The Mayo GBM Xenograft National Resource

梅奥 GBM 异种移植国家资源

• 批准号: 9356585
• 负责人: Jann N. Sarkaria
• 金额: $ 25.88万
• 依托单位: MAYO CLINIC ROCHESTER
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-30 至 2020-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9356585
• 关键词: Activation Analysis; Animal Experiments; Animal Model; Archives; Basic Science; Bioinformatics; Biological Models; Biology; Brain; Brain Neoplasms; Cell Count; Cell Culture Techniques; Cell model; Cells; Clinic; Collection; Communities; Complement; Complex; Computer software; DNA; Data; Data Analyses; Data Set; Databases; Development; Freezing; Funding; Gene Expression Profile; Genetic; Genomics; Genotype; Glioblastoma; Glioma; Goals; Gold; Grant; Growth; Histologic; Human; Human Characteristics; Immune; Immunocompromised Host; Implant; In Vitro; Large-Scale Sequencing; Malignant neoplasm of brain; Manuscripts; Memorial Sloan-Kettering Cancer Center; Modeling; Molecular; Molecular Target; Monoclonal Antibody R24; Morphology; Mus; National Institute of Neurological Disorders and Stroke; North America; Online Systems; Operating Rooms; Operative Surgical Procedures; Pathway Analysis; Patients; Peer Review; Pharmaceutical Preparations; Phenotype; Process; Proteins; Proteomics; RNA; Radiation; Reagent; Research; Research Personnel; Research Project Grants; Resources; Sampling; Serial Passage; Series; Serum; Signal Transduction; Systems Biology; Techniques; Testing; The Cancer Genome Atlas; Tissues; Translational Research; Tumor Initiators; Tumor Tissue; United States National Institutes of Health; Xenograft Model; Xenograft procedure; bevacizumab; clinical practice; clinically relevant; data portal; epigenetic profiling; established cell line; exome sequencing; experience; in vivo; individual patient; individualized medicine; insight; interest; methylome; molecular phenotype; nerve stem cell; neuro-oncology; novel therapeutics; open source; phosphoproteomics; repository; response; search engine; standard of care; temozolomide; tissue culture; transcriptome sequencing; transcriptomics; translational study; tumor; tumor xenograft; user-friendly; web portal

The Mayo Glioblastoma (GBM) Xenograft National Resource will provide users with robust animal models, with corresponding phenotypic and molecular characterizations, that recapitulate key molecular and histologic phenotypes of human GBM tumors from a panel of 79 patient-derived xenografts (PDX). These tumor models were created at the Mayo Clinic by implanting surgical tissue directly into immunocompromised mice and then serially passaging these tumors in mice. The PDX models are highly representative of human GBM tumors and preserve the complex molecular features of the human tumors they were derived from. These highly translational and relevant models have been used widely in neuro-oncology research; the Mayo GBM PDXs are used in over 100 peer-reviewed manuscripts and are key reagents in 37 NIH-funded grants (including 16 NINDS-funded grants). As a complement to the rich multi-omic data sets available on human tumor samples (e.g., The Cancer Genome Atlas), the goal of this R24 is to provide a similar level of molecular characterization across our GBM PDX models and make the data freely-available for Users. Availability of comprehensive multi-omic data for this large PDX panel is critically important to allow Users to readily identify the most relevant tumor model(s) for use in their specific research projects. Towards this goal, the RNAseq, total- and phospho-proteomics studies proposed in this study (Aim 1) will be combined with our whole-exome sequencing and whole methylome studies to provide a broad molecular characterization across the PDX panel. These datasets will be integrated using systems biology approaches to identify critically deregulated signaling networks, which will help Users with limited bioinformatics experience interpret the multi-omic PDX characterizations (Aim 2). We will host all of the PDX molecular and phenotypic characterizations using the open-source cBioPortal software (used to host The Cancer Genome Atlas data at MSKCC) to provide a user-friendly interface to a powerful database with robust integrative multi-omic search capabilities (Aim 3). In parallel, the Mayo GBM Xenograft National Resource will develop an archive of early-passage tumor analytes (DNA, RNA, and protein extracts) and frozen or cryopreserved tumor samples for distribution to Users (Aim 4). In this way, the Aims planned for this proposed National Resource will significantly enhance the availability of highly characterized GBM PDX models for use in basic and translational research across the neuro-oncology community.

梅奥胶质母细胞瘤(GBM)异种移植国家资源将为用户提供强大的动物模型，以及相应的表型和分子特征，这些模型概括了79例患者来源的异种移植物(PDX)中人GBM肿瘤的关键分子和组织表型。这些肿瘤模型是在梅奥诊所通过将手术组织直接植入免疫功能低下的小鼠，然后在小鼠身上连续传代而建立的。PDX模型具有高度的人类GBM肿瘤的代表性，并保留了它们所源自的人类肿瘤的复杂分子特征。这些高度翻译和相关的模型已被广泛用于神经肿瘤学研究；Mayo GBM PDX被用于100多篇同行审查的手稿，并是37项NIH资助的赠款(包括16项NINDS资助的赠款)的关键试剂。作为对人类肿瘤样本(例如癌症基因组图谱)上丰富的多组数据集的补充，R24的目标是在我们的GBM PDX模型中提供类似水平的分子表征，并使用户可以免费获得数据。为这个大型的PDX小组提供全面的多组学数据至关重要，这样用户就可以容易地识别最相关的肿瘤模型(S)，用于他们的特定研究项目。为了实现这一目标，本研究中提出的RNAseq、总蛋白质组和磷酸蛋白质组研究(目标1)将与我们的全外显子组测序和全甲基组研究相结合，以提供整个PDX小组的广泛分子特征。这些数据集将使用系统生物学方法进行整合，以识别严重放松管制的信号网络，这将帮助生物信息学经验有限的用户解释多组PDX的特征(目标2)。我们将使用开源的cBioPortal软件(用于在MSKCC托管癌症基因组图谱数据)来托管所有PDX分子和表型特征，以提供一个用户友好的界面，以建立一个强大的数据库，具有强大的综合多基因组搜索能力(AIM 3)。同时，Mayo GBM异种移植国家资源将开发一份早期传代肿瘤分析物(DNA、RNA和蛋白质提取物)以及冷冻或冷冻保存的肿瘤样本的档案，以分发给用户(目标4)。通过这种方式，为这项拟议的国家资源计划的AIMS将显著增加高度特征化的GBM PDX模型的可用性，用于整个神经肿瘤学社区的基础和翻译研究。