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Qiagen ingenuity pathway analysis ipa

Transcriptomic <t>analysis</t> of feline diffuse iris melanoma (FDIM). The principal component analysis (PCA) plot grouping samples by the top 500 transcripts after variance-stabilising transformation of transcript counts ( A ). There is clear and separate clustering of the iris melanosis and late FDIM samples, with the early FDIM samples overlapping both groups, showing that early FDIM is an intermediate disease stage. Volcano plots highlight the number of significantly dysregulated transcripts between early FDIM and iris melanosis ( B i), late FDIM and iris melanosis ( C i) and between late and early FDIM ( D i). A logfold-change threshold was set at − 1.5 and 1.5 and an adjusted P-value threshold of 0.05 was used. <t>Ingenuity</t> <t>pathway</t> analysis identified cancer and organismal injury and abnormalities to be the top dysregulated disease pathways between early FDIM and iris melanosis ( B ii), late and iris melanosis ( C ii) and late and early FDIM ( D ii). The disease progression of FDIM is associated with key molecular events ( E ). Tumour initiation is associated with upregulation of STOX1, PEG3, XIAP and VIM , increasing invasive tendencies and immune cell recruitment. Progression to late FDIM is characterised by downregulation of SOX11, FOXC1 and FOXC2 , likely leading to a more dedifferentiated and plastic cellular phenotype. Significant upregulation of BIRC2 and BIRC5 leads to inhibition of apoptosis. Additionally, upregulation of BIRC5, CCL2 and HAVCR2 lead to immune-microenvironment remodelling, associated with the M2 (immunosuppressive) tumour associated macrophages as well as T-regulator (Treg) cells and inhibition of cytotoxic T-cells (CTC), aiding immune escape. Created in BioRender. Kayes, D. (2025) https://BioRender.com/m39r385 .

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Article Title: Uncovering the molecular signature of feline diffuse iris melanoma through transcriptomic analysis of disease severity

Journal: Scientific Reports

doi: 10.1038/s41598-025-09632-5

Transcriptomic analysis of feline diffuse iris melanoma (FDIM). The principal component analysis (PCA) plot grouping samples by the top 500 transcripts after variance-stabilising transformation of transcript counts ( A ). There is clear and separate clustering of the iris melanosis and late FDIM samples, with the early FDIM samples overlapping both groups, showing that early FDIM is an intermediate disease stage. Volcano plots highlight the number of significantly dysregulated transcripts between early FDIM and iris melanosis ( B i), late FDIM and iris melanosis ( C i) and between late and early FDIM ( D i). A logfold-change threshold was set at − 1.5 and 1.5 and an adjusted P-value threshold of 0.05 was used. Ingenuity pathway analysis identified cancer and organismal injury and abnormalities to be the top dysregulated disease pathways between early FDIM and iris melanosis ( B ii), late and iris melanosis ( C ii) and late and early FDIM ( D ii). The disease progression of FDIM is associated with key molecular events ( E ). Tumour initiation is associated with upregulation of STOX1, PEG3, XIAP and VIM , increasing invasive tendencies and immune cell recruitment. Progression to late FDIM is characterised by downregulation of SOX11, FOXC1 and FOXC2 , likely leading to a more dedifferentiated and plastic cellular phenotype. Significant upregulation of BIRC2 and BIRC5 leads to inhibition of apoptosis. Additionally, upregulation of BIRC5, CCL2 and HAVCR2 lead to immune-microenvironment remodelling, associated with the M2 (immunosuppressive) tumour associated macrophages as well as T-regulator (Treg) cells and inhibition of cytotoxic T-cells (CTC), aiding immune escape. Created in BioRender. Kayes, D. (2025) https://BioRender.com/m39r385 .

