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spatial transcriptomics sequencing data  (Spatial Transcriptomics Inc)

 
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    Spatial Transcriptomics Inc spatial transcriptomics sequencing data
    Investigations on SGMS2—related Cellular and Molecular Interactions in Hepatocellular Carcinoma. a Western blotting analysis of SGMS2 expression in THP—1 cells and differentiated macrophages. Each experiment was independently repeated three times. b , c Apoptosis levels of Huh7 tumor cells co—cultured with control macrophages and SGMS2—overexpressing macrophages were detected by flow cytometry (FCM). d Expression of SGMS2 in spatial <t>transcriptomics</t> <t>sequencing</t> data. e Abundance estimation of the CD56dimCD16highNR4A3high NK cell population by single—sample gene—set enrichment analysis (ssGSEA). f Multiplex immunofluorescence (mIF) images of SGMS2, CD68, CD16, CD56, and NR4A3 markers in 6 human HCC tissue samples. “Zoom macrophage” indicates the aggregation area of SGMS2—positive macrophages, and “Zoom NK cell” represents the CD56dimCD16highNR4A3high NK cells. The scale bar is 50 um or 20 um. g Scatter plots showing the density of CD56dimCD16highNR4A3high NK cells between patients with high and low infiltration of SGMS2—positive macrophages. Statistical analysis was performed using the Mann—Whitney U test. h Pearson correlation analysis of the density of CD56dimCD16highNR4A3high NK cells and the density of SGMS2—positive macrophages. i Kaplan—Meier analysis of OS, RFS, and early RFS in HCC patients with different infiltration densities of SGMS2—positive macrophages and CD56dimCD16highNR4A3high NK cells. Survival distributions were compared using the log—rank test. Statistical significance is indicated as follows: * P < 0.05, ** P < 0.01, *** P < 0.001; ns indicates no significant difference
    Spatial Transcriptomics Sequencing Data, 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/spatial+transcriptomics+sequencing+data/data+sequencing+spatial+transcriptomics/pmc12763894-100-0-0
    Average 86 stars, based on 1 article reviews
    spatial transcriptomics sequencing data - by Bioz Stars, 2026-10
    86/100 stars

    Images

    1) Product Images from "SGMS2+ macrophages enhance NR4A3hi NK cell infiltration to improve prognosis and PD-1 treatment efficacy in hepatocellular carcinoma"

    Article Title: SGMS2+ macrophages enhance NR4A3hi NK cell infiltration to improve prognosis and PD-1 treatment efficacy in hepatocellular carcinoma

    Journal: Journal of Translational Medicine

    doi: 10.1186/s12967-025-07040-x

    Investigations on SGMS2—related Cellular and Molecular Interactions in Hepatocellular Carcinoma. a Western blotting analysis of SGMS2 expression in THP—1 cells and differentiated macrophages. Each experiment was independently repeated three times. b , c Apoptosis levels of Huh7 tumor cells co—cultured with control macrophages and SGMS2—overexpressing macrophages were detected by flow cytometry (FCM). d Expression of SGMS2 in spatial transcriptomics sequencing data. e Abundance estimation of the CD56dimCD16highNR4A3high NK cell population by single—sample gene—set enrichment analysis (ssGSEA). f Multiplex immunofluorescence (mIF) images of SGMS2, CD68, CD16, CD56, and NR4A3 markers in 6 human HCC tissue samples. “Zoom macrophage” indicates the aggregation area of SGMS2—positive macrophages, and “Zoom NK cell” represents the CD56dimCD16highNR4A3high NK cells. The scale bar is 50 um or 20 um. g Scatter plots showing the density of CD56dimCD16highNR4A3high NK cells between patients with high and low infiltration of SGMS2—positive macrophages. Statistical analysis was performed using the Mann—Whitney U test. h Pearson correlation analysis of the density of CD56dimCD16highNR4A3high NK cells and the density of SGMS2—positive macrophages. i Kaplan—Meier analysis of OS, RFS, and early RFS in HCC patients with different infiltration densities of SGMS2—positive macrophages and CD56dimCD16highNR4A3high NK cells. Survival distributions were compared using the log—rank test. Statistical significance is indicated as follows: * P < 0.05, ** P < 0.01, *** P < 0.001; ns indicates no significant difference
    Figure Legend Snippet: Investigations on SGMS2—related Cellular and Molecular Interactions in Hepatocellular Carcinoma. a Western blotting analysis of SGMS2 expression in THP—1 cells and differentiated macrophages. Each experiment was independently repeated three times. b , c Apoptosis levels of Huh7 tumor cells co—cultured with control macrophages and SGMS2—overexpressing macrophages were detected by flow cytometry (FCM). d Expression of SGMS2 in spatial transcriptomics sequencing data. e Abundance estimation of the CD56dimCD16highNR4A3high NK cell population by single—sample gene—set enrichment analysis (ssGSEA). f Multiplex immunofluorescence (mIF) images of SGMS2, CD68, CD16, CD56, and NR4A3 markers in 6 human HCC tissue samples. “Zoom macrophage” indicates the aggregation area of SGMS2—positive macrophages, and “Zoom NK cell” represents the CD56dimCD16highNR4A3high NK cells. The scale bar is 50 um or 20 um. g Scatter plots showing the density of CD56dimCD16highNR4A3high NK cells between patients with high and low infiltration of SGMS2—positive macrophages. Statistical analysis was performed using the Mann—Whitney U test. h Pearson correlation analysis of the density of CD56dimCD16highNR4A3high NK cells and the density of SGMS2—positive macrophages. i Kaplan—Meier analysis of OS, RFS, and early RFS in HCC patients with different infiltration densities of SGMS2—positive macrophages and CD56dimCD16highNR4A3high NK cells. Survival distributions were compared using the log—rank test. Statistical significance is indicated as follows: * P < 0.05, ** P < 0.01, *** P < 0.001; ns indicates no significant difference

