Molecular profiling of breast cancer: transcriptomic studies and beyond.
Utilisation of 'omics' technologies, in particular gene expression profiling, has increased dramatically in recent years. In basic research, high-throughput profiling applications are increasingly used and may now even be considered standard research tools. In the clinic, there is a need for better and more accurate diagnosis, prognosis and treatment response indicators. As such, clinicians have looked to omics technologies for potential biomarkers. These prediction profiling studies have in turn attracted the attention of basic researchers eager to uncover biological mechanisms underlying clinically useful signatures. Here we highlight some of the seminal work establishing the arrival of the omics, in particular transcriptomics, in breast cancer research and discuss a sample of the most current applications. We also discuss the challenges of data analysis and integrated data analysis with emphasis on utilising the current publicly available gene expression datasets. (Part of a Multi-author Review).
Culhane
A C
AC
Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02115, USA. aedin@jimmy.harvard.edu
Howlin
J
J
D000818:Animals; D000970:Antineoplastic Agents / Q000627:therapeutic use; D001943:Breast Neoplasms / Q000145:classification / Q000175:diagnosis / Q000188:drug therapy / Q000235:genetics*; D004354:Drug Screening Assays, Antitumor; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D023281:Genomics; D006801:Humans; D008954:Models, Biological; D020411:Oligonucleotide Array Sequence Analysis; D011379:Prognosis
D000970:Antineoplastic Agents