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Spatial Transcriptomics Inc geomx spatial transcriptomics technology
Geomx Spatial Transcriptomics Technology, 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/geomx+spatial+transcriptomics/3d+spatial+technology+transcriptomics/pm41457181-197-38-39
Average 86 stars, based on 1 article reviews
geomx spatial transcriptomics technology - by Bioz Stars, 2026-10
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Related Articles

Spatial Transcriptomics:

Article Title: Diverse clonal fates emerge upon drug treatment of homogeneous cancer cells.
Article Snippet: Yogesh Goyal1,2,3,4 ✉, Gianna T. Busch, Maalavika Pillai, Jingxin Li, Ryan H. Boe, Emanuelle I. Grody, Manoj Chelvanambi, Ian P. Dardani, Benjamin Emert, Nicholas Bodkin, Jonas Braun, Dylan Fingerman, Amanpreet Kaur, Naveen Jain, Pavithran T. Ravindran, Ian A. Mellis, Karun Kiani, Gretchen M. Alicea, Mitchell E. Fane, Syeda Subia Ahmed, Haiyin Li, Yeqing Chen, Cedric Chai, Jessica Kaster, Russell G. Witt, Rossana Lazcano, Davis R. Ingram, Sarah B. Johnson, Khalida Wani, Margaret C. Dunagin, Alexander J. Lazar, Ashani T. Weeraratna, Jennifer A. Wargo, Meenhard Herlyn & Arjun Raj4,13 ✉

Expressing:

Article Title: Novel Integration of Spatial and Single-Cell Omics Data Sets Enables Deeper Insights into IPF Pathogenesis.
Article Snippet: .. In this example, differential analysis extracted up-regulated fibroblast foci-specific genes (n = 50) from GeoMx spatial transcriptomics [17], and the sum expression of the whole gene set was queried as a z-score in PLIN2+ fibroblast cells from scRNA-seq transcriptomics [21]. (B) PCA plotting of gene expression pattern. (C) Venn graph of the up-regulated region-specific gene sets in five histopathological region types: 32 up-regulated region-specific differential genes for control alveoli, 27 for IPF blood vessel, 41 for IPF distant alveoli, 50 for IPF fibroblast foci and 106 for IPF immune infiltrate. (D) Enrichment z-score summary of 30 cell types in five histopathological region types from spatial transcriptomics. ..

Gene Expression:

Article Title: Novel Integration of Spatial and Single-Cell Omics Data Sets Enables Deeper Insights into IPF Pathogenesis.
Article Snippet: .. In this example, differential analysis extracted up-regulated fibroblast foci-specific genes (n = 50) from GeoMx spatial transcriptomics [17], and the sum expression of the whole gene set was queried as a z-score in PLIN2+ fibroblast cells from scRNA-seq transcriptomics [21]. (B) PCA plotting of gene expression pattern. (C) Venn graph of the up-regulated region-specific gene sets in five histopathological region types: 32 up-regulated region-specific differential genes for control alveoli, 27 for IPF blood vessel, 41 for IPF distant alveoli, 50 for IPF fibroblast foci and 106 for IPF immune infiltrate. (D) Enrichment z-score summary of 30 cell types in five histopathological region types from spatial transcriptomics. ..

Control:

Article Title: Novel Integration of Spatial and Single-Cell Omics Data Sets Enables Deeper Insights into IPF Pathogenesis.
Article Snippet: .. In this example, differential analysis extracted up-regulated fibroblast foci-specific genes (n = 50) from GeoMx spatial transcriptomics [17], and the sum expression of the whole gene set was queried as a z-score in PLIN2+ fibroblast cells from scRNA-seq transcriptomics [21]. (B) PCA plotting of gene expression pattern. (C) Venn graph of the up-regulated region-specific gene sets in five histopathological region types: 32 up-regulated region-specific differential genes for control alveoli, 27 for IPF blood vessel, 41 for IPF distant alveoli, 50 for IPF fibroblast foci and 106 for IPF immune infiltrate. (D) Enrichment z-score summary of 30 cell types in five histopathological region types from spatial transcriptomics. ..

