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Boster Bio primary antibody rabbit polyclonal anti dbpa antibody
Primary Antibody Rabbit Polyclonal Anti Dbpa Antibody, supplied by Boster Bio, used in various techniques. Bioz Stars score: 90/100, based on 2 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/rabbit+polyclonal+anti+dbpa+antibody/Anti-CSDA+Antibody/pm27569444-57-21-27
Average 90 stars, based on 2 article reviews

primary antibody rabbit polyclonal anti dbpa antibody - by Bioz Stars, 2026-09

90/100 stars

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Incubation:

Article Title: RNAi-mediated downregulation of DNA binding protein A inhibits tumorigenesis in colorectal cancer
Article Snippet: .. Subsequently, the slides were incubated overnight at 4°C with the rabbit polyclonal anti-dbpA antibody (ab48952; Boster Biological Technology, Ltd., Wuhan, China) at a 1:500 dilutions. .. Subsequently, the sections were incubated with HRP polymer (1:500; ab6721; Boster Biological Technology, Ltd.) for 30 min at room temperature and DAB mix (Tiangen Biotechnology, Beijing, China) was applied for staining.

Article Title: RNAi-mediated downregulation of DNA binding protein A inhibits tumorigenesis in colorectal cancer
Article Snippet: The cell lysate samples (40 μ g) were separated by 15% SDS-PAGE and transferred onto a polyvinylidene difluoride filter (Immobilon; Millipore, Bedford, MA, USA). .. After blocking with 5% milk, the filter was incubated overnight with a primary rabbit polyclonal anti-dbpA antibody (ab48952; Boster Biological Technology, Ltd.) at 1:500 dilutions for 1 h. The samples were then incubated with the HRP-conjugated secondary antibodies (ab6721) at 1:1,000, and the bands were detected by enhanced chemiluminescence (both from Amersham Biosciences, Piscataway, NJ, USA), and then analyzed using Quantity One software (Bio-Rad Laboratories, Inc., Hercules, CA, USA). ..

Blocking Assay:

Software:

Image Search Results

(A) Immunoblots of overexpression of FLAG-tagged Chek2 in mouse glioma cells GL261. (B) Glioma cells GL261 overexpressing Chek2 were injected intracranially into mice. Tumors were collected for immunoprecipitation followed by mass spectrometry analysis. (C) Volcano plot of mass spectrometry analysis of protein enrichment by immunoprecipitation. The plot displays the log2 fold-change (x-axis) versus the significance (-log10 p-value) for all proteins. Proteins shown in red represent the significantly increased proteins (log2 fold-change.1.5). (D) Volcano plot of TCGA GBM6 RNA-seq data integrated with mass spectrometry-based protein enrichment analysis. (E) Scatter plot showing the correlation between YBX1 and CHEK2 mRNA expression in the TCGA GBM dataset. Statistical analysis was performed using a two-tailed Pearson correlation, revealing a significant positive correlation (r = 0.50, P = 1.07 × 10⁻¹⁰). (F) Schematic representation of the phosphoproteomic assay. (G) Volcano plot showing log2 fold-change (average Chek2 KO/average NTC) versus −log10 (p-value) for all quantified phosphopeptides. Proteins above the dashed line (> 1.3) on the y-axis are statistically significant. Red and green markers represent significantly increased and decreased in phosophorylation, respectively. (H-I) Schematic representative of co-immunoprecipitation assay followed by immunoblots of Chk2, Ybx1 and Ybx3 in mouse glioma cell line GL261.

