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bulk rna-seq/microarray data  (Human Protein Atlas)

 
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    Human Protein Atlas bulk rna-seq/microarray data
    Bulk Rna Seq/Microarray Data, supplied by Human Protein Atlas, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/rna-seq+and+microarray+data/whole+retina+bulk+rna+sequencing+data/pmc11232326-140-1-18
    Average 90 stars, based on 1 article reviews
    bulk rna-seq/microarray data - by Bioz Stars, 2026-09
    90/100 stars

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    Article Title: Predicting intercellular communication based on metabolite-related ligand-receptor interactions with MRCLinkdb
    Article Snippet: The bulk RNA-seq/microarray data for gene expression across different tissues in human and mouse were collected from the Human Protein Atlas (HPA) project (62 human tissues) [ ] and the TISSUES 2.0 database (39 mouse tissues) [ ], respectively.

    Article Title: Tissue-adjusted pathway analysis of cancer (TPAC): A novel approach for quantifying tumor-specific gene set dysregulation relative to normal tissue.
    Article Snippet: The findings detailed in this paper are based on bulk RNA-seq and clinical data from The Cancer Genome Atlas (TCGA) [22] for 21 human solid cancers and bulk RNA-seq data from the Human Protein Atlas (HPA) [28] for the associated 18 normal human tissues.

    Article Title: NMNAT2 is a druggable target to drive neuronal NAD production
    Article Snippet: Whole retina bulk RNA-sequencing data is available from The Genotype-Tissue Expression (GTEx) Project through The Human Protein Atlas [accessed 11/22/2022].

    Article Title: Molecular mimicry in multisystem inflammatory syndrome in children.
    Article Snippet: For each autoantigen, tissue RNA-sequencing data from Human Protein Atlas (Proteinatlas.org) is shown.

    Article Title: Deciphering autoantibody landscape of systemic sclerosis through systems-based approach: insights from a B-cell depletion clinical trial
    Article Snippet: Expression of autoantigens associated with “import across plasma membrane” (A) or with “peptide GPCRs” (B) in multiple human tissues, as measured by bulk RNA-sequencing from the Human Protein Atlas.

    Article Title: A lymphocyte chemoaffinity axis for lung, non-intestinal mucosae and CNS.
    Article Snippet: Tissue-selective chemoattractants direct lymphocytes to epithelial surfaces to establish local immune environments, regulate immune responses to food antigens and commensal organisms, and protect from pathogens.. Homeostatic chemoattractants for small intestines, colon and skin are known, but chemotropic mechanisms selective for respiratory tract and other non-intestinal mucosal tissues remain poorly understood.. Here we leveraged diverse omics datasets to identify GPR25 as a lymphocyte receptor for CXCL17, a chemoattractant cytokine whose expression by epithelial cells of airways, upper gastrointestinal and squamous mucosae unifies the non-intestinal mucosal tissues and distinguishes them from intestinal mucosae.

    Article Title: ARTN and CCL23 predicted chemosensitivity in acute myeloid leukemia: an Olink ® proteomics approach
    Article Snippet: Statistical significance is denoted by * p < 0.05 and ** p < 0.01. ( D ) The Human Protein Atlas data show that ARTN and CCL23 are expressed at significantly higher levels ( p < 0.001) in AML patients compared to those with other cancers We used the bulk RNA-seq dataset (GSE164894) to corroborate the plasma proteomic analysis data.

    RNA Sequencing:

    Article Title: CD70-targeted iPSC-derived CAR-NK cells display potent function against tumors and alloreactive T cells
    Article Snippet: Bulk RNA seq (pan-tumor) , The Cancer Genome Atlas , https://portal.gdc.cancer.gov. .. Bulk RNA seq (cancer cell lines) , Human Protein Atlas , https://www.proteinatlas.org. .. Bulk RNA seq , GEPIA database , http://gepia.cancer-pku.cn/.



