Low-Cost Digital Gene Expression System

描述(申请人提供)：癌症是美国第二常见的死亡原因，是由生物体基因组的随机突变引起的。尽管对肿瘤组织内基因组序列的精确了解可以作为治疗的指标，例如乳腺癌的erbB-2受体基因(HER-2)，但这种相关性很少，而且往往不能充分确定对治疗决策重要的肿瘤亚型。这种无法识别可能对标准治疗无效的肿瘤亚类的能力，可能会限制更有效的治疗策略的发展。基因表达分析是通过对调控途径的分析来间接衡量肿瘤中的遗传变化。微阵列技术已被证明是强大的工具，并提供了更好的基于肿瘤表型的临床决策的前景。对白血病、淋巴瘤和实体肿瘤的非常有希望的初步研究表明，基因表达数据可以突出其他组织学上相同的疾病之间的差异。然而，基于微阵列的技术在分析低表达水平方面受到限制。我们使用一种独特的合成测序技术作为数字基因表达系统来获得表达的mRNA分子的精确计数。这可以提供比微阵列系统高一个数量级的灵敏度。在这个第二阶段项目中，我们将建立在第一阶段开发的样品制备协议的基础上，并将这些协议与极低成本的专有下一代测序系统一起使用，该系统可以以大约100美元的价格进行基因表达研究所需的测序，或者大约是最具竞争力的测序方法的1/20。

DESCRIPTION (provided by applicant): 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.