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visium ffpe technology ffpe tissue sections  (Spatial Transcriptomics Inc)

 
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    Spatial Transcriptomics Inc visium ffpe technology ffpe tissue sections
    Fig. 4 | NP137 treatment inhibits EMT in patients with EC. a, Diagram showing EMT score calculated with Mak’s signature20 from RNA-seq of biopsies before (C1D1) and following two cycles of NP137 (C3D1) treatment (n = 12). Boxplots represent mean (25th–75th), whiskers range from minimum to maximum values and paired samples are identified on single-value representation; *P = 0.0161 by two-sided t-test. b, Swimmer plots showing individual evolution of EMT score for each patient; ΔEMT is the EMT score at C3D1 minus that at C1D1; ΔEMT < 0 means evolution towards epithelial phenotype (green) and >0 towards mesenchymal (red). c, Percentage of EpCAM high-expressing cells in C1D1 versus C3D1 biopsy samples as identified by IHC; *P = 0.0313 by Wilcoxon two-sided test (n = 6 patients). Boxplots represent mean (25th–75th), whiskers range from minimum to maximum values and paired samples are identified on single-value representation. d, Representative IHC of EpCAM in tumours in C1D1 and C3D1 for patient nos. 01-030, 01-035 and 01-040. Scale bar, 50 µm. e, Representative images of pancytokeratin (PanKRT) and vimentin (VIM) expression (colocalization of pancytokeratin (green) and vimentin (red) in the merged picture, right) in primary endometrial adenocarcinoma from patient no. 01-040 before and after NP137 treatment. Scale bars, 50 μm. Quantifications were performed on the full slides and similar results were observed for patient nos. 01-030 and 01-034. f, Analysis of tumour cell compartment in patient nos. 01-034 and 01-039 by <t>Visium</t> spatial gene expression. Violin plot of EMT UCell normalized enrichment score (NES) from tumoural histologically selected Visium spot between cells of C1D1 and C3D1 biopsy. ***P < 0.01 by Mann–Whitney two-sided test.
    Visium Ffpe Technology Ffpe Tissue Sections, 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+methods+10x+visium/sections+tissue/pm37532934-375-3-0
    Average 86 stars, based on 1 article reviews
    visium ffpe technology ffpe tissue sections - by Bioz Stars, 2026-11
    86/100 stars

    Images

    1) Product Images from "Netrin-1 blockade inhibits tumour growth and EMT features in endometrial cancer."

    Article Title: Netrin-1 blockade inhibits tumour growth and EMT features in endometrial cancer.

    Journal: Nature

    doi: 10.1038/s41586-023-06367-z

    Fig. 4 | NP137 treatment inhibits EMT in patients with EC. a, Diagram showing EMT score calculated with Mak’s signature20 from RNA-seq of biopsies before (C1D1) and following two cycles of NP137 (C3D1) treatment (n = 12). Boxplots represent mean (25th–75th), whiskers range from minimum to maximum values and paired samples are identified on single-value representation; *P = 0.0161 by two-sided t-test. b, Swimmer plots showing individual evolution of EMT score for each patient; ΔEMT is the EMT score at C3D1 minus that at C1D1; ΔEMT < 0 means evolution towards epithelial phenotype (green) and >0 towards mesenchymal (red). c, Percentage of EpCAM high-expressing cells in C1D1 versus C3D1 biopsy samples as identified by IHC; *P = 0.0313 by Wilcoxon two-sided test (n = 6 patients). Boxplots represent mean (25th–75th), whiskers range from minimum to maximum values and paired samples are identified on single-value representation. d, Representative IHC of EpCAM in tumours in C1D1 and C3D1 for patient nos. 01-030, 01-035 and 01-040. Scale bar, 50 µm. e, Representative images of pancytokeratin (PanKRT) and vimentin (VIM) expression (colocalization of pancytokeratin (green) and vimentin (red) in the merged picture, right) in primary endometrial adenocarcinoma from patient no. 01-040 before and after NP137 treatment. Scale bars, 50 μm. Quantifications were performed on the full slides and similar results were observed for patient nos. 01-030 and 01-034. f, Analysis of tumour cell compartment in patient nos. 01-034 and 01-039 by Visium spatial gene expression. Violin plot of EMT UCell normalized enrichment score (NES) from tumoural histologically selected Visium spot between cells of C1D1 and C3D1 biopsy. ***P < 0.01 by Mann–Whitney two-sided test.
    Figure Legend Snippet: Fig. 4 | NP137 treatment inhibits EMT in patients with EC. a, Diagram showing EMT score calculated with Mak’s signature20 from RNA-seq of biopsies before (C1D1) and following two cycles of NP137 (C3D1) treatment (n = 12). Boxplots represent mean (25th–75th), whiskers range from minimum to maximum values and paired samples are identified on single-value representation; *P = 0.0161 by two-sided t-test. b, Swimmer plots showing individual evolution of EMT score for each patient; ΔEMT is the EMT score at C3D1 minus that at C1D1; ΔEMT < 0 means evolution towards epithelial phenotype (green) and >0 towards mesenchymal (red). c, Percentage of EpCAM high-expressing cells in C1D1 versus C3D1 biopsy samples as identified by IHC; *P = 0.0313 by Wilcoxon two-sided test (n = 6 patients). Boxplots represent mean (25th–75th), whiskers range from minimum to maximum values and paired samples are identified on single-value representation. d, Representative IHC of EpCAM in tumours in C1D1 and C3D1 for patient nos. 01-030, 01-035 and 01-040. Scale bar, 50 µm. e, Representative images of pancytokeratin (PanKRT) and vimentin (VIM) expression (colocalization of pancytokeratin (green) and vimentin (red) in the merged picture, right) in primary endometrial adenocarcinoma from patient no. 01-040 before and after NP137 treatment. Scale bars, 50 μm. Quantifications were performed on the full slides and similar results were observed for patient nos. 01-030 and 01-034. f, Analysis of tumour cell compartment in patient nos. 01-034 and 01-039 by Visium spatial gene expression. Violin plot of EMT UCell normalized enrichment score (NES) from tumoural histologically selected Visium spot between cells of C1D1 and C3D1 biopsy. ***P < 0.01 by Mann–Whitney two-sided test.

