MOLECULAR CLASSIFICATION OF OVARIAN CANCERS

上皮性卵巢癌是所有妇科癌症中导致死亡的主要原因。与这种恶性肿瘤相关的低生存率是由于在诊断时经常处于晚期，并且无法使用目前的手术和化疗标准连续治疗大多数晚期疾病病例。虽然有许多临床、手术结果和组织病理学变量与卵巢癌的预后相关，但在典型病例中，即绝经后患有中度至低分化浆液性肿瘤的晚期手术期妇女中，无复发间隔的长度和生存期存在很大差异。这种临床结果的异质性可能反映了个体癌症潜在分子遗传特征的差异，但卵巢癌的分子基础在很大程度上仍不清楚。因此，该项目的长期目标是解决这样一个假设，即卵巢癌的全面分子遗传学分类将提高我们预测临床结果的能力，特别是关于化疗后无复发间隔的持续时间和生存率。此外，阐明这些临床结果参数的分子决定因素将为卵巢肿瘤发生的生物学基础提供实质性的见解，并为卵巢癌治疗提供潜在的新靶点或策略。我们建议，这一目标可以通过系统地应用新的、全面的分子筛选方法来实现，特别是使用cDNA微阵列进行基因表达分析和比较基因组杂交进行遗传分析，以及与广泛的外科、组织病理学和临床数据相关的大量卵巢癌组织资源。该项目的具体目标是：1)利用cDNA微阵列技术获得大量卵巢癌的RNA表达谱，以确定表达特征组装的亚群；2)通过对相同样本进行比较基因组杂交，获得有关卵巢癌染色体失衡的全面信息；3)定义卵巢癌不同的分子和遗传亚群，通过将这些分子和遗传观察与临床和病理结果相关联，预测化疗后复发时间和生存；4)使用靶向分析和基于组织的方法的发展，确认和完善来自特定目标1和2的观察结果。这些目标将由具有分子生物学、遗传学、cDNA和组织阵列技术、生物信息学、妇科肿瘤学和病理学专业知识的国家合作肿瘤签名组完成。

Epithelial ovarian carcinoma is the leading cause of mortality among all gynecologic cancers. Poor survival rates associated with this malignancy are attributable to a frequently advanced stage at diagnosis and the inability to successively treat most cases of advanced stage disease using current standards of surgery and chemotherapy. While there are a number of clinical, surgical outcome, and histopathological variables that correlate with prognosis for ovarian cancer, there exists wide variation in the length of recurrence-free interval and survival among typical cases, i.e., post-menopausal women with moderately to poorly differentiated serous tumors of advanced surgical stage. This heterogeneity in clinical outcome presumably reflects differences in the underlying molecular genetic characteristics of individual cancers, but the molecular basis of ovarian cancer remains largely obscure. Thus, the long-term goal of this project is to address the hypothesis that a comprehensive molecular genetic classification of ovarian cancer will improve our ability to predict clinical outcome, specifically with regard to duration of recurrence-free interval following chemotherapy, and survival. Furthermore, elucidation of the molecular determinants of these clinical outcome parameters should provide substantial insights into the biological basis of ovarian tumorigenesis, as well as suggest potential new targets or strategies for ovarian cancer therapy. We propose that this goal may be accomplished through the systematic application of new, comprehensive molecular screening methodologies, specifically, use of cDNA microarrays for gene expression analysis and comparative genomic hybridization for genetic analysis, together with a large ovarian cancer tissue resource linked to extensive surgical, histopathological, and clinical data. The specific aims of this project are to: 1) obtain RNA expression profiles of a large number of ovarian cancers using cDNA microarrays to identify subgroups assembled by expression characteristics; 2) obtain comprehensive information concerning chromosomal imbalances in ovarian cancers by performing comparative genomic hybridizations on the same samples; 3) define distinct molecular and genetic subsets of ovarian cancer that will predict time to recurrence following chemotherapy, and survival, by correlating these molecular and genetic observations with clinical and pathological outcomes; and 4) confirm and refine observations from specific aims one and two using targeted assays and the development of tissue-based approaches. These aims will be accomplished by a National Cooperative Tumor Signature Group with expertise in molecular biology, genetics, cDNA and tissue array technology, bioinformatics, gynecologic oncology and pathology.