    Techniques Used: Western Blot, Expressing, Cell Culture, Control, Flow Cytometry, Sequencing, Multiplex Assay, Immunofluorescence, MANN-WHITNEY

    Related Articles

    Expressing:

    Article Title: Multiomic analysis of CCNE1 amplification associated molecular and immune features in gynecological cancers
    Article Snippet: .. C Spatial transcriptomics ( GSM8207499 ) revealed diffuse CCNE1 expression without distinct clustering, with elevated VEGFB and FBLN2 levels observed in CCNE1-high regions. ..

    Spatial Transcriptomics:


    Article Title: Multi-omics integration and machine learning define robust molecular subtypes and prognostic signatures in hepatocellular carcinoma.
    Article Snippet: .. Single-cell RNA-seq data were obtained from GSE166635 [20] and spatial transcriptomics data (HCC1R and HCC4R) from GSE238264 [21]. ..

    Article Title: SpaConTDS: A multimodal contrastive learning framework for identifying spatial domains by applying tuple disturbing strategy
    Article Snippet: .. In-depth exploration of the multimodal information within Spatial Transcriptomics (ST) data is essential for understanding the heterogeneity of tissue structure, investigating biological functions and tracking disease progression. ..

    Article Title: Single-cell and spatial transcriptomics unveils key regulators governing cell differentiation for Schistosoma sexual development
    Article Snippet: .. The sequencing data from Stereo-seq spatial transcriptomics was processed using Stereo-seq Analysis Workflow (SAW) v8.0 ( https://en.stomics.tech ). ..

    Article Title: SGMS2+ macrophages enhance NR4A3hi NK cell infiltration to improve prognosis and PD-1 treatment efficacy in hepatocellular carcinoma
    Article Snippet: .. Spatial transcriptomics sequencing data were obtained from http://lifeome.net/supp/livercancer-st/data.htm and analyzed using Seurat in R. Subsequently, SCTtransform normalization was performed. ..

    Article Title: SpaConTDS: A multimodal contrastive learning framework for identifying spatial domains by applying tuple disturbing strategy.
    Article Snippet: .. In-depth exploration of the multimodal information within Spatial Transcriptomics (ST) data is essential for understanding the heterogeneity of tissue structure, investigating biological functions and tracking disease progression. ..

    Single Cell:

    Article Title: Multi-omics integration and machine learning define robust molecular subtypes and prognostic signatures in hepatocellular carcinoma.
    Article Snippet: .. Single-cell RNA-seq data were obtained from GSE166635 [20] and spatial transcriptomics data (HCC1R and HCC4R) from GSE238264 [21]. ..

    RNA Sequencing:

    Article Title: Multi-omics integration and machine learning define robust molecular subtypes and prognostic signatures in hepatocellular carcinoma.
    Article Snippet: .. Single-cell RNA-seq data were obtained from GSE166635 [20] and spatial transcriptomics data (HCC1R and HCC4R) from GSE238264 [21]. ..

    Gene Expression:

    Article Title: Multiomic analysis of CCNE1 amplification associated molecular and immune features in gynecological cancers
    Article Snippet: .. C Spatial transcriptomics ( GSM7019835 ) depicting the gene expression patterns of CCNE1, EPCAM (epithelial marker), and the colocalized genes ARHGAP1 and STK24, which are involved in structural remodeling and cell motility. ..

    Marker:

    Article Title: Multiomic analysis of CCNE1 amplification associated molecular and immune features in gynecological cancers
    Article Snippet: .. C Spatial transcriptomics ( GSM7019835 ) depicting the gene expression patterns of CCNE1, EPCAM (epithelial marker), and the colocalized genes ARHGAP1 and STK24, which are involved in structural remodeling and cell motility. ..

    Biomarker Discovery:

    Article Title: SpaConTDS: A multimodal contrastive learning framework for identifying spatial domains by applying tuple disturbing strategy
    Article Snippet: .. In-depth exploration of the multimodal information within Spatial Transcriptomics (ST) data is essential for understanding the heterogeneity of tissue structure, investigating biological functions and tracking disease progression. ..