Journal: bioRxiv

Article Title: Targeting CHEK2-YBX1&YBX3 regulatory hub to potentiate immune checkpoint blockade response in gliomas

doi: 10.1101/2025.03.09.642289

Figure Lengend Snippet: (A) Immunoblots of overexpression of FLAG-tagged Chek2 in mouse glioma cells GL261. (B) Glioma cells GL261 overexpressing Chek2 were injected intracranially into mice. Tumors were collected for immunoprecipitation followed by mass spectrometry analysis. (C) Volcano plot of mass spectrometry analysis of protein enrichment by immunoprecipitation. The plot displays the log2 fold-change (x-axis) versus the significance (-log10 p-value) for all proteins. Proteins shown in red represent the significantly increased proteins (log2 fold-change.1.5). (D) Volcano plot of TCGA GBM6 RNA-seq data integrated with mass spectrometry-based protein enrichment analysis. (E) Scatter plot showing the correlation between YBX1 and CHEK2 mRNA expression in the TCGA GBM dataset. Statistical analysis was performed using a two-tailed Pearson correlation, revealing a significant positive correlation (r = 0.50, P = 1.07 × 10⁻¹⁰). (F) Schematic representation of the phosphoproteomic assay. (G) Volcano plot showing log2 fold-change (average Chek2 KO/average NTC) versus −log10 (p-value) for all quantified phosphopeptides. Proteins above the dashed line (> 1.3) on the y-axis are statistically significant. Red and green markers represent significantly increased and decreased in phosophorylation, respectively. (H-I) Schematic representative of co-immunoprecipitation assay followed by immunoblots of Chk2, Ybx1 and Ybx3 in mouse glioma cell line GL261.

Article Snippet: Membranes were incubated overnight at 4°C with primary antibodies: CHK2 (#2662S), YBX1 (#4202S), β-Actin (#4970S), ATM (#2873S), and CHK1 (#2360S) from Cell Signaling, and YBX3 (#TA324558) from Origene.

Techniques: Western Blot, Over Expression, Injection, Immunoprecipitation, Mass Spectrometry, Protein Enrichment, RNA Sequencing, Expressing, Two Tailed Test, Co-Immunoprecipitation Assay

(A) Immunoblots of single gene knockout of CHEK2, YBX1 or YBX3 in the human GBM cell line U87. The experiments were independently repeated three times. (B) Immunoblots of single gene knockout of CHEK2, YBX1 or YBX3 in the human GBM cell line GBM6. The experiments were independently repeated three times. (C) Immunoblots of single gene knockout of Chek2, Ybx1 or Ybx3 in the mouse glioma cell line GL261. The experiments were independently repeated at least three times. (D) Immunoblots of single gene knockout of Chek2 in the mouse glioma cell line NPA. (E) Schematic representation of gene expression changes in CHEK2 KO, YBX1 KO, and YBX3 KO conditions. Green downward arrows indicate decreased expression, while the red upward arrow represents increased expression. (F-H) RT-qPCR of CHEK2, YBX1 and YBX3 genes in human GBM6 cells with knockout of CHEK2 (F), YBX1 (G), and YBX3 (H). GAPDH was used to normalize target gene expression. The values were expressed as the fold change. Data are expressed as mean ± SE. N = 3 independent experiments with 3 technical replicates per experiment. Statistical differences between cell types were evaluated using one-way ANOVA.

Journal: bioRxiv

Article Title: Targeting CHEK2-YBX1&YBX3 regulatory hub to potentiate immune checkpoint blockade response in gliomas

doi: 10.1101/2025.03.09.642289

Figure Lengend Snippet: (A) Immunoblots of single gene knockout of CHEK2, YBX1 or YBX3 in the human GBM cell line U87. The experiments were independently repeated three times. (B) Immunoblots of single gene knockout of CHEK2, YBX1 or YBX3 in the human GBM cell line GBM6. The experiments were independently repeated three times. (C) Immunoblots of single gene knockout of Chek2, Ybx1 or Ybx3 in the mouse glioma cell line GL261. The experiments were independently repeated at least three times. (D) Immunoblots of single gene knockout of Chek2 in the mouse glioma cell line NPA. (E) Schematic representation of gene expression changes in CHEK2 KO, YBX1 KO, and YBX3 KO conditions. Green downward arrows indicate decreased expression, while the red upward arrow represents increased expression. (F-H) RT-qPCR of CHEK2, YBX1 and YBX3 genes in human GBM6 cells with knockout of CHEK2 (F), YBX1 (G), and YBX3 (H). GAPDH was used to normalize target gene expression. The values were expressed as the fold change. Data are expressed as mean ± SE. N = 3 independent experiments with 3 technical replicates per experiment. Statistical differences between cell types were evaluated using one-way ANOVA.

