER2-amplified and HER2-enriched subtype tumors and had the worst prognosis. The amplifier and mixed subtypes contained tumors from all gene-expression subtypes, the former being enriched for 8p12-amplified cases, whereas the mixed subtype included many tumors with predominantly DNA copy-number losses and poor prognosis.ConclusionsGlobal DNA copy-number analysis integrated with gene-expression data can be used to dissect the complexity of breast cancer. This revealed six genomic subtypes with different clinical behavior and a striking concordance to the intrinsic subtypes. These genomic subtypes may prove useful for understanding the mechanisms of tumor development and for prognostic and treatment prediction purposes.

Background: Assessing RNA quality is essential for gene expression analysis, as the inclusion of degraded samples may influence the interpretation of expression levels in relation to biological and/or clinical parameters. RNA quality can be analyzed by agarose gel electrophoresis, UV spectrophotometer, or microcapillary electrophoresis traces, and can furthermore be evaluated using different methods. No generally accepted recommendations exist for which technique or evaluation method is the best choice. The aim of the present study was to use microcapillary electrophoresis traces from the Bioanalyzer to compare three methods for evaluating RNA quality in 24 fresh frozen invasive breast cancer tissues: 1) Manual method = subjective evaluation of the electropherogram, 2) Ratio Method = the ratio between the 28S and 18S peaks, and 3) RNA integrity number (RIN) method = objective evaluation of the electropherogram. The results were also related to gene expression profiling analyses using 27K oligonucleotide microarrays, unsupervised hierarchical clustering analysis and ontological mapping.

Male breast cancer (MBC) is extremely rare and poorly characterized on the molecular level. Using high-resolution genomic data, we aimed to characterize MBC by genomic imbalances and to compare it with female breast cancer (FBC), and further to investigate whether the genomic profiles hold any prognostic information. Fifty-six fresh frozen MBC tumors were analyzed using high-resolution tiling BAC arrays. Significant regions in common between cases were assessed using Genomic Identification of Significant Targets in Cancer (GISTIC) analysis. A publicly available genomic data set of 359 FBC tumors was used for reference purposes. The data revealed a broad pattern of aberrations, confirming that MBC is a heterogeneous tumor type. Genomic gains were more common in MBC than in FBC and often involved whole chromosome arms, while losses of genomic material were less frequent. The most common aberrations were similar between the genders, but high-level amplifications were more common in FBC. We identified two genomic subgroups among MBCs; male-complex and male-simple. The male-complex subgroup displayed striking similarities with the previously reported luminal-complex FBC subgroup, while the male-simple subgroup seems to represent a new subgroup of breast cancer occurring only in men. There are many similarities between FBC and MBC with respect to genomic imbalances, but there are also distinct differences as revealed by high-resolution genomic profiling. MBC can be divided into two comprehensive genomic subgroups, which may be of prognostic value. The male-simple subgroup appears notably different from any genomic subgroup so far defined in FBC.

Background: The two-gene expression ratio HOXB13:IL17BR has been proposed to predict