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    FIGURE 3 Upregulation of IL4I1 infers an unfavorable prognosis for glioma. (A) Representative images (left) and quantification (right) showing IL4I1 staining of normal brain tissues (n = 16) and glioma tissues (n = 37) with the anti-IL4I1 antibody, with scale bars 100 µm (up) and 20 µm (down). (B–D) Kaplan– Meier analysis for OS based on three glioma datasets <t>(CGGA,</t> Rembrandt, and GSE16011). (E–G) ROC curves of OS in CGGA, Rembrandt, and GSE16011 datasets. (H, I) Univariate and multivariate analyses of OS based on CGGA-glioma datasets. ****p < 0.0001.
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    FIGURE 3 Upregulation of IL4I1 infers an unfavorable prognosis for glioma. (A) Representative images (left) and quantification (right) showing IL4I1 staining of normal brain tissues (n = 16) and glioma tissues (n = 37) with the anti-IL4I1 antibody, with scale bars 100 µm (up) and 20 µm (down). (B–D) Kaplan– Meier analysis for OS based on three glioma datasets <t>(CGGA,</t> Rembrandt, and GSE16011). (E–G) ROC curves of OS in CGGA, Rembrandt, and GSE16011 datasets. (H, I) Univariate and multivariate analyses of OS based on CGGA-glioma datasets. ****p < 0.0001.
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    FIGURE 3 Upregulation of IL4I1 infers an unfavorable prognosis for glioma. (A) Representative images (left) and quantification (right) showing IL4I1 staining of normal brain tissues (n = 16) and glioma tissues (n = 37) with the anti-IL4I1 antibody, with scale bars 100 µm (up) and 20 µm (down). (B–D) Kaplan– Meier analysis for OS based on three glioma datasets <t>(CGGA,</t> Rembrandt, and GSE16011). (E–G) ROC curves of OS in CGGA, Rembrandt, and GSE16011 datasets. (H, I) Univariate and multivariate analyses of OS based on CGGA-glioma datasets. ****p < 0.0001.
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    FIGURE 3 Upregulation of IL4I1 infers an unfavorable prognosis for glioma. (A) Representative images (left) and quantification (right) showing IL4I1 staining of normal brain tissues (n = 16) and glioma tissues (n = 37) with the anti-IL4I1 antibody, with scale bars 100 µm (up) and 20 µm (down). (B–D) Kaplan– Meier analysis for OS based on three glioma datasets <t>(CGGA,</t> Rembrandt, and GSE16011). (E–G) ROC curves of OS in CGGA, Rembrandt, and GSE16011 datasets. (H, I) Univariate and multivariate analyses of OS based on CGGA-glioma datasets. ****p < 0.0001.
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    FIGURE 3 Upregulation of IL4I1 infers an unfavorable prognosis for glioma. (A) Representative images (left) and quantification (right) showing IL4I1 staining of normal brain tissues (n = 16) and glioma tissues (n = 37) with the anti-IL4I1 antibody, with scale bars 100 µm (up) and 20 µm (down). (B–D) Kaplan– Meier analysis for OS based on three glioma datasets <t>(CGGA,</t> Rembrandt, and GSE16011). (E–G) ROC curves of OS in CGGA, Rembrandt, and GSE16011 datasets. (H, I) Univariate and multivariate analyses of OS based on CGGA-glioma datasets. ****p < 0.0001.
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    FIGURE 3 Upregulation of IL4I1 infers an unfavorable prognosis for glioma. (A) Representative images (left) and quantification (right) showing IL4I1 staining of normal brain tissues (n = 16) and glioma tissues (n = 37) with the anti-IL4I1 antibody, with scale bars 100 µm (up) and 20 µm (down). (B–D) Kaplan– Meier analysis for OS based on three glioma datasets <t>(CGGA,</t> Rembrandt, and GSE16011). (E–G) ROC curves of OS in CGGA, Rembrandt, and GSE16011 datasets. (H, I) Univariate and multivariate analyses of OS based on CGGA-glioma datasets. ****p < 0.0001.
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    FIGURE 3 Upregulation of IL4I1 infers an unfavorable prognosis for glioma. (A) Representative images (left) and quantification (right) showing IL4I1 staining of normal brain tissues (n = 16) and glioma tissues (n = 37) with the anti-IL4I1 antibody, with scale bars 100 µm (up) and 20 µm (down). (B–D) Kaplan– Meier analysis for OS based on three glioma datasets (CGGA, Rembrandt, and GSE16011). (E–G) ROC curves of OS in CGGA, Rembrandt, and GSE16011 datasets. (H, I) Univariate and multivariate analyses of OS based on CGGA-glioma datasets. ****p < 0.0001.

    Journal: Frontiers in immunology

    Article Title: IL4I1 in M2-like macrophage promotes glioma progression and is a promising target for immunotherapy.

    doi: 10.3389/fimmu.2023.1338244

    Figure Lengend Snippet: FIGURE 3 Upregulation of IL4I1 infers an unfavorable prognosis for glioma. (A) Representative images (left) and quantification (right) showing IL4I1 staining of normal brain tissues (n = 16) and glioma tissues (n = 37) with the anti-IL4I1 antibody, with scale bars 100 µm (up) and 20 µm (down). (B–D) Kaplan– Meier analysis for OS based on three glioma datasets (CGGA, Rembrandt, and GSE16011). (E–G) ROC curves of OS in CGGA, Rembrandt, and GSE16011 datasets. (H, I) Univariate and multivariate analyses of OS based on CGGA-glioma datasets. ****p < 0.0001.

    Article Snippet: Dataset Data type WHO grade II WHO grade III WHO grade IV CGGA RNA-seq 291 334 388 Rembrandt Microarray 98 85 130 GSE16011 Microarray 24 85 159 frontiersin.org (1:2000, 60143-1-Ig, Proteintech), CD163 (1:1,000, ab182422, Abcam), CD86 (1:1,000, ab239075, Abcam), and beta-tubulin (1:2000, DF7967, Affinity) overnight.

