Continuous spatially informed microenvironment programs show cross-cohort concordance and context-dependent spatial...

Spatial transcriptomics resolves tissue organization in diffuse large B-cell lymphoma (DLBCL), whereas most clinically annotated cohorts remain bulk transcriptomic datasets.

We evaluated six literature-informed curated composite programs across bulk, single-cell and spatial datasets without assuming a discrete ecosystem taxonomy. The programs comprised Macrophage-rich, T cell-inflamed, Antigen-presentation, Stromal/fibrotic, Immune-cold/exclusion and Proliferative/cycling, with 22 memberships per program (132 memberships, 121 unique genes and 11 shared memberships).

In 498 GSE31312 tumors, principal components 1 and 2 (PC1 and PC2) explained 48.6% and 20.8% of score variance. No candidate discrete taxonomy demonstrated sufficient stability for retention; k=2 met silhouette and size criteria but failed both bootstrap-stability thresholds. Historical 15-edge concordance was high for GSE10846 (rho=0.936) and GSE181063 (rho=0.982), whereas the most restrictive GSE10846 edge-exclusion sensitivity, removing both shared-gene and proliferation-associated edges, reduced rho to 0.690. Single-cell analysis of 14,368 DLBCL cells from four patients and eight samples provided descriptive lineage context. In Visium V2 areas, the antigen-presentation series was treated as AP-residual (HLA-unmeasured) because only 13/22 program genes were measurable and all nine HLA genes in the defined program were unavailable. Matched-random-gene-set support was broad but not universal (24/30 DLBCL, 18/24 context/background, 42/54 overall; 25/32 primary-plus-exploratory), whereas both depth-adjusted residual endpoints were supported in 30/30 DLBCL area-program combinations.

These findings support continuous program-level interpretation while retaining explicit provenance, stability, assay, method and sampling limitations.