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: 10478920
• 负责人: Maureen Agnes Sartor
• 金额: $ 16.06万
• 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 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10478920
• 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; 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; 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; rational design; 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提案的总体目标是采用系统的方法来理解 可以指导新型组合免疫疗法的合理设计的免疫抵抗力有效地设计 治疗头颈鳞状细胞癌（HNSCC）患者。为了实现这一目标，我们将使用几个 来自批量和单细胞RNA测序（SCRNA-SEQ）数据的尖端生物信息学策略， 表观基因组学测定和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 具有互补的专业知识，包括HNSCC遗传学和生物学，先天和适应性免疫 反应，免疫生物信息学，单细胞动力学和SCRNA-seq，癌症基因组学的分析 和全基因组调节数据以及HNSCC临床试验数据分析。免疫的目的 生物信息学和计算生物学（IBCB）核心是提供特定于疾病的综合 以及对P01研究人员进行研究设计，分析，整合和的创新支持 解释广泛的基于OMIC的和临床试验研究。 IBCB核心将通过四个特定目标来支持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特定的分析。这包括，但不是 仅限于突变负担分析和新抗原预测，HLA I类等位基因的分析和免疫 细胞类型反卷积。第二个目的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的方法开发。我们将利用几个最近开发的scrna-seq QC，批化和归一化，插补，创新可视化的方法，自动细胞类型 识别和差分表达测试。第三个目的是提供有关实验的咨询 设计并提供表观基因组学数据的分析。我们将分析全基因组DNA甲基化和 不同免疫检查点阻滞（ICB）治疗方案之前和之后的转录组学数据。目的 四个是为临床试验分析，功率分析提供高级生物统计学和生物信息学支持， 以及上述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。