MICROSCALED PROTEOGENOMICS FOR CANCER CLINICAL TRIALS

用于癌症临床试验的微观蛋白质组学

基本信息

批准号：
9272692
负责人：
STEVEN A CARR
金额：
$ 145.25万
依托单位：
BAYLOR COLLEGE OF MEDICINE
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-06-07 至 2022-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9272692
关键词：
Aftercare Aromatase Inhibitors Automobile Driving Beds Biological Biological Assay Biology Biopsy Biopsy Specimen Cancer Therapy Evaluation Program Center for Translational Science Activities Cessation of life Chemotherapy-Oncologic Procedure Clinical Clinical Research Clinical Trials Clinical Trials Cooperative Group Collaborations Communities Complex Comprehensive Cancer Center Core Biopsy DNA sequencing Data Data Discovery Development Diagnostic Drug Targeting Drug resistance ERBB2 gene Enrollment Evaluation Event Funding Gene Expression Gene Mutation Genome Human Individual Informatics Institutes Investigation Link Malignant Neoplasms Mass Spectrum Analysis Measures Medicine Mind Modeling Neoadjuvant Study Neoadjuvant Therapy Outcome Pathogenesis Pathologic Pathway interactions Patients Pharmaceutical Preparations Pharmacotherapy Phosphotransferases Pre-Clinical Model Preclinical Testing Property Protein Kinase Proteins Proteome Proteomics Relapse Reproducibility Research Personnel Resistance Resources Sampling Scheme Selection for Treatments Signal Transduction Solid Somatic Mutation Technology Testing The Cancer Genome Atlas Therapeutic Translating Trastuzumab Tumor Biology Xenograft procedure anticancer research arm assay development base bevacizumab cancer clinical trial cancer genome cancer genomics cancer proteomics candidate marker chromatin modification clinical phenotype cohort college drug efficacy effective therapy experience improved innovation insight iterative design kinase inhibitor lapatinib malignant breast neoplasm metastatic process mortality multidisciplinary new therapeutic target next generation personalized diagnostics phosphoproteomics pre-clinical pre-clinical research predictive marker progenitor prognostic prospective proteogenomics resistance mechanism response standard of care therapy resistant triple-negative invasive breast carcinoma tumor tumor microenvironment

项目摘要

Gene expression-based approaches to breast cancer are largely for prognostication, not prediction of individual drug responses. Furthermore, there are still no clinically validated somatic mutation-based approaches in breast cancer management based on next generation DNA sequencing (NGS). A major obstacle to progress in NGS-based diagnostics is a fundamental one: we poorly understand how complex cancer somatic genomes drive clinical phenotypes and drug vulnerabilities. Key issues such as therapeutic resistance, the contribution of the tumor microenvironment and the metastatic process belie single gene/mutation explanations. The new field of proteogenomics provides an opportunity to generate new insights by melding the complexity of cancer genomics with cancer proteomics to more completely understand how somatic genomes activate aberrant signal transduction events that drive cancer pathogenesis. To this end, we have formed a multi-institutional, multi-omics center to engage in collaborative studies under the aegis of the NCI-CPTAC PTRC initiative. Our core builds upon ongoing collaborations between the highly experienced and innovative teams at Baylor College of Medicine and the Broad Institute with complementary strengths in cancer genomics, precision diagnostics, proteogenomic technologies and decades of experience in breast cancer research. Our proposal leverages state-of-the-art quantitative discovery proteomics and phosphoproteomics as well as targeted assays to measure the kinome and chromatin modifications. These sensitive and reproducible pipelines will be used to analyze preclinical models, well-annotated cohorts and clinical trial samples in an iterative design. A robust proteogenomics pipeline developed by our group will be used to analyze and visualize the data. These analyses, together with the primary data generated by this multidisciplinary proposal will be made rapidly available to the scientific community. While the FOA envisioned that only targeted approaches could be applicable in the Clinical Research Arm, it did not anticipate the major advances already well underway in discovery proteomics. We show that the global, discovery-based proteome and phosphoproteome pipeline we have developed is already applicable to biopsy-scale tumor samples, providing deep and broad quantitative coverage of the proteome and phosphoproteome with excellent reproducibility and robustness. This key conceptual and practical advance enables us to employ discovery and targeted approaches in both Preclinical and Clinical arms thereby greatly increasing the power of our proposed studies to generate impactful insight into the causes of breast cancer mortality. We postulate that this integrated approach will provide new understanding of the biology of response and resistance to chemotherapeutics, sounder therapeutic hypotheses and identify more accurate predictive biomarkers for drug resistance and treatment selection that could be developed and deployed as clinical tests.

基于基因表达的乳腺癌方法主要用于预后，而不是预测个别药物反应。此外，仍然没有临床验证的基于体细胞突变基于下一代DNA测序（NGS）的乳腺癌管理方法。专业基于NGS的诊断的障碍是一个基本的：我们不太了解复杂程度癌症体细胞基因组驱动临床表型和药物脆弱性。诸如治疗等关键问题抗性，肿瘤微环境的贡献和转移过程相信单一基因/突变解释。新的蛋白质组学领域为生成新的机会提供了机会通过融合癌症基因组学与癌症蛋白质组学的复杂性来完全理解的见解体细胞基因组如何激活驱动癌症发病机理的异常信号转导事件。为此，我们成立了一个多机构的多派中心，用于从事协作研究 NCI-CPTAC PTRC计划的宙斯盾。我们的核心建立在高度合作的基础上贝勒医学院和广大研究所的经验丰富的创新团队与补充癌症基因组学，精确诊断，蛋白质组技术和数十年经验的优势在乳腺癌研究中。我们的建议利用最先进的定量发现蛋白质组学和磷蛋白质组学以及靶向测定法以测量活化组和染色质修饰。这些敏感且可重复的管道将用于分析临床前模型，宣布良好的队列和临床试验样本迭代设计。我们组开发的强大蛋白质组学管道将用于分析和可视化数据。这些分析以及该多学科建议生成的主要数据将迅速向科学界提供。而FOA设想仅针对目标方法可能适用于临床研究部门，它并没有预料到主要进步在发现蛋白质组学方面正在进行中。我们表明，全球，基于发现的蛋白质组和我们开发的磷酸蛋白酶管道已经适用于活检尺度肿瘤样品，提供蛋白质组和磷蛋白质组的深度和广泛的定量覆盖范围具有出色的可重复性和鲁棒性。这个关键的概念和实际的进步使我们能够采用发现并针对目标临床前和临床方面的方法都大大提高了我们拟议的研究的力量为了产生对乳腺癌死亡率的原因有影响力的见解。我们假设这种综合方法将为响应的生物学提供新的了解和对化学治疗药的耐药性，较明显的治疗假设并确定更准确的预测性可以开发和部署作为临床测试的耐药性和治疗选择的生物标志物。