Figure Legend Snippet: Transcriptomic analysis of feline diffuse iris melanoma (FDIM). The principal component analysis (PCA) plot grouping samples by the top 500 transcripts after variance-stabilising transformation of transcript counts ( A ). There is clear and separate clustering of the iris melanosis and late FDIM samples, with the early FDIM samples overlapping both groups, showing that early FDIM is an intermediate disease stage. Volcano plots highlight the number of significantly dysregulated transcripts between early FDIM and iris melanosis ( B i), late FDIM and iris melanosis ( C i) and between late and early FDIM ( D i). A logfold-change threshold was set at − 1.5 and 1.5 and an adjusted P-value threshold of 0.05 was used. Ingenuity pathway analysis identified cancer and organismal injury and abnormalities to be the top dysregulated disease pathways between early FDIM and iris melanosis ( B ii), late and iris melanosis ( C ii) and late and early FDIM ( D ii). The disease progression of FDIM is associated with key molecular events ( E ). Tumour initiation is associated with upregulation of STOX1, PEG3, XIAP and VIM , increasing invasive tendencies and immune cell recruitment. Progression to late FDIM is characterised by downregulation of SOX11, FOXC1 and FOXC2 , likely leading to a more dedifferentiated and plastic cellular phenotype. Significant upregulation of BIRC2 and BIRC5 leads to inhibition of apoptosis. Additionally, upregulation of BIRC5, CCL2 and HAVCR2 lead to immune-microenvironment remodelling, associated with the M2 (immunosuppressive) tumour associated macrophages as well as T-regulator (Treg) cells and inhibition of cytotoxic T-cells (CTC), aiding immune escape. Created in BioRender. Kayes, D. (2025) https://BioRender.com/m39r385 .

Techniques Used: Transformation Assay, Biomarker Discovery, Inhibition

Indirect Immunoperoxidase Assay:

Article Title: High-throughput transcriptomics analysis of equipotent and human relevant mixtures of BPA alternatives reveal additive effects in vitro.
Article Snippet: .. Ingenuity pathway analysis (IPA; Qiagen) was used to identify upstream regulators and canonical pathways from genes fitting BMCs. ..

Article Title: Alcohol use reduces the efficacy of anti-PD1 immunotherapy by disrupting anti-tumor immunity
Article Snippet: .. Ingenuity Pathway Analysis (IPA, Qiagen, Germantown, MA) was used to understand upstream mediators of RNA expression and graphical summaries of transcriptomic changes. ..

Article Title: NEDDylation Regulates CD8 + T-cell Metabolism and Antitumor Immunity
Article Snippet: .. Ingenuity pathway analysis (IPA, QIAGEN) was used for a characterization of the molecular events lying behind the differential protein patterns under analysis. ..

Article Title: Uncovering the molecular signature of feline diffuse iris melanoma through transcriptomic analysis of disease severity
Article Snippet: .. Pathway analysis and graphical display of the data was performed using QIAGEN Ingenuity Pathway Analysis (IPA; QIAGEN Inc., https://digitalinsights.qiagen.com/IPA ) – . ..

Article Title: The transcriptomic fingerprint of cancer response to Tumor Treating Fields (TTFields).
Article Snippet: .. Canonical pathways, upstream regulators analysis and drug analysis Ingenuity canonical pathways and upstream regulators analysis (including drug analysis) were done using QIAGEN Ingenuity Pathway Analysis (IPA, https://digitalinsights.qiagen.com/IPA, summer update 2023) [77]. ..

Article Title: BDNF-DT and BDNF-AS-DT : Novel Genes in the BDNF locus
Article Snippet: .. We investigated whether these four sets of genes are enriched for particular biological features, using QIAGEN’s Ingenuity Pathway Analysis (IPA, QIAGEN, Redwood City, CA, USA; http://www.qiagen.com/ingenuity ). ..

Article Title: Loss of UBE3A impacts both neuronal and non-neuronal cells in human cerebral organoids
Article Snippet: .. Ingenuity pathway analysis (IPA, version 60467501, QIAGEN digital insights, https://digitalinsights.qiagen.com/IPA ) was used to predict activated or inhibited biological functions. ..

Article Title: Biomimetic Catechol-Incorporated Polyacrylonitrile Nanofiber Scaffolds for Tissue Engineering of Functional Salivary Glands
Article Snippet: .. Ingenuity pathway analysis (IPA, Qiagen Inc., version 94302991) was used to interpret the biological significance of the differentially expressed genes (DEGs) identified in our study. ..

