An integrated overview of cancer drug discovery and development from the bench to the clinic, showing with broad strokes and representative examples the drug development process as a network of linked components leading from the discovered target to the ultimate therapeutic product. Following a systems biology approach, the authors explain genomic databases and how to discover oncological targets from them, how then to advance from the gene and transcript to the level of protein biochemistry, how next to move from the chemical realm to that of the living cell and, ultimately, pursue animal modeling and clinical development. Emerging cancer therapeutics including Ritux an, Erbitux, Gleevec Herceptin, Avastin, ABX-EGF, Velcade, Kepivance, Iressa, Tarceva, and Zevalin are addressed. Highlights include cancer genomics, pharmacogenomics, transcriptomics, gene expression analysis, proteomic and enzymatic cancer profiling technologies, and cellular and animal approaches to cancer target validation.

Leading scientists in gene expression methodology and bioinformatics data analysis describe readily reproducible methods for measuring RNA levels in cells and tissues. The techniques presented include new methods for applying the Affymetrix GeneChip (R), SAR-SAGE, StaRT-PCR, SSH, the Invader Assay (R), and ADGEM. The authors also provide critical bioinformatics insight and resources for data analysis and management. By distilling the basic underlying principles of many methods to a few straightforward concepts, investigators can easily choose the method most appropriate to their application.

Leading scientists in gene expression methodology and bioinformatics data analysis describe readily reproducible methods for measuring RNA levels in cells and tissues. The techniques presented include new methods for applying the Affymetrix GeneChip (R), SAR-SAGE, StaRT-PCR, SSH, the Invader Assay (R), and ADGEM. The authors also provide critical bioinformatics insight and resources for data analysis and management. By distilling the basic underlying principles of many methods to a few straightforward concepts, investigators can easily choose the method most appropriate to their application.