Interpreting Microarray Data: Towards the Complete Bioinformatics Toolkit for Cancer

Functional genomics has been applied in the study of human malignancies since the inception of this field nearly a decade ago. Microarray analysis has been specifically used in an attempt to reclassify carcinomas at the molecular level, to aid in diagnosis/prognosis and to predict how various types of tumour respond to different therapeutic agents. Bioinformatics is now at the forefront of the post-genomics era and is providing a number of tools with which to mine the large datasets produced by genome-wide analysis. Of particular importance is the emergence of techniques that give the ability to reveal the transcription regulatory networks that are active in the cell in response to environmental stimuli or disease states. Deciphering the transcription networks that function in malignant cells not only will provide the knowledge to understand how carcinomas progress, but would also allow the construction of useful therapeutic tools for their effective treatment. In this review the recent advances that have been made in functional genomics that allow microarray data to be more fully interpreted and reveal the transcription networks that have gone awry in transformed cells are described. The application of microarray analysis, in the study of human malignancies, has undergone a paradigm shift in recent years so that datasets are now being used to elucidate the complex transcriptional programs that are active in human cancer. The use of integrative bioinformatics that allows this type of interpretation is a relatively new phenomenon and most studies to date have been carried out using microarray data from yeast. However, a number of studies have been recently published that have used meta- analysis of cancer datasets in an effort to identify transcriptional programs that are specifically active in cancer. In this review the recent advances that have been made in the development of bioinformatics resources that are used to analyse microarray data will be summarised, paying particular attention to algorithms that function to delineate cellular transcription networks. The studies that have been conducted, thus far, that have used these new tools to analyse the cellular networks that have gone awry during the development of cancer will be specifically discussed. Transcription Factor Databases