卵巢癌是病死率最高的妇科恶性肿瘤。目前研究认为，肿瘤组织内存在各种亚克隆即肿瘤内异质性，其临床生理病理表型和遗传特性均存在一定的差异，并在肿瘤转移、复发和耐药中扮演重要的角色。肿瘤内异质性分子标记物的识别和作用机理是目前需要解决的关键问题之一。基因拷贝数变异（CNV）在肿瘤发生发展中广泛存在，是影响DNA剂量的结构变异，对基因表达和功能有重要影响。本项目选取遗传背景相同但具有不同侵袭/迁移能力的卵巢癌异质性细胞亚群为研究模型，对其在细胞周期、增殖、凋亡、抗药性及裸鼠在体成瘤能力等方面进行比较；在全基因组范围内分析筛选异质性亚群基因的拷贝数变异。采用病例-对照研究策略，对筛选出的分子标记物进行癌内多部位多阶段样本的临床验证。开展基于CNV的基因相互作用网络分析和数据挖掘，探讨卵巢癌遗传异质性及表型转换的相关分子机制，为卵巢癌的分层和个体化治疗，提高卵巢癌的诊治水平提供新的理论依据。

Ovarian cancer is the leading cause of death from gynecological malignancy. It is also well recognized over the past decades that tumors are morphologically heterogeneous consisting of multiple sub-clones with different phenotypes and genetic characteristics, which may contribute to tumor metastasis, chemo-resistance and disease relapse. However, the understanding of the functional significance of intratumoral heterogeneity is lacking. Genomic copy number variations (CNV) are deletions or duplications of DNA. CNVs have been increasingly well studied in numerous malignancies. In this study, we will construct models to isolate and functionally profile tumorigenic clones with different invasive and migratory capacity from ovarian carcinoma cell lines with the same genetic background. The ability of cell proliferation and apoptosis, drug-resistance and the tumor formation in vivo will be examined and compared between the individual heterogeneous clones. A global profile of genomic alterations of CNVs will be selected and confirmed in cohorts of case control studies. A network analysis will be performed to generate an interaction network containing relevant biological information for the molecular targets. Understanding the links between genetic and functional behavior of heterogeneous clones will lead to the discovery of novel molecular mechanisms and will be essential for new insights in ovarian cancer and personalized cancer treatment.