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e h spatial transcriptomics heterotypic cell network analysis shows colocalization  (Spatial Transcriptomics Inc)

 
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    Spatial Transcriptomics Inc e h spatial transcriptomics heterotypic cell network analysis shows colocalization
    STK24 is elevated in LUAD epithelial cells. A UMAP showing cell types after batch correction and dimensionality reduction clustering. B Bubble plot showing STK24 expression levels across various cell types. C Violin plot showing STK24 expression in normal and tumor cells across various cell types. D , E STK24 expression levels and regional variation analysis in spatial <t>transcriptomics.</t> F Violin plot showing STK24 expression in normal and tumor samples in the TCGA-LUAD cohort. G Immunohistochemistry results showing STK24 staining in LUAD and normal tissue samples from the HPA database. H Independent prognostic analysis to evaluate whether the association between STK24 and tumor survival is independent of traditional clinical variables. **** P < 0.0001, *** P < 0.001, ** P < 0.01, * P < 0.05, ns P > 0.05
    E H Spatial Transcriptomics Heterotypic Cell Network Analysis Shows Colocalization, supplied by Spatial Transcriptomics Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/colocalization+analysis/analysis+cell+colocalization+e+h+heterotypic+network+shows+spatial+transcriptomics/pmc12574022-295-0-3
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    Images

    1) Product Images from "Genome-wide association, single-cell, and spatial transcriptomics analyses reveal the role of the STK24-expressing positive cells in LUAD progression and the tumor microenvironment, identifying STK24 as a potential therapeutic target"

    Article Title: Genome-wide association, single-cell, and spatial transcriptomics analyses reveal the role of the STK24-expressing positive cells in LUAD progression and the tumor microenvironment, identifying STK24 as a potential therapeutic target

    Journal: Journal of Translational Medicine

    doi: 10.1186/s12967-025-07111-z

    STK24 is elevated in LUAD epithelial cells. A UMAP showing cell types after batch correction and dimensionality reduction clustering. B Bubble plot showing STK24 expression levels across various cell types. C Violin plot showing STK24 expression in normal and tumor cells across various cell types. D , E STK24 expression levels and regional variation analysis in spatial transcriptomics. F Violin plot showing STK24 expression in normal and tumor samples in the TCGA-LUAD cohort. G Immunohistochemistry results showing STK24 staining in LUAD and normal tissue samples from the HPA database. H Independent prognostic analysis to evaluate whether the association between STK24 and tumor survival is independent of traditional clinical variables. **** P < 0.0001, *** P < 0.001, ** P < 0.01, * P < 0.05, ns P > 0.05
    Figure Legend Snippet: STK24 is elevated in LUAD epithelial cells. A UMAP showing cell types after batch correction and dimensionality reduction clustering. B Bubble plot showing STK24 expression levels across various cell types. C Violin plot showing STK24 expression in normal and tumor cells across various cell types. D , E STK24 expression levels and regional variation analysis in spatial transcriptomics. F Violin plot showing STK24 expression in normal and tumor samples in the TCGA-LUAD cohort. G Immunohistochemistry results showing STK24 staining in LUAD and normal tissue samples from the HPA database. H Independent prognostic analysis to evaluate whether the association between STK24 and tumor survival is independent of traditional clinical variables. **** P < 0.0001, *** P < 0.001, ** P < 0.01, * P < 0.05, ns P > 0.05

    Techniques Used: Expressing, Immunohistochemistry, Staining

    Exploring the origins of STK24 Group cells through spatial transcriptomics (ST). A Schematic diagram of RCTD deconvolution and spatial trajectory analysis of spatial transcriptomics data. B – D Cell types after ST deconvolution. E , F Cell developmental trajectory and trajectory tree in ST ERS17014180. G , H Cell developmental trajectory and trajectory tree in ST ERS17014184. I , J Cell developmental trajectory and trajectory tree in ST ERS17014196. (K-M) Scatter plots showing the correlation between STK24 gene expression and developmental trajectory genes
    Figure Legend Snippet: Exploring the origins of STK24 Group cells through spatial transcriptomics (ST). A Schematic diagram of RCTD deconvolution and spatial trajectory analysis of spatial transcriptomics data. B – D Cell types after ST deconvolution. E , F Cell developmental trajectory and trajectory tree in ST ERS17014180. G , H Cell developmental trajectory and trajectory tree in ST ERS17014184. I , J Cell developmental trajectory and trajectory tree in ST ERS17014196. (K-M) Scatter plots showing the correlation between STK24 gene expression and developmental trajectory genes

