<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>12</volume><submitter>Tran T</submitter><pubmed_abstract>Recent advances in spatial transcriptomics (ST) and spatial proteomics (SP) technologies have enabled high-dimensional molecular profiling at single-cell resolution, providing deeper insights into the tumour-immune microenvironment. However, these modalities are typically applied to separate tissue sections, limiting direct comparisons across molecular layers. We developed a wet-lab and computational framework to perform and integrate ST and SP from the same tissue section, as demonstrated on human lung cancer samples. Applying ST, SP, and hematoxylin and eosin (H&amp;E) staining from the same section ensured consistency in tissue morphology and spatial context. Computational registration using Weave software allowed accurate alignment and annotation transfer across modalities. This co-registe</pubmed_abstract><journal>Frontiers in molecular biosciences</journal><pagination>1614288</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12304548</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>An integrated approach for analyzing spatially resolved multi-omics datasets from the same tissue section.</pubmed_title><pmcid>PMC12304548</pmcid><pubmed_authors>Zhang W</pubmed_authors><pubmed_authors>Tran T</pubmed_authors><pubmed_authors>Wee F</pubmed_authors><pubmed_authors>Chong LY</pubmed_authors><pubmed_authors>Yap FHX</pubmed_authors><pubmed_authors>Yeong J</pubmed_authors><pubmed_authors>Patterson NH</pubmed_authors><pubmed_authors>Neo ZW</pubmed_authors><pubmed_authors>Joseph CR</pubmed_authors><pubmed_authors>Ly A</pubmed_authors><pubmed_authors>Lim JCT</pubmed_authors><pubmed_authors>Claesen M</pubmed_authors></additional><is_claimable>false</is_claimable><name>An integrated approach for analyzing spatially resolved multi-omics datasets from the same tissue section.</name><description>Recent advances in spatial transcriptomics (ST) and spatial proteomics (SP) technologies have enabled high-dimensional molecular profiling at single-cell resolution, providing deeper insights into the tumour-immune microenvironment. However, these modalities are typically applied to separate tissue sections, limiting direct comparisons across molecular layers. We developed a wet-lab and computational framework to perform and integrate ST and SP from the same tissue section, as demonstrated on human lung cancer samples. Applying ST, SP, and hematoxylin and eosin (H&amp;E) staining from the same section ensured consistency in tissue morphology and spatial context. Computational registration using Weave software allowed accurate alignment and annotation transfer across modalities. This co-registe</description><dates><release>2025-01-01T00:00:00Z</release><publication>2025</publication><modification>2026-03-27T17:10:06.261Z</modification><creation>2025-08-30T03:06:45.904Z</creation></dates><accession>S-EPMC12304548</accession><cross_references><pubmed>40735471</pubmed><doi>10.3389/fmolb.2025.1614288</doi></cross_references></HashMap>