Cross-comparison of patient-derived xenografts and derivative organoids and cell lines for translational research in hepatocellular carcinoma

项目总结 肝细胞癌(HCC)是全球第二大癌症相关死亡原因，超过 仅2012年就有74.5万人死亡。大多数肝细胞癌患者存在不能切除的疾病 确诊和预期寿命不到20个月，其中只有15%的患者能存活一次以上 确诊后一年。这一令人沮丧的预后突显了这些患者有限的治疗选择。肝细胞癌 是一种臭名昭著的化疗耐药恶性肿瘤，靶向治疗的进展在 提高存活率导致了一些人所说的治疗方法开发中的“一场失败的战斗”。这 不足的问题，在很大程度上是由于当前临床前模型的局限性：(I)概括了 肿瘤内的异质性是肝细胞癌的特征和(Ii)预测患者对治疗的反应。 虽然患者来源的肿瘤模型已被证明更真实地概括了 人类肿瘤，这些模型的翻译相关性的验证是有限的 他们对肿瘤内和肿瘤间突变异质性的忠诚度以及他们的能力 为新的或现有的设计、测试和/或结果评估提供可靠的翻译信息 治疗。事实上，创建新的患者来源的肝癌模型需要对结果进行严格的验证 肿瘤以确认其对感兴趣癌症的保真度，以及可靠的认证标准以确定其生物学特性 作为患者反应的替代物的相关性和可靠性。 在初步研究中，我们有：1)展示了从以下来源产生PDX和PDX衍生细胞系的能力 中期肝细胞癌患者的经皮肿瘤活检和2)发展了方法学 支持对这些模型进行表征、验证和优化。拟议中的项目将建立在此基础上 先前的工作是评估患者衍生的肝细胞癌模型的保真度和预测潜力。 我们假设，从经皮活检衍生的患者来源的肝细胞癌模型概括了 以及其亲代活检的肿瘤内异质性，并且这些模型可以预测患者的反应 去接受治疗。为了验证这一假设，建议的项目将追求三个目标：(1)定义表示 靶向测序研究肝癌患者模型的瘤内和瘤内克隆异质性 和数字聚合酶链式反应；(2)确定患者来源的肝癌模型的预测潜力 对常见肝细胞癌治疗的反应；以及(3)研究肝细胞癌肿瘤起始细胞(TICs)在 提高患者衍生的肝细胞癌模型的产量和预测潜力。重要的是，实现 拟议的目标将改变患者衍生的肝细胞癌模型用于转译研究的用途。

PROJECT SUMMARY Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related death worldwide with more than 745,000 fatalities in 2012 alone. The majority of patients with HCC present with unresectable disease at diagnosis and a life expectancy of less than 20 months, with only 15% of these patients surviving more than one year after diagnosis. This dismal prognosis underscores the limited therapeutic options for these patients. HCC is a notoriously chemoresistant malignancy and advances in targeted therapeutics have been unsuccessful in improving survival resulting in what some have called “a losing battle” in the development of therapies. This deficiency issues, in large part, from limitations of current preclinical models in (i) recapitulating the inter- and intra-tumoral heterogeneity that characterizes HCC and (ii) predicting patient response to therapeutics. While patient-derived tumor models have been demonstrated to more faithfully recapitulate the heterogeneity of human tumors, there has been limited validation of the translational relevance of these models with respect to their fidelity to the intra- and inter-tumoral mutational heterogeneity that characterizes HCC as well as their ability to provide translationally reliable information for the design, testing and/or outcome evaluation of novel or existing therapies. Indeed, the creation of new patient-derived models of HCC requires rigorous validation of the resulting tumors to confirm their fidelity to the cancer of interest and robust credentialing criteria to ascertain their biological relevance and reliability as surrogates of patient response. In preliminary studies we have: 1) demonstrated the ability to generate PDXs and PDX-derived cell lines from percutaneous biopsies of tumors in patients with intermediate stage HCC and 2) developed methodologies to enable the characterization, validation and optimization of these models. The proposed project will build on this prior work to assess the fidelity and predictive potential of patient-derived models of HCC. We hypothesize that patient-derived models of HCC derived from percutaneous biopsies recapitulate the inter- and intra-tumoral heterogeneity of their parent biopsies and that these models are predictive of patient response to therapy. To test this hypothesis the proposed project will pursue three aims: (1) to define the representation of inter- and intra-tumoral clonal heterogeneity of patient-derived models of HCC through targeted sequencing and digital polymerase chain reaction; (2) to determine the predictive potential of patient-derived models of HCC for response to common HCC therapies; and (3) to investigate the role of HCC tumor initiating cells (TICs) in improving the yield and predictive potential of patient-derived models of HCC. Importantly, the achievement of the proposed aims will transform the utility of patient-derived models of HCC for translational research.