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        <datestamp>2026-09-30T04:47:54Z</datestamp>
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          <dc:title>Data Sheet 2_Integration of bulk and single-cell transcriptomics with spatial analysis identifies candidate hub genes and inferred regulatory programs in atopic dermatitis.zip</dc:title>
          <dc:creator>Yuqiao Chen (9602267)</dc:creator>
          <dc:creator>Yulong Pan (25141524)</dc:creator>
          <dc:creator>Jiajie Chen (386048)</dc:creator>
          <dc:creator>Li Lin (111038)</dc:creator>
          <dc:creator>Shengxiu Liu (4506682)</dc:creator>
          <dc:subject>Genetic Immunology</dc:subject>
          <dc:subject>atopic dermatitis</dc:subject>
          <dc:subject>candidate hub genes</dc:subject>
          <dc:subject>inferred regulatory programs</dc:subject>
          <dc:subject>multi-omics</dc:subject>
          <dc:subject>single-cell RNA-seq</dc:subject>
          <dc:subject>spatial transcriptomics</dc:subject>
          <dc:description>Background&lt;p&gt;Atopic dermatitis (AD) is a common chronic inflammatory disorder of the skin. Despite the availability of targeted biologics like dupilumab, heterogeneous treatment responses persist, highlighting the need for reliable biomarkers and a deeper understanding of cell-type-associated molecular programs within the tissue microenvironment.&lt;/p&gt;Methods&lt;p&gt;This exploratory study integrated public microarray, single-cell RNA sequencing, and spatial transcriptomic datasets. GSE130588, comprising 124 lesional AD skin samples, was used for weighted gene co-expression network analysis (WGCNA). GSE59294 comprised 40 skin biopsies from 18 patients, including 16 pre-treatment lesional, 12 post-treatment lesional, 7 pre-treatment non-lesional, and 5 post-treatment non-lesional samples, and was used for differential expression analysis. The single-cell query cohort comprised 66,846 cells from 25 samples, with downstream analyses restricted to 19 blister-derived samples. Regulon activity was computationally inferred. GSE197023 comprised 20 spatial transcriptomic samples, including 7 lesional AD, 7 non-lesional AD, and 6 healthy-control samples, and was analyzed using cell-population deconvolution. CCR7 immunoreactivity was assessed by immunohistochemistry in independent healthy-control and lesional AD skin samples (n = 5 per group) analyze.&lt;/p&gt;Results&lt;p&gt;WGCNA identified disease-severity-associated gene modules enriched in immune and cell-cycle-related processes. Nominal-P-value-based integration with differential expression results identified seven exploratory candidate hub genes (GZMB, CCR7, GPR183, MMP12, IL7R, RGS1, and KLHDC7B) associated with immune- cell abundance patterns. FDR-adjusted sensitivity analysis supported MMP12 and RGS1 in the lesional-versus-non-lesional comparison, whereas none of the seven genes reached nominal or FDR-adjusted significance in the paired treatment analysis. Single-cell reference mapping showed cell-type-associated expression of GZMB in cytotoxic T-cell populations and CCR7 and MMP12 in dendritic-cell subsets. Computational regulon analysis identified candidate cell-type-associated regulatory signals and differences in inferred regulon activity across treatment-state groups. Spatial deconvolution indicated predominantly dermal distributions of inferred immune-cell populations. Immunohistochemical assessment showed higher relative CCR7 immunoreactivity in lesional AD skin than in healthy-control skin.&lt;/p&gt;Conclusion&lt;p&gt;These cross-modal analyses linked candidate molecular signals todendritic-cell- and T- cell-associated patterns in AD. These findings are exploratory and hypothesis-generating and do not establish validated biomarkers, causal regulatory mechanisms, or predictors of treatment response. Independent cohort replication and functional and cell-type-specific validation are required.&lt;/p&gt;</dc:description>
          <dc:date>2026-09-30T04:47:54Z</dc:date>
          <dc:type>Dataset</dc:type>
          <dc:type>Dataset</dc:type>
          <dc:identifier>10.3389/fimmu.2026.1863607.s003</dc:identifier>
          <dc:relation>https://figshare.com/articles/dataset/Data_Sheet_2_Integration_of_bulk_and_single-cell_transcriptomics_with_spatial_analysis_identifies_candidate_hub_genes_and_inferred_regulatory_programs_in_atopic_dermatitis_zip/34029705</dc:relation>
          <dc:rights>CC BY 4.0</dc:rights>
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