SBIR-STTR Award

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

As the second most common cause of death in the US, cancer is caused by random mutations in an organism's genome. 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 histologically identical diseases. However, microarray-based technologies are limited in their ability to analyze low expression levels. We use of a unique sequencing by synthesis technology as a digital gene expression system to obtain precise counts of expressed mRNA molecules. This can provide an order of magnitude more sensitivity than microarray systems. In this Phase II project, we will build upon the sample preparation protocols developed in Phase I and use these with an extremely low-cost, proprietary, next-generation sequencing system that can perform the sequencing required for a gene expression study for about $100 or about 1/20th the price of the most competitive sequencing method.

Public Health Relevance:
Ultimately, the ability to produce very inexpensive gene expression and detailed DNA sequence information related to cancer will lead for a much wider use of expression and sequence analyses for research and treatment of this devastating disease. In addition, the ability to analyze complex organisms' genomes at a very low cost 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.