多路复用
质量细胞仪
计算生物学
蛋白质组学
肿瘤微环境
背景(考古学)
质谱成像
马尔迪成像
分子成像
蛋白质组
生物
计算机科学
生物信息学
癌症研究
化学
肿瘤细胞
质谱法
表型
基因
古生物学
生物化学
生物技术
有机化学
色谱法
解吸
吸附
体内
基质辅助激光解吸/电离
作者
Sammy Ferri‐Borgogno,Jared K. Burks,Erin H. Seeley,Trevor D. McKee,Danielle L. Stolley,Akshay Basi,Javier A. Gomez,Basant T. Gamal,Shamini Ayyadhury,Barrett Lawson,Melinda S. Yates,Michael J. Birrer,Karen H. Lu,Samuel C. Mok
出处
期刊:Cancers
[MDPI AG]
日期:2024-02-20
卷期号:16 (5): 846-846
被引量:1
标识
DOI:10.3390/cancers16050846
摘要
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.
科研通智能强力驱动
Strongly Powered by AbleSci AI