Immunohistochemistry:

Article Title: CSF1 expression associated with M2 macrophages and decreased survival in colorectal liver metastases
Article Snippet: S. Behrens, S. Behrens, W. Do, A. Jacobs, E. Maestri, L. Wang, C. W. Chang, T. Greten and X. W. Wang National Institutes of Health Background: Hepatocellular carcinoma (HCC) is the leading cause of liver cancer and survival remains low due to poor treatment response.. Surgery is the current first-line therapy for eligible candidates; however, patients relapse despite curative resection or require systemic treatment for advanced disease.. Immune checkpoint inhibition (ICI) therapy has recently shown promise in the treatment of cancers, including HCC; yet, we do not know which patients may benefit.

Marker:

Article Title: Interferon-responsive HEVs drive tumor tertiary lymphoid structure formation and predict immunotherapy response in nasopharyngeal carcinoma.
Article Snippet: .. For marker identification of NPC TLS from GeoMx spatial transcriptomics, differentially expressed genes (NPC TLS versus CN TLS) were filtered with the parameter ‘‘log2 fold change > 0.5 & adjusted P value < 0.05’’. ..



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( A ) Representative haematoxylin and eosin (H&E) stained sections showing arterial lesions of varying severity (mild, moderate and severe). Specific regions are highlighted at a higher magnification to reveal morphological differences across lesion severity, indicating progressive changes from near normal to severe. ( B ) Workflow for spatial <t>transcriptomics</t> using <t>GeoMx®</t> <t>DSP:</t> slide preparation with morphology markers and ~18,000 oligo-conjugated RNA probes; selection of ROIs in each sample analysed; cleavage with UV light of barcodes from RNA probes; collection and release of collected barcodes onto a 96-well plate for all selected ROIs; generation of a cDNA library for next generation sequencing and upload of resulting sequencing data onto the GeoMx® DSP. ( C ) Fluorescent imaging of arterial lesions with varying severities, reflecting those shown at higher magnification in ( A ). Fluorescent imaging is a prerequisite for choosing regions of interest (ROIs) for downstream profiling by GeoMx. Samples were stained with SYTO13 (nuclear dye, blue), CD45 (pan-leucocyte marker, yellow) and CD4 (T cell subset marker, red). Representative ROIs chosen for downstream spatial profiling are indicated by white circles. .
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( A ) Representative haematoxylin and eosin (H&E) stained sections showing arterial lesions of varying severity (mild, moderate and severe). Specific regions are highlighted at a higher magnification to reveal morphological differences across lesion severity, indicating progressive changes from near normal to severe. ( B ) Workflow for spatial <t>transcriptomics</t> using <t>GeoMx®</t> <t>DSP:</t> slide preparation with morphology markers and ~18,000 oligo-conjugated RNA probes; selection of ROIs in each sample analysed; cleavage with UV light of barcodes from RNA probes; collection and release of collected barcodes onto a 96-well plate for all selected ROIs; generation of a cDNA library for next generation sequencing and upload of resulting sequencing data onto the GeoMx® DSP. ( C ) Fluorescent imaging of arterial lesions with varying severities, reflecting those shown at higher magnification in ( A ). Fluorescent imaging is a prerequisite for choosing regions of interest (ROIs) for downstream profiling by GeoMx. Samples were stained with SYTO13 (nuclear dye, blue), CD45 (pan-leucocyte marker, yellow) and CD4 (T cell subset marker, red). Representative ROIs chosen for downstream spatial profiling are indicated by white circles. .