RNA Expression:

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GSEA of KEGG pathways and canonical pathways analysis in the DRG tissues post-surgery. Ranked by NES score, the selected six of top 20 enriched KEGG pathways were the Adherens Junction (a), JAK-STAT (d), NOD like receptor (g), Apoptosis (j), WNT (m), and MAPK (p) signaling pathways. The heat maps showing the dynamic expression of the core enrichment genes involved in these signaling pathways (b, e, h, k, n, q). The PPI network shows the interaction of the proteins involved in the above signaling pathways (c, f, i, l, o, r). The enrichment heat-map showing the dynamic activity of canonical pathways at 6 h, 12 h, 1 d, 4 d, 7 d, and 14 d post-surgery (s). Each pathway is depicted with a pseudo color (orange for an activated pathway with positive Z-score ≥2, blue for an inhibited pathway with negative Z-score ≤−2, and spot for a non-active pathway with −2 ≤ Z-score ≤2). The canonical pathways were classified into different types according to the IPA database. IPA, Ingenuity Pathway Analysis. GSEA, gene set enrichment analysis; NES, normalized enrichment score; PPI, protein–protein interaction. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Journal: Journal of Advanced Research

Article Title: Dynamic molecular landscape in dorsal root ganglion for peripheral nerve regeneration promoted by tissue engineered nerve graft

doi: 10.1016/j.jare.2025.07.059

Figure Lengend Snippet: GSEA of KEGG pathways and canonical pathways analysis in the DRG tissues post-surgery. Ranked by NES score, the selected six of top 20 enriched KEGG pathways were the Adherens Junction (a), JAK-STAT (d), NOD like receptor (g), Apoptosis (j), WNT (m), and MAPK (p) signaling pathways. The heat maps showing the dynamic expression of the core enrichment genes involved in these signaling pathways (b, e, h, k, n, q). The PPI network shows the interaction of the proteins involved in the above signaling pathways (c, f, i, l, o, r). The enrichment heat-map showing the dynamic activity of canonical pathways at 6 h, 12 h, 1 d, 4 d, 7 d, and 14 d post-surgery (s). Each pathway is depicted with a pseudo color (orange for an activated pathway with positive Z-score ≥2, blue for an inhibited pathway with negative Z-score ≤−2, and spot for a non-active pathway with −2 ≤ Z-score ≤2). The canonical pathways were classified into different types according to the IPA database. IPA, Ingenuity Pathway Analysis. GSEA, gene set enrichment analysis; NES, normalized enrichment score; PPI, protein–protein interaction. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Article Snippet: The Ingenuity Pathway Analysis (IPA) software suite (Ingenuity Systems, Redwood City, CA) was employed to identify canonical pathways that are significantly overrepresented.

Techniques: Protein-Protein interactions, Expressing, Activity Assay

GSEA of GO biological process gene sets in the DRG tissues post-surgery. Ranked by NES score, the selected six of top 20 enriched GO biological process gene sets were nitric oxide mediated transduction (a), central nervous system neuron axongenesis (c), positive regulation of epithelial mesenchymal transition (e), regulation of JNK cascade (j), regulation of cellular response to insulin stimulus (i), and maintenance of blood brain barrier (k). The heatmaps showing the dynamic expression of the core enrichment genes involved in these GO biological process gene sets (b, d, f, h, j, l). The enrichment heat-map showing the dynamic activity of diseases and functions at 6 h, 12 h, 1 d, 4 d, 7 d, and 14 d post-surgery (m). Each disease and function are depicted with a pseudo color (orange for an activated disease and function with positive Z-score ≥2, blue for an inhibited disease and function with negative Z-score ≤−2, and spot for a non-active disease and function with −2 ≤ Z-score ≤2). The diseases and functions were classified into different types according to the IPA database. IPA, Ingenuity Pathway Analysis. GSEA, gene set enrichment analysis; NES, normalized enrichment score; PPI, protein–protein interaction. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Journal: Journal of Advanced Research

