Proteogenomics of Cancer Training Program

摘要 这是我们的T32癌症蛋白质基因组学培训计划(PCTP)的续订申请，地址为 密歇根大学。国家癌症研究所在新技术上进行了大量投资 癌症蛋白质组学平台，最近通过临床蛋白质组肿瘤分析联盟 (CPTAC)。蛋白质组对于理解癌症的功能基因组学和系统生物学至关重要。 以及发现和验证用于治疗和预防的生物标记物候选和分子靶点。 复杂的蛋白质组分析需要先进的信息学来处理复杂的 样本，蛋白质浓度的极端动态范围，翻译后修饰， 选择性剪接异构体，对各种干扰的反应，以及数据库和数据中的差异 格式。此外，对使用多组学产生的数据进行综合蛋白质组学分析 技术(蛋白质组学、基因组学、转录组学、代谢组学等)已经成为一个强大的 重建癌症靶向通路的方法。PCTP的主要目标是解决当前 缺乏能够有效地生成和生物信息分析他们自己的蛋白质组学数据的科学家，以 利用CPTAC和其他公开可用的大规模蛋白质组数据集，并执行 多层次蛋白质组学数据整合。PCTP是一个真正的多学科培训计划，也是 非常独特，在密歇根大学和全国范围内。总部设在大学范围内的计算中心 医学和生物信息学，它为来自不同背景的学生提供了成为 精通PCTP的所有重点领域--癌症生物学、蛋白质组学、生物信息学和蛋白质组学。 PCTP要求每年提供7个名额，为博士前实习生提供1-2年的支持。我们有一个健壮的 癌症研究人员、生物信息学家、数据科学家、统计学家和化学家的社区。我们的教职员工 学生是人类蛋白质组组织倡议、发展和全球的领导者 部署数据储存库和数据分析系统，并创建蛋白质组新算法 生物信息学和多组学数据集成。我们的实习生来自更大规模的研究生项目 密歇根大学(包括生物信息学、病理学、癌症生物学、化学和生物医学工程) 并接受癌症生物学、生物信息学和蛋白质组学方面的培训，通过课程、研讨会和 特别工作坊。PCTP强烈鼓励由一名癌症研究人员和一名癌症研究人员对每名学员进行双重指导 一位计算科学家。我们将进一步加强我们的培训计划，增加一个特别的 为我们的T32受训人员举办的蛋白质组数据分析年度研讨会，利用我们教员的 参与CPTAC财团的努力。总而言之，我们正在进行的NCI培训计划 癌症蛋白质组学培养新一代科学家为独立的职业生涯做好准备 跨学科生物医学研究，加强教师研究，支持NCI的目标。

ABSTRACT This is a renewal application for our T32 Proteogenomics of Cancer Training Program (PCTP) at the University of Michigan. The National Cancer Institute has made substantial investments in new technology platforms for cancer proteomics, most recently through the Clinical Proteomic Tumor Analysis Consortium (CPTAC). The proteome is critical to understanding functional genomics and systems biology of cancers and to discovery and validation of biomarker candidates and molecular targets for therapy and prevention. Sophisticated analysis of proteomes requires advanced informatics to deal with the complexity of specimens, the extreme dynamic range of protein concentrations, post-translational modifications, alternative splice isoforms, responses to all sorts of perturbations, and differences in databases and data formats. Furthermore, integrative proteogenomics analysis of data generated using multiple omics technologies (proteomics, genomics, transcriptomics, metabolomics, etc.) has emerged as a powerful approach for reconstructing targetable pathways in cancer. The main goal of PCTP is to address the current scarcity of scientists able to effectively generate and bioinformaticly analyze their own proteomics data, to take advantage of CPTAC and other publicly available large-scale proteomics datasets, and to perform multi-level proteogenomics data integration. PCTP is a truly multi-disciplinary Training Program that is also very unique, with the U of M and nationally. Anchored in the university-wide Center for Computational Medicine and Bioinformatics, it provides an opportunity to students from diverse backgrounds to become well skilled in all PCTP focus areas - cancer biology, proteomics, bioinformatics, and proteogenomics. PCTP is requesting 7 slots/year to supports pre-doctoral trainees for 1-2 years. We have a robust community of cancer researchers, bioinformaticians, data scientists, statisticians, and chemists. Our faculty and students are in the leadership of Human Proteome Organization initiatives, development and global deployment of data repositories and data analysis systems, and creation of new algorithms for proteome bioinformatics and multi-omics data integration. Our trainees come from larger Graduate Programs within the U of M (including Bioinformatics, Pathology, Cancer Biology, Chemistry, and Biomedical Engineering) and receive training in cancer biology, bioinformatics, and proteomics through courses, seminars, and special workshops. PCTP strongly encourages dual mentorship of each trainee by a cancer researcher and a computational scientist. We will further strengthen our Training Program with an addition of a special Annual Workshop for our T32 trainees on Proteogenomics Data Analysis, taking advantage of our Faculty’s engagement in the efforts of the CPTAC consortium. In summary, our ongoing NCI training program in Proteogenomics of Cancer trains a new generation of scientists well prepared for an independent career in interdisciplinary biomedical research, enhances faculty research, and supports NCI goals.