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10X Genomics spatial transcriptomic sequencing data
Spatial Transcriptomic Sequencing Data, supplied by 10X Genomics, 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+transcriptome+sequencing+data/data+spatial+transcriptomic/pm41044625-67-0-11
Average 86 stars, based on 1 article reviews
spatial transcriptomic sequencing data - by Bioz Stars, 2026-09
86/100 stars

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Related Articles

Spatial Transcriptomics:

Article Title: Single-cell multiomics gene regulatory landscape reveals impaired spermatogonial stem cells and macrophage-driven inflammaging during testicular aging.
Article Snippet: 29 Testicular aging is a key driver of declining male reproductive health, but a comprehensive 30 understanding of its underlying epigenetic drivers is lacking.. To address this, we construct a 31 multiomics aging atlas by integrating single-cell RNA sequencing, single-cell assay for 32 transposase-accessible chromatin sequencing (scATAC-seq), and spatial transcriptomics of 33 young and aged mouse testes.. Our analysis reveals that altered chromatin accessibility 34 accompanies transcriptional dysregulation and identifies spermatogonial stem cells (SSCs) as 35 the most epigenetically vulnerable population.

Sequencing:

Article Title: Single-cell multiomics gene regulatory landscape reveals impaired spermatogonial stem cells and macrophage-driven inflammaging during testicular aging.
Article Snippet: 29 Testicular aging is a key driver of declining male reproductive health, but a comprehensive 30 understanding of its underlying epigenetic drivers is lacking.. To address this, we construct a 31 multiomics aging atlas by integrating single-cell RNA sequencing, single-cell assay for 32 transposase-accessible chromatin sequencing (scATAC-seq), and spatial transcriptomics of 33 young and aged mouse testes.. Our analysis reveals that altered chromatin accessibility 34 accompanies transcriptional dysregulation and identifies spermatogonial stem cells (SSCs) as 35 the most epigenetically vulnerable population.

Article Title: Spatial single-cell landscape of tumor-associated macrophages and their crosstalk with the tumor microenvironment.
Article Snippet: .. To minimize batch effects caused by differences in sequencing platforms and methodologies, all single-cell and spatial transcriptomic data were obtained exclusively from the 10x Genomics and 10x Visium platforms. ..

Gene Expression:

Article Title: Single-cell multiomics gene regulatory landscape reveals impaired spermatogonial stem cells and macrophage-driven inflammaging during testicular aging.
Article Snippet: 29 Testicular aging is a key driver of declining male reproductive health, but a comprehensive 30 understanding of its underlying epigenetic drivers is lacking.. To address this, we construct a 31 multiomics aging atlas by integrating single-cell RNA sequencing, single-cell assay for 32 transposase-accessible chromatin sequencing (scATAC-seq), and spatial transcriptomics of 33 young and aged mouse testes.. Our analysis reveals that altered chromatin accessibility 34 accompanies transcriptional dysregulation and identifies spermatogonial stem cells (SSCs) as 35 the most epigenetically vulnerable population.

Single Cell:

Article Title: Spatial single-cell landscape of tumor-associated macrophages and their crosstalk with the tumor microenvironment.
Article Snippet: .. To minimize batch effects caused by differences in sequencing platforms and methodologies, all single-cell and spatial transcriptomic data were obtained exclusively from the 10x Genomics and 10x Visium platforms. ..

Article Title: The Role of Tumor Necrosis Factor Signaling in Atherosclerosis and Stroke
Article Snippet: .. To characterise TNF signaling within atherosclerotic plaques, we analysed two publicly available datasets: (i) an integrated single-cell RNA-sequencing (scRNA-seq) atlas of 259,116 cells from human carotid, coronary, and femoral plaques (73 donors), and (ii) Xenium (10x Genomics) spatial transcriptomic data comprising 120,164 cells from carotid endarterectomy specimens with pathologist-annotated subregions (12 donors). ..

In Situ:

Article Title: SARS-CoV-2 infection and vaccination elicit distinct pharyngeal mucosal B cell responses in children.
Article Snippet: .. Spatial transcriptomic profiling with Xenium In Situ platform Slides were prepared following the manufacturer’s instructions and workflow for FFPE tissue samples (CG000578 Rev A; 10x Genomics). .. A 5-μm section from the tissue block containing the same paired tonsil and adenoid samples (one from INF donor and one from VAC donor) used for immunofluorescence were carefully attached to the sample area on a Xenium slide (Histoserv, MD).

Article Title: An antioxidant therapy elicits distinct transcriptome responses in 22q11-deleted upper layer cortical projection neurons.
Article Snippet: .. To assess L 2/3 PN transcriptional responses that underlie NAC’s therapeutic effects in vivo, we first established that spatial transcriptomic RNA quantification in situ (10X Genomics Xenium) securely identifies L 2/3 PNs and their neighbors, thus ensuring that transcriptional states can be assessed in intact cortices of early post-natal WT, LgDel, LgDel + NAC and WT + NAC L 2/3 mice. ..

Article Title: Won't you be my neighbor? Control of the immune response by stromal and immune cell microenvironments within the lymph node.
Article Snippet: Efficacious immune responses require the coordinated encounter of rare antigen-specific adaptive lymphocytes with their cognate innate antigen-presenting cells (APCs) in space and time.. This spatiotemporal problem of immunity is solved by secondary lymphoid organs, such as lymph nodes (LNs), which coordinate adaptive immune responses by recruiting APCs and lymphocytes into close juxtaposition with tissue antigens drained from the periphery.. A central tenet to the overall function of the LN is the spatial organization of leukocytes into discrete microenvironments orchestrated by the mesenchymal and endothelial cells, collectively termed LN stromal cells (LNSCs).

Formalin-fixed Paraffin-Embedded:

Article Title: SARS-CoV-2 infection and vaccination elicit distinct pharyngeal mucosal B cell responses in children.
Article Snippet: .. Spatial transcriptomic profiling with Xenium In Situ platform Slides were prepared following the manufacturer’s instructions and workflow for FFPE tissue samples (CG000578 Rev A; 10x Genomics). .. A 5-μm section from the tissue block containing the same paired tonsil and adenoid samples (one from INF donor and one from VAC donor) used for immunofluorescence were carefully attached to the sample area on a Xenium slide (Histoserv, MD).

In Vivo:

Article Title: An antioxidant therapy elicits distinct transcriptome responses in 22q11-deleted upper layer cortical projection neurons.
Article Snippet: .. To assess L 2/3 PN transcriptional responses that underlie NAC’s therapeutic effects in vivo, we first established that spatial transcriptomic RNA quantification in situ (10X Genomics Xenium) securely identifies L 2/3 PNs and their neighbors, thus ensuring that transcriptional states can be assessed in intact cortices of early post-natal WT, LgDel, LgDel + NAC and WT + NAC L 2/3 mice. ..

RNA sequencing:

Article Title: The Role of Tumor Necrosis Factor Signaling in Atherosclerosis and Stroke
Article Snippet: .. To characterise TNF signaling within atherosclerotic plaques, we analysed two publicly available datasets: (i) an integrated single-cell RNA-sequencing (scRNA-seq) atlas of 259,116 cells from human carotid, coronary, and femoral plaques (73 donors), and (ii) Xenium (10x Genomics) spatial transcriptomic data comprising 120,164 cells from carotid endarterectomy specimens with pathologist-annotated subregions (12 donors). ..



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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
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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
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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
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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
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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