Open-ST: High-resolution spatial transcriptomics in 3D [xenium]
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ABSTRACT:
PROVIDER: PRJNA1097649 | ENA |
REPOSITORIES: ENA
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Project description:Spatial transcriptomics (ST) methods unlock molecular mechanisms underlying tissue development, homeostasis, or disease. However, there is a need for easy-to-use, high-resolution, cost-efficient, and 3D-scalable methods. Here, we report Open-ST, a sequencing-based, open-source experimental and computational resource to address these challenges and to study the molecular organization of tissues in 2D and 3D. In mouse brain, Open-ST captured transcripts at subcellular resolution and reconstructed cell types. In primary head-and-neck tumors and patient-matched healthy/metastatic lymph nodes, Open-ST captured the diversity of immune, stromal, and tumor populations in space, validated by imaging-based ST. Distinct cell states were organized around cell-cell communication hotspots in the tumor but not the metastasis. Strikingly, the 3D reconstruction and multimodal analysis of the metastatic lymph node revealed spatially contiguous structures not visible in 2D and potential biomarkers precisely at the 3D tumor/lymph node boundary. All protocols and software are available at https://rajewsky-lab.github.io/openst.
2024-06-23 | GSE263498 | GEO
Project description:Spatial transcriptomics (ST) methods unlock molecular mechanisms underlying tissue development, homeostasis, or disease. However, there is a need for easy-to-use, high-resolution, cost-efficient, and 3D-scalable methods. Here, we report Open-ST, a sequencing-based, open-source experimental and computational resource to address these challenges and to study the molecular organization of tissues in 2D and 3D. In mouse brain, Open-ST captured transcripts at subcellular resolution and reconstructed cell types. In primary head-and-neck tumors and patient-matched healthy/metastatic lymph nodes, Open-ST captured the diversity of immune, stromal, and tumor populations in space, validated by imaging-based ST. Distinct cell states were organized around cell-cell communication hotspots in the tumor but not the metastasis. Strikingly, the 3D reconstruction and multimodal analysis of the metastatic lymph node revealed spatially contiguous structures not visible in 2D and potential biomarkers precisely at the 3D tumor/lymph node boundary. All protocols and software are available at https://rajewsky-lab.github.io/openst.
2024-06-23 | GSE251926 | GEO
Project description:Open-ST: High-resolution spatial transcriptomics in 3D
| PRJNA1055947 | ENA
Project description:10X Genomics Xenium data from human Medulloblastoma samples. The data was acuired in the course of a study performing a comparison of four imaging-based ST methods – RNAscope HiPlex, Molecular Cartography, MERFISH/Merscope, and Xenium – together with sequencing-based ST (Visium). These technologies were used to study cryosections of medulloblastoma with extensive nodularity (MBEN), a tumor chosen for its distinct microanatomical features. Our analysis reveals that automated imaging-based ST methods are well suited to delineating the intricate MBEN microanatomy, capturing cell-type-specific transcriptome profiles. We devise approaches to compare the sensitivity and specificity of the different methods together with their unique attributes to guide method selection based on the research aim. Furthermore, we demonstrate how reimaging of slides after the ST analysis can markedly improve cell segmentation accuracy and integrate additional transcript and protein readouts to expand the analytical possibilities and depth of insights. This study highlights key distinctions between various ST technologies and provides a set of parameters for evaluating their performance. Our findings aid in the informed choice of ST methods and delineate approaches for enhancing the resolution and breadth of spatial transcriptomic analyses, thereby contributing to advancing ST applications in solid tumor research.
