Hasan Noor, Ohman Anders W, Dinulescu Daniela M
Department of Pathology, Division of Women's and Perinatal Pathology, Eugene Braunwald Research Center, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA.
Transl Cancer Res. 2015 Feb;4(1):14-28. doi: 10.3978/j.issn.2218-676X.2015.01.02.
The complexity and heterogeneity of ovarian cancer cases are difficult to reproduce in studies, which cannot adequately elucidate the molecular events involved in tumor initiation and disease metastasis. It has now become clear that, although the multiple histological subtypes of ovarian cancer are being treated with similar surgical and therapeutic approaches, they are in fact characterized by distinct phenotypes, cell of origin, and underlying key genetic and genomic alterations. Consequently, the development of more personalized treatment methodologies, which are aimed at improving patient care and prognosis, will greatly benefit from a better understanding of the key differences between various subtypes. To accomplish this, animal models of all histotypes need to be generated in order to provide accurate platforms for research and the testing of targeted treatments and immune therapies. Both genetically engineered mouse models (GEMMs) and xenograft models have the ability to further our understanding of key mechanisms facilitating tumorigenesis, and at the same time offer insight into enhanced imaging and treatment modalities. While genetic models may be better suited to examine oncogenic functions and interactions during tumorigenesis, patient-derived xenografts (PDXs) are likely a superior model to assess drug efficacy, especially in concurrent clinical trials, due to their similarity to the tumors from which they are derived. Genetic and avatar models possess great clinical utility and have both benefits and limitations. Additionally, the laying hen model, which spontaneously develops ovarian tumors, has inherent advantages for the study of epithelial ovarian cancer (EOC) and recent work champions this model especially when assessing chemoprevention strategies. While high-grade ovarian serous tumors are the most prevalent form of EOC, rarer ovarian cancer variants, such as small cell ovarian carcinoma of the hypercalcemic type and transitional cell carcinoma, or non-epithelial tumors, including germ cell tumors, will also benefit from the generation of improved models to advance our understanding of tumorigenic mechanisms and the development of selective therapeutic options.
卵巢癌病例的复杂性和异质性在研究中难以重现,这些研究无法充分阐明肿瘤发生和疾病转移所涉及的分子事件。现在已经清楚的是,尽管卵巢癌的多种组织学亚型采用相似的手术和治疗方法进行治疗,但它们实际上具有不同的表型、起源细胞以及潜在的关键基因和基因组改变。因此,旨在改善患者护理和预后的更个性化治疗方法的开发,将极大地受益于对各种亚型之间关键差异的更好理解。为实现这一目标,需要建立所有组织学类型的动物模型,以便为研究以及靶向治疗和免疫疗法的测试提供准确的平台。基因工程小鼠模型(GEMMs)和异种移植模型都有能力加深我们对促进肿瘤发生的关键机制的理解,同时提供对增强成像和治疗方式的见解。虽然遗传模型可能更适合研究肿瘤发生过程中的致癌功能和相互作用,但患者来源的异种移植(PDXs)可能是评估药物疗效的更优模型,特别是在同步临床试验中,因为它们与所源自的肿瘤相似。遗传模型和替身模型具有很大的临床实用性,且都有优点和局限性。此外,自发发生卵巢肿瘤的蛋鸡模型在研究上皮性卵巢癌(EOC)方面具有固有优势,最近的研究尤其推崇该模型,特别是在评估化学预防策略时。虽然高级别卵巢浆液性肿瘤是EOC最常见的形式,但较罕见的卵巢癌变体,如高钙血症型小细胞卵巢癌和移行细胞癌,或非上皮性肿瘤,包括生殖细胞肿瘤,也将受益于改进模型的建立,以推进我们对致瘤机制的理解和选择性治疗方案的开发。