Article Title: Dynamic molecular landscape in dorsal root ganglion for peripheral nerve regeneration promoted by tissue engineered nerve graft

doi: 10.1016/j.jare.2025.07.059

Figure Lengend Snippet: GSEA of GO biological process gene sets in the DRG tissues post-surgery. Ranked by NES score, the selected six of top 20 enriched GO biological process gene sets were nitric oxide mediated transduction (a), central nervous system neuron axongenesis (c), positive regulation of epithelial mesenchymal transition (e), regulation of JNK cascade (j), regulation of cellular response to insulin stimulus (i), and maintenance of blood brain barrier (k). The heatmaps showing the dynamic expression of the core enrichment genes involved in these GO biological process gene sets (b, d, f, h, j, l). The enrichment heat-map showing the dynamic activity of diseases and functions at 6 h, 12 h, 1 d, 4 d, 7 d, and 14 d post-surgery (m). Each disease and function are depicted with a pseudo color (orange for an activated disease and function with positive Z-score ≥2, blue for an inhibited disease and function with negative Z-score ≤−2, and spot for a non-active disease and function with −2 ≤ Z-score ≤2). The diseases and functions were classified into different types according to the IPA database. IPA, Ingenuity Pathway Analysis. GSEA, gene set enrichment analysis; NES, normalized enrichment score; PPI, protein–protein interaction. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Article Snippet: The Ingenuity Pathway Analysis (IPA) software suite (Ingenuity Systems, Redwood City, CA) was employed to identify canonical pathways that are significantly overrepresented.

Techniques: Transduction, Expressing, Activity Assay

GSEA of GO cellular component, molecular function, and upstream regulators prediction in the DRG tissues post-surgery. Ranked by NES score, the selected three of top 20 enriched GO cellular component gene sets were cytoplasmic stress granule (a), P body (c), actin-based cell projection (e), the selected three of top 20 enriched GO molecular function gene sets were ATPase binding (g), kinase inhibitor activity (i), and Smad binding (k). The heatmaps showing the dynamic expression of the core enrichment genes involved in these GO cellular component (b, d, f) and molecular function (h, j, l) gene sets. The enrichment heatmap showing the predicted upstream regulators at 6 h, 12 h, 1 d, 4 d, 7 d, and 14 d post-surgery (m). Each predicted upstream regulator is depicted with a pseudo color (orange for an activated upstream regulator with positive Z-score ≥2, blue for an inhibited upstream regulator with negative Z-score ≤−2, and spot for a non-active upstream regulator with −2 ≤ Z-score ≤2). The predicted upstream regulators were classified into different types according to the IPA database. IPA, Ingenuity Pathway Analysis. GSEA, gene set enrichment analysis; NES, normalized enrichment score; PPI, protein–protein interaction. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Journal: Journal of Advanced Research

Article Title: Dynamic molecular landscape in dorsal root ganglion for peripheral nerve regeneration promoted by tissue engineered nerve graft

doi: 10.1016/j.jare.2025.07.059

Figure Lengend Snippet: GSEA of GO cellular component, molecular function, and upstream regulators prediction in the DRG tissues post-surgery. Ranked by NES score, the selected three of top 20 enriched GO cellular component gene sets were cytoplasmic stress granule (a), P body (c), actin-based cell projection (e), the selected three of top 20 enriched GO molecular function gene sets were ATPase binding (g), kinase inhibitor activity (i), and Smad binding (k). The heatmaps showing the dynamic expression of the core enrichment genes involved in these GO cellular component (b, d, f) and molecular function (h, j, l) gene sets. The enrichment heatmap showing the predicted upstream regulators at 6 h, 12 h, 1 d, 4 d, 7 d, and 14 d post-surgery (m). Each predicted upstream regulator is depicted with a pseudo color (orange for an activated upstream regulator with positive Z-score ≥2, blue for an inhibited upstream regulator with negative Z-score ≤−2, and spot for a non-active upstream regulator with −2 ≤ Z-score ≤2). The predicted upstream regulators were classified into different types according to the IPA database. IPA, Ingenuity Pathway Analysis. GSEA, gene set enrichment analysis; NES, normalized enrichment score; PPI, protein–protein interaction. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Article Snippet: The Ingenuity Pathway Analysis (IPA) software suite (Ingenuity Systems, Redwood City, CA) was employed to identify canonical pathways that are significantly overrepresented.

