Proteogenomic Characterization of Tumor Tissues and Preclinical Models with High Precision

肿瘤组织的蛋白质组学表征和高精度临床前模型

• 批准号: 10440934
• 负责人: DANIEL Wanyui CHAN
• 金额: $ 115.78万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-06-01 至 2027-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10440934
• 关键词: Acetylation; Advanced Malignant Neoplasm; Bioinformatics; Biological; Biological Assay; Biometry; Cancer Biology; Center for Translational Science Activities; Clinical; Clinical Research; Collaborations; Communities; DNA Sequence Alteration; Data; Data Analyses; Databases; Development; Diagnostic; Future; Generations; Genes; Genome; Genomics; Goals; Human; Infrastructure; International; Knowledge; Label; Literature; Malignant Neoplasms; Mass Spectrum Analysis; Mission; Modeling; Molecular; Normal tissue morphology; Organoids; Pathway interactions; Phosphorylation; Pilot Projects; Play; Post-Translational Protein Processing; Pre-Clinical Model; Process; Proteins; Proteome; Proteomics; Protocols documentation; Publishing; Reproducibility; Research; Research Personnel; Resources; Role; Sampling; Scientist; Signal Pathway; Signal Transduction; Specimen; Standardization; Technology; Therapeutic; Tissue Model; Translations; Tumor Tissue; Ubiquitination; Work; base; cancer diagnosis; cancer genomics; cancer type; carcinogenesis; clinical center; cohort; data resource; experience; genome analysis; genomic data; glycoproteomics; glycosylation; improved; mortality; multidisciplinary; multiple reaction monitoring; novel; patient derived xenograft model; phosphoproteomics; pre-clinical; precision medicine; precision oncology; prognostic; programs; protein complex; protein protein interaction; proteogenomics; repository; success; technological innovation; technology development; translational study; tumor

Summary During the last 10 years of both CPTAC2 and CPTAC3, the JHU Proteome Characterization Center (JHU/PCC) has repeatedly demonstrated superior technological innovation and robust data generation that have played critical roles in the success of CPTAC's core mission of accelerating the understanding of the molecular basis of cancer through the application of large-scale proteome and genome analysis technologies to different cancer types. As one of the 3 current CPTAC3 PCCs, we established robust and standardized proteomic analysis protocols and technologies and applied them to 7 human cancer cohorts and an additional 200 patient-derived xenografts from the Patient-Derived Models Repository. Together with the Proteogenomic Data Analysis Centers (PGDACs), we published articles on integrated proteogenomic studies in four cancer types. For our CPTAC4 PCC application, the overarching goal of our PCC is to generate accurate and reproducible data using sensitive, quantitative, and standardized technologies. We will leverage our established Center's infrastructure and capitalize on our success in clinical cancer proteogenomic discoveries to characterize proteins, protein modifications, and protein complexes associated with genomic alterations of cancer from additional human tumor types and pre-clinical models. We will identify unique features that are inherent to proteins such as post-translational modifications covering acetylation and ubiquitination, as well as protein- protein interactions in addition to glycosylation and phosphorylation that have been included in our current PCC. We propose a three-step strategy to characterize defined sets of genomics-characterized samples using technology platforms validated during CPTAC3: (1) Discovery of target proteins from both clinical specimens and preclinical models using quantitative proteomics by tandem mass tags and data dependent acquisition mass spectrometry; (2) Verification of findings using orthogonal data-independent acquisition mass spectrometry; and (3) Confirmation of the verified targets using high-throughput, CPTAC Tier 2 analytically-validated targeted Multiple Reaction Monitoring Mass Spectrometry (MRM-MS) assays. We further propose pilot studies for technology improvement. While this PCC application is focused on the proteomic characterization of clinical specimens and preclinical models, we believe that the understanding of and the expertise in proteogenomic data analysis and translation will be critical for the success of the PCC and the overall CPTAC network. We have assembled a team of outstanding investigators with complementary expertise and years of experience in the CPTAC program (CPTAC2 and CPTAC3), and evidence of successful collaborations with investigators/PIs from the CPTAC PGDACs and Proteogenomic Translational Research Centers (PTRCs). We believe that our PCC offers the best opportunity for the successful characterization of biological and clinical specimens to discover and confirm cancer targets to advance precision cancer medicine.

概括 在CPTAC2和CPTAC3的最后10年中，JHU蛋白质组表征中心（JHU/PCC） 一再证明了卓越的技术创新和强大的数据生成 CPTAC成功的关键作用，即加速对分子基础的理解的核心使命 通过将大规模蛋白质组和基因组分析技术应用于不同癌症的癌症 类型。作为当前3个CPTAC3 PCC之一，我们建立了鲁棒和标准化的蛋白质组学分析 方案和技术，并将其应用于7个人类癌群，另外200名患者衍生 来自患者衍生模型存储库的异种移植物。与蛋白质组数据分析中心一起 （PGDACS），我们发表了四种癌症类型综合蛋白质组学研究的文章。对于我们的CPTAC4 PCC应用程序，我们的PCC的总体目标是使用 敏感，定量和标准化技术。我们将利用我们已建立的中心的 基础设施并利用我们在临床癌症蛋白质组发现中的成功表征 与癌症基因组改变相关的蛋白质，蛋白质修饰和蛋白质复合物 来自其他人类肿瘤类型和临床前模型。我们将确定固有的独特功能 对于蛋白质，例如涵盖乙酰化和泛素化的翻译后修饰，以及蛋白质 除糖基化和磷酸化外，我们当前的PCC中还包括蛋白质相互作用。 我们提出了一个三步策略，以表征使用定义的基因组特征样品集 在CPTAC3期间验证的技术平台：（1）从两个临床标本中发现靶蛋白 和临床前模型使用定量蛋白质组学通过串联质量标签和数据依赖性采集质量 光谱法； （2）使用正交数据依赖性采集质谱法对发现的验证；和 （3）使用高通量，CPTAC Tier 2分析验证的目标确认已验证的目标 多反应监测质谱法（MRM-MS）测定法。我们进一步提出了试点研究 技术改进。虽然该PCC应用集中于临床的蛋白质组学表征 标本和临床前模型，我们认为对蛋白质组数据的理解和专业知识 分析和翻译对于PCC和整体CPTAC网络的成功至关重要。我们有 组建了一个杰出调查员团队，拥有互补的专业知识和多年的经验 CPTAC计划（CPTAC2和CPTAC3），以及与研究人员/PIS成功合作的证据 CPTAC PGDAC和蛋白质组转化研究中心（PTRCS）。我们相信我们的PCC 为成功表征生物学和临床标本提供了最佳机会，以发现 并确认癌症靶标可以推进精确的癌症医学。