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.

项目总结（免疫生物信息学和计算生物学核心）