转移性神经内分泌肿瘤（NETs）的治疗是目前的瓶颈，主要原因是基因组缺少可以作用（actionable）的基因改变，临床前模型缺乏，且药物敏感性评估主要针对肿瘤细胞增殖能力，而忽视激素分泌能力评估。课题组前期积累21种NETs的体细胞突变类型的“泛癌症图谱”，7类NETs的单细胞RNA测序数据，10类NETs原代细胞分选培养模型，完成2000余种化合物高通量筛选，并发现激素分泌与细胞/亚细胞结构具有良好的相关关系。本项目拟在前期工作的基础上，以不同组织来源的NET细胞株、原代细胞（2D培养及3D培养-微肿瘤模型）及体内模型为研究对象，利用高通量、高内涵筛选、细胞成像创建NET敏感性药物筛选可视化评估、量化分析平台，联合组织与单细胞多组学数据，在单细胞水平解析NET肿瘤及其微环境的分子特征与交互作用，最终通过整合分子特征与可视化的细胞药物反应寻找敏感性药物，建立新型NET个体化精准治疗方案。

Treatment of metastatic neuroendocrine tumors (NETs) remains one of the biggest challenges for oncologists. The main problems involve the lack of actionable target and preclinical models, as well as the inaccuracy of current evaluation system for drug screening which mainly focuses on cell viability, ignoring another critical issue of NETs——hormone production. Previously, our team has accomplished pan-cancer analysis of somatic mutations across 21 neuroendocrine tumor types, sc-RNAseq of seven types of NETs, established the culture protocols of 10 types of primary NET cells and high-throughput screening of over 2000 chemicals. We also found hormone production is well related to cellular/subcellular morphology. In this project, by using models of cell lines, primary cells（2D culture and 3D models mimic tumor microenvironmet）and in vivo models, we aimed to establish a visualization and quantitative-analysis platform of high-throughput drug screening for NETs based on microscopy-based high-content screening system and cell imaging. Also, bulk and single-cell multi-omics researches will be conducted to finely unravel the molecular profiling of NETs and its microenvironment as well as its constituent cellular interactions at a single-cell resolution. Ultimately, efficient and effective drug screening will be achieved via the comprehensive molecular profiling integrated with visualization of cellular response upon drug treatment and, in turn, make its contribution to the precision therapy for NETs.