Elucidating mechanisms of cellular communication critical for head and neck cancer progression and metastasis.

阐明对头颈癌进展和转移至关重要的细胞通讯机制。

• 批准号: 10752228
• 负责人: Lina Kroehling
• 金额: $ 4.21万
• 依托单位: BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-11-01 至 2026-10-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10752228
• 关键词: Affect; Algorithms; Architecture; Atlases; Automobile Driving; B-Lymphocytes; Catalogs; Cell Communication; Cell Count; Cells; Clinical; Communication; Communication Methods; Communication Tools; Computing Methodologies; DNA Sequence Alteration; Data; Data Set; Death Rate; Development; Disease; Drug Targeting; Epithelium; Event; Fibroblasts; Gene Expression; Genes; Genetic Variation; Genotype; Head and Neck Cancer; Head and Neck Squamous Cell Carcinoma; Heterogeneity; Human; Human Papillomavirus; Immunohistochemistry; Incidence; Langerhans cell; Ligands; Link; Malignant Neoplasms; Molecular; Morbidity - disease rate; Neoplasm Metastasis; Outcome; Pathogenesis; Pathway interactions; Patients; Phenotype; Play; Plug-in; Population; Publishing; Resistance; Resolution; Role; Sampling; Signal Transduction; Specificity; Squamous cell carcinoma; Survival Rate; Tissues; Tumor Subtype; Tumor Tissue; Tumor stage; Validation; cancer initiation; carcinogenesis; cell population study; cell type; data resource; experimental study; human RNA sequencing; human tissue; immune cell infiltrate; in silico; innovation; insight; intercellular communication; knock-down; monocyte; mouse model; mouth squamous cell carcinoma; multiple datasets; neoplastic cell; neutrophil; overexpression; programs; receptor; repository; single cell analysis; single-cell RNA sequencing; stem; stem-like cell; targeted treatment; therapy design; therapy resistant; tool; transcriptomics; tumor; tumor growth; tumor heterogeneity; tumor microenvironment; tumor progression

PROJECT SUMMARY Head and neck squamous cell carcinoma (HNSCC) is a devastating disease associated with high morbidity, poor survival rates, and limited treatment options with the majority of cases presenting as oral squamous cell carcinoma (OSCC). Fatality due to this disease is most often caused by metastasis and resistance to treatment. To develop targeted therapies, a better mechanistic understanding of molecular signaling and their contribution to intra-tumor phenotypes is needed. Growing evidence has indicated that cell plasticity, including the loss of the epithelial state and the acquisition of a partial EMT (p-EMT) phenotype, as well as acquisition of stem-like features, contribute to cancer initiation and progression to aggressive disease. The degree of immune infiltration has been linked to EMT, supporting the idea that inter-cellular interaction events within the tumor microenvironment (TME) can affect tumor growth. While many studies focus on the interaction between cancer associated fibroblasts (CAFs) and CSCs, there are many other populations that have been shown to influence clinical outcome in these tumors, which we have also identified in our studies using mouse models of HNSCC, such as neutrophils, B cells, and Langerhans cells. However, the mechanisms through which these populations influence tumor progression is largely unknown. Studying how cell populations and cellular signaling interactions change across tumor phenotypes is essential for a deep mechanistic understanding of the disease and identification of targets for potential therapies, which our proposal seeks to do in 3 aims. In Aim 1 we will build a comprehensive human HNSCC single cell RNA-seq (scRNAseq) atlas which will provide unprecedented resolution to predict associations between phenotypes, genotypes, and cellular heterogeneity. We will leverage this atlas to catalogue all cell populations, identify rare cell types and tumor subtypes, quantify how these populations change across tumor stage, and produce a list of predicted interactions occurring in the TME. Through Aim 2 we will construct a pre-processing tool to be used prior to cell-cell communication algorithms to both increase accuracy and specificity of interaction predictions which we will apply to the HNSCC atlas created in Aim 1. Aim 3 will validate our in-silico interaction predictions using both targeted and nontargeted approaches. First, we will utilize mouse models to perform knockdown and overexpression experiments on our top three ligand-receptor pairs to demonstrate their role in tumor progression. Secondly, we will use RNAscope, immunohistochemistry and spatial transcriptomics with human HNSCC tumor tissues sections to elucidate the proximity of predicted interacting cell populations within the tissue architecture. Overall, our project aims to define cellular interaction events that drive tumor cell plasticity, progression and metastasis in tumors. We postulate critical interactions can provide potential targets for drugs to inhibit HNSCC progression.

项目摘要 头颈部鳞状细胞癌（HNSCC）是一种高发病率的毁灭性疾病， 生存率低，治疗选择有限，大多数病例表现为口腔鳞状细胞癌 癌（OSCC）。由于这种疾病的死亡率最常见的是由转移和耐药性引起的。 治疗为了开发靶向治疗，需要更好地理解分子信号传导及其 需要对肿瘤内表型的贡献。越来越多的证据表明，细胞的可塑性，包括 上皮状态的丧失和部分EMT（p-EMT）表型的获得，以及 干细胞样特征，有助于癌症的发生和进展为侵袭性疾病。程度 免疫浸润与EMT有关，支持了细胞内的细胞间相互作用事件的观点。 肿瘤微环境（TME）可以影响肿瘤生长。虽然许多研究关注的是 癌症相关成纤维细胞（CAF）和CSC，还有许多其他人群已被证明， 影响这些肿瘤的临床结果，我们也在使用小鼠模型的研究中发现了这些肿瘤。 HNSCC，如嗜中性粒细胞、B细胞和朗格汉斯细胞。然而，这些机制 人群对肿瘤进展的影响在很大程度上是未知的。研究细胞群和细胞 跨肿瘤表型的信号相互作用变化对于深入理解肿瘤的发生机制至关重要。 疾病和识别潜在治疗的目标，我们的建议旨在实现3个目标。在 目的1我们将建立一个全面的人类HNSCC单细胞RNA-seq（scRNAseq）图谱， 前所未有的分辨率来预测表型、基因型和细胞异质性之间的关联。 我们将利用该图谱对所有细胞群进行分类，识别罕见细胞类型和肿瘤亚型， 这些群体如何在肿瘤阶段发生变化，并产生一系列预测的相互作用， TME。通过目标2，我们将构建一个在细胞间通信之前使用的预处理工具 算法，以提高相互作用预测的准确性和特异性，我们将应用于 在Aim 1中创建的HNSCC图谱。Aim 3将验证我们的计算机交互预测， 非目标方法。首先，我们将利用小鼠模型进行敲除和过表达 在我们的前三个配体-受体对上进行实验，以证明它们在肿瘤进展中的作用。第二、 我们将使用RNAscope、免疫组织化学和空间转录组学对人HNSCC肿瘤组织进行研究， 切片以阐明组织结构内预测的相互作用细胞群的接近度。 总的来说，我们的项目旨在定义驱动肿瘤细胞可塑性，进展和增殖的细胞相互作用事件。 肿瘤转移。我们假设关键的相互作用可以为药物提供潜在的靶点， HNSCC进展。