Core 2: Immune Bioinformatics and Computational Biology Core

核心2：免疫生物信息学和计算生物学核心

• 批准号: 10251175
• 负责人: Ramnik J Xavier
• 金额: $ 16.62万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-19 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10251175
• 关键词: Address; Alleles; Area; Binding; Bioinformatics; Biological; Biological Assay; Biology; Biometry; Cells; Chromatin; Clinical Trials; Code; Combination immunotherapy; Combined Modality Therapy; Complex; Computational Biology; Confounding Factors (Epidemiology); Consensus; Consult; Consultations; CpG Islands; DNA Methylation; DNA sequencing; Data; Data Analyses; Data Set; Detection; Disease; Drops; Enhancers; Ensure; Epigenetic Process; Experimental Designs; Gene Targeting; Generations; Genetic; Goals; Head and Neck Cancer; Head and Neck Squamous Cell Carcinoma; Heterogeneity; Human Papillomavirus; Immune; Individual; Knowledge; Malignant Neoplasms; Methods; Methylation; Molecular; Mutation; Pathway Analysis; Pathway interactions; Patients; Peptide antibodies; Regimen; Research Design; Research Personnel; Shapes; Site; Statistical Data Interpretation; Statistical Models; Structure; T-Lymphocyte; Technology; Testing; Therapeutic; Tumor Immunity; Uncertainty; Universities; Visualization; adaptive immune response; base; cancer cell; cell type; clinical trial analysis; data management; data sharing; data visualization; design; differential expression; epigenomics; exome sequencing; experience; experimental study; genetic signature; genome-wide; genomic data; immune checkpoint blockade; immune resistance; immunogenicity; improved; innovation; method development; neoantigens; next generation sequencing; novel; power analysis; response; single-cell RNA sequencing; transcription factor; transcriptomics; tumor

PROJECT SUMMARY (IMMUNE BIOINFORMATICS AND COMPUTATIONAL BIOLOGY CORE) The overall goal of this P01 proposal is to apply a systematic approach to understanding mechanisms of immune resistance that can guide the rational design of novel combinatorial immunotherapies to effectively treat head and neck squamous cell carcinoma (HNSCC) patients. To accomplish this goal, we will use several cutting-edge bioinformatics strategies on data from bulk and single cell RNA sequencing (scRNA-seq), epigenomics assays, and exome sequencing, as well as biostatistics analysis of clinical trial data. Our team has complementary expertise encompassing HNSCC genetics and biology, innate and adaptive immune response, immune bioinformatics, single cell dynamics and the analysis of scRNA-seq, cancer epigenomics and genome-wide regulatory data, and HNSCC clinical trial data analyses. The objective of the Immune BioInformatics and Computational Biology (IBCB) Core is to provide, disease-specific comprehensive and innovative support to the P01 investigators for the study design, analysis, integration and interpretation of a broad range of omics-based and clinical trial studies. The IBCB Core will support the three projects of the P01 through four specific aims. First, we will recommend strategies for study design and provide analyses specific to immune bioinformatics. This includes, but is not limited to, mutational burden analysis and neoantigen prediction, analysis of HLA class I alleles, and immune cell type deconvolution. The second aim is to provide expertise for study design and perform various analyses and methods development for single cell bioinformatics. We will utilize several recently developed scRNA-seq methods for QC, batch correction and normalization, imputation, innovative visualizations, automatic cell type identification, and differential expression testing. The third aim is to provide consultation on experimental design and provide analyses for epigenomics data. We will analyze genome-wide DNA methylation and transcriptomics data before and after different immune checkpoint blockade (ICB) therapeutic regimens. Aim four is to provide advanced biostatistics and bioinformatics support for clinical trial analyses, power analyses, and other bioinformatics support not mentioned above, including data management, transparency, and data sharing.

项目摘要（免疫生物信息学和计算生物学核心） 该 P01 提案的总体目标是应用系统方法来理解 免疫抵抗可以指导新型组合免疫疗法的合理设计，以有效地治疗 治疗头颈鳞状细胞癌（HNSCC）患者。为了实现这个目标，我们将使用几个 针对批量和单细胞 RNA 测序 (scRNA-seq) 数据的尖端生物信息学策略， 表观基因组学分析、外显子组测序以及临床试验数据的生物统计学分析。我们的团队 拥有涵盖 HNSCC 遗传学和生物学、先天性和适应性免疫的互补专业知识 反应、免疫生物信息学、单细胞动力学和 scRNA-seq 分析、癌症表观基因组学 全基因组监管数据以及 HNSCC 临床试验数据分析。免疫的目标 生物信息学和计算生物学（IBCB）核心是提供针对特定疾病的综合 为 P01 研究人员提供研究设计、分析、整合和创新支持 解释广泛的基于组学和临床试验的研究。 IBCB 核心将通过四个具体目标支持 P01 的三个项目。首先我们会推荐 研究设计策略并提供针对免疫生物信息学的分析。这包括但不包括 仅限于突变负荷分析和新抗原预测、HLA I 类等位基因分析以及免疫 细胞类型反卷积。第二个目标是为研究设计提供专业知识并进行各种分析 和单细胞生物信息学方法开发。我们将利用几个最近开发的 scRNA-seq QC 方法、批量校正和标准化、插补、创新可视化、自动细胞类型 鉴定、差异表达检测。第三个目的是提供实验咨询 设计并提供表观基因组数据分析。我们将分析全基因组 DNA 甲基化并 不同免疫检查点阻断（ICB）治疗方案前后的转录组学数据。目的 四是为临床试验分析、功效分析、 以及上面未提及的其他生物信息学支持，包括数据管理、透明度和数据 分享。