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Pan-Cancer characterization of 3’UTR somatic mutations controlling tumor immune evasion

控制肿瘤免疫逃避的 3-UTR 体细胞突变的泛癌症特征

基本信息

批准号：
10556376
负责人：
Ioannis Vlachos
金额：
$ 61.04万
依托单位：
BETH ISRAEL DEACONESS MEDICAL CENTER
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-02-01 至 2027-01-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10556376
关键词：
3&apos Untranslated Regions 3-Dimensional Affect Alleles Bioinformatics Biological Assay Biological Markers Biomimetics Bypass Cancer Patient Cell Fraction Cells Clinical Coculture Techniques Code Data Data Set Detection Development Devices Disease ERBB2 gene Epigenetic Process Evaluation Event Exhibits Gene Expression Gene Expression Regulation Genes Hematoxylin and Eosin Staining Method Image Immune Immune checkpoint inhibitor Immune system Immunologic Surveillance Immunooncology Immunophenotyping Immunotherapeutic agent Immunotherapy In Situ In Vitro Investigation Light Malignant Neoplasms Massive Parallel Sequencing Mediating Messenger RNA Methods MicroRNAs Microfluidic Microchips Minority Molecular Multiomic Data Mutate Mutation Natural Immunity Neoplasm Metastasis Nucleic Acid Regulatory Sequences Oncogenes Oncogenic Outcome Pathology Pathway interactions Patients Phenotype Poly A Polyadenylation Post-Transcriptional Regulation Process Quantitative Trait Loci RNA Editing RNA-Binding Proteins Regulation Research Research Personnel Resistance Resources Role Sampling Somatic Mutation T-Lymphocyte Technology The Cancer Genome Atlas Time Translations Tumor Escape Tumor-Infiltrating Lymphocytes Untranslated RNA Validation Variant adaptive immunity brca gene cancer immunotherapy cancer type cell killing checkpoint inhibition cohort deep learning model exome genome sequencing genomic data immune checkpoint immunoregulation in silico innovation malignant breast neoplasm multimodal data neoplastic neoplastic cell new therapeutic target novel patient stratification posttranscriptional predicting response response statistical learning therapeutic target transcriptome transcriptome sequencing transcriptomics translational potential treatment response tumor tumor immunology tumor microenvironment

项目摘要

SUMMARY All stages of neoplastic disease, from its development to metastasis, are intertwined with cancer immune evasion. The epigenetic mechanisms involved in the regulation of the tumor immune landscape are intensely investigated as biomarkers or therapeutic targets. 3' untranslated regions (3'UTRs) dictate the post- transcriptional mRNA fate and are often targeted by regulatory molecules such as microRNAs (miRNAs) and RNA binding proteins (RBPs). Tumor cells have been shown to evade this tight regulation by mutating or truncating these regions. The first such identified events have shed light on somatic regulatory mechanisms that could potentially affect tumor immune evasion, response to immunotherapy, and patient management. However, the transcriptome-wide detection, validation, and functional characterization of 3'UTR somatic events and their effects on the tumor immune landscape are still pressing -yet unmet- needs. In this project we will deploy an in silico/experimental framework that combines massively parallel variant validation, spatial transcriptomics, and bioinformatic detection/functionalization technologies to characterize Pan-Cancer and transcriptome-wide 3'UTR somatic mutation/truncation events, as well as to assess their potential as immunoediting mechanisms, markers for patient stratification, and novel therapeutic targets. Aim 1: By efficiently integrating raw multi-omic datasets, we will identify somatic 3'UTR mutations and truncations in more than 10,000 cancer patients across 33 cancer types. We will prioritize all 3'UTR variants affecting gene expression in cis, delineating the 3'UTR-mediated regulatory landscape across cancer types. Aim 2: We will identify mutations and disrupted circuitry affecting cancer immunophenotypes and the tumor microenvironment. We will utilize extensive post-transcriptional data/experimental resources to uncover the regulators (miRNAs, RBPs) and mechanisms involved in such immunoediting events. Aim 3a: We will validate up to 20,000 somatic 3'UTR events using a massively parallel sequencing technology. Prioritized interactions will be investigated in vitro as well as using a biomimetic 3D device to characterize their effects on gene regulation and T-Cell killing, while patient samples will be investigated using spatial transcriptomics. Aim 3b) We will assess the translational potential of the leading 3'UTR events and genes as predictors of immunotherapy response using Deep Learning models, against an extensive cohort of >300 cancer patients treated with immune checkpoint inhibition. We are uniquely suited to perform this in-depth characterization, since our research team comprises leading post transcriptional regulation and immune-oncology researchers, while the relevant resources (in silico, experimental, samples) are already in place. We will perform the first Pan-Cancer and transcriptome-wide investigation of tumor immune evasion by 3'UTR somatic mutations and truncations. We will use an innovative in silico-experimental framework to identify 3'UTR events, miRNAs, and RBPs that can be used as markers for efficient patient stratification as well as novel immunotherapeutic targets.

总结