Techniques: Western Blot, Gene Knockout, Gene Expression, Expressing, Quantitative RT-PCR, Knock-Out, Targeted Gene Expression

(A) Volcano plot showing differentially expressed genes (upregulated and downregulated) in CHK2 knockout U87 cells. Upregulated genes are highlighted in the right half, and downregulated genes are in the left half. (B) Volcano plot showing differentially expressed genes in YBX1 knockout U87 cells. (C) Volcano plot showing differentially expressed genes in YBX3 knockout U87 cells. (D) Venn diagram illustrating the overlap of downregulated genes among CHK2, YBX1, and YBX3 knockout U87 cells, with the central red-labeled region indicating the 244 shared genes. (E) Venn diagram illustrating the overlap of upregulated genes among CHK2, YBX1, and YBX3 knockout U87 cells, with 462 shared genes in the center. (F) KEGG pathway enrichment analysis of the 462 overlapping upregulated genes, visualized as a bar graph. The x-axis represents the-log10(p-value), while the y-axis lists significantly enriched pathways. Darker green bars indicate more significant pathways. (G) Venn diagram showing ChIP-seq data from publicly available ENCODE datasets, illustrating 2,606 genes that are co-bound by YBX1 and YBX3. (H) Venn diagram depicting the overlap between ChIP-seq peaks (YBX1/YBX3-bound regions) and genes upregulated in CHK2, YBX1, and YBX3 knockout cells. The 32 identified genes are likely direct transcriptional targets. (I) Heatmap showing the expression of 32 upregulated genes across CHK2, YBX1, and YBX3 knockout conditions. The color scale represents Z-score normalized expression, where red indicates upregulation and green indicates downregulation. Hierarchical clustering was applied to group genes with similar expression patterns across knockout conditions.

Journal: bioRxiv

Article Title: Targeting CHEK2-YBX1&YBX3 regulatory hub to potentiate immune checkpoint blockade response in gliomas

doi: 10.1101/2025.03.09.642289

Figure Lengend Snippet: (A) Volcano plot showing differentially expressed genes (upregulated and downregulated) in CHK2 knockout U87 cells. Upregulated genes are highlighted in the right half, and downregulated genes are in the left half. (B) Volcano plot showing differentially expressed genes in YBX1 knockout U87 cells. (C) Volcano plot showing differentially expressed genes in YBX3 knockout U87 cells. (D) Venn diagram illustrating the overlap of downregulated genes among CHK2, YBX1, and YBX3 knockout U87 cells, with the central red-labeled region indicating the 244 shared genes. (E) Venn diagram illustrating the overlap of upregulated genes among CHK2, YBX1, and YBX3 knockout U87 cells, with 462 shared genes in the center. (F) KEGG pathway enrichment analysis of the 462 overlapping upregulated genes, visualized as a bar graph. The x-axis represents the-log10(p-value), while the y-axis lists significantly enriched pathways. Darker green bars indicate more significant pathways. (G) Venn diagram showing ChIP-seq data from publicly available ENCODE datasets, illustrating 2,606 genes that are co-bound by YBX1 and YBX3. (H) Venn diagram depicting the overlap between ChIP-seq peaks (YBX1/YBX3-bound regions) and genes upregulated in CHK2, YBX1, and YBX3 knockout cells. The 32 identified genes are likely direct transcriptional targets. (I) Heatmap showing the expression of 32 upregulated genes across CHK2, YBX1, and YBX3 knockout conditions. The color scale represents Z-score normalized expression, where red indicates upregulation and green indicates downregulation. Hierarchical clustering was applied to group genes with similar expression patterns across knockout conditions.

