Similar Datasets
Project description:Spatial Transcriptomic Analysis of a Human Bone Marrow Clot Biopsy Using Xenium 5K
| PRJNA1432041 | ENA
Project description:Lactate transport is an important regulator of cellular metabolism and may contribute to fibroblast activation and extracellular matrix remodeling during pulmonary fibrosis. To define the spatial transcriptional landscape associated with pharmacologic inhibition of lactate transport during fibrotic lung remodeling, we performed spatial transcriptomic profiling of mouse lung tissue using the 10x Genomics Xenium Analyzer. Lung sections from mice with bleomycin-induced pulmonary fibrosis treated with inhibitors of monocarboxylate transport were analyzed using the Xenium Prime 5K Mouse Pan Tissue & Pathways panel to generate cell-resolved spatial gene expression maps. The resulting dataset provides spatially resolved transcriptional profiles across epithelial, stromal, endothelial, and immune compartments of the injured lung, enabling analysis of fibroblast activation states and spatial microenvironments associated with fibrotic remodeling.
2026-03-24 | GSE325253 | GEO
Project description:Targeted spatial transcriptomic profiling was performed on seven formalin-fixed paraffin-embedded pleural mesothelioma tumor samples from four cases using the 10x Genomics Xenium platform. The Xenium Human Immuno-Oncology panel supplemented with 100 additional custom genes selected from known pleural mesothelioma biomarkers and single-cell RNA-seq-derived marker genes was used. Raw and processed Xenium files are provided for each sample. To ensure data integrity with downloaded Xenium files, md5 checksums are provided in 'Xenium_GEO.md5'. This dataset is part of a multi-modality study including matched scRNA-seq, bulk RNA-seq, and Xenium spatial transcriptomics generated from overlapping pleural mesothelioma samples. Related controlled-access sequencing data are available in dbGaP under accession phs004285.
2026-04-08 | GSE327347 | GEO
Project description:To spatially contextualize and extend disease-associated cellular states, we generated Xenium spatial transcriptomics data from FFPE lung tissue of 38 participants spanning the COPD disease spectrum. Four tissue microarrays (TMA1–TMA4) were profiled using a custom 480-gene Xenium panel. These data capture the in situ organization of inflammatory, regenerative, and remodeling cell states and reveal spatially localized niches and patterns of cell–cell communications relevant to COPD pathology. This dataset provides high-resolution spatial context for characterizing microenvironmental structure and cell–cell interactions in COPD lung tissue.
2025-12-09 | GSE313006 | GEO
Project description:Recent work has shown that the spatial organization of immune responses is a critical determinant of anti-tumor immunity. Here, we profiled ten head and neck squamous cell carcinoma (HNSCC) patient tumors and one ameloblastoma tumor using Xenium V1 spatial transcriptomics. The 10X genomics human multi-tissue and cancer gene expression panel targeting 377 genes was used in combination with 100 custom Xenium probes targeting patient-specific CDR3 regions of T cell receptors (TCRs) in T cells, additoinal T cell specific genes, HPV oncoprotein genes, and tumor genes of interest. This enabled the detection of 477 transcripts within each tumor sample at a single-cell resolution. For seven of the ten HNSCC samples, different tissue sections run on different days were analyzed as technical replicates. Together, these findings introduce a scalable platform for spatial clonal T cell analysis and provide new insight into the spatial relationship of cells within the HNSCC tumor microenvironment.
