Nanoscale proteomic profiles of hypoxia pathways to develop biomarkers of renal c

描述(申请人提供)：肾细胞癌(肾细胞癌，肾癌)是最常见的诊断癌症之一，与显著的死亡率有关。在美国，2011年估计将有60,920名患者被诊断，13,120名患者将死亡 死于肾癌。来自国家癌症研究所监测、流行病学和最终结果项目的数据表明，在过去的30年里，肾癌发病率稳步上升。大多数透明细胞肾癌患者存在von Hippel-Lindau(VHL)基因突变，导致缺氧诱导因子(HIF)转录因子复合体的表达不受调控。基于对低氧在肾癌发生中的作用的认识，大多数转移性肾癌患者接受靶向HIF轴的药物治疗，形式为血管内皮生长因子或mTOR抑制剂。小分子多酪氨酸激酶抑制剂(TKI)如舒尼替尼、帕佐帕尼、索拉非尼、阿西替尼等，以及抗血管内皮生长因子抗体(如贝伐单抗)在肾癌中均显示出临床活性。然而，令人惊讶的是，尽管这些药物可以广泛用于治疗肾癌，但仍然存在许多挑战：肾癌中血管内皮生长因子的表达模式和下游通路的激活还没有得到很好的表征。TKIs是非选择性的，通常会产生显著的毒性非靶点效应，导致不能治疗的20%的人出现无效的毒性。因此，迫切需要确定分子标记，以识别每个肿瘤中相关的致癌途径，以帮助选择全身治疗方法，并大幅减少无效毒性的量。然而，在肾癌中识别和开发生物标记物一直是极具挑战性的，一个主要的威慑因素是无法测量患者细胞在治疗前、治疗中和治疗后的特定生物蛋白质组变化。使用现有的方法，几乎不可能从临床标本中获得实时的蛋白质组信息。我们发展了纳米级免疫分析(NIA)，作为一种高度灵敏、定量和独特的方法，可以同时测量蛋白质及其不同的异构体和多个磷酸化状态。此外，纳米级蛋白质组学分析有可能极大地减少原发或其他转移部位活检诊断所需的组织数量。能够在单个时间点对同一患者的多个肿瘤部位进行蛋白质组分析，并随着时间的推移对多个样本进行分析，将加快翻译研究，并最终改善对肾癌患者的护理。我们相信，分子标记有望为肾癌患者护理的每一个步骤提供信息，包括诊断、手术和系统治疗的选择以及监测靶向治疗的反应。我们的目标是使用放射免疫分析来识别肾癌患者常见的失调缺氧途径的不同蛋白质组特征，从而通过靶向患者的肿瘤特异性途径(S)来帮助选择个性化和有效的系统治疗方法。

DESCRIPTION (provided by applicant): Renal cell carcinoma (RCC, kidney cancer) is one of the most commonly diagnosed cancers and is associated with significant mortality. In the United States in 2011, it is estimated that 60,920 patients will be diagnosed and 13,120 patients will die from kidney cancer. Data from the Surveillance, Epidemiology, and End Results program of the National Cancer Institute illustrates the steady rise of RCC incidence over the past 30 years. The majority of clear cell RCC patients have mutations in the von Hippel-Lindau (VHL) gene that result in unregulated expression of the hypoxia-inducible factor (HIF) transcription factor complex. Based on this recognition of the role of hypoxia in RCC carcinogenesis, most patients with metastatic RCC are treated with agents that target the HIF axis, either in the form of a VEGF or mTOR inhibitor. The VEGF inhibitors including small molecule multi-tyrosine kinase inhibitors (TKIs) such as sunitinib, pazopanib, sorafenib, and axitinib, and antibodies to VEGF such as bevacizumab have all shown clinical activity in RCC. Surprisingly however, despite the wide availability of these agents to treat RCC, many challenges remain: VEGF expression patterns and activation of downstream pathways in RCC are not well characterized. TKIs are non-selective and often incur significant toxic off-target effects that result in subtherapeutic treatment and futile toxicity in the 20% that do not respond. Thus, there is an urgent need to identify molecular markers that identify the relevant oncogenic pathway in each tumor to aid in the selection of systemic treatments and drastically reduce the amount of futile toxicity. However, identifying and developing biomarkers in RCC has been extremely challenging and a major deterrent has been the inability to measure specific biologic proteomic alterations in patient cells before, during and after treatment. Using existing methods, it is virtually impossibl to obtain real-time proteomic information from clinical specimens. We developed nanoscale immunoassay (NIA) as a highly sensitive, quantitative and unique way to concurrently measure proteins, their different isoforms and multiple phosphorylation states. Further, nanoscale proteomic analysis has the potential to dramatically reduce the amount of tissue required for diagnosis both in primary or other metastatic site biopsy. The ability to perform proteomic analysis of multiple tumor sites at a single time point from same patient, as well as in multiple samples over time, will accelerate translational research and ultimately improve care for patients with RCC. We believe that molecular markers hold the promise to inform every step of patient care in RCC including diagnosis, selection of surgical and systemic treatment, and monitoring response to targeted therapies. We aim to use NIA to identify distinct proteomic signatures of the commonly dysregulated hypoxia pathway in RCC patients and thus aid the selection of personalized and effective systemic therapies by targeting the patient's tumor-specific pathway(s).