Techniques: Binding Assay, Activity Assay, Expressing

The impact of DRG neuron axonal promotion via SKP-SCs. (a) Schematic illustration of DRG neurons culture in vitro. The cultured DRG neurons for 20 h and 40 h (b) showed increased neurite outgrowth. Scale bar: 50 μm. (c) The β-Tubulin III cell immunofluorescent staining (red) showed neurites are undergoing a process of growth in length from 48 h to 96 h. Scale bar: 50 μm. Schematic illustration showed the direct (d) and in-direct (Transwell®) (e) co-culture of DRG neurons and SKP-SCs. (h) After direct co-culture 48 h, GFP-SKP-SCs promoted DRGs neurite outgrowth significantly compared to control group (i). (k) After in-direct co-culture 72 h, GFP-SKP-SCs promoted DRGs neurite outgrowth (j) significantly compared to control group (g). Scale bar: 50 μm for f, g, i, j. (l) Morphological changes under phase contrast microscopy in DRG neurons and SKP-SCs direct co-culture, DRG neurons in separate culture, and in-direct (Transwell®) co-culture of DRG neurons and SKP-SCs after 24 h, 48 h, and 72 h. Scale bar: 100 μm. (m) Schematic illustration of LC-MS/MS analysis to identify the secreted proteins from SKP-SCs cultured in serum free basic medium for 4 h. After concentration, the cleared conditioned medium was collected for LC-MS/MS analysis, database search, and protein identification. The enrichment analysis showed top 20 diseases and functions (n) and canonical pathways (o) according to the IPA database. The PPI network shows the interaction of the proteins involved in the functions highly correlated with regeneration (p). Among them, functions as formation of lamellipodia, extension of neurites, extension of cellular protrusions, and related proteins were highlighted (q). Functions as migration of endothelial cells, development of endothelial tissue, vasculogenesis, development of epithelial tissue, endothelial cell development, and related proteins were highlighted (r). Orange nodes stand for a predicted activation state. Blue nodes stand for a predicted inhibition state. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Journal: Journal of Advanced Research

Article Title: Dynamic molecular landscape in dorsal root ganglion for peripheral nerve regeneration promoted by tissue engineered nerve graft

doi: 10.1016/j.jare.2025.07.059

Figure Lengend Snippet: The impact of DRG neuron axonal promotion via SKP-SCs. (a) Schematic illustration of DRG neurons culture in vitro. The cultured DRG neurons for 20 h and 40 h (b) showed increased neurite outgrowth. Scale bar: 50 μm. (c) The β-Tubulin III cell immunofluorescent staining (red) showed neurites are undergoing a process of growth in length from 48 h to 96 h. Scale bar: 50 μm. Schematic illustration showed the direct (d) and in-direct (Transwell®) (e) co-culture of DRG neurons and SKP-SCs. (h) After direct co-culture 48 h, GFP-SKP-SCs promoted DRGs neurite outgrowth significantly compared to control group (i). (k) After in-direct co-culture 72 h, GFP-SKP-SCs promoted DRGs neurite outgrowth (j) significantly compared to control group (g). Scale bar: 50 μm for f, g, i, j. (l) Morphological changes under phase contrast microscopy in DRG neurons and SKP-SCs direct co-culture, DRG neurons in separate culture, and in-direct (Transwell®) co-culture of DRG neurons and SKP-SCs after 24 h, 48 h, and 72 h. Scale bar: 100 μm. (m) Schematic illustration of LC-MS/MS analysis to identify the secreted proteins from SKP-SCs cultured in serum free basic medium for 4 h. After concentration, the cleared conditioned medium was collected for LC-MS/MS analysis, database search, and protein identification. The enrichment analysis showed top 20 diseases and functions (n) and canonical pathways (o) according to the IPA database. The PPI network shows the interaction of the proteins involved in the functions highly correlated with regeneration (p). Among them, functions as formation of lamellipodia, extension of neurites, extension of cellular protrusions, and related proteins were highlighted (q). Functions as migration of endothelial cells, development of endothelial tissue, vasculogenesis, development of epithelial tissue, endothelial cell development, and related proteins were highlighted (r). Orange nodes stand for a predicted activation state. Blue nodes stand for a predicted inhibition state. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Article Snippet: The Ingenuity Pathway Analysis (IPA) software suite (Ingenuity Systems, Redwood City, CA) was employed to identify canonical pathways that are significantly overrepresented.