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( A ) Representative haematoxylin and eosin (H&E) stained sections showing arterial lesions of varying severity (mild, moderate and severe). Specific regions are highlighted at a higher magnification to reveal morphological differences across lesion severity, indicating progressive changes from near normal to severe. ( B ) Workflow for spatial <t>transcriptomics</t> using <t>GeoMx®</t> <t>DSP:</t> slide preparation with morphology markers and ~18,000 oligo-conjugated RNA probes; selection of ROIs in each sample analysed; cleavage with UV light of barcodes from RNA probes; collection and release of collected barcodes onto a 96-well plate for all selected ROIs; generation of a cDNA library for next generation sequencing and upload of resulting sequencing data onto the GeoMx® DSP. ( C ) Fluorescent imaging of arterial lesions with varying severities, reflecting those shown at higher magnification in ( A ). Fluorescent imaging is a prerequisite for choosing regions of interest (ROIs) for downstream profiling by GeoMx. Samples were stained with SYTO13 (nuclear dye, blue), CD45 (pan-leucocyte marker, yellow) and CD4 (T cell subset marker, red). Representative ROIs chosen for downstream spatial profiling are indicated by white circles. .
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( A ) Representative haematoxylin and eosin (H&E) stained sections showing arterial lesions of varying severity (mild, moderate and severe). Specific regions are highlighted at a higher magnification to reveal morphological differences across lesion severity, indicating progressive changes from near normal to severe. ( B ) Workflow for spatial <t>transcriptomics</t> using <t>GeoMx®</t> <t>DSP:</t> slide preparation with morphology markers and ~18,000 oligo-conjugated RNA probes; selection of ROIs in each sample analysed; cleavage with UV light of barcodes from RNA probes; collection and release of collected barcodes onto a 96-well plate for all selected ROIs; generation of a cDNA library for next generation sequencing and upload of resulting sequencing data onto the GeoMx® DSP. ( C ) Fluorescent imaging of arterial lesions with varying severities, reflecting those shown at higher magnification in ( A ). Fluorescent imaging is a prerequisite for choosing regions of interest (ROIs) for downstream profiling by GeoMx. Samples were stained with SYTO13 (nuclear dye, blue), CD45 (pan-leucocyte marker, yellow) and CD4 (T cell subset marker, red). Representative ROIs chosen for downstream spatial profiling are indicated by white circles. .
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( A ) Representative haematoxylin and eosin (H&E) stained sections showing arterial lesions of varying severity (mild, moderate and severe). Specific regions are highlighted at a higher magnification to reveal morphological differences across lesion severity, indicating progressive changes from near normal to severe. ( B ) Workflow for spatial <t>transcriptomics</t> using <t>GeoMx®</t> <t>DSP:</t> slide preparation with morphology markers and ~18,000 oligo-conjugated RNA probes; selection of ROIs in each sample analysed; cleavage with UV light of barcodes from RNA probes; collection and release of collected barcodes onto a 96-well plate for all selected ROIs; generation of a cDNA library for next generation sequencing and upload of resulting sequencing data onto the GeoMx® DSP. ( C ) Fluorescent imaging of arterial lesions with varying severities, reflecting those shown at higher magnification in ( A ). Fluorescent imaging is a prerequisite for choosing regions of interest (ROIs) for downstream profiling by GeoMx. Samples were stained with SYTO13 (nuclear dye, blue), CD45 (pan-leucocyte marker, yellow) and CD4 (T cell subset marker, red). Representative ROIs chosen for downstream spatial profiling are indicated by white circles. .
