Molecular Characterization of Parotid Gland Tumors

7.项目总结/摘要 唾液腺肿瘤占头颈部肿瘤的1-6%，每年有3600例新发病例， 美方虽然罕见，但有37种组织病理学恶性亚型和13种良性亚型的唾液腺 腺肿瘤，使其成为最具挑战性的肿瘤诊断之一。虽然手术是治疗的主要方式， 在治疗中，晚期不可切除的原发性、复发性和转移性肿瘤通常是致命的。的稀有 肿瘤和多种组织病理学亚型产生了早期检测的主要临床挑战， 涎腺肿瘤的诊断、治疗措施和预后。 这种应用程序解决了缺失的差距，唾液腺肿瘤的研究，通过推进基本的 和转化科学。我们的方法是进行全面的分子表征唾液 使用最先进的组学技术结合先进的数据和生物信息学 分析，以开发用于唾液腺恶性肿瘤检测的基于组织的生物标志物， 使用唾液生物标志物筛选/风险评估有症状的患者的唾液腺恶性肿瘤。在 系统网络分析方法（加权基因共表达网络分析，WGCNA） 将用于检查衍生的组学数据库，以确定关键的分子途径和基因靶点， 唾液腺恶性肿瘤发展。集体这些方法将导致翻译和机械 唾液腺肿瘤发展的见解，可以进一步转化为临床应用，以及 使用啮齿动物模型进行唾液腺致癌作用的机制评价。 六个具体目标是为了测试本申请中的假设。目标1是采购新鲜冷冻食品 恶性和良性腮腺组织，来自UCLA头颈肿瘤诊所。目标二：执行 腮腺肿瘤的转录组、microRNA和表观基因组的综合分析， 先进的RNA测序和甲基组学阵列。目标3将进行统计和生物信息学分析 为组学数据库选择候选生物标志物，可以检测腮腺恶性肿瘤。这些 候选生物标志物将在目标4中在腮腺恶性肿瘤的独立队列中进行预先验证， 良性肿瘤目的5是探讨在恶性肿瘤中，基于组织的生物标志物失调的假说， 腮腺在这些患者的唾液中一致地失调。最后，目标6是一个系统网络 基于组学数据库的分析，以确定关键的生物学途径和基因靶点， 腮腺恶性肿瘤的发展。这些途径和目标的结果可以在 通过啮齿动物模型或细胞系进行的唾液腺恶性肿瘤发展的未来机制研究。 我们的多学科研究团队拥有专业知识和跟踪记录，可以开展拟议的 腮腺肿瘤的分子特征以及进行机制和 为充分实现本RFA的目标，我们将采取下一步的具体措施。

7. Project Summary/Abstract Salivary gland tumors constitute 1-6% of head and neck tumors numbering 3600 new cases per year in the US. Though rare, there are 37 histopathological malignant subtypes and 13 benign subtypes of salivary gland tumors, making it one of the most challenging tumors to diagnose. While surgery is the main modality of treatment, advance unresectable primary, recurrent and metastatic tumors are generally fatal. The rarity of the tumors and multiple histopathological subtypes generated major clinical challenges for the early detection, diagnosis, therapeutic interventions and prognosis of patients with salivary gland tumors. This application addresses the missing gaps in salivary gland tumor research by advancing the basic and translational sciences. Our approach is to perform comprehensive molecular characterization of salivary gland tumors using the most advanced omics technologies coupled with advanced data and bioinformatics analysis to develop tissue-based biomarkers for salivary gland malignancy detection as well as the potential use of salivary biomarkers to screen/risk assess symptomatic patients for salivary gland malignancies. In additional a systems network analysis approach (Weighted-Gene Co-Expression Network Analysis, WGCNA) will be use to examine the derived omics databases to identify pivotal molecular pathways and gene targets for salivary gland malignancy development. Collective these approaches will lead to translational and mechanistic insights for salivary tumor development that can be further translated for clinical applications as well as mechanistic evaluations using rodent models for salivary gland carcinogenesis. Six Specific Aims are in place to test the hypothesis in this application. Aim 1 is to procure fresh frozen malignant and benign parotid gland tissues from the UCLA Head & Neck Oncology Clinic. Aim 2 is to perform comprehensive profiling of parotid gland tumors' transcriptome; microRNA and epigenome using most advanced RNA sequencing and methylomics arrays. Aim 3 will perform statistical and bioinformatics analysis for the omics databases to select candidate biomarkers that can detect parotid gland malignancies. These candidate biomarkers will be pre-validated in Aim 4 in an independent cohort of parotid gland malignant and benign tumors. Aim 5 is to explore the hypothesis that tissue-based dysregulated biomarkers in malignant parotid glands are concordantly dysregulated in saliva of these patients. Finally Aim 6 is a systems network based analysis of the omics databases to identify critical biological pathways and gene targets that are pivotal in the development of parotid gland malignancies. These pathway and targets outcome can be evaluated in future mechanistic studies in salivary gland malignancy development by rodent models or cell lines. Our multidisciplinary research team has the expertise and track record to carry out the proposed molecular characterization of parotid gland tumors as well as expertise to carryout the mechanistic and translational next steps to fully materialize the goals of this RFA.