Techniques: In Vitro, Cell Culture, Staining, Co-Culture Assay, Control, Microscopy, Liquid Chromatography with Mass Spectroscopy, Concentration Assay, Migration, Activation Assay, Inhibition

The transcriptional alteration of DRG neurons co-cultured with SKP-SCs. (a) Representative images of phase contrast microscopy of SKP-SCs in the upper chamber and lower ventricular DRG neurons after 48 h co-culture. Scale bar: 100 μm. (b) Schematic illustration of transcriptional analysis of lower ventricular DRG neurons for 48 h co-culture, and bioinformatics. The enrichment analysis showed top 20 diseases and functions (c) and canonical pathways (d) according to the IPA database. The PPI network shows the interaction of the key proteins involved in the functions highly correlated with regeneration (e). Up-regulated EGR2 (red) was selected to show multi-functions highly correlated with neuroregeneration (f). The interaction network of downstream regulators of EGR2, its downstream up-regulated (red) genes and down-regulated (green) proteins and their functions (g). Orange nodes stand for a predicted activation state. Blue nodes stand for a predicted inhibition state. Color intensity of the nodes in networks were proportional to differentially expression level. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Journal: Journal of Advanced Research

Article Title: Dynamic molecular landscape in dorsal root ganglion for peripheral nerve regeneration promoted by tissue engineered nerve graft

doi: 10.1016/j.jare.2025.07.059

Figure Lengend Snippet: The transcriptional alteration of DRG neurons co-cultured with SKP-SCs. (a) Representative images of phase contrast microscopy of SKP-SCs in the upper chamber and lower ventricular DRG neurons after 48 h co-culture. Scale bar: 100 μm. (b) Schematic illustration of transcriptional analysis of lower ventricular DRG neurons for 48 h co-culture, and bioinformatics. The enrichment analysis showed top 20 diseases and functions (c) and canonical pathways (d) according to the IPA database. The PPI network shows the interaction of the key proteins involved in the functions highly correlated with regeneration (e). Up-regulated EGR2 (red) was selected to show multi-functions highly correlated with neuroregeneration (f). The interaction network of downstream regulators of EGR2, its downstream up-regulated (red) genes and down-regulated (green) proteins and their functions (g). Orange nodes stand for a predicted activation state. Blue nodes stand for a predicted inhibition state. Color intensity of the nodes in networks were proportional to differentially expression level. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Article Snippet: The Ingenuity Pathway Analysis (IPA) software suite (Ingenuity Systems, Redwood City, CA) was employed to identify canonical pathways that are significantly overrepresented.

Techniques: Cell Culture, Microscopy, Co-Culture Assay, Activation Assay, Inhibition, Expressing

Journal: Scientific Reports

Article Title: Uncovering the molecular signature of feline diffuse iris melanoma through transcriptomic analysis of disease severity

doi: 10.1038/s41598-025-09632-5

Figure Lengend Snippet: Transcriptomic analysis of feline diffuse iris melanoma (FDIM). The principal component analysis (PCA) plot grouping samples by the top 500 transcripts after variance-stabilising transformation of transcript counts ( A ). There is clear and separate clustering of the iris melanosis and late FDIM samples, with the early FDIM samples overlapping both groups, showing that early FDIM is an intermediate disease stage. Volcano plots highlight the number of significantly dysregulated transcripts between early FDIM and iris melanosis ( B i), late FDIM and iris melanosis ( C i) and between late and early FDIM ( D i). A logfold-change threshold was set at − 1.5 and 1.5 and an adjusted P-value threshold of 0.05 was used. Ingenuity pathway analysis identified cancer and organismal injury and abnormalities to be the top dysregulated disease pathways between early FDIM and iris melanosis ( B ii), late and iris melanosis ( C ii) and late and early FDIM ( D ii). The disease progression of FDIM is associated with key molecular events ( E ). Tumour initiation is associated with upregulation of STOX1, PEG3, XIAP and VIM , increasing invasive tendencies and immune cell recruitment. Progression to late FDIM is characterised by downregulation of SOX11, FOXC1 and FOXC2 , likely leading to a more dedifferentiated and plastic cellular phenotype. Significant upregulation of BIRC2 and BIRC5 leads to inhibition of apoptosis. Additionally, upregulation of BIRC5, CCL2 and HAVCR2 lead to immune-microenvironment remodelling, associated with the M2 (immunosuppressive) tumour associated macrophages as well as T-regulator (Treg) cells and inhibition of cytotoxic T-cells (CTC), aiding immune escape. Created in BioRender. Kayes, D. (2025) https://BioRender.com/m39r385 .

