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Mapping the Emergent Spatial Organization of Mammalian Cells using Micropatterns and Quantitative Imaging

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Published on: April 30, 2019

Spatial omics in 3D culture model systems: decoding cellular positioning mechanisms and microenvironmental dynamics.

Liwei Du¹, Huayu Yang²

¹Department of Liver Surgery, Peking Union Medical College (PUMC) Hospital, Peking Union Medical College (PUMC), Chinese Academy of Medical Sciences (CAMS), Beijing, 100730, China.

Journal of Translational Medicine

|November 27, 2025

Summary

Spatial omics integrated with 3D models provides detailed molecular maps of tissue architecture. This synergy enhances understanding of disease and accelerates personalized treatment discovery.

Keywords:

3D model Cellular interaction Spatial omics Spatial positioning Tumor microenvironment

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Area of Science:

Biotechnology
Genomics
Systems Biology

Background:

Three-dimensional (3D) culture models like organoids and tumor spheroids mimic in vivo tissue architecture.
Spatial omics technologies (transcriptomics, proteomics, metabolomics, epigenomics) spatially encode molecular data within this context.
These integrated approaches reveal cellular interactions and responses to microenvironmental cues.

Purpose of the Study:

To review the integration of spatial omics technologies with 3D culture models.
To highlight the creation of comprehensive molecular maps preserving native microenvironmental context.
To discuss the potential for more predictive in vitro systems and personalized medicine.

Main Methods:

Integration of high-resolution spatial-omics platforms with 3D models (organoids, spheroids, bioprinted tissues, organ-on-chip devices).
Multiplexed, longitudinal analyses under physiological conditions (flow, mechanical stimulation).
Advancements in imaging resolution, probe multiplexing, and computational data-fusion.

Main Results:

Spatial profiling of tumor spheroids revealed gene-expression gradients and metabolic heterogeneity.
These findings illuminate mechanisms of therapeutic resistance and immune evasion within the tumor microenvironment (TME).
Demonstrated unprecedented maps of gene, protein, metabolite, and chromatin landscapes.

Conclusions:

The seamless integration of spatial omics and 3D models offers powerful tools for biological research.
This synergy accelerates the discovery of clinically actionable biomarkers and personalized treatment strategies.
Future improvements promise deeper insights into tissue patterning, disease progression, and therapeutic interventions.