Microarray analysis of thyroid neoplasm

甲状腺肿瘤的微阵列分析

• 批准号: 6740276
• 负责人: MARTHA Allen ZEIGER
• 金额: $ 16.35万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-05-01 至 2006-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6740276
• 关键词: RNA; adenoma; clinical research; complementary DNA; fine needle aspiration; gene expression; human tissue; microarray technology; molecular oncology; neoplasm /cancer diagnosis; neoplastic growth; polymerase chain reaction; thyroid neoplasm

DESCRIPTION (provided by applicant): Although fine needle aspiration (FNA) cytology is the best diagnostic tool in the differential diagnosis of a thyroid nodule, it often cannot differentiate a benign from a malignant lesion. Consequently, a majority of patients with thyroid nodules require surgery because of a suspicious, but not definitive, diagnosis of malignancy. Because the surgical management for benign and malignant thyroid neoplasms differ, patients with suspicious FNAs may be treated in a less than ideal fashion surgically. Although others and we have documented various genetic alterations in thyroid neoplasms, no specific alteration(s) can reliably distinguish benign from malignant lesions. We propose that there are specific gene expression patterns associated with the various thyroid tumor types and that these differing expression patterns can be capitalized upon to differentiate one tumor type from another. We therefore propose to genotype the most common benign and malignant thyroid lesions that present as suspicious thyroid FNA samples by cDNA microarray analysis. To accomplish these goals we propose the following: Specific Aim 1: To evaluate pooled thyroid tumor samples from follicular adenomas and corresponding normal thyroid by comprehensive cDNA microarray analysis using nylon filter arrays containing 37,000 genes. We have evaluated papillary thyroid cancers with this approach. We propose the same for follicular adenomas. Specific Aim 2: To evaluate individual thyroid tumor samples from follicular adenomas and papillary thyroid cancers and corresponding normal thyroid using cDNA glass slide arrays. In concert with the analysis described under specific aim 1, data will be analyzed to discover consistent gene expression patterns in these tumors by cluster analysis. Specific Aim 3: To independently validate the results of the array analysis by measuring expression levels of selected genes individually. This will be performed using quantitative real-time RT-PCR on RNA samples from a panel of thyroid tumors.

描述（申请人提供）：虽然细针抽吸（FNA）细胞学是鉴别诊断甲状腺结节的最佳诊断工具，但它通常无法区分良性病变和恶性病变。因此，大多数甲状腺结节患者由于可疑但不确定的恶性肿瘤诊断而需要手术。由于良性和恶性甲状腺肿瘤的手术治疗不同，可疑 FNA 患者的手术治疗方式可能不太理想。尽管其他人和我们已经记录了甲状腺肿瘤的各种遗传改变，但没有特定的改变可以可靠地区分良性病变和恶性病变。我们提出，存在与各种甲状腺肿瘤类型相关的特定基因表达模式，并且可以利用这些不同的表达模式来区分一种肿瘤类型与另一种肿瘤类型。因此，我们建议通过 cDNA 微阵列分析对最常见的良性和恶性甲状腺病变进行基因分型，这些病变表现为可疑的甲状腺 FNA 样本。为了实现这些目标，我们提出以下建议： 具体目标 1：使用包含 37,000 个基因的尼龙过滤阵列，通过全面的 cDNA 微阵列分析来评估来自滤泡性腺瘤和相应正常甲状腺的甲状腺肿瘤混合样本。我们已经用这种方法评估了甲状腺乳头状癌。我们对滤泡性腺瘤提出同样的建议。具体目标 2：使用 cDNA 载玻片阵列评估来自滤泡性腺瘤和乳头状甲状腺癌的个体甲状腺肿瘤样本以及相应的正常甲状腺。与具体目标 1 中描述的分析相一致，将分析数据以通过聚类分析发现这些肿瘤中一致的基因表达模式。 具体目标 3：通过单独测量所选基因的表达水平来独立验证阵列分析的结果。这将使用定量实时 RT-PCR 对一组甲状腺肿瘤的 RNA 样本进行。