    Techniques Used: RNA Sequencing, Expressing, Paraffin-embedded Immunohistochemistry, Gene Expression, MANN-WHITNEY

    Related Articles

    Spatial Transcriptomics:

    Article Title: Multi-Scale Transcriptomics Redefining the Tumor Immune Microenvironment
    Article Snippet: scRNA-seq , Analyzing Transcriptomic Features at the Single-Cell Level , (1) Reveals cellular heterogeneity and subpopulation structure; (2) Identifies rare cells and transient state cells; (3) Suitable for developmental trajectory and cell lineage tracing analysis; (4) Constructs intercellular communication networks. , (1) High cost and limited sequencing depth; (2) Sparse data, high noise levels, small sample size, and limited representativeness; (3) Difficulty in preserving spatial information and disruption of tissue structure.. .. Spatial transcriptomics , Transcriptome sequencing preserving spatial information of tissue sections. , (1) Reveals the spatial distribution characteristics of gene expression; (2) Preserves tissue morphology and structural information; (3) Identifies functional regions and intercellular spatial interactions; (4) Aids in understanding the spatial ecology of the tumor microenvironment. , (1) Limited resolution, with partial signal mixing; (2) Large data volume and complex analysis algorithms; (3) High cost and relatively low technological maturity; (4) Difficulty in direct matching with large clinical samples.. .. Bulk RNA-seq + scRNA-seq , CIBERSORT MuSiC SCDC EPIC , Reference-based deconvolution using scRNA-seq-derived cell-type signatures , Immune composition profiling; Prognostic modeling; Cohort stratification..

    Article Title: Netrin-1 blockade inhibits tumour growth and EMT features in endometrial cancer.
    Article Snippet: .. Spatial transcriptomics using Visium FFPE technology FFPE tissue sections were placed on Visium slides and prepared according to the 10x Genomics protocols. .. After H&E staining, imaging and de-crosslinking steps, tissue sections were incubated with human-specific probes targeting 17,943 genes (10x Genomics, Visium Human Transcriptome Probe Set v.1.0).

    Sequencing:

    Article Title: Multi-Scale Transcriptomics Redefining the Tumor Immune Microenvironment
    Article Snippet: scRNA-seq , Analyzing Transcriptomic Features at the Single-Cell Level , (1) Reveals cellular heterogeneity and subpopulation structure; (2) Identifies rare cells and transient state cells; (3) Suitable for developmental trajectory and cell lineage tracing analysis; (4) Constructs intercellular communication networks. , (1) High cost and limited sequencing depth; (2) Sparse data, high noise levels, small sample size, and limited representativeness; (3) Difficulty in preserving spatial information and disruption of tissue structure.. .. Spatial transcriptomics , Transcriptome sequencing preserving spatial information of tissue sections. , (1) Reveals the spatial distribution characteristics of gene expression; (2) Preserves tissue morphology and structural information; (3) Identifies functional regions and intercellular spatial interactions; (4) Aids in understanding the spatial ecology of the tumor microenvironment. , (1) Limited resolution, with partial signal mixing; (2) Large data volume and complex analysis algorithms; (3) High cost and relatively low technological maturity; (4) Difficulty in direct matching with large clinical samples.. .. Bulk RNA-seq + scRNA-seq , CIBERSORT MuSiC SCDC EPIC , Reference-based deconvolution using scRNA-seq-derived cell-type signatures , Immune composition profiling; Prognostic modeling; Cohort stratification..

