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.
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.
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.
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.
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.
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).
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.
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.
Project description:Mammalian chromatin is dynamic and contains structural information that leads to transcriptional regulation of genes by recruiting transcription factors and altering nucleosome positioning. Here, we describe open chromatin mapping using Nicking Enzyme assisted sequencing (NicE-seq) for integrative epigenomic analysis. NicE-seq captures open chromatin sites in both fixed and native cells and reveals the genomic location of open chromatin sites (OCS) and transcription factor occupancy at single nucleotide resolution, with as few as 250 HCT116 cells. In HCT116 cells a large percentage of the OCS were coincident with DHS (DNaseI hypersensitive site) and ATAC-seq sites. OCSs correlated well with RNA pol II occupancy and transcriptionally active chromatin marks, while displaying a pattern contrasting to CpG methylation. ChIP CTCF peaks common to OCS and DHS displayed a strong correlation with H3K4me3 and H3K27ac marks. Further peaks unique to OCS and ChIP CTCF peaks also correlated strongly with H3K4me3, H3K27ac and higher transcription. Similar results were also obtained for Max and Sp1 transcription factors. Using NicE-seq we have demonstrated that HCT116 cells, treated with anti cancer drug decitabine, displayed time dependent accumulation of OCS coinciding with hypomethylation of the genome, particularly in SINE and satellite repetitive DNA. Differentially methylated regions (DMRs) were more pronounced in promoters, 5’UTR, CpG islands and exons. In summary, sequence specificity offered by a nicking enzyme allows a means to study open chromatin structure and hypomethylation of genomes, revealing the open chromatin landscape in cellular context.