The acknowledged heterogeneity of breast cancer both at the clinical and at the molecular level has been a challenge in classification of breast cancer. This study aimed at identifying distinct molecular subgroups of the disease.
By using data from high resolution microarrays measuring copy number variation throughout the genome, two objective measurements were defined. A combination of these were used to group almost 600 breast carcinomas into four main groups, each further subdivided into two groups. Comparison with other molecular alterations at the DNA, RNA and protein level from the tumors showed that the groups had different characteristics; this was also reflected by distinct clinical profiles including differences in survival. As separate works, the relationship between molecular subgroups and methylation alterations, allele-specific genomic variation and bilateral disease were examined.
This work illustrates that the heterogeneity of breast carcinomas can be explained by distinct molecular alterations. It also shows the importance of platform independent algorithms; by merging data from different cohorts to obtain a large sample set, clinical relevant subgroups can be identified