Article Snippet: Pathway analysis and graphical display of the data was performed using QIAGEN Ingenuity Pathway Analysis (IPA; QIAGEN Inc., https://digitalinsights.qiagen.com/IPA ) – .

Techniques: Transformation Assay, Biomarker Discovery, Inhibition

Purified CD4 + T cells from HDs ( n = 3) and patients with acute ATL ( n = 5) were stimulated with anti-CD3 and anti-CD28 in presence of IL-2 for 4 hours at 37°C. The cells were harvested and subjected to scRNA-seq. ( A ) Schematic representation of the experimental setup for ( B to H ). Created in BioRender. S. Roy (2025) https://BioRender.com/9zdi679 . (B) Uniform Manifold Approximation and Projection (UMAP) plot showing all cells split by HD cells (left) and ATL cells (right). (C) Bar plot showing proportion of the cells in each cluster annotated by Azimuth for each HD and ATL sample. (D) UMAP plot showing distribution of T reg cells split by HD cells (left) and ATL cells (right). (E) Violin plot showing PRDM1 expression in T reg cells in HDs and patients with ATL. (F) UMAP plot showing distribution of PRDM1 − versus PRDM1 + T reg populations in HDs and patients with ATL. (G) Pie chart showing percentage of cells in HDs and patients with ATL that express any amount of PRDM1 . (H) Bar plot showing top pathways (by z score) from Qiagen IPA using differentially expressed genes derived from PRDM1 − versus PRDM1 + populations within T reg cells cluster in patients with ATL.

Journal: Science Advances

Article Title: BLIMP1 negatively regulates IL-2 signaling in T cells

doi: 10.1126/sciadv.adx8105

Figure Lengend Snippet: Purified CD4 + T cells from HDs ( n = 3) and patients with acute ATL ( n = 5) were stimulated with anti-CD3 and anti-CD28 in presence of IL-2 for 4 hours at 37°C. The cells were harvested and subjected to scRNA-seq. ( A ) Schematic representation of the experimental setup for ( B to H ). Created in BioRender. S. Roy (2025) https://BioRender.com/9zdi679 . (B) Uniform Manifold Approximation and Projection (UMAP) plot showing all cells split by HD cells (left) and ATL cells (right). (C) Bar plot showing proportion of the cells in each cluster annotated by Azimuth for each HD and ATL sample. (D) UMAP plot showing distribution of T reg cells split by HD cells (left) and ATL cells (right). (E) Violin plot showing PRDM1 expression in T reg cells in HDs and patients with ATL. (F) UMAP plot showing distribution of PRDM1 − versus PRDM1 + T reg populations in HDs and patients with ATL. (G) Pie chart showing percentage of cells in HDs and patients with ATL that express any amount of PRDM1 . (H) Bar plot showing top pathways (by z score) from Qiagen IPA using differentially expressed genes derived from PRDM1 − versus PRDM1 + populations within T reg cells cluster in patients with ATL.

Article Snippet: Using the differentially expressed genes (DEGs) as input (see table S3), the Qiagen Ingenuity Pathway Analysis (IPA) in PRDM1 − versus PRDM1 + populations within T reg cells revealed up-regulation of pathways including JAK-STAT signaling and IL-2 signaling pathways in the PRDM1 − subpopulation of cells from patients with ATL ( ; see table S4 for the genes used by the Qiagen IPA to identify the pathways).

Techniques: Purification, Expressing, Derivative Assay

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