High Throughput Method to Assess SNP Functionality in Prostate Cancer

高通量方法评估前列腺癌中的 SNP 功能

• 批准号: 8336846
• 负责人: Mary Szatkowski Ozers
• 金额: $ 14.47万
• 依托单位: PROTEOVISTA, LLC
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-21 至 2014-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8336846
• 关键词: 8q24; Adverse effects; Affect; Affinity; Binding; Binding Proteins; Binding Sites; Biological Assay; Cancer Etiology; Cells; Clinic; Colorectal Cancer; Custom; DNA; DNA Binding; DNA Microarray Chip; DNA Sequence; Data; Devices; Diagnosis; Diagnostic Neoplasm Staging; Disease; Disease model; Drug Delivery Systems; Fluorescence; Gene Expression Regulation; Genes; Genetic; Genetic Variation; Genome; Genomics; Goals; Hand; Human Genome; Incidence; Incubated; Industry; Junk DNA; Laboratories; Malignant Neoplasms; Malignant neoplasm of ovary; Malignant neoplasm of prostate; Marketing; Measures; Medical; Medicine; Methods; Pathway interactions; Patients; Phase; Positioning Attribute; Prevalence; Protein Microchips; Proteins; Risk; Risk Assessment; S-nitro-N-acetylpenicillamine; Services; Single Nucleotide Polymorphism; Site; Sorting - Cell Movement; Source; Specificity; TCF Transcription Factor; Technology; Therapeutic; Translating; United States; Variant; cancer cell; cancer diagnosis; cancer type; chromatin immunoprecipitation; commercialization; cost; design; disorder risk; ds-DNA; improved; malignant breast neoplasm; men; patient population; preference; prototype; research study; therapeutic target; transcription factor; tumor molecular fingerprint

Project Summary High Throughput Method to Assess SNP Functionality in Prostate Cancer PIs: Christopher L. Warren and Mary S. Ozers A critical unmet need in implementing personalized medicine is the ability to sort through the millions of single nucleotide polymorphisms (SNPs) present in the human genome and to pinpoint which of these DNA variations are causative in disease. A key under-studied function of SNPs is their ability to generate or disrupt genomic binding sites for transcription factors involved in cancer. Toward this goal, we are inventing the SNP-SNAP (Specificity and Affinity for Proteins) microarray as a prototype high throughput device to evaluate SNP function. The SNP-SNAP arrays will be used to display a quarter-million prostate cancer- related SNPs as double-stranded DNA molecules and to assay transcription factors (i.e. drug targets) for their binding to these SNP DNA sequences. The resulting data will be correlated with prostate cancer incidence. The million-plus data points from the SNP-SNAP arrays will be analyzed using SNP-Sequence Specificity Landscapes, creating a prostate cancer "molecular signature" that relates transcription factor binding, SNP preferences, and chromosomal position of the nearest genes. Our findings will also relate prostate cancer-associated SNP function with cancer stage and aggressiveness. Understanding SNP function will have a major impact on personalized medicine, by providing individualized disease risk assessment, identifying new personalized therapeutic targets, and predicting efficacy and potential off- target side effects of common therapeutics. The goals of this Phase I project are to: 1. Design and synthesize a customized SNP-SNAP DNA microarray to tile across a quarter-million SNPs that are associated with prostate cancer. 2. Examine the DNA binding specificity and affinity of 5 prostate cancer-related transcription factors, as purified proteins and from cell lysates, on the SNP-SNAP array and annotate the human genome with the transcription factor binding differences due to SNPs. Verify results with chromatin immunoprecipitation in prostate cancer cells. 3. Obtain SNP data from patients with prostate cancer and determine if there is a statistically significant association of functional SNPs, which yielded differential binding of prostate cancer specific transcription factors on the SNP-SNAP array, with prostate cancer incidence. This technology can assay millions of SNPs and multiple transcription factors simultaneously, thus representing one of the first methods to evaluate SNP functionality in a high throughput manner. Our SNP- SNAP technology, by virtue of the array custom design and ability to examine millions of DNA permutations, is also broadly applicable to any cancer type and disease model.

项目摘要 评估前列腺癌中SNP功能的高通量方法 PIS：Christopher L. Warren和Mary S. Ozers 实施个性化医学的至关重要的需求是能够分类数百万 人类基因组中存在的单核苷酸多态性（SNP），并查明这些DNA中的哪个 变异在疾病中是病因。 SNP的关键功能不足的功能是它们生成或 破坏涉及癌症转录因子的基因组结合位点。达到这个目标，我们正在发明 SNP-SNAP（蛋白质的特异性和亲和力）微阵列作为原型高吞吐装置 评估SNP功能。 SNP-SNAP阵列将用于展示250万个前列腺癌 - 相关的SNP作为双链DNA分子和分析转录因子（即药物靶标）的相关SNP 它们与这些SNP DNA序列的结合。所得数据将与前列腺癌相关 发病率。 SNP序列将分析SNP-SNAP阵列中的百万多个数据点 特异性景观，形成与转录因子相关的前列腺癌“分子签名” 最近基因的结合，SNP偏好和染色体位置。我们的发现也将与 前列腺癌相关的SNP与癌症阶段和侵略性相关。了解SNP 通过提供个性化疾病风险，功能将对个性化医学产生重大影响 评估，确定新的个性化治疗靶标，并预测功效和潜在的效果 常见治疗剂的目标副作用。我项目的目标是： 1。设计和合成一个定制的SNP-SNAP DNA微阵列，遍及250万SNP 与前列腺癌相关的。 2。检查5个前列腺癌相关转录因子的DNA结合特异性和亲和力，作为 纯化的蛋白质和来自细胞裂解物，在SNP-SNAP阵列上，并以人类基因组注释 转录因子结合因SNP引起的差异。验证染色质免疫沉淀的结果 前列腺癌细胞。 3。从前列腺癌患者那里获取SNP数据，并确定是否存在统计学意义 功能性SNP的关联，产生了前列腺癌特异性转录的差异结合 SNP-SNAP阵列的因素，前列腺癌发病率。 该技术可以同时分析数百万个SNP和多个转录因子，因此 代表以高通量方式评估SNP功能的第一个方法之一。我们的SNP- SNAP技术，凭借阵列的自定义设计以及检查数百万个DNA排列的能力， 也广泛适用于任何癌症类型和疾病模型。