Digital Gene Expression for Cancer

癌症数字基因表达

• 批准号: 7325905
• 负责人: Steven Jeffrey Gordon
• 金额: $ 15.35万
• 依托单位: INTELLIGENT BIO-SYSTEMS, INC.
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-15 至 2009-09-14
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7325905
• 关键词: Automation; Bioinformatics; Biology; Chemistry; Clinical; Complex; Count; DNA Sequence; Data; Decision Making; Development; Disease; Eye; Gene Expression; Genes; Genome; Genomics; Genotype; Individual; Knowledge; Lead; Libraries; Measures; Medicine; Messenger RNA; Methods; Microarray Analysis; Molecular Profiling; Mutation; Organism; Pharmacogenomics; Phase; Phenotype; Preparation; Protocols documentation; RNA; Receptor Gene; Regulatory Pathway; Research; Reverse Transcription; Sampling; Solid Neoplasm; Staging; Standards of Weights and Measures; Symptoms; System; Technology; Therapeutic; Tissues; Transcript; Tumor Subtype; Universities; base; cancer gene expression; cost; design; digital; erbB-2 Receptor; instrument; leukemia/lymphoma; malignant breast neoplasm; neoplastic; next generation; prototype; tool; tumor

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.

描述（由申请人提供）：尽管肿瘤组织内基因组序列的精确知识可以是治疗的指标，例如乳腺癌的erbB-2受体基因（Her-2），但这种相关性很少，并且通常不能充分定义在治疗决策中重要的肿瘤亚型。这种无法识别可能对标准疗法无反应的肿瘤亚类的能力可能会限制更有效治疗策略的开发。基因表达的分析代表了通过分析调控途径对肿瘤中遗传改变的间接测量。微阵列技术已被证明是强大的工具，并提供了更好的临床决策的基础上肿瘤表型的承诺。对白血病、淋巴瘤和实体瘤的非常有希望的初步研究表明，基因表达数据可以突出组织学相同疾病之间的差异。然而，基于微阵列的技术在其分析低表达水平的能力方面是有限的。我们建议使用独特的合成测序技术作为数字基因表达系统，以获得表达的mRNA分子的精确计数。这有望提供比微阵列系统高一个数量级的灵敏度。在这个I期项目中，提出了一种利用高度平行测序技术的样品制备新方法。最终，为复杂生物体的基因组产生非常便宜的详细DNA序列信息的能力将加速整个生物学的发现，并为药物基因组学提供基础，药物基因组学是一种新的治疗模式，其中药物是基于个体基因型而不仅仅是观察到的症状。