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: 10626073
• 负责人: DANIEL Wanyui CHAN
• 金额: $ 111.91万
• 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/10626073
• 关键词: Acceleration; 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; Patients; 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; cancer diagnosis; cancer genomics; cancer therapy; cancer type; carcinogenesis; clinical center; cohort; data resource; experience; genome analysis; genomic data; glycoproteomics; glycosylation; improved; mortality; multidisciplinary; multiple reaction monitoring; new technology; 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; technology platform; 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) 多次展示了卓越的技术创新和强大的数据生成能力，发挥了作用 CPTAC 加速理解分子基础这一核心使命的成功发挥了关键作用 通过大规模蛋白质组和基因组分析技术对不同癌症的应用 类型。作为当前 3 个 CPTAC3 PCC 之一，我们建立了稳健且标准化的蛋白质组分析 方案和技术，并将其应用于 7 个人类癌症队列和另外 200 个源自患者的队列 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 (PGDAC)，我们发表了关于四种癌症类型的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 PCC 的总体目标是使用以下方法生成准确且可重复的数据 敏感、定量和标准化的技术。我们将利用我们已建立的中心 基础设施并利用我们在临床癌症蛋白质组学发现方面的成功来表征 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。我们将识别固有的独特特征 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- 除了糖基化和磷酸化之外，蛋白质相互作用也已包含在我们当前的 PCC 中。 我们提出了一个三步策略来表征定义的基因组学特征样本集，使用 CPTAC3期间验证的技术平台：（1）从两个临床标本中发现目标蛋白 以及通过串联质量标签和数据相关采集质量使用定量蛋白质组学的临床前模型 光谱测定； (2) 使用正交数据独立采集质谱验证结果；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 多重反应监测质谱 (MRM-MS) 分析。我们进一步建议试点研究 技术改进。虽然该 PCC 应用的重点是临床药物的蛋白质组学表征 标本和临床前模型，我们相信对蛋白质组数据的理解和专业知识 分析和翻译对于 PCC 和整个 CPTAC 网络的成功至关重要。我们有 组建了一支由具有互补专业知识和多年经验的优秀研究人员组成的团队 CPTAC 计划（CPTAC2 和 CPTAC3），以及与来自以下国家的研究者/PI 成功合作的证据 CPTAC PGDAC 和蛋白质基因组转化研究中心 (PTRC)。我们相信我们的PCC 为成功表征生物和临床标本提供最佳机会 并确认癌症靶点以推进精准癌症医学。