NOVEL APPROACHES TO GENE PROFILING IN OVARIAN CANCER

卵巢癌基因分析的新方法

• 批准号: 7060081
• 负责人: TOWIA A. LIBERMANN
• 金额: $ 14.28万
• 依托单位: BETH ISRAEL DEACONESS MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-05-01 至 2008-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7060081
• 关键词: bioinformatics; cancer risk; clinical research; female; gene expression; gene expression profiling; human subject; immunocytochemistry; microarray technology; neoplasm /cancer chemotherapy; neoplasm /cancer diagnosis; neoplasm /cancer genetics; neoplasm /cancer relapse /recurrence; ovary neoplasms; pharmacogenetics; polymerase chain reaction; prognosis

DESCRIPTION (provided by applicant): Epithelial ovarian cancer (EOC) is the most lethal of gynecologic malignancies. Advanced disease typically involves the upper abdomen and affects 70% of patients, associated with 5 year survival in the range of 10- 25% after treatment with surgery followed by chemotherapy. Early stage disease confined to the pelvis is associated with 5 year survival of greater than 90%, although the presence of high risk features still requires treatment with post-operative chemotherapy. Traditional clinical and molecular markers as stage, postoperative debulking status, p53 mutation, and BAX expression are reasonable but imperfect measures of outcome. This observation suggests that no single marker can serve as a surrogate for the complex genetic changes that are responsible for tumor growth and response to chemotherapy. In this regard, microarray gene profiling is a powerful technique that is capable of simultaneously assessing the expression of thousands of genes, although its clinical utility for patients with EOC remains to be determined. Using this technique, we have developed novel bioinformatics approaches to identify gene profiles in a training set that are highly prognostic of clinical outcome in EOC. In this grant, we will validate these data in a test set comprised of a large number of tumor samples from a separate institution, and we will also determine whether it is possible to streamline tumor profiling using RT-PCR and immunohistochemistry assays (Specific Aim 1). Furthermore, we challenge the generally accepted concept that accurate prognostic information can always be obtained from analysis of a static, pre-treatment tumor sample. Thus, in Specific Aim 2 we will obtain a dynamic assessment of gene expression in response to chemotherapy in vivo, based upon the accessibility of tumor cells from ascites immediately before as well as for several days after chemotherapy has begun. Finally, in Specific Aim 3 we will apply the micro-array technique to a study of patients with early stage disease, in an attempt to determine whether it is possible to identify only those patients who will derive the greatest benefit from post-operative chemotherapy. We anticipate that the ability to accurately identify predictive and prognostic factors in EOC will permit a more tailored approach to post-operative management for patients with this disease.

描述（由申请人提供）：上皮性卵巢癌（EOC）是最致命的妇科恶性肿瘤。晚期疾病通常累及上腹部，影响 70% 的患者，手术后化疗后的 5 年生存率为 10-25%。局限于骨盆的早期疾病与超过 90% 的 5 年生存率相关，尽管高风险特征的存在仍然需要术后化疗。传统的临床和分子标志物，如分期、术后减灭状态、p53 突变和 BAX 表达，是合理但不完善的结果衡量标准。这一观察结果表明，没有任何单一标记可以替代导致肿瘤生长和化疗反应的复杂遗传变化。在这方面，微阵列基因分析是一种强大的技术，能够同时评估数千个基因的表达，尽管其对 EOC 患者的临床实用性仍有待确定。利用这项技术，我们开发了新的生物信息学方法来识别训练集中的基因谱，这些基因谱对 EOC 的临床结果具有高度的预后作用。在这笔资助中，我们将在由来自独立机构的大量肿瘤样本组成的测试集中验证这些数据，我们还将确定是否可以使用 RT-PCR 和免疫组织化学检测来简化肿瘤分析（具体目标 1） ）。此外，我们挑战了普遍接受的概念，即始终可以通过分析静态的治疗前肿瘤样本来获得准确的预后信息。因此，在具体目标 2 中，我们将根据化疗开始前以及化疗开始后几天腹水中肿瘤细胞的可及性，对体内化疗反应的基因表达进行动态评估。最后，在具体目标 3 中，我们将应用微阵列技术对早期疾病患者进行研究，试图确定是否可以仅识别那些将从术后化疗中获得最大益处的患者。我们预计，准确识别 EOC 的预测和预后因素的能力将为该疾病患者提供更有针对性的术后管理方法。