Core 2: Immune Bioinformatics and Computational Biology Core

项目总结（免疫生物信息学和计算生物学核心）

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.