Spatial transcriptomics stratifies psoriatic disease by emergent cellular ecosystems
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA834043 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:The skin is recognized as a window into the immunopathogenic mechanisms driving the vast phenotypic spectrum of psoriatic disease. To better decipher the cellular landscape of both healthy and psoriatic skin, we employed spatial transcriptomics (ST), a ground-breaking technology that precisely maps gene expression from histologically-intact tissue sections. Findings gleaned from computationally integrating our 23 matched lesional and non-lesional psoriatic and 7 healthy control samples with publicly-available single cell RNA seq data sets provided insights into the emergent cellular ecosystems at play in psoriatic disease.
2022-05-12 | GSE202011 | GEO
Project description: Not available
| S-EPMC10502701 | biostudies-literature
Project description:Intra-tumoral heterogeneity in melanoma arises from dynamic cancer cell plasticity and underlies various mechanisms of immune escape. Here, we combined high-plex immunofluorescence imaging with spatially resolved transcriptomics to map the architecture of melanoma cell states and their interactions with the immune microenvironment in primary cutaneous tumours prior to adjuvant anti-PD1 immune checkpoint inhibitor (ICI) treatment. Computational analyses showed that melanoma cells organise into spatially restricted patches, with a preferential organisation of undifferentiated cells associated with poor ICI efficacy. Neighbouring immune cell composition varied according to cancer cell states, with a crucial involvement of specific subsets of tumour-associated macrophages, driven by signalling pathways involving tumour-derived and microenvironmental cues such as IFN-γ and hypoxia. Integrated spatial analyses further revealed tumour-immune ecosystems that stratify patient outcomes, delineating configurations either associated with ICI efficacy or metastatic relapse. These results uncover the spatial landscape of tumour ecosystems and identify signalling pathways as potential targets for improving the efficacy of ICI in melanoma.
2026-06-23 | GSE300445 | GEO
Project description:Enthesitis, a hallmark of psoriatic arthritis (PsA), reflects the interplay between mechanical stress and immune dysregulation at tendon-bone interfaces. We aimed to investigates the cellular and molecular responses in entheseal tissues following IL-17A inhibition in patients with active PsA. To identify changes in the mesenchymal and non-mesenchymal compartments pre- and post-treatment, we performed GeoMx spatial transcriptomics on CD45+ and vimentin+ cells on entheseal biopsies from 6 PsA patients before and after treatment with secukinumab.
2025-12-31 | E-MTAB-15134 | biostudies-arrayexpress
Project description:Intra-tumoral heterogeneity in melanoma arises from dynamic cancer cell plasticity and underlies various mechanisms of immune escape. Here, we combined high-plex immunofluorescence imaging with spatially resolved transcriptomics to map the architecture of melanoma cell states and their interactions with the immune microenvironment in primary cutaneous tumours prior to adjuvant anti-PD1 immune checkpoint inhibitor (ICI) treatment. Computational analyses showed that melanoma cells organise into spatially restricted patches, with a preferential organisation of undifferentiated cells associated with poor ICI efficacy. Neighbouring immune cell composition varied according to cancer cell states, with a crucial involvement of specific subsets of tumour-associated macrophages, driven by signalling pathways involving tumour-derived and microenvironmental cues such as IFN-γ and hypoxia. Integrated spatial analyses further revealed tumour-immune ecosystems that stratify patient outcomes, delineating configurations either associated with ICI efficacy or metastatic relapse. These results uncover the spatial landscape of tumour ecosystems and identify signalling pathways as potential targets for improving the efficacy of ICI in melanoma.
2026-06-23 | GSE300793 | GEO
Project description:Intra-tumoral heterogeneity in melanoma arises from dynamic cancer cell plasticity and underlies various mechanisms of immune escape. Here, we combined high-plex immunofluorescence imaging with spatially resolved transcriptomics to map the architecture of melanoma cell states and their interactions with the immune microenvironment in primary cutaneous tumours prior to adjuvant anti-PD1 immune checkpoint inhibitor (ICI) treatment. Computational analyses showed that melanoma cells organise into spatially restricted patches, with a preferential organisation of undifferentiated cells associated with poor ICI efficacy. Neighbouring immune cell composition varied according to cancer cell states, with a crucial involvement of specific subsets of tumour-associated macrophages, driven by signalling pathways involving tumour-derived and microenvironmental cues such as IFN-γ and hypoxia. Integrated spatial analyses further revealed tumour-immune ecosystems that stratify patient outcomes, delineating configurations either associated with ICI efficacy or metastatic relapse. These results uncover the spatial landscape of tumour ecosystems and identify signalling pathways as potential targets for improving the efficacy of ICI in melanoma.
2026-06-23 | GSE300446 | GEO
Project description:This dataset comprises spatial transcriptomic profiles from 10 tissue samples of Diffuse Large B-cell Lymphoma (DLBCL) the most common subtype of non-Hodgkin’s lymphoma and secondary lymphoid organ controls (SLO). The diffuse nature of DLBCL challenges the analysis of cellular organization within the immune tumor microenvironment (TME). We employed spatial transcriptomics to map spatially-resolved gene expression patterns. The analysis led to the identification of six cellular ecosystems (Cell-Eco) that differ in cellular composition, functional patterns, and neighborhood characteristics. The spatially-resolved Cell-Eco signatures provided prognostic scores that stratified patients with different overall survival rates. We also found that C1q+ tumor-associated macrophages are the primary cells interacting with malignant B cells and influencing the spatial architecture of the TME. This resource offers valuable insights into the spatial complexity of the DLBCL microenvironment and its potential prognostic significance.
2026-04-29 | GSE276542 | GEO
Project description:Characterize active synovial fluid (SF) serine proteinases in psoriatic arthritis (PsA) in comparison to osteoarthritis (OA) and rheumatoid arthritis (RA)
2021-03-29 | PXD022442 | Pride
Project description:The complexity of the tumor microenvironment poses significant challenges in cancer therapy. Here, to comprehensively investigate the tumor-normal ecosystems, we perform an integrative analysis of 4.9 million single-cell transcriptomes from 1,070 tumor and 493 normal samples in combination with pan-cancer 137 spatial transcriptomics, 8,887 TCGA, and 1,261 checkpoint inhibitor-treated bulk tumors. We define a myriad of cell states constituting the tumor-normal ecosystems and also identify hallmark gene signatures across different cell types and organs. Our atlas characterizes distinctions between inflammatory fibroblasts marked by AKR1C1 or WNT5A in terms of cellular interactions and spatial co-localization patterns. Co-occurrence analysis reveals interferon-enriched community states including tertiary lymphoid structure (TLS) components, which exhibit differential rewiring between tumor, adjacent normal, and healthy normal tissues. The favorable response of interferon-enriched community states to immunotherapy is validated using immunotherapy-treated cancers (n=1,261) including our lung cancer cohort (n=497). Deconvolution of spatial transcriptomes discriminates TLS-enriched from non-enriched cell types among immunotherapy-favorable components. Our systematic dissection of tumor-normal ecosystems provides a deeper understanding of inter- and intra-tumoral heterogeneity.
2024-02-14 | GSE218989 | GEO