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( A ) Representative haematoxylin and eosin (H&E) stained sections showing arterial lesions of varying severity (mild, moderate and severe). Specific regions are highlighted at a higher magnification to reveal morphological differences across lesion severity, indicating progressive changes from near normal to severe. ( B ) Workflow for spatial <t>transcriptomics</t> using <t>GeoMx®</t> <t>DSP:</t> slide preparation with morphology markers and ~18,000 oligo-conjugated RNA probes; selection of ROIs in each sample analysed; cleavage with UV light of barcodes from RNA probes; collection and release of collected barcodes onto a 96-well plate for all selected ROIs; generation of a cDNA library for next generation sequencing and upload of resulting sequencing data onto the GeoMx® DSP. ( C ) Fluorescent imaging of arterial lesions with varying severities, reflecting those shown at higher magnification in ( A ). Fluorescent imaging is a prerequisite for choosing regions of interest (ROIs) for downstream profiling by GeoMx. Samples were stained with SYTO13 (nuclear dye, blue), CD45 (pan-leucocyte marker, yellow) and CD4 (T cell subset marker, red). Representative ROIs chosen for downstream spatial profiling are indicated by white circles. .
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( A ) Representative haematoxylin and eosin (H&E) stained sections showing arterial lesions of varying severity (mild, moderate and severe). Specific regions are highlighted at a higher magnification to reveal morphological differences across lesion severity, indicating progressive changes from near normal to severe. ( B ) Workflow for spatial <t>transcriptomics</t> using <t>GeoMx®</t> <t>DSP:</t> slide preparation with morphology markers and ~18,000 oligo-conjugated RNA probes; selection of ROIs in each sample analysed; cleavage with UV light of barcodes from RNA probes; collection and release of collected barcodes onto a 96-well plate for all selected ROIs; generation of a cDNA library for next generation sequencing and upload of resulting sequencing data onto the GeoMx® DSP. ( C ) Fluorescent imaging of arterial lesions with varying severities, reflecting those shown at higher magnification in ( A ). Fluorescent imaging is a prerequisite for choosing regions of interest (ROIs) for downstream profiling by GeoMx. Samples were stained with SYTO13 (nuclear dye, blue), CD45 (pan-leucocyte marker, yellow) and CD4 (T cell subset marker, red). Representative ROIs chosen for downstream spatial profiling are indicated by white circles. .
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Representative H&E images of granulomas from A) Case 3, B) Case 2, and C) Case 4 showing a range of granuloma morphology with D) necrotizing granulomas, E) cellular non-necrotizing granulomas, and F) small, lymphocyte rich granulomas as assessed by a pulmonary pathologist using traditional morphological annotation. Regions of interest (ROIs) ( G-K ) were selected based on morphological and fluorescence staining for DNA (blue), CD3 (green), CD68/CD163 (red), and vimentin (yellow). ROIs bordering necrotic (G) granulomas and (H) solid or cellular granulomas were selected in addition to tertiary lymphoid structures (I), lymph node (J), and uninvolved lung (K) for spatial transcriptional profiling using the human whole <t>transcriptome</t> probe set using GeoMx (Bruker).
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Representative H&E images of granulomas from A) Case 3, B) Case 2, and C) Case 4 showing a range of granuloma morphology with D) necrotizing granulomas, E) cellular non-necrotizing granulomas, and F) small, lymphocyte rich granulomas as assessed by a pulmonary pathologist using traditional morphological annotation. Regions of interest (ROIs) ( G-K ) were selected based on morphological and fluorescence staining for DNA (blue), CD3 (green), CD68/CD163 (red), and vimentin (yellow). ROIs bordering necrotic (G) granulomas and (H) solid or cellular granulomas were selected in addition to tertiary lymphoid structures (I), lymph node (J), and uninvolved lung (K) for spatial transcriptional profiling using the human whole <t>transcriptome</t> probe set using GeoMx (Bruker).
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Image Search Results


