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

Recent advances in spatial omics have revolutionized our ability to decode cell-positioning dynamics within three-dimensional (3D) culture models, such as organoids, tumor spheroids, and 3D bioprinting constructs, which faithfully mimic in vivo tissue architecture. By "spatially encoding" high-dimensional molecular information while preserving native microenvironmental context, spatial transcriptomics, proteomics, metabolomics, and epigenomics provide unprecedented maps of gene, protein, metabolite, and chromatin landscapes. When integrated with 3D culture systems, these approaches enable real-time visualization of how cells interact, self-organize, and respond to local biochemical and biophysical cues. Notably, spatial profiling of tumor spheroids has revealed discrete gene-expression gradients and region-specific metabolic heterogeneity, illuminating mechanisms by which the tumor microenvironment (TME) drives therapeutic resistance and immune evasion. Despite these insights, systematic integration of complex multimodal datasets and their translation into clinically actionable biomarkers remain formidable challenges. Emerging high-resolution spatial-omics platforms, which paired with precision-engineered 3D models such as bioprinted tissues and microfluidic organ-on-chip devices are beginning to bridge these gaps by enabling multiplexed, longitudinal analyses under physiologically relevant flow and mechanical stimulation. Looking ahead, ongoing improvements in imaging resolution, probe multiplexing, computational data-fusion, and standardized analytical pipelines are poised to deepen our understanding of tissue patterning, disease progression, and the spatial dynamics of therapeutic intervention. This review uniquely focuses on the seamless integration of cutting-edge spatial-omics technologies into 3D culture models, a synergy that provides unprecedented maps of gene, protein, metabolite, and chromatin landscapes while preserving native microenvironmental context, which will yield more predictive in vitro systems and accelerate the discovery of personalized treatment strategies.