    Techniques Used: Gene Expression

    Interactions between STK24-positive tumor epithelial cells (STK24posEpi) and fibroblasts. A Analysis of interaction strength between STK24posEpi and various cell types. B Activated pathways in various cell communications. C Analysis of activated ligand-receptor pairs. D Schematic diagram of Heterotypic cellular network analysis and cell co-localization analysis of spatial tran-scriptomics data. E – H Spatial transcriptomics heterotypic cell network analysis shows colocalization of STK24posEpi and fibroblasts. I Heatmap displaying cell–cell dependency analysis in the colocated, neighboring, and extended neighboring (15-point) regions of the spatial transcriptomics data
    Figure Legend Snippet: Interactions between STK24-positive tumor epithelial cells (STK24posEpi) and fibroblasts. A Analysis of interaction strength between STK24posEpi and various cell types. B Activated pathways in various cell communications. C Analysis of activated ligand-receptor pairs. D Schematic diagram of Heterotypic cellular network analysis and cell co-localization analysis of spatial tran-scriptomics data. E – H Spatial transcriptomics heterotypic cell network analysis shows colocalization of STK24posEpi and fibroblasts. I Heatmap displaying cell–cell dependency analysis in the colocated, neighboring, and extended neighboring (15-point) regions of the spatial transcriptomics data

    Techniques Used:

    Communication and signal flow changes between STK24posEpi and fibroblasts in spatial transcriptomics (ST). A Schematic diagram of Cell–cell communication analysis and signal flow direction analysis of spatial transcriptomics data. B Analysis of communication intensity between STK24posEpi and fibroblasts by integrating multiple spatial transcriptomics samples. C , D Communication between STK24posEpi and fibroblasts in the PDGF signaling pathway across different spatial transcriptomics samples. E Importance of Sender, Receiver, Mediator, and Influencer in different cell types in the PDGF signaling pathway. F , G Expression and co-expression of ligand-receptor pairs related to the PDGF signaling pathway in various spatial transcriptomics samples. H Importance of Sender, Receiver, Mediator, and Influencer in different cell types in the VEGF signaling pathway. I , J Communication between STK24posEpi and fibroblasts in the VEGF signaling pathway across different spatial transcriptomics samples. K Importance of Sender, Receiver, Mediator, and Influencer in different cell types in the MIF signaling pathway. L , M Communication between STK24posEpi and fibroblasts in the MIF signaling pathway across different spatial transcriptomics samples. N , O COMMOT analysis showing the direction of MIF signal flow and expression of Senders and Receivers in various spatial transcriptomics samples
    Figure Legend Snippet: Communication and signal flow changes between STK24posEpi and fibroblasts in spatial transcriptomics (ST). A Schematic diagram of Cell–cell communication analysis and signal flow direction analysis of spatial transcriptomics data. B Analysis of communication intensity between STK24posEpi and fibroblasts by integrating multiple spatial transcriptomics samples. C , D Communication between STK24posEpi and fibroblasts in the PDGF signaling pathway across different spatial transcriptomics samples. E Importance of Sender, Receiver, Mediator, and Influencer in different cell types in the PDGF signaling pathway. F , G Expression and co-expression of ligand-receptor pairs related to the PDGF signaling pathway in various spatial transcriptomics samples. H Importance of Sender, Receiver, Mediator, and Influencer in different cell types in the VEGF signaling pathway. I , J Communication between STK24posEpi and fibroblasts in the VEGF signaling pathway across different spatial transcriptomics samples. K Importance of Sender, Receiver, Mediator, and Influencer in different cell types in the MIF signaling pathway. L , M Communication between STK24posEpi and fibroblasts in the MIF signaling pathway across different spatial transcriptomics samples. N , O COMMOT analysis showing the direction of MIF signal flow and expression of Senders and Receivers in various spatial transcriptomics samples

