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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：
10364784
负责人：
Ioannis Vlachos
金额：
$ 61.85万
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/10364784
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 Genetic Transcription 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 Mutate Mutation Natural Immunity Neoplasm Metastasis Oncogenes Oncogenic Outcome Pathology Pathway interactions Patients Phenotype 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 multiple omics neoplastic neoplastic cell new therapeutic target novel novel therapeutics patient stratification 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.

总结肿瘤疾病的所有阶段，从其发展到转移，都与癌症免疫相关。逃避参与肿瘤免疫景观调节的表观遗传机制强烈地作为生物标志物或治疗靶点进行研究。3'非翻译区（3' UTR）决定了后翻译区的功能。转录mRNA的命运，并且经常被调节分子如microRNA（miRNAs）和 RNA结合蛋白（RBP）。肿瘤细胞已经被证明通过突变或突变来逃避这种严格的调节。截断这些区域。第一个这样确定的事件揭示了体细胞调节机制，可能会影响肿瘤免疫逃避，对免疫治疗的反应和患者管理。然而，在这方面， 3 'UTR体细胞事件的转录组范围的检测、验证和功能表征及其对肿瘤免疫状况的影响仍然是迫切的-但尚未满足的-需求。在这个项目中，我们将部署一个在硅片/实验框架，结合大规模并行变量验证、空间转录组学和生物信息学检测/功能化技术来表征泛癌症和转录组范围的3 'UTR体细胞突变/截短事件，以及评估它们的生物学效应。作为免疫编辑机制、患者分层的标志物和新的治疗靶点的潜力。目的1：通过有效整合原始多组学数据集，我们将鉴定体细胞3 'UTR突变和截短在超过10，000名癌症患者的33种癌症类型中。我们将优先考虑所有影响基因的3 'UTR变体，以顺式表达，描绘了跨癌症类型的3 'UTR介导的调控景观。目标2：我们识别影响癌症免疫表型和肿瘤微环境的突变和破坏的电路。我们将利用广泛的转录后数据/实验资源来揭示调控因子（miRNAs， RBP）和参与此类免疫编辑事件的机制。目标3a：我们将验证多达20，000个体细胞使用大规模平行测序技术检测3 'UTR事件。优先考虑的相互作用将在体外以及使用仿生3D设备来表征它们对基因调控和T细胞杀伤的影响，同时使用空间转录组学研究患者样品。目标3b）我们将评估翻译使用深度学习，领先的3 'UTR事件和基因作为免疫治疗反应预测因子的潜力模型，针对用免疫检查点抑制治疗的>300名癌症患者的广泛队列。我们非常适合进行这种深入的表征，因为我们的研究团队由领先的转录后调节和免疫肿瘤学研究人员，而相关的资源（在计算机上，实验，样品）已经到位。我们将进行第一次泛癌症和转录组范围内的通过3 'UTR体细胞突变和截短研究肿瘤免疫逃避。我们将采用创新的在计算机模拟实验框架中鉴定可用作以下标记物的3 'UTR事件、miRNA和RBP：有效的患者分层以及新的免疫靶点。