<HashMap><database>GEO</database><file_versions><headers><Content-Type>application/xml</Content-Type></headers><body><files><Other>ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE282nnn/GSE282124/</Other></files><type>primary</type></body><statusCode>OK</statusCode><statusCodeValue>200</statusCodeValue></file_versions><scores/><additional><omics_type>Other</omics_type><species>Homo sapiens</species><gds_type>Other</gds_type><full_dataset_link>https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE282124</full_dataset_link><repository>GEO</repository><entry_type>GSE</entry_type></additional><is_claimable>false</is_claimable><name>Single-cell spatial transcriptomics of formalin-fixed, paraffin-embedded biopsies reveals colitis-associated cell networks [Merscope]</name><description>Imaging-based single-cell spatial transcriptomics (iSCST) on formalin-fixed, paraffin-embedded (FFPE) tissue enables comprehensive analysis of archived specimens while preserving spatial context, critical to an understanding of ulcerative colitis (UC) pathology. Here, we developed, benchmarked, and applied a robust framework for applying iSCST to clinical FFPE mucosal biopsies from patients with UC, immune checkpoint inhibitor-induced (ICI) colitis and healthy controls. iSCST using custom Xenium gene panels enabled precise detection of diverse cell subsets and disease-specific genes. We mapped transcriptionally distinct fibroblast subsets within mucosal niches, including inflammation-associated fibroblasts (IAFs), and identified colitis-specific neighborhoods formed by IAFs, monocytes, and neutrophils. Transcriptional signatures uncovered through iSCST were associated with vedolizumab (VDZ) response, with non-responders exhibiting either an IAF-monocyte signature or adaptive gut-associated lymphoid tissue (GALT) signature, while responders showed enrichment of epithelial gene expression. These signatures were validated in both internal and publicly-available external datasets. This iSCST framework provides a powerful approach for analyzing FFPE tissues, offering insights into colitis-associated cellular networks and identifying biomarkers to enhance patient risk stratification in routine clinical workflows.</description><dates><publication>2026/05/21</publication></dates><accession>GSE282124</accession><cross_references><GSM>GSM8636485</GSM><GPL>33762</GPL><GSE>282124</GSE><taxon>Homo sapiens</taxon></cross_references></HashMap>