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Spatial Transcriptomics Inc spatial transcriptomics sequencing data
a Flow cytometry staining of H226 tumor cells in vitro for CD73 expression. Isotype control (gray), anti-CD73 antibody (pink). b Immunofluorescent micrographs of H226 tumors resected from NCG mice 46 days post-implantation. Nucleated cells (DAPI, blue), hypoxia (Hypoxyprobe, green) and CD73 (pink). Representative images from four individual tumors from 10 to 20 different cutting surfaces. c Quantification of hypoxia in various tumor regions within resected H226 tumors from NCG mice determined by mean fluorescence intensity (MFI) of Hypoxyprobe. Representative image of a resected tumor section; quantification was performed across 6 independent slides (3 tumors per slide from individual mice) with an average of 13.5 regions of interest (ROI) analyzed per slide. d Spatial <t>transcriptomics</t> gene expression analysis from hypoxic regions in ( c ) (white = low hypoxia, light green = medium hypoxia, dark green = high hypoxia). Boxplots show the median (line), interquartile range (box), and whiskers extending to values within 1.5× the IQR. e 2 × 10 6 UTD T cells (white, n = 5 individual mice) or unedited (gray, n = 5 individual mice) and A 2A R-KO (red, n = 5 individual mice) CAR T-cells injected I.V. into H226 tumor-bearing NCG mice. Group average of tumor volumes measured via calipers over time (Two-sided Mann–Whitney t-test, n = group average of individual mice, mean ± SEM, P** = 0.0079, P** = 0.0072). f Cumulative tumor burden, calculated as area under the curve, from ( e ) (Two-sided Mann–Whitney t-test, n = average of individual mice as above, mean ± SD, n.s. = 0.0556, P** = 0.00379). g 2 × 10 6 UTD T cells (white, n = 5 individual mice) or unedited (gray, n = 5 individual mice) and A 2A R-KO (red, n = 5 individual mice) CAR T-cells injected I.V. into A549 tumor-bearing NCG mice. Group average of tumor volumes measured via calipers over time (Graph represents group mean ± SD, P** = 0.0072). h Cumulative tumor burden, calculated as area under the curve, from ( g ). (Two-sided Mann–Whitney t-test, n = average of individual mice as above, mean ± SD, n.s. = 0.490, P** = 0.0037). For all data, symbols and error bars reflect individual biological replicates and group mean ± S.E.M. e – h Mann–Whitney t-test performed to calculate statistical significance, ** P < 0.01, * P < 0.05.
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
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Average 86 stars, based on 1 article reviews
spatial transcriptomics sequencing data - by Bioz Stars, 2026-08
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1) Product Images from "Multiplex gene-editing strategy to engineer allogeneic EGFR-targeting CAR T-cells with improved efficacy against solid tumors"

Article Title: Multiplex gene-editing strategy to engineer allogeneic EGFR-targeting CAR T-cells with improved efficacy against solid tumors

