Molecular, Metabolic, and Subcellular Mapping of the Tumor Immune Microenvironment via 3D Targeted and Non-Targeted Multiplex Multi-Omics Analyses

Author:

Ferri-Borgogno Sammy1ORCID,Burks Jared K.2ORCID,Seeley Erin H.3ORCID,McKee Trevor D.4ORCID,Stolley Danielle L.2,Basi Akshay V.2ORCID,Gomez Javier A.2ORCID,Gamal Basant T.1,Ayyadhury Shamini4ORCID,Lawson Barrett C.5,Yates Melinda S.6,Birrer Michael J.7,Lu Karen H.1,Mok Samuel C.1ORCID

Affiliation:

1. Department of Gynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA

2. Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA

3. Department of Chemistry, The University of Texas at Austin, Austin, TX 78712, USA

4. Pathomics, Inc., Toronto, ON M4C 3K2, Canada

5. Department of Anatomical Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA

6. Department of Pathology and Laboratory Medicine, The University of North Carolina, Chapel Hill, NC 27599, USA

7. Winthrop P. Rockefelle Cancer Institute, The University of Arkanasas for Medical Sciences, Little Rock, AR 72205, USA

Abstract

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.

Funder

Ovarian Cancer Research Alliance

Sie Foundation

Stephanie C. Stelter Endowment Fund

Cancer Prevention and Research Institute of Texas award

National Institutes of Health

NCI’s Research Specialist

Publisher

MDPI AG

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Spatial multiplexing and omics;Nature Reviews Methods Primers;2024-08-01

2. Spatial transcriptomics: a new frontier in cancer research;Clinical Cancer Bulletin;2024-06-04

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