Techniques: Knock-Out, Labeling, ChIP-sequencing, Expressing

(A) Pathway enrichment analysis of upregulated genes overlapping in CHK2, YBX1, and YBX3 knockout (KO) U87 cells. The bar graph represents significant pathways, showing the adjusted p-values along the x-axis and the associated genes within each pathway. (B) Venn diagram illustrating the overlap between downregulated genes at the RNA level (from CHK2, YBX1, and YBX3 KO cells) and genes transcriptionally regulated by YBX1 and YBX3 (identified through ChIP-seq). A total of 29 genes were identified as common between the two datasets. (C) Heatmap representing the expression levels of the 29 downregulated genes in CHK2, YBX1, and YBX3 KO cells. The color gradient represents the Z-score normalized expression, with red indicating upregulation and green indicating downregulation. Hierarchical clustering was applied to visualize gene expression patterns across different KO conditions.

Journal: bioRxiv

Article Title: Targeting CHEK2-YBX1&YBX3 regulatory hub to potentiate immune checkpoint blockade response in gliomas

doi: 10.1101/2025.03.09.642289

Figure Lengend Snippet: (A) Pathway enrichment analysis of upregulated genes overlapping in CHK2, YBX1, and YBX3 knockout (KO) U87 cells. The bar graph represents significant pathways, showing the adjusted p-values along the x-axis and the associated genes within each pathway. (B) Venn diagram illustrating the overlap between downregulated genes at the RNA level (from CHK2, YBX1, and YBX3 KO cells) and genes transcriptionally regulated by YBX1 and YBX3 (identified through ChIP-seq). A total of 29 genes were identified as common between the two datasets. (C) Heatmap representing the expression levels of the 29 downregulated genes in CHK2, YBX1, and YBX3 KO cells. The color gradient represents the Z-score normalized expression, with red indicating upregulation and green indicating downregulation. Hierarchical clustering was applied to visualize gene expression patterns across different KO conditions.

Techniques: Knock-Out, ChIP-sequencing, Expressing, Gene Expression

(A) Single-cell RNA sequencing UMAP plots showing the expression of CHEK2, YBX1, and YBX3 across different cell clusters. The color scale indicates the expression levels of each gene, where purple represents low or no expression, and yellow-green represents high expression. (B) Enrichment score distribution in all tumor cell subsets. (C) Density plot showing the cutoff for Chek2 gene set enrichment score in tumor cells. (D) Annotation of complete scRNA-seq reference including Hub KO high positive tumor cells.

Journal: bioRxiv

Article Title: Targeting CHEK2-YBX1&YBX3 regulatory hub to potentiate immune checkpoint blockade response in gliomas

doi: 10.1101/2025.03.09.642289

Figure Lengend Snippet: (A) Single-cell RNA sequencing UMAP plots showing the expression of CHEK2, YBX1, and YBX3 across different cell clusters. The color scale indicates the expression levels of each gene, where purple represents low or no expression, and yellow-green represents high expression. (B) Enrichment score distribution in all tumor cell subsets. (C) Density plot showing the cutoff for Chek2 gene set enrichment score in tumor cells. (D) Annotation of complete scRNA-seq reference including Hub KO high positive tumor cells.

Techniques: RNA Sequencing, Expressing

(A) Overview of annotated GBM reference single cell RNA-seq and spatial transcriptomics data. (B) Neoplastic cell subpopulations of scRNA-seq reference in A. (C) Single cell enrichment scores for the consensus upregulated gene signature from Chek2, YBX1 and YBX2 KO of U87 human glioma. (D) Assignment of a Hub KO high positive tumor cell subpopulation. (E) Distribution of the tumor subpopulations for Hub KO high positive and negative tumor cells. (F) Scaled expression values of the genes identified from CHIP-Seq overlapping common upregulated genes of CHEK2, YBX1&YBX3 KO cells. (G) Spatial expression of marker genes from Hub KO high positive tumor cell subcluster. (H) Two examples of spatial enrichment for the marker genes from the Hub KO high positive tumor cell subcluster. (I) Spatial correlation between cell types in the tumor microenvironment and Hub Hub KO high positive tumor cells. (J) Consensus of enriched gene sets associated with CHEK2-positive tumor cell regions across the spatial cohort.