    Article Title: SpaConTDS: A multimodal contrastive learning framework for identifying spatial domains by applying tuple disturbing strategy.
    Article Snippet: .. In-depth exploration of the multimodal information within Spatial Transcriptomics (ST) data is essential for understanding the heterogeneity of tissue structure, investigating biological functions and tracking disease progression. ..

    Sequencing:

    Article Title: Single-cell and spatial transcriptomics unveils key regulators governing cell differentiation for Schistosoma sexual development
    Article Snippet: .. The sequencing data from Stereo-seq spatial transcriptomics was processed using Stereo-seq Analysis Workflow (SAW) v8.0 ( https://en.stomics.tech ). ..

    Article Title: SGMS2+ macrophages enhance NR4A3hi NK cell infiltration to improve prognosis and PD-1 treatment efficacy in hepatocellular carcinoma
    Article Snippet: .. Spatial transcriptomics sequencing data were obtained from http://lifeome.net/supp/livercancer-st/data.htm and analyzed using Seurat in R. Subsequently, SCTtransform normalization was performed. ..



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    Image Search Results


    Investigations on SGMS2—related Cellular and Molecular Interactions in Hepatocellular Carcinoma. a Western blotting analysis of SGMS2 expression in THP—1 cells and differentiated macrophages. Each experiment was independently repeated three times. b , c Apoptosis levels of Huh7 tumor cells co—cultured with control macrophages and SGMS2—overexpressing macrophages were detected by flow cytometry (FCM). d Expression of SGMS2 in spatial transcriptomics sequencing data. e Abundance estimation of the CD56dimCD16highNR4A3high NK cell population by single—sample gene—set enrichment analysis (ssGSEA). f Multiplex immunofluorescence (mIF) images of SGMS2, CD68, CD16, CD56, and NR4A3 markers in 6 human HCC tissue samples. “Zoom macrophage” indicates the aggregation area of SGMS2—positive macrophages, and “Zoom NK cell” represents the CD56dimCD16highNR4A3high NK cells. The scale bar is 50 um or 20 um. g Scatter plots showing the density of CD56dimCD16highNR4A3high NK cells between patients with high and low infiltration of SGMS2—positive macrophages. Statistical analysis was performed using the Mann—Whitney U test. h Pearson correlation analysis of the density of CD56dimCD16highNR4A3high NK cells and the density of SGMS2—positive macrophages. i Kaplan—Meier analysis of OS, RFS, and early RFS in HCC patients with different infiltration densities of SGMS2—positive macrophages and CD56dimCD16highNR4A3high NK cells. Survival distributions were compared using the log—rank test. Statistical significance is indicated as follows: * P < 0.05, ** P < 0.01, *** P < 0.001; ns indicates no significant difference

    Journal: Journal of Translational Medicine

    Article Title: SGMS2+ macrophages enhance NR4A3hi NK cell infiltration to improve prognosis and PD-1 treatment efficacy in hepatocellular carcinoma

    doi: 10.1186/s12967-025-07040-x

    Figure Lengend Snippet: Investigations on SGMS2—related Cellular and Molecular Interactions in Hepatocellular Carcinoma. a Western blotting analysis of SGMS2 expression in THP—1 cells and differentiated macrophages. Each experiment was independently repeated three times. b , c Apoptosis levels of Huh7 tumor cells co—cultured with control macrophages and SGMS2—overexpressing macrophages were detected by flow cytometry (FCM). d Expression of SGMS2 in spatial transcriptomics sequencing data. e Abundance estimation of the CD56dimCD16highNR4A3high NK cell population by single—sample gene—set enrichment analysis (ssGSEA). f Multiplex immunofluorescence (mIF) images of SGMS2, CD68, CD16, CD56, and NR4A3 markers in 6 human HCC tissue samples. “Zoom macrophage” indicates the aggregation area of SGMS2—positive macrophages, and “Zoom NK cell” represents the CD56dimCD16highNR4A3high NK cells. The scale bar is 50 um or 20 um. g Scatter plots showing the density of CD56dimCD16highNR4A3high NK cells between patients with high and low infiltration of SGMS2—positive macrophages. Statistical analysis was performed using the Mann—Whitney U test. h Pearson correlation analysis of the density of CD56dimCD16highNR4A3high NK cells and the density of SGMS2—positive macrophages. i Kaplan—Meier analysis of OS, RFS, and early RFS in HCC patients with different infiltration densities of SGMS2—positive macrophages and CD56dimCD16highNR4A3high NK cells. Survival distributions were compared using the log—rank test. Statistical significance is indicated as follows: * P < 0.05, ** P < 0.01, *** P < 0.001; ns indicates no significant difference

    Article Snippet: Spatial transcriptomics sequencing data were obtained from http://lifeome.net/supp/livercancer-st/data.htm and analyzed using Seurat in R. Subsequently, SCTtransform normalization was performed.

    Techniques: Western Blot, Expressing, Cell Culture, Control, Flow Cytometry, Sequencing, Multiplex Assay, Immunofluorescence, MANN-WHITNEY