Defining and targeting the lung cancer progenitor cell niche using a high-resolution, multi-omics approach

使用高分辨率、多组学方法定义和靶向肺癌祖细胞生态位

基本信息

批准号：
10678892
负责人：
Daniel Charytonowicz
金额：
$ 5.27万
依托单位：
ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-09-07 至 2025-09-06
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10678892
关键词：
ALCAM gene Address Aftercare Apoptotic Automobile Driving Bar Codes Biological Assay Biopsy CD44 gene Cancer Etiology Cancer Patient Cell Fraction Cell Line Cell Separation Cells Clinical Coculture Techniques Critical Pathways Cryoultramicrotomy Custom Cytotoxic Chemotherapy DNA Repair Data Disease Progression Down-Regulation Drug Efflux Drug resistance Elements Endowment Equilibrium Excision Exhibits Exposure to Fibroblasts Gene Expression Gene Expression Profile Gene Expression Profiling Generations Genetic Genetic Transcription Genomics Goals Growth Heterogeneity Human Immune signaling In Vitro Ionizing radiation Lentivirus Vector Lung Lung Neoplasms Malignant Neoplasms Malignant neoplasm of lung Mediating Modeling Molecular Neoplasm Metastasis Non-Small-Cell Lung Carcinoma Outcome Pathway interactions Patients Pharmaceutical Preparations Phenotype Play Population Population Growth Prognostic Marker Proliferating Property Protocols documentation RNA Regulation Regulator Genes Research Resistance Resolution Role Sampling Selection for Treatments Serial Passage Signal Pathway Signal Transduction Sorting Specificity Stimulus Stromal Cells Surface Therapeutic Time Time Series Analysis Tissue-Specific Gene Expression Transfection Translating Tumor Tissue United States Up-Regulation Validation Variant Woman cancer cell cancer drug resistance cancer stem cell cancer therapy computerized tools drug sensitivity experience high dimensionality improved in vivo informatics tool insight lung cancer cell matrigel men mortality multimodality multiple omics neoplastic cell new therapeutic target next generation sequencing novel pressure progenitor receptor response self-renewal single-cell RNA sequencing stem cells targeted biomarker targeted treatment therapy resistant transcriptome sequencing transcriptomics tumor tumor growth tumor heterogeneity tumor initiation tumor microenvironment tumor progression tumorigenesis

项目摘要

Project Summary Despite advances in treatment options, 5-year overall survival (OS) for non-small cell lung cancer (NSCLC) patients remains around 20% [1]. Subpopulations of tumor initiating cells (TICs) representing <1.5% of the overall tumor population exhibit the capacity for self-renewal, drug-resistance, and are believed to drive disease progression [2]. Although surface markers including CD133, CD44, CD166, and EPCAM have been proposed to isolate lung TICs, results are inconsistent. Micro-heterogeneity within the tumor microenvironment (TME) is believed to regulate balance between progenitor-like and differentiated tumor cell phenotypes, and consequently supports heterogeneous drug responses. This proposed research attempts to definitively characterize expression profiles of TICs, and study the relationship between the tumor micro-environment and TIC dynamics in the context of drug response, with the goal of identifying critical pathways that mediate transitions to a progenitor-like state. Aim 1 - Lineage tracing studies suggest that TICs exhibit clonal dominance in culture, whereby a small fraction of tumor cells tend to drive outgrowth of the overall population. Having already established a protocol using cell line models, I will transfect patient-derived NSCLC cells with RNA-expressed barcodes and analyze growing populations using serial passaging assays under normal and drug-treated conditions. Using transcriptional analysis of time-series single-cell RNA Sequencing (scRNA-Seq) data in combination with custom computational tools, I aim to identify gene expression profiles and surface markers unique to progenitor-like subclones that drive population growth under treatment selection pressure. Aim 2 - TICs are dependent on niche signalling from a heterogeneous tumor microenvironment (TME) to support the progenitor phenotype. We hypothesize that micro-heterogeneity within the TME regulates the ratio of progenitor-to-differentiated tumor cells and influences drug sensitivity. I will first develop an in-vitro spheroid culture platform combining clonally barcoded patient-derived tumor and stromal cells exposed to cytotoxic therapy, processing them with the 10X Genomics Spatial Transcriptomics platform. This data will enable assessment of essential TME crosstalk signalling and its impact on spatial cancer projenitor-like transcriptional signatures defined from Aim 1. We will confirm these insights by integrating scRNA-Seq and Spatial Transcriptomics data from naive and post-treatment patient-derived lung samples used for Aim 1 to characterize patient-specific TIC niches. Through the robust profiling of the TIC transcriptional profile and its associated microenvironment using multimodal sequencing approaches, we hope to potentially identify new targets or prognostic biomarkers to aid in the treatment of NSCLC.

项目摘要尽管治疗方案取得了进步，但非小细胞肺癌的5年总生存期（OS）（NSCLC）患者仍保持约20％[1]。肿瘤引发细胞的亚群（TICS）代表<1.5％的整体肿瘤种群表现出自我更新的能力，抗药性，被认为会促进疾病进展[2]。虽然表面标记已经提出了包括CD133，CD44，CD166和EPCAM来隔离肺部，结果是不一致。据信肿瘤微环境（TME）内的微观异质性调节祖细胞状和分化的肿瘤细胞表型之间的平衡，因此支持异质药物反应。这项拟议的研究试图确定表征抽动的表达曲线，并研究关系在药物反应的背景下，肿瘤微环境和抽动动力学之间目的是确定介导向某人过渡的关键途径祖细胞状状态。目标1-谱系跟踪研究表明，抽动表现出克隆培养中的主导地位，因此，一小部分肿瘤细胞倾向于驱动生长总体人口。已经建立了使用单元线模型的协议，我将转染具有RNA表达条形码的患者来源的NSCLC细胞并分析了增长的种群在正常和药物处理的条件下使用串行传递测定。使用时间序列单细胞RNA测序（SCRNA-SEQ）数据的转录分析结合自定义计算工具，我旨在识别基因表达概况和表面标记物是祖细胞样子克隆的特有的，这些亚克隆在治疗选择压力。 AIM 2 -TIC取决于来自异质的利基信号传导肿瘤微环境（TME）支持祖细胞表型。我们假设这一点 TME内的微生物性调节祖细胞与分化的肿瘤细胞的比率并影响药物敏感性。我将首先发展一个体外球体培养物平台结合了克隆条形码的患者衍生肿瘤和暴露于细胞毒性的基质细胞治疗，使用10倍基因组学空间转录组学平台处理它们。这个数据将能够评估必需的TME串扰信号及其对空间癌的影响 AIM 1定义的类似于Projenitor的转录签名。我们将确认这些见解通过整合来自幼稚和治疗后患者来源的肺样本用于AIM 1以表征特定于患者的TIC小众。通过TIC转录的强大分析配置文件及其相关的微环境采用多模式测序方法，我们希望有可能识别新的靶标或预后生物标志物，以帮助治疗NSCLC。