    Preserving:

    Article Title: Multi-Scale Transcriptomics Redefining the Tumor Immune Microenvironment
    Article Snippet: scRNA-seq , Analyzing Transcriptomic Features at the Single-Cell Level , (1) Reveals cellular heterogeneity and subpopulation structure; (2) Identifies rare cells and transient state cells; (3) Suitable for developmental trajectory and cell lineage tracing analysis; (4) Constructs intercellular communication networks. , (1) High cost and limited sequencing depth; (2) Sparse data, high noise levels, small sample size, and limited representativeness; (3) Difficulty in preserving spatial information and disruption of tissue structure.. .. Spatial transcriptomics , Transcriptome sequencing preserving spatial information of tissue sections. , (1) Reveals the spatial distribution characteristics of gene expression; (2) Preserves tissue morphology and structural information; (3) Identifies functional regions and intercellular spatial interactions; (4) Aids in understanding the spatial ecology of the tumor microenvironment. , (1) Limited resolution, with partial signal mixing; (2) Large data volume and complex analysis algorithms; (3) High cost and relatively low technological maturity; (4) Difficulty in direct matching with large clinical samples.. .. Bulk RNA-seq + scRNA-seq , CIBERSORT MuSiC SCDC EPIC , Reference-based deconvolution using scRNA-seq-derived cell-type signatures , Immune composition profiling; Prognostic modeling; Cohort stratification..

    Gene Expression:

    Article Title: Multi-Scale Transcriptomics Redefining the Tumor Immune Microenvironment
    Article Snippet: scRNA-seq , Analyzing Transcriptomic Features at the Single-Cell Level , (1) Reveals cellular heterogeneity and subpopulation structure; (2) Identifies rare cells and transient state cells; (3) Suitable for developmental trajectory and cell lineage tracing analysis; (4) Constructs intercellular communication networks. , (1) High cost and limited sequencing depth; (2) Sparse data, high noise levels, small sample size, and limited representativeness; (3) Difficulty in preserving spatial information and disruption of tissue structure.. .. Spatial transcriptomics , Transcriptome sequencing preserving spatial information of tissue sections. , (1) Reveals the spatial distribution characteristics of gene expression; (2) Preserves tissue morphology and structural information; (3) Identifies functional regions and intercellular spatial interactions; (4) Aids in understanding the spatial ecology of the tumor microenvironment. , (1) Limited resolution, with partial signal mixing; (2) Large data volume and complex analysis algorithms; (3) High cost and relatively low technological maturity; (4) Difficulty in direct matching with large clinical samples.. .. Bulk RNA-seq + scRNA-seq , CIBERSORT MuSiC SCDC EPIC , Reference-based deconvolution using scRNA-seq-derived cell-type signatures , Immune composition profiling; Prognostic modeling; Cohort stratification..

    Functional Assay:

    Article Title: Multi-Scale Transcriptomics Redefining the Tumor Immune Microenvironment
    Article Snippet: scRNA-seq , Analyzing Transcriptomic Features at the Single-Cell Level , (1) Reveals cellular heterogeneity and subpopulation structure; (2) Identifies rare cells and transient state cells; (3) Suitable for developmental trajectory and cell lineage tracing analysis; (4) Constructs intercellular communication networks. , (1) High cost and limited sequencing depth; (2) Sparse data, high noise levels, small sample size, and limited representativeness; (3) Difficulty in preserving spatial information and disruption of tissue structure.. .. Spatial transcriptomics , Transcriptome sequencing preserving spatial information of tissue sections. , (1) Reveals the spatial distribution characteristics of gene expression; (2) Preserves tissue morphology and structural information; (3) Identifies functional regions and intercellular spatial interactions; (4) Aids in understanding the spatial ecology of the tumor microenvironment. , (1) Limited resolution, with partial signal mixing; (2) Large data volume and complex analysis algorithms; (3) High cost and relatively low technological maturity; (4) Difficulty in direct matching with large clinical samples.. .. Bulk RNA-seq + scRNA-seq , CIBERSORT MuSiC SCDC EPIC , Reference-based deconvolution using scRNA-seq-derived cell-type signatures , Immune composition profiling; Prognostic modeling; Cohort stratification..

