微陣列空間轉錄組與單細胞測序揭示胰腺癌結構
作者：
小柯機器人發布時間：2020/1/16 10:36:33
美國紐約大學Itai Yanai團隊利用基於微陣列的空間轉錄組學和單細胞RNA測序（scRNA-seq）揭示了胰腺導管腺癌的組織結構。2020年1月13日，《自然—生物技術》雜誌在線發表了這項成果。
研究人員結合了基於微陣列的空間轉錄組學方法，該方法使用一系列斑點揭示了基因表達的空間模式，每個斑點都捕獲了多個相鄰細胞的轉錄組，並從同一樣品中生成了scRNA-Seq。為了注釋不同組織區域的精確細胞組成，研究人員報導了一種用於多峰相交分析的方法。將多模式相交分析應用於原發性胰腺腫瘤，研究人員發現導管細胞、巨噬細胞、樹突狀細胞和癌細胞的亞群具有空間受限的富集，以及與其他細胞類型的獨特共富集。此外，研究人員確定表達壓力反應基因模塊的炎症成纖維細胞和癌細胞的共定位。這一用於繪製scRNA-seq定義的亞群結構的方法可用於揭示複雜組織固有的相互作用。
據了解，scRNA-seq可以系統地識別組織中的細胞群，但是表徵其空間組織仍然具有挑戰性。
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