    Techniques Used: Expressing

    Exploration of apoptosis and STK24posEpi-related pathways in spatial transcriptomics (ST). A Schematic diagram of Pathway dependency analysis of spatial transcriptomics data. B Enrichment results for the ST apoptosis pathway and comparison of differences between regions. C Heatmap displaying apoptosis-dependent cell pathways within regions in the spatial context. D , F Network diagrams showing apoptosis-dependent cell pathways in intra ( D ), juxta_5 ( E ), and para_15 ( F ) regions. G Enrichment results for the ST cell proliferation pathway and comparison of differences between the STK24 Group. H Enrichment results for the ST cell damage pathway and comparison of differences between the STK24 Group. I Comparison of ST cell cycle and DNA repair pathways between the STK24 Groups. J , K Heatmaps showing cell pathway dependency analysis for different cell types within the intra ( J ) and para_15 ( K ) regions in the spatial context. **** P < 0.0001, *** P < 0.001, ** P < 0.01, * P < 0.05, ns P > 0.05
    Figure Legend Snippet: Exploration of apoptosis and STK24posEpi-related pathways in spatial transcriptomics (ST). A Schematic diagram of Pathway dependency analysis of spatial transcriptomics data. B Enrichment results for the ST apoptosis pathway and comparison of differences between regions. C Heatmap displaying apoptosis-dependent cell pathways within regions in the spatial context. D , F Network diagrams showing apoptosis-dependent cell pathways in intra ( D ), juxta_5 ( E ), and para_15 ( F ) regions. G Enrichment results for the ST cell proliferation pathway and comparison of differences between the STK24 Group. H Enrichment results for the ST cell damage pathway and comparison of differences between the STK24 Group. I Comparison of ST cell cycle and DNA repair pathways between the STK24 Groups. J , K Heatmaps showing cell pathway dependency analysis for different cell types within the intra ( J ) and para_15 ( K ) regions in the spatial context. **** P < 0.0001, *** P < 0.001, ** P < 0.01, * P < 0.05, ns P > 0.05

    Techniques Used: Comparison

    Clinical significance of STK24posEpi. A Schematic diagram of Homotypic cellular network analysis of spatial transcriptomics data. B Homotypic cell network analysis of STK24posEpi in spatial transcriptomics. C Survival analysis of STK24posEpi across multiple bulk transcriptome cohorts after Bayesian deconvolution. D Comparison of tumor-infiltrating lymphocyte scores between STK24posEpi Groups in the TCGA-LUAD cohort. E Histological slides showing differences in tumor-infiltrating lymphocytes between STK24posEpi Groups in the TCGA-LUAD cohort. F Correlation analysis of STK24posEpi and B cells in multiple bulk transcriptomes. G Differential expression of BCR signaling pathway-related genes between STK24posEpi Groups in the TCGA-LUAD cohort. H Differential expression of antigen processing and presentation pathway-related genes between STK24posEpi Groups in the TCGA-LUAD cohort. I Comparison of clinical factors between STK24posEpi Groups in the TCGA-LUAD cohort. **** P < 0.0001, *** P < 0.001, ** P < 0.01, * P < 0.05, ns P > 0.05
    Figure Legend Snippet: Clinical significance of STK24posEpi. A Schematic diagram of Homotypic cellular network analysis of spatial transcriptomics data. B Homotypic cell network analysis of STK24posEpi in spatial transcriptomics. C Survival analysis of STK24posEpi across multiple bulk transcriptome cohorts after Bayesian deconvolution. D Comparison of tumor-infiltrating lymphocyte scores between STK24posEpi Groups in the TCGA-LUAD cohort. E Histological slides showing differences in tumor-infiltrating lymphocytes between STK24posEpi Groups in the TCGA-LUAD cohort. F Correlation analysis of STK24posEpi and B cells in multiple bulk transcriptomes. G Differential expression of BCR signaling pathway-related genes between STK24posEpi Groups in the TCGA-LUAD cohort. H Differential expression of antigen processing and presentation pathway-related genes between STK24posEpi Groups in the TCGA-LUAD cohort. I Comparison of clinical factors between STK24posEpi Groups in the TCGA-LUAD cohort. **** P < 0.0001, *** P < 0.001, ** P < 0.01, * P < 0.05, ns P > 0.05

