One paper focuses on comparing 51 breast cancer cell lines to 145 breast cancer samples, using a combination of array CGH and mRNA profiling. The general notion is to identify which cell lines resemble which subsets of the actual breast cancer world. Cell lines long propagated in vitro are likely (almost assured) to have undergone evolution in the lab; this means they are not the perfect proxies for studying the disease. Array CGH is a technique for examining DNA copy number changes, which are rampant in many cancers. Its use has exploded over the last few years, with a number of interesting discoveries. It is also a useful way to fingerprint cell lines; at least one cell line was described recently as an imposter (wrong tissue type), but I can't find the paper because of the huge flood of papers a query for 'array CGH' brings up.
The second paper looks at a set of clinical samples from early breast cancer, and again uses both transcriptional profiling and aCGH. I need to really dig into this paper, but the abstract has some interesting tidbits (CNAs=copy number abberations) -- emphasis my own
The mini-review does highlight a key point: as impressive as this study is, no study can ever hope to be the final word. As new omics tools are developed, new studies will be desirable. Two obvious examples here: running intensive proteomics and looking in depth at alternative transcripts.
It shows that the recurrent CNAs differ between tumor subtypes defined by expression pattern and that stratification of patients according to outcome can be improved by measuring both expression and copy number, especially high-level amplification. Sixty-six genes deregulated by the high-level amplifications are potential therapeutic targets.