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.

总结 在CPTAC 2和CPTAC 3的过去10年中，JHU蛋白质组表征中心（JHU/PCC） 一再展示了上级技术创新和强大的数据生成能力， 在CPTAC的核心使命的成功，加速理解的分子基础， 通过将大规模蛋白质组和基因组分析技术应用于不同的癌症， 类型作为目前3个CPTAC 3 PCC之一，我们建立了稳健和标准化的蛋白质组学分析， 方案和技术，并将其应用于7个人类癌症队列和另外200个患者来源的 来自患者衍生模型库的异种移植物。与蛋白基因组数据分析中心一起 （PGDAC），我们发表了关于四种癌症类型的整合蛋白基因组学研究的文章。对于我们的CPTAC 4 PCC应用程序，我们PCC的首要目标是使用 敏感、定量和标准化的技术。我们将利用我们建立的中心的 基础设施，并利用我们在临床癌症蛋白基因组学发现方面的成功， 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 蛋白质如翻译后修饰，包括乙酰化和泛素化，以及蛋白质- 蛋白质相互作用，除了糖基化和磷酸化，已包括在我们目前的PCC。 我们提出了一个三步策略来表征定义的基因组学表征的样本集，使用 在CPTAC 3期间验证的技术平台：（1）从两种临床标本中发现靶蛋白 和使用通过串联质量标签和数据依赖性采集质量的定量蛋白质组学的临床前模型 （2）使用正交数据独立采集质谱法验证发现;以及 (3)使用经分析验证的高通量CPTAC Tier 2靶向检测器确认经验证的靶点 多反应监测质谱（MRM-MS）测定。我们进一步建议进行试验研究， 技术改进。虽然该PCC应用集中于临床肿瘤的蛋白质组学表征， 标本和临床前模型，我们相信，蛋白质组学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 组建了一个由杰出的调查人员组成的团队，他们在这方面具有互补的专门知识和多年的经验， CPTAC计划（CPTAC 2和CPTAC 3），以及与研究者/PI成功合作的证据， CPTAC PGDAC和蛋白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了最佳机会， 并确认癌症靶点以推进精准癌症医学。