    Techniques Used: Comparison, Quantitative Proteomics

    Related Articles

    Expressing:



    Immunohistochemistry:



    Staining:



    Gene Expression:



    Comparison:



    Quantitative Proteomics:





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    Image Search Results


    A-B ) Volume of mitochondria colocalized to autophagosomes expressed in absolute value or relative to total mitochondrial volume in in situ fixed, freshly sorted quiescent and 4h in vitro activated MuSCs ( n =48-55 cells from 3 mice in each group and experimental condition). C) Confocal image and 3D reconstruction of TOM20-labeled mitochondria (green) and LC3-labeled autophagosomes (red) in each of the experimental conditions examined. The volume of mitochondria overlapping with autophagosomes is shown in yellow in the right-end panels, where mitochondria and autophagosomes surfaces have been removed to highlight changes in colocalization. D) Colocalization of PARKIN to TOM20-labeled mitochondria expressed in absolute volume of PARKIN + structures overlapping with mitochondria per cell ( n =25-36 cells from 3 mice in each group and experimental condition). E) Proportion of TOM20-labeled mitochondria labeled with PARKIN, computed using data presented in panel D and total mitochondrial content (Fig. S1A). F) Confocal image and 3D reconstruction of TOM20-labeled mitochondria (green) and PARKIN-labeled structures (red) in each of the experimental conditions examined. The volume of PARKIN overlapping with mitochondria is shown in yellow in the right-end panels, where mitochondria and PARKIN + surfaces have been removed to highlight changes in colocalization. G) Total cellular PARKIN content in the indicated experimental conditions. H) Parkin transcript levels in MuSCs purified from muscles that were fixed in situ in healthy uninjured conditions or at 15, 30, 60, 90 and 120 min after CTX injury. Data is taken from (GSE163856 ). All data are presented as mean ± SEM. ns: not significant, *: p<0.05, **: p<0.01, ***: p<0.001, ****: p<0001 on unpaired two-tailed t tests or one-way ANOVAs. I) Changes in the transcript levels of ubiquitin- and receptor-dependent mitophagy in three transcriptomics datasets (GSE70736, GSE55490, GSE47177 , , ) that compared quiescent and in vivo activated MuSCs 36-72h following muscle injury with CTX or BaCl 2 . Each dot represents data from an individual dataset and a specific timepoints. Genes shown where differentially expressed in all datasets with a q value of less than 0.05. Level of statistical significance shown is based on the average q value.

    Journal: bioRxiv

    Article Title: Loss of Parkin Disrupts Nuclear and Mitochondrial Programs Required for Muscle Regeneration

    doi: 10.64898/2026.03.20.712989

    Figure Lengend Snippet: A-B ) Volume of mitochondria colocalized to autophagosomes expressed in absolute value or relative to total mitochondrial volume in in situ fixed, freshly sorted quiescent and 4h in vitro activated MuSCs ( n =48-55 cells from 3 mice in each group and experimental condition). C) Confocal image and 3D reconstruction of TOM20-labeled mitochondria (green) and LC3-labeled autophagosomes (red) in each of the experimental conditions examined. The volume of mitochondria overlapping with autophagosomes is shown in yellow in the right-end panels, where mitochondria and autophagosomes surfaces have been removed to highlight changes in colocalization. D) Colocalization of PARKIN to TOM20-labeled mitochondria expressed in absolute volume of PARKIN + structures overlapping with mitochondria per cell ( n =25-36 cells from 3 mice in each group and experimental condition). E) Proportion of TOM20-labeled mitochondria labeled with PARKIN, computed using data presented in panel D and total mitochondrial content (Fig. S1A). F) Confocal image and 3D reconstruction of TOM20-labeled mitochondria (green) and PARKIN-labeled structures (red) in each of the experimental conditions examined. The volume of PARKIN overlapping with mitochondria is shown in yellow in the right-end panels, where mitochondria and PARKIN + surfaces have been removed to highlight changes in colocalization. G) Total cellular PARKIN content in the indicated experimental conditions. H) Parkin transcript levels in MuSCs purified from muscles that were fixed in situ in healthy uninjured conditions or at 15, 30, 60, 90 and 120 min after CTX injury. Data is taken from (GSE163856 ). All data are presented as mean ± SEM. ns: not significant, *: p<0.05, **: p<0.01, ***: p<0.001, ****: p<0001 on unpaired two-tailed t tests or one-way ANOVAs. I) Changes in the transcript levels of ubiquitin- and receptor-dependent mitophagy in three transcriptomics datasets (GSE70736, GSE55490, GSE47177 , , ) that compared quiescent and in vivo activated MuSCs 36-72h following muscle injury with CTX or BaCl 2 . Each dot represents data from an individual dataset and a specific timepoints. Genes shown where differentially expressed in all datasets with a q value of less than 0.05. Level of statistical significance shown is based on the average q value.