Journal: Nature Communications

doi: 10.1038/s41467-025-66737-1

a Flow cytometry staining of H226 tumor cells in vitro for CD73 expression. Isotype control (gray), anti-CD73 antibody (pink). b Immunofluorescent micrographs of H226 tumors resected from NCG mice 46 days post-implantation. Nucleated cells (DAPI, blue), hypoxia (Hypoxyprobe, green) and CD73 (pink). Representative images from four individual tumors from 10 to 20 different cutting surfaces. c Quantification of hypoxia in various tumor regions within resected H226 tumors from NCG mice determined by mean fluorescence intensity (MFI) of Hypoxyprobe. Representative image of a resected tumor section; quantification was performed across 6 independent slides (3 tumors per slide from individual mice) with an average of 13.5 regions of interest (ROI) analyzed per slide. d Spatial transcriptomics gene expression analysis from hypoxic regions in ( c ) (white = low hypoxia, light green = medium hypoxia, dark green = high hypoxia). Boxplots show the median (line), interquartile range (box), and whiskers extending to values within 1.5× the IQR. e 2 × 10 6 UTD T cells (white, n = 5 individual mice) or unedited (gray, n = 5 individual mice) and A 2A R-KO (red, n = 5 individual mice) CAR T-cells injected I.V. into H226 tumor-bearing NCG mice. Group average of tumor volumes measured via calipers over time (Two-sided Mann–Whitney t-test, n = group average of individual mice, mean ± SEM, P** = 0.0079, P** = 0.0072). f Cumulative tumor burden, calculated as area under the curve, from ( e ) (Two-sided Mann–Whitney t-test, n = average of individual mice as above, mean ± SD, n.s. = 0.0556, P** = 0.00379). g 2 × 10 6 UTD T cells (white, n = 5 individual mice) or unedited (gray, n = 5 individual mice) and A 2A R-KO (red, n = 5 individual mice) CAR T-cells injected I.V. into A549 tumor-bearing NCG mice. Group average of tumor volumes measured via calipers over time (Graph represents group mean ± SD, P** = 0.0072). h Cumulative tumor burden, calculated as area under the curve, from ( g ). (Two-sided Mann–Whitney t-test, n = average of individual mice as above, mean ± SD, n.s. = 0.490, P** = 0.0037). For all data, symbols and error bars reflect individual biological replicates and group mean ± S.E.M. e – h Mann–Whitney t-test performed to calculate statistical significance, ** P < 0.01, * P < 0.05.
Figure Legend Snippet: a Flow cytometry staining of H226 tumor cells in vitro for CD73 expression. Isotype control (gray), anti-CD73 antibody (pink). b Immunofluorescent micrographs of H226 tumors resected from NCG mice 46 days post-implantation. Nucleated cells (DAPI, blue), hypoxia (Hypoxyprobe, green) and CD73 (pink). Representative images from four individual tumors from 10 to 20 different cutting surfaces. c Quantification of hypoxia in various tumor regions within resected H226 tumors from NCG mice determined by mean fluorescence intensity (MFI) of Hypoxyprobe. Representative image of a resected tumor section; quantification was performed across 6 independent slides (3 tumors per slide from individual mice) with an average of 13.5 regions of interest (ROI) analyzed per slide. d Spatial transcriptomics gene expression analysis from hypoxic regions in ( c ) (white = low hypoxia, light green = medium hypoxia, dark green = high hypoxia). Boxplots show the median (line), interquartile range (box), and whiskers extending to values within 1.5× the IQR. e 2 × 10 6 UTD T cells (white, n = 5 individual mice) or unedited (gray, n = 5 individual mice) and A 2A R-KO (red, n = 5 individual mice) CAR T-cells injected I.V. into H226 tumor-bearing NCG mice. Group average of tumor volumes measured via calipers over time (Two-sided Mann–Whitney t-test, n = group average of individual mice, mean ± SEM, P** = 0.0079, P** = 0.0072). f Cumulative tumor burden, calculated as area under the curve, from ( e ) (Two-sided Mann–Whitney t-test, n = average of individual mice as above, mean ± SD, n.s. = 0.0556, P** = 0.00379). g 2 × 10 6 UTD T cells (white, n = 5 individual mice) or unedited (gray, n = 5 individual mice) and A 2A R-KO (red, n = 5 individual mice) CAR T-cells injected I.V. into A549 tumor-bearing NCG mice. Group average of tumor volumes measured via calipers over time (Graph represents group mean ± SD, P** = 0.0072). h Cumulative tumor burden, calculated as area under the curve, from ( g ). (Two-sided Mann–Whitney t-test, n = average of individual mice as above, mean ± SD, n.s. = 0.490, P** = 0.0037). For all data, symbols and error bars reflect individual biological replicates and group mean ± S.E.M. e – h Mann–Whitney t-test performed to calculate statistical significance, ** P < 0.01, * P < 0.05.

Techniques Used: Flow Cytometry, Staining, In Vitro, Expressing, Control, Fluorescence, Gene Expression, Injection, MANN-WHITNEY



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Transcription programs of ccRCC cells in response to cuproptosis. A UMAP showing the 10 subtypes of 26,981 Epithelial cells; B heatmap showing inferred CNV of scRNA-seq dataset; C dot plot of the relative cellular proportions of Epithelial subtypes in each group; D GSEA analysis revealed the activated CRGs enriched in Normal Epithelial cells; E violin plot showing the relative CRGs score in each cancer subtype; F survival plot of HILPDA + ccRCC1 signature high and low group in the KIRC samples; G violin plots of HILPDA expression levels and hypoxia scores in each cancer subtypes; H spatial <t>transcriptome</t> displayed the distribution of CRGs, HILPDA + ccRCC1 signatures, hypoxia scores and HILPDA expression; I the regulon specificity scores of TFs in HILPDA + ccRCC1 subtype. The top 5 TFs ordered by scores were listed; J violin plot showing the expression levels of the top 5 TFs in HILPDA + ccRCC1 subtype across stage I–IV.
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Transcription programs of ccRCC cells in response to cuproptosis. A UMAP showing the 10 subtypes of 26,981 Epithelial cells; B heatmap showing inferred CNV of scRNA-seq dataset; C dot plot of the relative cellular proportions of Epithelial subtypes in each group; D GSEA analysis revealed the activated CRGs enriched in Normal Epithelial cells; E violin plot showing the relative CRGs score in each cancer subtype; F survival plot of HILPDA + ccRCC1 signature high and low group in the KIRC samples; G violin plots of HILPDA expression levels and hypoxia scores in each cancer subtypes; H spatial <t>transcriptome</t> displayed the distribution of CRGs, HILPDA + ccRCC1 signatures, hypoxia scores and HILPDA expression; I the regulon specificity scores of TFs in HILPDA + ccRCC1 subtype. The top 5 TFs ordered by scores were listed; J violin plot showing the expression levels of the top 5 TFs in HILPDA + ccRCC1 subtype across stage I–IV.
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Transcription programs of ccRCC cells in response to cuproptosis. A UMAP showing the 10 subtypes of 26,981 Epithelial cells; B heatmap showing inferred CNV of scRNA-seq dataset; C dot plot of the relative cellular proportions of Epithelial subtypes in each group; D GSEA analysis revealed the activated CRGs enriched in Normal Epithelial cells; E violin plot showing the relative CRGs score in each cancer subtype; F survival plot of HILPDA + ccRCC1 signature high and low group in the KIRC samples; G violin plots of HILPDA expression levels and hypoxia scores in each cancer subtypes; H spatial transcriptome displayed the distribution of CRGs, HILPDA + ccRCC1 signatures, hypoxia scores and HILPDA expression; I the regulon specificity scores of TFs in HILPDA + ccRCC1 subtype. The top 5 TFs ordered by scores were listed; J violin plot showing the expression levels of the top 5 TFs in HILPDA + ccRCC1 subtype across stage I–IV.

