Same-Slide Spatial Multiomics Integration with IN-DEPTH Reveals Tumor Virus-Linked Spatial Reorganization of the...

Spatial transcriptomics and proteomics have enabled profound insights into tissue organization, yet these technologies remain largely disparate, and emerging same-slide multiomics approaches are limited in plex, spatial resolution, signal retention, and integrative analytics. We introduce IN-situ DEtailed Phenotyping To High-resolution transcriptomics (IN-DEPTH), a streamlined, resource-efficient, commercially compatible workflow using single-cell spatial proteomics-derived imaging to guide transcriptomic capture on the same slide without RNA signal loss. To integrate modalities beyond niche-level mapping, we developed Spectral Graph Cross-Correlation (SGCC), a proteomic-transcriptomic framework resolving spatially coordinated functional state changes across interacting cell populations. Applied to diffuse large B-cell lymphoma (DLBCL), IN-DEPTH and SGCC enabled stepwise discovery from Epstein-Barr virus (EBV)-positive and EBV-negative tumor comparisons with single-cell resolution, revealing coordinated tumor-macrophage-CD4 T-cell remodeling, immunosuppressive C1Q macrophage enrichment, CD4 T-cell dysfunction, and a candidate IL27-STAT3 signaling axis. Collectively, IN-DEPTH enables scalable spatial multiomics to uncover clinically relevant microenvironmental mechanisms and toward robust spatial multimodal AI models.

IN-DEPTH enables same-slide spatial multiomics across commercial platforms via a protein-first strategy preserving protein epitopes, RNA quality, and tissue integrity. Coupled with SGCC, it resolves coordinated spatial immune remodeling, revealing EBV/LMP1-driven C1Q macrophage polarization and CD4 T-cell dysfunction in DLBCL, with broad applicability to other diseases.