( A ) Representative haematoxylin and eosin (H&E) stained sections showing arterial lesions of varying severity (mild, moderate and severe). Specific regions are highlighted at a higher magnification to reveal morphological differences across lesion severity, indicating progressive changes from near normal to severe. ( B ) Workflow for spatial transcriptomics using GeoMx® DSP: slide preparation with morphology markers and ~18,000 oligo-conjugated RNA probes; selection of ROIs in each sample analysed; cleavage with UV light of barcodes from RNA probes; collection and release of collected barcodes onto a 96-well plate for all selected ROIs; generation of a cDNA library for next generation sequencing and upload of resulting sequencing data onto the GeoMx® DSP. ( C ) Fluorescent imaging of arterial lesions with varying severities, reflecting those shown at higher magnification in ( A ). Fluorescent imaging is a prerequisite for choosing regions of interest (ROIs) for downstream profiling by GeoMx. Samples were stained with SYTO13 (nuclear dye, blue), CD45 (pan-leucocyte marker, yellow) and CD4 (T cell subset marker, red). Representative ROIs chosen for downstream spatial profiling are indicated by white circles. .

Journal: EMBO Molecular Medicine

Article Title: Spatial transcriptomics elucidates localized immune responses in atherosclerotic coronary artery

doi: 10.1038/s44321-025-00280-w

Figure Lengend Snippet: ( A ) Representative haematoxylin and eosin (H&E) stained sections showing arterial lesions of varying severity (mild, moderate and severe). Specific regions are highlighted at a higher magnification to reveal morphological differences across lesion severity, indicating progressive changes from near normal to severe. ( B ) Workflow for spatial transcriptomics using GeoMx® DSP: slide preparation with morphology markers and ~18,000 oligo-conjugated RNA probes; selection of ROIs in each sample analysed; cleavage with UV light of barcodes from RNA probes; collection and release of collected barcodes onto a 96-well plate for all selected ROIs; generation of a cDNA library for next generation sequencing and upload of resulting sequencing data onto the GeoMx® DSP. ( C ) Fluorescent imaging of arterial lesions with varying severities, reflecting those shown at higher magnification in ( A ). Fluorescent imaging is a prerequisite for choosing regions of interest (ROIs) for downstream profiling by GeoMx. Samples were stained with SYTO13 (nuclear dye, blue), CD45 (pan-leucocyte marker, yellow) and CD4 (T cell subset marker, red). Representative ROIs chosen for downstream spatial profiling are indicated by white circles. .

Article Snippet: Spatial Transcriptomics GeoMx® DSP and CosMxTM SMI analyses of human coronary arteries with different stages of atherosclerosis progression provide state-of-the-art datasets to interrogate immune pathways involved in disease establishment and progression.

Techniques: Staining, Selection, cDNA Library Assay, Next-Generation Sequencing, Sequencing, Imaging, Marker

( A ) In situ expression of ANXA2 in a representative severe lesion in GeoMx® (top panel) and CosMx ™ (bottom panel). Higher magnification boxes show ANXA2 expression in an ATLO. Figure was reused to create this panel. ( B ) NanoString-provided workflow for spatial deconvolution of GeoMx® data. ( C ) Proposed workflow for spatial deconvolution utilising a CosMx-generated single cell matrix (from the same tissue) to inform cell estimates. .

Journal: EMBO Molecular Medicine

Article Title: Spatial transcriptomics elucidates localized immune responses in atherosclerotic coronary artery

doi: 10.1038/s44321-025-00280-w

Figure Lengend Snippet: ( A ) In situ expression of ANXA2 in a representative severe lesion in GeoMx® (top panel) and CosMx ™ (bottom panel). Higher magnification boxes show ANXA2 expression in an ATLO. Figure was reused to create this panel. ( B ) NanoString-provided workflow for spatial deconvolution of GeoMx® data. ( C ) Proposed workflow for spatial deconvolution utilising a CosMx-generated single cell matrix (from the same tissue) to inform cell estimates. .

Article Snippet: Spatial Transcriptomics GeoMx® DSP and CosMxTM SMI analyses of human coronary arteries with different stages of atherosclerosis progression provide state-of-the-art datasets to interrogate immune pathways involved in disease establishment and progression.

Techniques: In Situ, Expressing, Generated

( A ) Heatmap of spatial deconvolution estimates using the inbuilt GeoMx® reference matrix 'safeTME'. Scaled abundances are shown as a ratio to the maximum value are displayed across five tissue localisations (adventitia, plaque, negative control, muscle and infiltrated muscle layer). 'Subsets' correspond to ROIs segmented on the GeoMx® platform and are highlighted. Cell types present in the safeTME matrix are indicated as rows. ( B ) Heatmap of the CosMx™-derived cell signature matrix. Census-annotated cell populations from the CosMx™ are represented as columns with rows representing genes on the CosMx™ platform. Genes are scaled from red to white, with red indicating a higher expression. ( C ) Heatmap of the genes present in the GeoMx® dataset from the CosMx™-derived cell signature matrix. ( D ) Heatmap of spatial deconvolution estimates using the CosMx™-derived matrix. Cell types present in the CosMx™-matrix are indicated as rows.

