Most platforms used for the molecular reconstruction of the tumor–immune microenvironment (TIME) of a solid tumor fail to explore the spatial context of the three-dimensional (3D) space of the tumor at a single-cell resolution, and thus lack information about cell–cell or cell–extracellular matrix (ECM) interactions. To address this issue, a pipeline which integrated multiplex spatially resolved multi-omics platforms was developed to identify crosstalk signaling networks among various cell types and the ECM in the 3D TIME of two FFPE (formalin-fixed paraffin embedded) gynecologic tumor samples. These platforms include non-targeted mass spectrometry imaging (glycans, metabolites, and peptides) and Stereo-seq (spatial transcriptomics) and targeted seqIF (IHC proteomics). The spatially resolved imaging data in a two- and three-dimensional space demonstrated various cellular neighborhoods in both samples. The collection of spatially resolved analytes in a voxel (3D pixel) across serial sections of the tissue was also demonstrated. Data collected from this analytical pipeline were used to construct spatial 3D maps with single-cell resolution, which revealed cell identity, activation, and energized status. These maps will provide not only insights into the molecular basis of spatial cell heterogeneity in the TIME, but also novel predictive biomarkers and therapeutic targets, which can improve patient survival rates.
目前用于实体瘤肿瘤-免疫微环境（TIME）分子重建的大多数平台，难以在单细胞分辨率下探索肿瘤三维（3D）空间的空间背景，因而缺乏关于细胞-细胞或细胞-细胞外基质（ECM）相互作用的信息。为解决这一问题，本研究开发了一种整合多重空间分辨多组学平台的分析流程，用于识别两个福尔马林固定石蜡包埋（FFPE）妇科肿瘤样本三维TIME中不同细胞类型与ECM之间的信号交互网络。这些平台包括非靶向质谱成像（聚糖、代谢物和肽段）、Stereo-seq（空间转录组学）以及靶向seqIF（免疫组化蛋白质组学）。二维与三维空间中的空间分辨成像数据揭示了两个样本中存在的多种细胞邻域结构，并展示了跨组织连续切片在三维体素（3D像素）中采集空间分辨分析物的方法。通过该分析流程收集的数据构建了具有单细胞分辨率的空间三维图谱，这些图谱能够揭示细胞身份、活化状态及能量代谢状态。此类图谱不仅有助于深入理解TIME中空间细胞异质性的分子基础，还能为开发新型预测性生物标志物和治疗靶点提供依据，从而有望提高患者的生存率。
肿瘤(癌症)患者之家