Core C: Genomics and Bioinformatics

核心 C：基因组学和生物信息学

• 批准号: 10661815
• 负责人: Srinivasan Yegnasubramanian
• 金额: $ 29.48万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-06-01 至 2026-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10661815
• 关键词: ATAC-seq; Bioinformatics; Biological; Biological Models; Biometry; Budgets; Cells; ChIP-seq; Clinical; Clinical Trials; Clone Cells; Collaborations; Complement; Computer Analysis; Computing Methodologies; Core Grant; Coupled; Cytometry; Data; Data Analyses; Data Set; Dedications; Dimensions; Disparate; Epigenetic Process; Foundations; Genetic Transcription; Genomics; Goals; Human; Human Resources; Image; Immune; Immune System Diseases; Immune response; Immunogenomics; Immunotherapy; Infrastructure; Intervention; Malignant Neoplasms; Malignant neoplasm of pancreas; Measurement; Measures; Methodology; Methods; Modality; Molecular; Mutation; Myeloid Cells; Outcome; Pancreatic Ductal Adenocarcinoma; Pathway interactions; Pattern; Peripheral; Program Research Project Grants; Proteomics; Regimen; Research Personnel; Resistance; Resources; Shapes; T cell receptor repertoire sequencing; T-Cell Receptor; T-Lymphocyte; Techniques; Technology; Testing; Therapeutic; Tissues; Transcriptional Regulation; Treatment Protocols; Tumor Tissue; Universities; Vaccines; analysis pipeline; bioinformatics pipeline; data integration; digital pathology; diverse data; epigenetic regulation; epigenomics; exome sequencing; high dimensionality; human model; human tissue; immune cell infiltrate; immune checkpoint; multidimensional data; multimodal data; multiplexed imaging; neoantigens; next generation sequencing; novel; novel strategies; novel therapeutic intervention; peripheral blood; personalized immunotherapy; pre-clinical; programs; protein profiling; response; single cell sequencing; single-cell RNA sequencing; synergism; transcriptome sequencing; transfer learning; tumor; tumor microenvironment

PROJECT SUMMARY The Genomics and Bioinformatics Core (Core C) will provide state-of-the-art sequencing technologies to enable immunogenomic and epigenomic measurements and corresponding bioinformatics analyses for the proposed P01 Program Projects. This Core will deploy a wide range of bulk and single cell next generation sequencing technologies optimized for the preclinical and clinical biospecimens in the Projects. Technologies supported by this Core include: whole exome sequencing for neoantigen prediction, bulk and single cell RNA-sequencing for inference of molecular and cellular networks, bulk and single cell T cell receptor sequencing to query T cell clones and their associated function, and ATAC-seq and ChIP-seq technologies to query epigenetic and tran- scriptional regulation. These technologies are complemented by optimized bioinformatics pipelines and compu- tational methods tailored to immunogenomics developed by the Core and Program Investigators. Bioinformatics methods are tailored to customized analyses of the datasets generated in Program Projects, and proteomics measurements from the Digital Pathology and Mass Cytometry Core (Core D) to support TME characterization. This Genomics and Bioinformatics Core will perform further integrative analyses of biospecimens of the thera- peutic regimens employed across Projects in this Program and promote Program Synergy. The computational methods employed in this Core will summarize the high-dimensional data to provide low dimensional summaries to the Biostatistics and Clinical Trials Core (Core B) to identify molecular and cellular determinants of immuno- therapy response and resistance to support the Projects in defining new therapeutic strategies for precision immunotherapy. The Core Co-Leaders combine expertise in genomics technologies (Dr. Yegnasubramanian) and bioinformatics (Dr. Fertig). In addition to the Program-specific goals, this Core further leverages the existing infrastructure in the NCI-designated Johns Hopkins University SCCC Core Grant-supported Experimental and Computational Genomics Core (ECGC; Co-Director Yegnasubramanian; Co-Investigator Fertig). Both Leaders, Fertig and Yegnasubramanian, have an established track record in Genomics and Bioinformatics in collaboration with one another and Program Investigators ideally suited to enable the profiling and bioinformatics analysis proposed for the Program in this Core.

项目摘要 基因组学和生物信息学核心（核心C）将提供最先进的测序技术， 免疫基因组学和表观基因组学测量以及相应的生物信息学分析， P01计划项目。该核心将部署广泛的批量和单细胞下一代测序 为项目中的临床前和临床生物标本优化的技术。技术支持 该核心包括：用于新抗原预测的全外显子组测序，用于新抗原预测的批量和单细胞RNA测序， 分子和细胞网络推断、批量和单细胞T细胞受体测序以查询T细胞 克隆及其相关功能，以及ATAC-seq和ChIP-seq技术来查询表观遗传和转基因， 脚本规则。这些技术得到了优化的生物信息学管道和计算机的补充， 由核心和项目研究者开发的针对免疫基因组学的定量方法。生物信息 方法是定制的，以定制分析的数据集产生的计划项目，和蛋白质组学 数字病理学和质谱细胞计数核心（核心D）的测量结果，以支持TME表征。 该基因组学和生物信息学核心将对该物种的生物标本进行进一步的综合分析， 在本计划中的项目中采用不同的方案，并促进计划的协同作用。计算 本核心中采用的方法将对高维数据进行汇总，以提供低维汇总 生物统计学和临床试验核心（核心B），以确定免疫的分子和细胞决定因素， 治疗反应和耐药性，以支持项目定义新的治疗策略， 免疫疗法。 核心联合领导人联合收割机结合基因组学技术（Yegnasubramanian博士）和生物信息学的专业知识 (Dr. Fertig）。除了特定于计划的目标外，该核心还进一步利用现有的基础设施， NCI指定的约翰霍普金斯大学SCCC核心资助实验和计算 基因组学核心（ECGC;共同主任Yegnasubramanian;共同研究员Fertig）。两位领导人，Fertig和 Yegnasubramanian在基因组学和生物信息学方面有着良好的记录， 另一个和程序调查员非常适合使分析和生物信息学分析提出了 在这个核心的计划。