Immune Exclusion in Cancer Immunotherapy

癌症免疫治疗中的免疫排除

基本信息

批准号：
10693317
负责人：
Riyue Bao
金额：
$ 60.49万
依托单位：
UNIVERSITY OF PITTSBURGH AT PITTSBURGH
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：
2022-09-01 至 2027-07-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10693317
关键词：
Advanced Malignant Neoplasm Automobile Driving Bioinformatics Biological Biological Markers Biopsy CD8-Positive T-Lymphocytes Carcinogens Cell Communication Cell Differentiation process Cell Line Cell Proliferation Cells Clinical Trials Computational Biology Data Data Set Databases Dendritic Cells Dimensions Drug Combinations Evaluation Exclusion FDA approved Foundations Future Gene Expression Genes Genomics Goals HPV-negative head and neck cancer Head and Neck Cancer Head and Neck Squamous Cell Carcinoma Heterogeneity Human Human Papillomavirus Human papilloma virus infection Image Image Analysis Immune Immune checkpoint inhibitor Immunooncology Immunotherapy In Vitro Interferons Investigation Link Lymphocyte MAP Kinase Gene Machine Learning Macrophage Mass Spectrum Analysis Measures Mediating Modality Modeling Molecular Molecular Target Mus Mutation Nivolumab Oncogenic Organoids Pathway interactions Patients Pharmaceutical Preparations Phenotype Phosphotransferases Production Property Proteomics Public Domains Rationalization Research Resistance Resolution Role Safety Signal Transduction Solid Neoplasm Spatial Distribution Specimen T cell infiltration T-Lymphocyte T-cell inflamed Testing Translational Research Tumor-infiltrating immune cells VEGFA gene Variant Vascular Endothelial Growth Factors Vegf inhibition adjudication anti-PD-1 anti-PD1 therapy beta catenin biomarker development cancer immunotherapy checkpoint inhibition chemokine clinical translation cohort combinatorial deep learning drug repurposing drug sensitivity experimental study genomic data high dimensionality immune resistance immunosuppressive macrophages improved improved outcome in vivo inhibitor liquid crystal polymer mathematical model monocyte mouse model multidimensional data multiple omics multiplexed imaging neoplastic cell new therapeutic target novel novel therapeutic intervention p38 Mitogen Activated Protein Kinase patient population programmed cell death ligand 1 protein protein interaction public database resistance mechanism response synergism targeted treatment therapy resistant transcriptome sequencing treatment response tumor tumor microenvironment validation studies

项目摘要

ABSTRACT Most patients with solid tumors do not benefit from immune-checkpoint inhibition, emphasizing the need to improve immunotherapy. We have demonstrated that the T cell-inflamed tumor microenvironment (TME), characterized by CD8+ T cells and type I/II interferon (IFN) gene expression, is an important cancer immunotherapy biomarker. Tumor mutational burden may also dictate response with some oncogenic pathways, such as WNT/β-catenin, known to mediate immune-exclusion and drive the non-T cell-inflamed TME. Our research group has nominated a core group of molecular targets associated with immune-exclusion centered at p38 MAPK. p38 is known to regulate macrophages and dendritic cells. However, our data are the first to describe a tumor cell-intrinsic role for p38 driving the non-T cell-inflamed TME. In this project, we will investigate tumor cell p38 signaling as a new mechanism of resistance to immunotherapy in carcinogen- associated head and neck squamous cell carcinoma (HNSCC), lacking infection by human papillomavirus (HPV). Our research aims are to (1) Establish a causal link between p38, non-T cell-inflamed tumors, and resistance to ICI in HPV- HNSCC (2) Determine the impact of tumor cell p38 MAPK spatial distribution on T cell infiltration in HPV− HNSCC (3) Validate and uncover co-activated mechanisms with p38 MAPK in HPV− HNSCC. We will leverage our lab’s unique role at the center of large-scale, multi-omic approaches as well as field-leading clinical trial and translational investigation. We will utilize 11 independent cohorts of patients with HPV- HNSCC. From the public domain, we will include RNAseq and image analysis from three cohorts, scRNAseq from one cohort, as well as cell line, drug sensitivity and FDA-approved drug databases. These analyses will be augmented for RNAseq, scRNAseq, and multispectral spatial imaging data from seven other cohorts organized by our team. These will include immunotherapy naïve patients and patients treated on a clinical trial we are leading of the p38 inhibitor ARRY-614 + nivolumab. We will utilize a combination of the computational, machine- and deep-learning analyses plus mechanistic murine experiements in four syngeneic models as well as in vitro validation studies to pursue our research. Our systemic approach has already nominated further molecular targets for combination approaches with p38 and immunotherapy. We will validate these and nominate further molecular targets to enhance cancer immunotherapy.

抽象的大多数实体瘤患者无法从免疫检查点抑制中受益，强调需要我们已经证明，T 细胞发炎的肿瘤微环境 (TME)，以 CD8+ T 细胞和 I/II 型干扰素 (IFN) 基因表达为特征，是一种重要的癌症免疫治疗生物标志物也可能决定某些致癌物质的反应。已知可介导免疫排斥并驱动非 T 细胞发炎的途径，例如 WNT/β-连环蛋白 TME。我们的研究小组提名了一组与免疫排斥相关的核心分子靶点。已知 p38 以 p38 MAPK 为中心调节巨噬细胞和树突状细胞。首先描述 p38 驱动非 T 细胞炎症 TME 的肿瘤细胞内在作用。研究肿瘤细胞 p38 信号传导作为致癌物免疫治疗耐药的新机制相关头颈鳞状细胞癌 (HNSCC)，缺乏人乳头瘤病毒感染 (HPV)。我们的研究目标是 (1) 建立 p38、非 T 细胞炎症肿瘤和 HPV-HNSCC对ICI的抵抗（2）确定肿瘤细胞p38 MAPK空间分布对T细胞的影响 HPV− HNSCC 中的浸润 (3) 验证并揭示 HPV− 中与 p38 MAPK 的共激活机制我们将利用我们实验室在大规模、多组学方法和研究中心的独特作用。我们将利用 11 个独立的患者队列进行现场领先的临床试验和转化研究。从公共领域来看，我们将包括来自三个队列的 RNAseq 和图像分析，来自一组的 scRNAseq，以及细胞系、药物敏感性和 FDA 批准的药物数据库。将增强对来自其他七个的 RNAseq、scRNAseq 和多光谱空间成像数据的分析我们团队组织的队列将包括未接受过免疫治疗的患者和接受过免疫治疗的患者。我们正在领导 p38 抑制剂 ARRY-614 + nivolumab 的临床试验，我们将使用以下药物的组合。计算、机器和深度学习分析以及四个同系小鼠的机械实验模型以及体外验证研究来进行我们的研究。我们将验证 p38 和免疫疗法的组合方法的进一步分子靶点。这些并指定进一步的分子靶点来增强癌症免疫治疗。