Molecular profiles of colorectal adenomas by array CGH

描述（由申请人提供）：我正在申请K 07预防肿瘤学培训补助金的资金，这将有助于我进入癌症预防和诊断生物标志物的实验室转化研究职业生涯。 作为一名学术病理学家，我在基于组织的分析和组织显微切割方面具有专业知识，但我正在寻求高通量分子诊断技术（例如基于阵列的基因组染色体杂交（阵列CGH））与信息学，生物统计学，流行病学和癌症预防临床试验设计相结合的培训。在这个建议中，我概述了这些研究学科所需的研究生课程，这将使我能够完成一个假设驱动的研究计划，以分析与结直肠腺瘤复发和高风险腺瘤相关的基因组改变模式。 我的主要导师是Dave Alberts博士，他是结肠直肠腺瘤复发化学预防的大型III期临床试验的首席研究员。 Martinez博士提供流行病学方面的指导，Trent和Bittner博士提供基因组筛选技术方面的专业知识，Nagle和Bhattacharyya博士提供表型相关验证方案方面的专业知识。 统计学研究生课程和强大的信息学顾问团队有助于我在数据分析和数据挖掘策略方面的培训。 假设：通过阵列CGH分析结直肠腺瘤将产生预测腺瘤复发和肿瘤进展高风险的分子谱。 具体目标：1。利用福尔马林固定石蜡包埋的临床试验材料，通过阵列CGH进行全基因组分析。 2.通过分析匹配的基线和复发腺瘤，通过阵列CGH生成预测腺瘤复发的复合分子谱。 3.分析表型晚期腺瘤，以生成具有肿瘤进展高风险的复合特征。 患者人群：两项大型III期临床试验评估了饮食（麦麸纤维）和化学预防（熊去氧胆酸）对腺瘤复发的影响，超过2800例患者在3年随访结肠镜检查时的复发率为40 - 50%。 组织固定：10%福尔马林缓冲液。 微阵列：Agilent 60-mer寡核苷酸微阵列和图像扫描仪。 样本量：50对配对，基线和复发;验证研究，组织微阵列，FISH和RT-PCR。 生物信息学/生物统计学：非监督数据分析，分类器算法，包括强大的功能。

DESCRIPTION (provided by applicant): I am applying for funding of a K07 Preventive Oncology Training Grant that will facilitate my entry into a laboratory-based translational research career in cancer prevention and diagnostic biomarkers. As an academic pathologist, I have expertise in tissue based assays and tissue microdissection, but am seeking training in high throughput molecular diagnostic techniques (e.g. array based genomic chromosomal hybridization {array CGH)) combined with informatics, biostatistics, epidemiology and cancer prevention clinical trials design. In this proposal, I outline needed graduate coursework in these research disciplines that will enable my completion of a hypothesis-driven research plan to analyze genomic alteration patterns associated with colorectal adenoma recurrence and high risk adenomas. My primary mentor is Dr. Dave Alberts, principal investigator on large Phase III clinical trials on chemoprevention of colorectal adenoma recurrence. Dr. Martinez offers mentorship in epidemiology, Drs. Trent and Bittner offer expertise in genome screening techniques, and Drs. Nagle and Bhattacharyya offers expertise in validation schemes for phenotypic correlates. Graduate coursework in statistics and a strong team of informatics consultants contribute to my training in data analysis and data mining strategies. Hypothesis: Analysis of colorectal adenomas by array CGH will generate molecular profiles predictive of adenoma recurrence and of high risk for neoplastic progression. Specific Aims: 1. To perform genome-wide analysis by array CGH using formalin fixed paraffin embedded clinical trials material. 2. To generate composite molecular profiles by array CGH predictive of adenoma recurrence by analysis of matched baseline and recurrent adenomas. 3. To analyze phenotypic advanced adenomas to generate composite profiles with high risk of neoplastic progression. Patient Population: Two large phase III clinical trials assessing diet (Wheat Bran Fiber) and chemoprevention (Ursodeoxycholic Acid) effects on adenoma recurrence with over 2800 patients accrued and recurrence rates of 40 to 50% at 3-year follow-up colonoscopy. Tissue fixation: 10% buffered formalin. Microarray: Agilent 60-mer oligonucleotide microarrays and image scanner. Sample size: 50 matched pairs, baseline and recurrent; validation studies, tissue microarrays, FISH and RT-PCR. Bioinformatics/Biostatistics: Nonsupervised data analysis, classifier algorithms, including strong features.