Digital Gene Expression for Cancer

DESCRIPTION (provided by applicant): Although precise knowledge of the genomic sequence within neoplastic tissues can be an indicator for treatment, for example the erbB-2 receptor gene (Her-2) for breast cancer, such correlations are few and often do not adequately define tumor subtypes important in therapeutic decisions. Such inability to identify a subclass of tumors which may not respond to standard therapies can restrict the development of more efficacious treatment strategies. The analysis of gene expression represents an indirect measure of the genetic alterations in tumors through the analysis of regulatory pathways. Microarray technologies have proven to be powerful tools and offer the promise of better clinical decision-making based on tumor phenotypes. Highly promising preliminary studies of leukemia, lymphomas, and solid neoplasms demonstrate that gene expression data can highlight differences between otherwise histological identical diseases. However, microarray-based technologies are limited in their ability to analyze low expression levels. We propose the use of a unique sequencing by synthesis technology as a digital gene expression system to obtain precise counts of expressed mRNA molecules. This has the promise of providing an order of magnitude more sensitivity than microarray systems. In this Phase I project, a new method for sample preparation which takes advantage of highly parallel sequencing technology is proposed. Ultimately, the ability to produce very inexpensive detailed DNA sequence information for complex organisms' genomes will both lead to accelerated discoveries throughout biology and provide the basis for Pharmacogenomics, a new paradigm in therapeutics wherein medicines are prescribed based on individual genotypes rather than just observed symptoms.