<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/GSE348nnn/GSE348495/</Other></files><type>primary</type></body><statusCodeValue>200</statusCodeValue><statusCode>OK</statusCode></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=GSE348495</full_dataset_link><repository>GEO</repository><entry_type>GSE</entry_type></additional><is_claimable>false</is_claimable><name>Spatially resolved single-cell transcriptomic profiling of human colorectal cancer using NanoString CosMx SMI</name><description>This study used the NanoString CosMx Spatial Molecular Imager (SMI) to perform spatially resolved single-cell transcriptomic profiling of FFPE human colorectal tissue. Seventeen samples were analyzed, including three colorectal polyp samples (CA), eleven stage I colorectal cancer samples (CCP1–CCP4), and three colorectal cancer-adjacent tissue samples (HCT). CosMx SMI enabled in situ detection and spatial localization of RNA transcripts at single-cell and subcellular resolution. The processed dataset includes per-cell gene expression matrices, transcript coordinates, cell metadata, field-of-view (FOV) positions, and cell segmentation polygon data, providing a resource for investigating spatial cellular heterogeneity and the tumor microenvironment in colorectal cancer. This study used the NanoString CosMx Spatial Molecular Imager (SMI) to perform spatially resolved single-cell transcriptomic profiling of FFPE human colorectal tissue. Seventeen samples were analyzed, including three colorectal polyp samples (CA), eleven stage I colorectal cancer samples (CCP1–CCP4), and three colorectal cancer-adjacent tissue samples (HCT). CosMx SMI enabled in situ detection and spatial localization of RNA transcripts at single-cell and subcellular resolution. The processed dataset includes per-cell gene expression matrices, transcript coordinates, cell metadata, field-of-view (FOV) positions, and cell segmentation polygon data, providing a resource for investigating spatial cellular heterogeneity and the tumor microenvironment in colorectal cancer.</description><dates><publication>2026/09/30</publication></dates><accession>GSE348495</accession><cross_references><GSM>GSM10073459</GSM><GSM>GSM10073448</GSM><GSM>GSM10073449</GSM><GSM>GSM10073457</GSM><GSM>GSM10073458</GSM><GSM>GSM10073455</GSM><GSM>GSM10073456</GSM><GSM>GSM10073464</GSM><GSM>GSM10073453</GSM><GSM>GSM10073454</GSM><GSM>GSM10073462</GSM><GSM>GSM10073451</GSM><GSM>GSM10073452</GSM><GSM>GSM10073463</GSM><GSM>GSM10073460</GSM><GSM>GSM10073450</GSM><GSM>GSM10073461</GSM><GPL>33484</GPL><GSE>348495</GSE><taxon>Homo sapiens</taxon></cross_references></HashMap>