2025-08-06 | GSE300147 | GEO
Project description:Spatial transcriptomics is a rapidly growing field with the potential to enhance our ability to uncover novel biology, support drug development, and guide biomarker discovery. However, a biologically validated comparison of leading single-cell-level spatial transcriptomics platforms to guide scientists is lacking in the field. Using intestinal biopsies (n = 40) from patients with inflammatory bowel disease (IBD) of varying disease states and disease locations and non-diseased controls, we systematically compared two imaging based spatial transcriptomics platforms (CosMx and Xenium) to guide translational work for two NIDDK supported IBD consortiums and the Crohn’s and Colitis Foundation Plexus Biorepository. In vitro experiments were conducted to validate key biologic findings. We present a comprehensive data resource of over 1.5 million spatially profiled intestinal cells from healthy and IBD samples. We observed CosMx to have overall better data quality than Xenium in both ulcerative colitis and Crohn’s disease across the full spectrum of commercially available panels. The performance of Xenium, but not CosMx, was significantly influenced by block quality and panel size, with a decline in data quality as the panel size increased. We demonstrate operational feasibility for CosMx in multi-center studies, and CosMx uniquely identified Treg-associated biology in both ulcerative colitis and Crohn’s disease which was validated by in vitro experiments. This study highlights the performance differences between CosMx and Xenium, demonstrating the strengths of CosMx for biology discovery in IBD research. Further studies are needed to explore the broader applicability of CosMx in other gastrointestinal conditions.
2026-03-13 | GSE312420 | GEO
Project description:Xenium platform was used for the spatial transcriptomic analysis of human DRG neurons, 100 marker genes were selected as the customized probe panel and hybridized to fresh frozen hDRG sections. Manual segmentation of each neuron soma was performed, based on expressions of pan-neuronal marker gene PGP9.5, satellite glia cell marker FAB7B, and the corresponding H.E. staining. In total, 1340 neurons were identified (excluding 75 region-of-interest with poor or unclear neuronal soma morphology in H & E staining) and clustered into 16 groups. The 16 clusters were assigned as different cell types based on marker genes expression.
2024-08-14 | GSE273557 | GEO
Project description:Spatial transcriptomics faces a trade-off between the number of genes assayed and depth of per-gene sensitivity. We developed a 'dual chemistry' method that combines the high sensitivity of a 10X Genomics Xenium V1 custom panel (up to 480 genes) with the broad coverage of the Prime 5K panel (5001 genes) on a single tissue section. This involved co-hybridizing Prime and V1 probes and sequentially running the V1 and Prime decoding chemistries. Applied to a human lung tissue microarray, we observed high concordance between the V1 and Prime chemistries when run independently (on serial sections) and the dual chemistry runs. Overlapping genes (profiled on both V1 and Prime chemistries) showed similar expression patterns in the dual run demonstrating the fidelity of the assay. By combining information from both the V1 and Prime chemistries within the same cell, we retain more cells, gain valuable additional information, and enable both high sensitivity profiling and discovery.
2026-01-07 | GSE315411 | GEO
Project description:We performed Xenium single cell transcriptomics on 4 plaques with matched controls (8 samples in total) and 8 additional plaques. A total of 16 samples was sequenced with two panels each.
2025-11-04 | GSE294466 | GEO
Project description:Emerging imaging spatial transcriptomics (iST) platforms and coupled analytical methods can recover cell-to-cell interactions, groups of spatially covarying genes, and gene signatures associated with pathological features, and are thus particularly well-suited for applications in formalin fixed paraffin embedded (FFPE) tissues. Here, we benchmark the performance of three commercial iST platforms—10X Xenium, Vizgen MERSCOPE, and Nanostring CosMx—on serial sections from tissue microarrays (TMAs) containing 17 tumor and 16 normal tissue types for both relative technical and biological performance. On matched genes, we find that Xenium consistently generates higher transcript counts per gene without sacrificing specificity. Xenium and CosMx measure RNA transcripts in concordance with orthogonal single-cell transcriptomics. All three platforms can perform spatially resolved cell typing with varying degrees of sub-clustering capabilities, with Xenium and CosMx finding slightly more clusters than MERSCOPE, albeit with different false discovery rates and cell segmentation error frequencies. Taken together, our analyses provide a comprehensive benchmark to guide the choice of iST method as researchers design studies with precious samples in this rapidly evolving field.
2025-10-03 | GSE308148 | GEO