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Understanding how molecular features and cell\u2013cell interactions change across space and time is central to studying development, homeostasis and disease. Addressing these questions increasingly requires the integration of multi-modal spatial data, which provides complementary views of cellular and structural organization. However, existing computational approaches typically combine modalities by weighting them equally, overlooking domain-specific technical artifacts, differences in spatial resolution and non-overlapping feature spaces. In addition, methods for spatial cell\u2013cell communication analysis are largely developed for single-modality settings and do not model how interactions vary across the tissue. To address these gaps, we introduce LYNX, a deep generative framework that learns a shared latent representation of spatial dynamics from joint-measured modalities in the 2D or 3D domain, to provide a unified coordinate system for modeling how cell\u2013cell interactions, phenotypes, and molecular programs vary along continuous spatial gradients. LYNX identifies spatial programs difficult to resolve with existing approaches, including metabolically coupled porto-central interaction remodeling in liver, recovery of degraded proteomic signals along the cortico-medullary axis in thymus, and branching trajectories towards DCIS and invasive niches marked by distinct stromal activation-states and immune-tumor crosstalk in breast tumor microenvironment. We demonstrate that LYNX robustly infers spatially resolved gradients, maps functional compartments and cell-cell interactions along spatial axes and is compatible across diverse spatial profiling technologies, modalities, and resolution disparities. LYNX provides a foundational and scalable framework to advance our understanding of healthy tissue physiology and to decode temporal evolution of complex diseases.<\/jats:p>","DOI":"10.64898\/2026.07.09.737574","type":"posted-content","created":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T17:15:25Z","timestamp":1783703725000},"source":"Crossref","is-referenced-by-count":0,"title":["LYNX: a deep generative model for linking spatial dynamics and cell interactions in multimodal spatial data"],"prefix":"10.64898","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1889-8587","authenticated-orcid":false,"given":"Yinuo","family":"Jin","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering, Columbia University, New York, NY, USA"},{"name":"Irving Institute for Cancer Dynamics, Columbia University, New York, NY, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-8828-659X","authenticated-orcid":false,"given":"Joshua D.","family":"Myers","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, Columbia University, New York, NY, USA"},{"name":"Irving Institute for Cancer Dynamics, Columbia University, New York, NY, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2184-7238","authenticated-orcid":false,"given":"Presha","family":"Rajbhandari","sequence":"additional","affiliation":[{"name":"Department of Biological Sciences, Columbia University, New York, NY, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jia Yi","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, Columbia University, New York, NY, USA"},{"name":"Irving Institute for Cancer Dynamics, Columbia University, New York, NY, USA"},{"name":"Department of Statistics, University of Illinois Urbana-Champaign, Champaign, IL, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kaylee W.","family":"Fang","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, Columbia University, New York, NY, USA"},{"name":"Department of Computer Science, Columbia University, New York, NY, USA"},{"name":"Department of Radiology, Stanford University, Stanford, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John Shaw","family":"Moazami","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Columbia University, New York, NY, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Noreen","family":"Hosny","sequence":"additional","affiliation":[{"name":"Department of Molecular Biology, Princeton University, Princeton, NJ, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3532-3868","authenticated-orcid":false,"given":"Brent R.","family":"Stockwell","sequence":"additional","affiliation":[{"name":"Department of Biological Sciences, Columbia University, New York, NY, USA"},{"name":"Department of Chemistry, Columbia University, New York, NY, USA"},{"name":"Department of Pathology and Cell Biology, Columbia University Medical Center, New York, NY, USA"},{"name":"Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5059-6971","authenticated-orcid":false,"given":"Elham","family":"Azizi","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, Columbia University, New York, NY, USA"},{"name":"Irving Institute for Cancer Dynamics, Columbia University, New York, NY, USA"},{"name":"Department of Computer Science, Columbia University, New York, NY, USA"},{"name":"Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"54368","reference":[{"key":"2026071319200593000_2026.07.09.737574v1.1","doi-asserted-by":"publisher","DOI":"10.1126\/sciadv.adn3448"},{"key":"2026071319200593000_2026.07.09.737574v1.2","doi-asserted-by":"publisher","DOI":"10.1038\/nature21065"},{"key":"2026071319200593000_2026.07.09.737574v1.3","doi-asserted-by":"publisher","DOI":"10.1038\/nbt.4231"},{"issue":"7","key":"2026071319200593000_2026.07.09.737574v1.4","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1038\/s41575-019-0134-x","article-title":"Spatial heterogeneity in the mammalian liver","volume":"16","year":"2019","journal-title":"Nature reviews Gastroenterology & hepatology"},{"key":"2026071319200593000_2026.07.09.737574v1.5","doi-asserted-by":"crossref","unstructured":"Helena L Crowell , Irene Ruano , Zedong Hu , Yourae Hong , Gin Carat\u00f9 , Hubert Piessevaux , Ashley Heck , Rachel Liu , Max Walter , Megan Vandenberg , et al. 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