Spatial transcriptomics stratifies psoriatic disease by emergent cellular ecosystems
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ABSTRACT:
PROVIDER: PRJNA834043 | ENA |
REPOSITORIES: ENA
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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.
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Project description:The recent advance of spatial transcriptomics (ST) technique provides valuable insights into the organization and interactions of cells within the tumor microenvironment (TME). While various analytical tools have been developed for tasks such as spatial clustering, spatially variable gene identification, and cell type deconvolution, most of them are general methods lacking consideration of histological features in spatial data analysis. This limitation results in reduced performance and interpretability of their results when studying the TME. Here, we present a computational framework named, Morphology-Enhanced Spatial Transcriptome Analysis Integrator (METI) to address this gap. METI is an end-to-end framework capable of spatial mapping of both cancer cells and various TME cell components, robust stratification of cell type and transcriptional states, and cell co-localization analysis. By integrating both spatial transcriptomics, cell morphology and curated gene signatures, METI enhances our understanding of the molecular landscape and cellular interactions within the tissue, facilitating detailed investigations of the TME and its functional implications. The performance of METI has been evaluated on ST data generated from various tumor tissues, including gastric, lung, and bladder cancers, as well as premalignant tissues. Across all these tissues and conditions, METI has demonstrated robust performance with consistency.
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Project description:Psoriasis is a systemic disease with cutaneous manifestations. MicroRNAs (miRNAs) are non-coding RNA molecules that are differentially expressed in psoriatic skin, however; only few miRNAs have been localized to specific cells or regions of psoriatic lesions. We used laser capture microdissection (LCM) and next-generation sequencing to study the specific miRNA expression profiles in the epidermis (Epi) and dermal inflammatory aggregates (RD/ICs) of psoriatic skin. We identified 24 deregulated miRNAs in the Epi and 37 deregulated miRNAs in the RD/ICs of lesional psoriatic skin compared with non-lesional psoriatic skin (FCH>2, FDR<0.05). Interestingly, 9 of the 37 miRNAs, including miR-193b and miR-223 that have recently been described as deregulated in circulating peripheral blood mononuclear cells (PBMCs) from patients with psoriasis. Using flow cytometry and qRT-PCR, miR-193b and miR-223 were found to be expressed in Th17 cells. In conclusion, we demonstrate that LCM combined with small RNA sequencing provides a robust strategy to explore the global miRNA expression in the epidermal and dermal compartments of psoriatic skin. Furthermore, our results indicate that the altered local miRNA changes seen in the RD/ICs is reflected in the circulating immune cells, altogether emphasizing that miRNAs may contribute to a systemic component in the pathogenesis of psoriasis. Examination of the global miRNA expression in epidermis (Epi) and dermis (RD/ICs) of paired (non-lesional vs. lesional) psoriatic skin using a combination of laser-capture microdissection and barcoded small RNA sequencing
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