Background: Target validation in inflammatory cardiomyopathy requires more than bulk expression evidence: a credible target should be localized to pathology-relevant regions, track with disease stage, and respond appropriately to therapeutic intervention. Imaging-based spatial transcriptomics offers a framework to resolve all three axes simultaneously. We developed an integrated Xenium-based pipeline to contextualize candidate target genes across the inflammatory-to-fibrotic progression of experimental autoimmune myocarditis (EAM) and demonstrate its utility as a target-validation platform.
Methods: We applied 10x Genomics Xenium in situ sequencing (488-gene panel) to 20 murine hearts spanning Healthy, EAM, Placebo, and Treated arms across three timepoints (D14, D21, D42). Cells were segmented with Baysor, and lesions were defined transcriptionally from inflammatory and fibrotic marker activity and correlated with paired histology. The pipeline integrates pseudobulk differential expression (edgeR, dual-tier thresholds), k-nearest-neighbour cell–cell colocalization, niche composition, and compositional forest plots to profile each candidate target across disease stage, tissue region, cellular source, and treatment response.
Results: The pipeline successfully distinguished candidate targets by their temporal dynamics (acute versus chronic), lesion-specificity, cellular localization (immune vs stromal vs cardiomyocyte), and treatment reversibility. Contrasting target profiles emerged – some normalized under anti-inflammatory treatment while others persisted – clarifying which targets map onto composition-reducing versus tissue-remodelling therapeutic hypotheses.
Conclusions: Xenium spatial transcriptomics, coupled with this integrated analytical framework, provides a powerful target validation tool that contextualizes candidate genes across the inflammatory-fibrotic continuum of cardiac disease.

Co-authors: Greg Bass, Adele Richart, Ying He