2025-03-17 | GSE291688 | GEO
Project description:Spatial transcriptomics (ST) is fundamental for understanding molecular mechanisms in health and disease. Here, we present a protocol for efficient and high-resolution ST in 2D/3D with Open-ST. We describe all steps for repurposing Illumina flow cells into spatially barcoded capture areas and preparing ST libraries from stained cryosections. We detail the computational workflow for generating 2D/3D molecular maps ("virtual tissue blocks"), aligned with histological data, unlocking molecular pathways in space. Open-ST is applicable to any tissue, including clinical samples. For complete details on the use and execution of this protocol, please refer to Schott et al.1.
| S-EPMC11731217 | biostudies-literature
Project description:Imaging-based spatial transcriptomics (ST) is evolving as a pivotal technology in studying tumor biology and associated microenvironments. However, the strengths of the commercially available ST platforms in studying spatial biology have not been systematically evaluated using rigorously controlled experiments. We use serial 5 m sections of formalin-fixed, paraffin-embedded surgically resected lung adenocarcinoma and pleural mesothelioma samples in tissue microarrays to compare the performance of the ST platforms (CosMx, MERFISH, and Xenium (uni/multi-modal)) in reference to bulk RNA sequencing, multiplex immunofluorescence, GeoMx, and hematoxylin and eosin staining data. In addition to an objective assessment of automatic cell segmentation and phenotyping, we perform a manual phenotyping evaluation to assess pathologically meaningful comparisons between ST platforms. Here, we show the intricate differences between the ST platforms, reveal the importance of parameters such probe design in determining the data quality, and suggest reliable workflows for accurate spatial profiling and molecular discovery.
2025-06-30 | GSE300007 | GEO
Project description:One of the most common origins of Peritoneal metastasis (PM) is colon cancer, which occurs in about 20% of colon cancer patients. Given the cancer cell heterogeneity in PM, we first tried to dissect the spatial distribution of CAF and the associated niches at a single cell resolution, we exploited the Xenium In Situ high-plex spatial imaging platform. We performed the Xenium assays with 8 human PM samples of colon origin including one PM-adjacent tissue. Among the 8 PM samples, 3 samples carried a distinct iCMS3 epithelial signature (PM1, PM2, PM3), 2 carried iCMS2 signature (PM6, PM7), while the other 2 samples had a mix of both iCMS2 and iCMS3 signatures (PM4, PM5). We found that the presence of iCMS3 cancer cells was associated with an increase infiltration of lymphocytes and the formation of tertiary lymphoid structures (TLS).
2025-09-15 | GSE274623 | GEO
Project description:KRAS mutations are a predominant driver of metastatic colorectal cancer (mCRC), with approximately 10% of patients harboring the KRAS p.G12C variant. Despite the development of KRASG12C (G12Ci) and EGFR (EGFRi) inhibitors such as sotorasib and panitumumab, therapeutic resistance remains a major limitation. To define resistance mechanisms, we analyzed tissue biopsies from patients treated with G12Ci+EGFRi and employed Xenium spatial transcriptomics (Xenium ST), along with comprehensive multi-omics profiling of patient-derived xenograft (PDX) models. Known genomic alterations including NRAS p. Q61K mutations and KRASG12C amplifications were observed; however, non-genomic resistance was strongly associated with activation of the YAP-TEAD pathway. Xenium ST data revealed two key tumor subpopulations: tumor intestinal stem cells (TISCs), marked by upregulation of KRAS and YAP, and neuroendocrine-like (NE) cells, which showed KRAS upregulation alone. G12Ci+EGFRi-resistant PDX models were enriched for TISCs and associated stemness programs. The addition of a TEAD inhibitor (TEADi; IAG-933) to dual therapy induced deep tumor regression and suppressed KRAS, YAP, stemness pathways; however, NE-like cells were enriched following triple therapy. These findings suggest that TEADi enhances the efficacy of KRASG12C + EGFR inhibition by targeting TISCs but may not eliminate NE-like subpopulations, which could mediate TEAD-independent resistance and represent a therapeutic challenge.
2025-09-24 | GSE308699 | GEO
Project description:To explore the CAF niches in pancreatic ductal adenocarcinoma (PDAC), we performed Xenium assays in 3 treatment-naïve and 3 chemoradiotherapy-treated human PDAC samples. We found that after the chemoradiotherapy treatment, tissues became more desmoplastic with a larger CAF proportion. And interestingly, we found there was a reduction of cancer cell 1 in the chemoradiotherapy group while the ratio of cancer cell 2 remained similar, suggesting cancer cell 2 was the chemoradiotherapy-resistant cancer cell population. Through differential gene analysis, we found cancer 2 was marked by a high level of SPP1 expression.
2025-09-15 | GSE274673 | 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