    Article Snippet: Volume reconstruction and surface/surface colocalization analysis was performed in Imaris using fixed settings.

    Techniques: In Situ, In Vitro, Labeling, Purification, Muscles, Two Tailed Test, Ubiquitin Proteomics, Transcriptomics, In Vivo

    A-C) Parkin transcript and protein levels in FACS-purified MuSCs from MuSC Park2 +/+ and MuSC Park2 -/- mice 1 week after the last tamoxifen treatment ( n =4 mice per group). Protein abundance was quantified as the total volume of PARKIN + structures (B) in cells labeled with antibodies against PARKIN and TOM20 ( n =11-70 cells from 2-4 mice per group,) (C). D-E) transcript abundance expressed in Transcript Per Million (TPM) for genes involved in Parkin- and Receptor-mediated mitophagy ( n =3 mice per group). F-G) Volume of mitochondria colocalized to autophagosomes expressed in absolute value or relative to total mitochondrial volume in freshly sorted quiescent and 4h in vitro activated MuSCs ( n =41-52 cells from 3 mice in each group). H) Confocal image and 3D reconstruction of TOM20-labeled mitochondria (green) and LC3-labeled autophagosomes (red) in each of the experimental conditions examined. The volume of mitochondria overlapping with autophagosomes is shown in yellow in the right-end panels, where mitochondria and autophagosomes surfaces have been removed to highlight changes in colocalization. All data are presented as mean ±SEM. ns: not significant, *: p<0.05, **: p<0.01, ***: p<0.001, ****: p<0001 on unpaired two-tailed t tests or one-way ANOVAs.

    Journal: bioRxiv

    Article Title: Loss of Parkin Disrupts Nuclear and Mitochondrial Programs Required for Muscle Regeneration

    doi: 10.64898/2026.03.20.712989

    Figure Lengend Snippet: A-C) Parkin transcript and protein levels in FACS-purified MuSCs from MuSC Park2 +/+ and MuSC Park2 -/- mice 1 week after the last tamoxifen treatment ( n =4 mice per group). Protein abundance was quantified as the total volume of PARKIN + structures (B) in cells labeled with antibodies against PARKIN and TOM20 ( n =11-70 cells from 2-4 mice per group,) (C). D-E) transcript abundance expressed in Transcript Per Million (TPM) for genes involved in Parkin- and Receptor-mediated mitophagy ( n =3 mice per group). F-G) Volume of mitochondria colocalized to autophagosomes expressed in absolute value or relative to total mitochondrial volume in freshly sorted quiescent and 4h in vitro activated MuSCs ( n =41-52 cells from 3 mice in each group). H) Confocal image and 3D reconstruction of TOM20-labeled mitochondria (green) and LC3-labeled autophagosomes (red) in each of the experimental conditions examined. The volume of mitochondria overlapping with autophagosomes is shown in yellow in the right-end panels, where mitochondria and autophagosomes surfaces have been removed to highlight changes in colocalization. All data are presented as mean ±SEM. ns: not significant, *: p<0.05, **: p<0.01, ***: p<0.001, ****: p<0001 on unpaired two-tailed t tests or one-way ANOVAs.

    Article Snippet: Volume reconstruction and surface/surface colocalization analysis was performed in Imaris using fixed settings.

    Techniques: Purification, Quantitative Proteomics, Labeling, In Vitro, Two Tailed Test