    Techniques: Staining

    FIGURE 4 Heightened IL4I1 expression is correlated with the malignant phenotype of gliomas. (A–D) IL4I1 shows a significant increase in GBM (WHO IV) in TCGA, Rembrandt, GSE16011, and CGGA datasets. Additionally, box plots visualizing the associations between IL4I1 and various clinical characteristics based on the CGGA dataset. Specifically: (E) Age. (F) Status. (G) Histology. (H, I) High expression of IL4I1 in IDH wild-type and 1p/19q non-codel gliomas.

    Journal: Frontiers in immunology

    Article Title: IL4I1 in M2-like macrophage promotes glioma progression and is a promising target for immunotherapy.

    doi: 10.3389/fimmu.2023.1338244

    Figure Lengend Snippet: FIGURE 4 Heightened IL4I1 expression is correlated with the malignant phenotype of gliomas. (A–D) IL4I1 shows a significant increase in GBM (WHO IV) in TCGA, Rembrandt, GSE16011, and CGGA datasets. Additionally, box plots visualizing the associations between IL4I1 and various clinical characteristics based on the CGGA dataset. Specifically: (E) Age. (F) Status. (G) Histology. (H, I) High expression of IL4I1 in IDH wild-type and 1p/19q non-codel gliomas.

    Article Snippet: Dataset Data type WHO grade II WHO grade III WHO grade IV CGGA RNA-seq 291 334 388 Rembrandt Microarray 98 85 130 GSE16011 Microarray 24 85 159 frontiersin.org (1:2000, 60143-1-Ig, Proteintech), CD163 (1:1,000, ab182422, Abcam), CD86 (1:1,000, ab239075, Abcam), and beta-tubulin (1:2000, DF7967, Affinity) overnight.

    Techniques: Expressing

    FIGURE 6 IL4I1 is expressed in M2-like macrophages in glioma. (A) Summary of IL4I1 expression in 12 distinct single-cell datasets from glioma patients. (B) Association between IL4I1 and macrophages on XCELL, TIMER, and EPIC algorithms. (C) Association between IL4I1 expression and markers of M1 and M2 macrophages in CGGA and TCGA databases. Color depth and digital scale represent the strength of association. (D) Representative colocalization images from IF staining between IL4I1 and CD206 in clinical glioma specimens. DAPI (blue), IL4I1 (red) and CD206 (green). Scale bar: 20 mm. (E) Measurement of protein and mRNA expression levels for markers (CD11B, CD204, CD86, CD206, and CD163) of THP-1, M0, M1, and M2 macrophages using WB and RT-qPCR. (F) Assessment of IL4I1 expression in various macrophage subtypes (M0, M1, and M2) and glioma cells (U87, LN229, and U251). (G) Representative IF pictures of the difference of IL4I1 among M0, M1, and M2 macrophages, U87, and LN229 cells with DAPI (blue) and IL4I1 (red). *p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001.

    Journal: Frontiers in immunology

    Article Title: IL4I1 in M2-like macrophage promotes glioma progression and is a promising target for immunotherapy.

    doi: 10.3389/fimmu.2023.1338244

    Figure Lengend Snippet: FIGURE 6 IL4I1 is expressed in M2-like macrophages in glioma. (A) Summary of IL4I1 expression in 12 distinct single-cell datasets from glioma patients. (B) Association between IL4I1 and macrophages on XCELL, TIMER, and EPIC algorithms. (C) Association between IL4I1 expression and markers of M1 and M2 macrophages in CGGA and TCGA databases. Color depth and digital scale represent the strength of association. (D) Representative colocalization images from IF staining between IL4I1 and CD206 in clinical glioma specimens. DAPI (blue), IL4I1 (red) and CD206 (green). Scale bar: 20 mm. (E) Measurement of protein and mRNA expression levels for markers (CD11B, CD204, CD86, CD206, and CD163) of THP-1, M0, M1, and M2 macrophages using WB and RT-qPCR. (F) Assessment of IL4I1 expression in various macrophage subtypes (M0, M1, and M2) and glioma cells (U87, LN229, and U251). (G) Representative IF pictures of the difference of IL4I1 among M0, M1, and M2 macrophages, U87, and LN229 cells with DAPI (blue) and IL4I1 (red). *p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001.

    Article Snippet: Dataset Data type WHO grade II WHO grade III WHO grade IV CGGA RNA-seq 291 334 388 Rembrandt Microarray 98 85 130 GSE16011 Microarray 24 85 159 frontiersin.org (1:2000, 60143-1-Ig, Proteintech), CD163 (1:1,000, ab182422, Abcam), CD86 (1:1,000, ab239075, Abcam), and beta-tubulin (1:2000, DF7967, Affinity) overnight.

    Techniques: Expressing, Staining, Quantitative RT-PCR