    Imaging:

    Article Title: Single-Cell Omics in Legumes: Research Trends and Applications.
    Article Snippet: .. Spatial transcriptomics can be categorized into (1) RNA capture-based approaches (e.g., 10× Visium, Slide-seq) where tissue sections are placed on slides patterned with spatially barcoded primers that capture RNA molecules and tag them to record their spatial locations; (2) in probe- or imaging-based approaches [e.g., multiplexed error-robust fluorescence in situ hybridization (MERFISH), sequential FISH (seqFISH), Xenium in situ], where fluorescently labeled probes hybridize target transcripts on a tissue cross-section, enabling direct visualization of transcripts locations at high spatial resolution [71]. ..

    Fluorescence:

    Article Title: Single-Cell Omics in Legumes: Research Trends and Applications.
    Article Snippet: .. Spatial transcriptomics can be categorized into (1) RNA capture-based approaches (e.g., 10× Visium, Slide-seq) where tissue sections are placed on slides patterned with spatially barcoded primers that capture RNA molecules and tag them to record their spatial locations; (2) in probe- or imaging-based approaches [e.g., multiplexed error-robust fluorescence in situ hybridization (MERFISH), sequential FISH (seqFISH), Xenium in situ], where fluorescently labeled probes hybridize target transcripts on a tissue cross-section, enabling direct visualization of transcripts locations at high spatial resolution [71]. ..

    In Situ Hybridization:

    Article Title: Single-Cell Omics in Legumes: Research Trends and Applications.
    Article Snippet: .. Spatial transcriptomics can be categorized into (1) RNA capture-based approaches (e.g., 10× Visium, Slide-seq) where tissue sections are placed on slides patterned with spatially barcoded primers that capture RNA molecules and tag them to record their spatial locations; (2) in probe- or imaging-based approaches [e.g., multiplexed error-robust fluorescence in situ hybridization (MERFISH), sequential FISH (seqFISH), Xenium in situ], where fluorescently labeled probes hybridize target transcripts on a tissue cross-section, enabling direct visualization of transcripts locations at high spatial resolution [71]. ..

    Fluorescence In Situ Hybridization:

    Article Title: Single-Cell Omics in Legumes: Research Trends and Applications.
    Article Snippet: .. Spatial transcriptomics can be categorized into (1) RNA capture-based approaches (e.g., 10× Visium, Slide-seq) where tissue sections are placed on slides patterned with spatially barcoded primers that capture RNA molecules and tag them to record their spatial locations; (2) in probe- or imaging-based approaches [e.g., multiplexed error-robust fluorescence in situ hybridization (MERFISH), sequential FISH (seqFISH), Xenium in situ], where fluorescently labeled probes hybridize target transcripts on a tissue cross-section, enabling direct visualization of transcripts locations at high spatial resolution [71]. ..

    In Situ:

    Article Title: Single-Cell Omics in Legumes: Research Trends and Applications.
    Article Snippet: .. Spatial transcriptomics can be categorized into (1) RNA capture-based approaches (e.g., 10× Visium, Slide-seq) where tissue sections are placed on slides patterned with spatially barcoded primers that capture RNA molecules and tag them to record their spatial locations; (2) in probe- or imaging-based approaches [e.g., multiplexed error-robust fluorescence in situ hybridization (MERFISH), sequential FISH (seqFISH), Xenium in situ], where fluorescently labeled probes hybridize target transcripts on a tissue cross-section, enabling direct visualization of transcripts locations at high spatial resolution [71]. ..

    Labeling:

    Article Title: Single-Cell Omics in Legumes: Research Trends and Applications.
    Article Snippet: .. Spatial transcriptomics can be categorized into (1) RNA capture-based approaches (e.g., 10× Visium, Slide-seq) where tissue sections are placed on slides patterned with spatially barcoded primers that capture RNA molecules and tag them to record their spatial locations; (2) in probe- or imaging-based approaches [e.g., multiplexed error-robust fluorescence in situ hybridization (MERFISH), sequential FISH (seqFISH), Xenium in situ], where fluorescently labeled probes hybridize target transcripts on a tissue cross-section, enabling direct visualization of transcripts locations at high spatial resolution [71]. ..

    Formalin-fixed Paraffin-Embedded:

    Article Title: Netrin-1 blockade inhibits tumour growth and EMT features in endometrial cancer.
    Article Snippet: .. Spatial transcriptomics using Visium FFPE technology FFPE tissue sections were placed on Visium slides and prepared according to the 10x Genomics protocols. .. After H&E staining, imaging and de-crosslinking steps, tissue sections were incubated with human-specific probes targeting 17,943 genes (10x Genomics, Visium Human Transcriptome Probe Set v.1.0).



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