AI Briefing3D Spatial Biology, Pathology AI, and Multi-Omics Foundation Models
Key point
LG AI Research collaborated with VUMC to unveil next-generation cancer research achievements combining 3D/4D spatial biology and AI.
Details
Recent cancer research is evolving toward interpreting Spatial Information to understand the complex structure and signal transduction of the tumor microenvironment. LG AI Research shared various research achievements at 2026 AACR through a joint study with Vanderbilt University Medical Center (VUMC) in the United States.
The key research areas are as follows.
- 3D Spatial Multi-Omics: For gastric cancer tissue, RNA, protein, and fluorescent H&E information are aligned on the same slide coordinates, enabling precise interpretation of the three-dimensional structure and continuity of the tumor microenvironment that is difficult to capture with 2D analysis.
- 4D Dynamic Process Tracking: The mechanism of action of therapeutics such as ADCs (antibody-drug conjugates) is analyzed along a time axis. Holotomography is used to track the drug's intracellular uptake, lysosomal processing, and drug release process in real time.
- Analysis Interface and Predictive Models: An immersive VR/AR-based 3D/4D analysis environment is built, combined with the conversational AI ChatEXAONE to help researchers interpret data. In addition, the ProteoBridge model, which predicts protein maps for unmeasured cross-sections, fills gaps in the data.
These studies show that spatial biology is expanding beyond static structural interpretation into a technology that reads spatiotemporal context.
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