美团队利用微阵列空间转录组与单细胞测序揭示胰腺癌结构
美国纽约大学Itai Yanai团队利用基于微阵列的空间转录组学和单细胞RNA测序（scRNA-seq）揭示了胰腺导管腺癌的组织结构。2020年1月13日，《自然—生物技术》杂志在线发表了这项成果。
研究人员结合了基于微阵列的空间转录组学方法，该方法使用一系列斑点揭示了基因表达的空间模式，每个斑点都捕获了多个相邻细胞的转录组，并从同一样品中生成了scRNA-Seq。为了注释不同组织区域的精准细胞组成，研究人员报道了一种用于多峰相交分析的方法。将多模式相交分析应用于原发性胰腺肿瘤，研究人员发现导管细胞、巨噬细胞、树突状细胞和癌细胞的亚群具有空间受限的富集，以及与其他细胞类型的独特共富集。此外，研究人员确定表达压力反应基因模块的炎症成纤维细胞和癌细胞的共定位。这一用于绘制scRNA-seq定义的亚群结构的方法可用于揭示复杂组织固有的相互作用。
据了解，scRNA-seq可以系统地识别组织中的细胞群，但是表征其空间组织仍然具有挑战性。
附：英文原文
Title: Integrating microarray-based spatial transcriptomics and single-cell RNA-seq reveals tissue architecture in pancreatic ductal adenocarcinomas
Author: Reuben Moncada, Dalia Barkley, Florian Wagner, Marta Chiodin, Joseph C. Devlin, Maayan Baron, Cristina H. Hajdu, Diane M. Simeone, Itai Yanai
Issue&Volume: 2020-01-13
Abstract: Single-cell RNA sequencing (scRNA-seq) enables the systematic identification of cell populations in a tissue, but characterizing their spatial organization remains challenging. We combine a microarray-based spatial transcriptomics method that reveals spatial patterns of gene expression using an array of spots, each capturing the transcriptomes of multiple adjacent cells, with scRNA-Seq generated from the same sample. To annotate the precise cellular composition of distinct tissue regions, we introduce a method for multimodal intersection analysis. Applying multimodal intersection analysis to primary pancreatic tumors, we find that subpopulations of ductal cells, macrophages, dendritic cells and cancer cells have spatially restricted enrichments, as well as distinct coenrichments with other cell types. Furthermore, we identify colocalization of inflammatory fibroblasts and cancer cells expressing a stress-response gene module. Our approach for mapping the architecture of scRNA-seq-defined subpopulations can be applied to reveal the interactions inherent to complex tissues.
DOI: 10.1038/s41587-019-0392-8
Source: https://www.nature.com/articles/s41587-019-0392-8
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