Journal: EMBO Molecular Medicine

Article Title: Spatial transcriptomics elucidates localized immune responses in atherosclerotic coronary artery

doi: 10.1038/s44321-025-00280-w

Figure Lengend Snippet: ( A ) Heatmap of spatial deconvolution estimates using the inbuilt GeoMx® reference matrix 'safeTME'. Scaled abundances are shown as a ratio to the maximum value are displayed across five tissue localisations (adventitia, plaque, negative control, muscle and infiltrated muscle layer). 'Subsets' correspond to ROIs segmented on the GeoMx® platform and are highlighted. Cell types present in the safeTME matrix are indicated as rows. ( B ) Heatmap of the CosMx™-derived cell signature matrix. Census-annotated cell populations from the CosMx™ are represented as columns with rows representing genes on the CosMx™ platform. Genes are scaled from red to white, with red indicating a higher expression. ( C ) Heatmap of the genes present in the GeoMx® dataset from the CosMx™-derived cell signature matrix. ( D ) Heatmap of spatial deconvolution estimates using the CosMx™-derived matrix. Cell types present in the CosMx™-matrix are indicated as rows.

Article Snippet: Spatial Transcriptomics GeoMx® DSP and CosMxTM SMI analyses of human coronary arteries with different stages of atherosclerosis progression provide state-of-the-art datasets to interrogate immune pathways involved in disease establishment and progression.

Techniques: Negative Control, Derivative Assay, Expressing

Representative H&E images of granulomas from A) Case 3, B) Case 2, and C) Case 4 showing a range of granuloma morphology with D) necrotizing granulomas, E) cellular non-necrotizing granulomas, and F) small, lymphocyte rich granulomas as assessed by a pulmonary pathologist using traditional morphological annotation. Regions of interest (ROIs) ( G-K ) were selected based on morphological and fluorescence staining for DNA (blue), CD3 (green), CD68/CD163 (red), and vimentin (yellow). ROIs bordering necrotic (G) granulomas and (H) solid or cellular granulomas were selected in addition to tertiary lymphoid structures (I), lymph node (J), and uninvolved lung (K) for spatial transcriptional profiling using the human whole transcriptome probe set using GeoMx (Bruker).

Journal: bioRxiv

Article Title: Multiomic analysis identifies suppressive myeloid cell populations in human TB granulomas

doi: 10.1101/2025.03.10.642376

Figure Lengend Snippet: Representative H&E images of granulomas from A) Case 3, B) Case 2, and C) Case 4 showing a range of granuloma morphology with D) necrotizing granulomas, E) cellular non-necrotizing granulomas, and F) small, lymphocyte rich granulomas as assessed by a pulmonary pathologist using traditional morphological annotation. Regions of interest (ROIs) ( G-K ) were selected based on morphological and fluorescence staining for DNA (blue), CD3 (green), CD68/CD163 (red), and vimentin (yellow). ROIs bordering necrotic (G) granulomas and (H) solid or cellular granulomas were selected in addition to tertiary lymphoid structures (I), lymph node (J), and uninvolved lung (K) for spatial transcriptional profiling using the human whole transcriptome probe set using GeoMx (Bruker).

Article Snippet: Due to the limited data on the functional role and significance of MDSCs in TB infected lung tissues, we used an unbiased spatial whole transcriptome analysis (WTA) platform (GeoMx, Bruker, Inc) integrated with single-cell immunophenotyping via highly multiplexed tissue cyclic immunofluorescence (CyCIF) to initiate this study of human TB.

Techniques: Fluorescence, Staining