Journal: Discover Oncology

Article Title: Characterization of cuproptosis signature in clear cell renal cell carcinoma by single cell and spatial transcriptome analysis

doi: 10.1007/s12672-024-01162-2

Figure Lengend Snippet: Transcription programs of ccRCC cells in response to cuproptosis. A UMAP showing the 10 subtypes of 26,981 Epithelial cells; B heatmap showing inferred CNV of scRNA-seq dataset; C dot plot of the relative cellular proportions of Epithelial subtypes in each group; D GSEA analysis revealed the activated CRGs enriched in Normal Epithelial cells; E violin plot showing the relative CRGs score in each cancer subtype; F survival plot of HILPDA + ccRCC1 signature high and low group in the KIRC samples; G violin plots of HILPDA expression levels and hypoxia scores in each cancer subtypes; H spatial transcriptome displayed the distribution of CRGs, HILPDA + ccRCC1 signatures, hypoxia scores and HILPDA expression; I the regulon specificity scores of TFs in HILPDA + ccRCC1 subtype. The top 5 TFs ordered by scores were listed; J violin plot showing the expression levels of the top 5 TFs in HILPDA + ccRCC1 subtype across stage I–IV.

Article Snippet: The spatial transcriptome sequencing (ST-seq) dataset was obtained from Mendeley Data platform ( https://data.mendeley.com/datasets/g67bkbnhhg/1 ) and input to python environment.

Techniques: Expressing

Dissection of immunosuppressive cells of cuproptosis-related tumor microenvironment. A UMAP showing the 16 subtypes of 99,210 Immune cells; B violin plot of the relative expression levels of the canocial markers in each subtype; C heatmap showing the enrichment of immune checkpoint and suppressive genes; D spatial transcriptome displayed the distribution of Treg, CD8_Exhausted and TAM signature scores; E heatmap showing the four gene expression patterns deduced by TDEseq analysis; F violin plots showing the relative expression levels of CRG scores in the immunosuppressive cells across different stages; G Chord diagram showing the number of interactions among the four subtypes; H Bubble plot showing the ligand-receptor pairs in the main subtype; I Heatmap showing the relative expression levels of key genes of the four subtypes among the different stages. The paired ligand-receptor shown in H were connected by lines.

Journal: Discover Oncology

Article Title: Characterization of cuproptosis signature in clear cell renal cell carcinoma by single cell and spatial transcriptome analysis

doi: 10.1007/s12672-024-01162-2

Figure Lengend Snippet: Dissection of immunosuppressive cells of cuproptosis-related tumor microenvironment. A UMAP showing the 16 subtypes of 99,210 Immune cells; B violin plot of the relative expression levels of the canocial markers in each subtype; C heatmap showing the enrichment of immune checkpoint and suppressive genes; D spatial transcriptome displayed the distribution of Treg, CD8_Exhausted and TAM signature scores; E heatmap showing the four gene expression patterns deduced by TDEseq analysis; F violin plots showing the relative expression levels of CRG scores in the immunosuppressive cells across different stages; G Chord diagram showing the number of interactions among the four subtypes; H Bubble plot showing the ligand-receptor pairs in the main subtype; I Heatmap showing the relative expression levels of key genes of the four subtypes among the different stages. The paired ligand-receptor shown in H were connected by lines.

Article Snippet: The spatial transcriptome sequencing (ST-seq) dataset was obtained from Mendeley Data platform ( https://data.mendeley.com/datasets/g67bkbnhhg/1 ) and input to python environment.

Techniques: Dissection, Expressing, Gene Expression