Journal: bioRxiv

Article Title: Targeting CHEK2-YBX1&YBX3 regulatory hub to potentiate immune checkpoint blockade response in gliomas

doi: 10.1101/2025.03.09.642289

Figure Lengend Snippet: (A) Overview of annotated GBM reference single cell RNA-seq and spatial transcriptomics data. (B) Neoplastic cell subpopulations of scRNA-seq reference in A. (C) Single cell enrichment scores for the consensus upregulated gene signature from Chek2, YBX1 and YBX2 KO of U87 human glioma. (D) Assignment of a Hub KO high positive tumor cell subpopulation. (E) Distribution of the tumor subpopulations for Hub KO high positive and negative tumor cells. (F) Scaled expression values of the genes identified from CHIP-Seq overlapping common upregulated genes of CHEK2, YBX1&YBX3 KO cells. (G) Spatial expression of marker genes from Hub KO high positive tumor cell subcluster. (H) Two examples of spatial enrichment for the marker genes from the Hub KO high positive tumor cell subcluster. (I) Spatial correlation between cell types in the tumor microenvironment and Hub Hub KO high positive tumor cells. (J) Consensus of enriched gene sets associated with CHEK2-positive tumor cell regions across the spatial cohort.

Techniques: RNA Sequencing, Expressing, ChIP-sequencing, Marker

(A) Schematic representation of YBX1 inhibitor SU056 inhibiting YBX1 protein. (B) Proposed model of SU056 targeting the CHK2-YBX1&YBX3 hub. (C-E) Immunoblots of CHK2, YBX1, and YBX3 in human (C) U87 NTC (D) GBM6 and mouse (E) GL261 glioma cells treated with or without SU056 β-Actin. (F–G) RT-qPCR of CHK2, YBX1, and YBX3 mRNA expression in U87 (F) and GL261 (G) cells treated with or without SU056. The values were expressed as the fold change. Data are expressed as mean ± SE. N = 3 independent experiments with 3 technical replicates per experiment. (H–I) GBM cell viability assay. CellTiter-Glo® assay in U87 (H) and GL261 (I) cells following with or without SU056 treatment. N = 4 independent experiments.

Journal: bioRxiv

Article Title: Targeting CHEK2-YBX1&YBX3 regulatory hub to potentiate immune checkpoint blockade response in gliomas

doi: 10.1101/2025.03.09.642289

Figure Lengend Snippet: (A) Schematic representation of YBX1 inhibitor SU056 inhibiting YBX1 protein. (B) Proposed model of SU056 targeting the CHK2-YBX1&YBX3 hub. (C-E) Immunoblots of CHK2, YBX1, and YBX3 in human (C) U87 NTC (D) GBM6 and mouse (E) GL261 glioma cells treated with or without SU056 β-Actin. (F–G) RT-qPCR of CHK2, YBX1, and YBX3 mRNA expression in U87 (F) and GL261 (G) cells treated with or without SU056. The values were expressed as the fold change. Data are expressed as mean ± SE. N = 3 independent experiments with 3 technical replicates per experiment. (H–I) GBM cell viability assay. CellTiter-Glo® assay in U87 (H) and GL261 (I) cells following with or without SU056 treatment. N = 4 independent experiments.

Techniques: Western Blot, Quantitative RT-PCR, Expressing, Viability Assay, Glo Assay

(A) Schematic representation of the experimental targeting engagement of SU056 timeline. C57BL/6 mice implanted intracranially with GL261 glioma cells, and administration of SUO56 started on day 21. Tumors were collected for WB and IHC analysis between on day 24. (B) Immunoblots of Chk2, Ybx1 and Ybx3 of tumor lysates harvested from brain tumor tissue of mice treated with SU056 or vehicle captisol. (C-D) Representative IHC staining of glioma sections for CD8a in vehicle-treated (C) and SU056-treated (D) mice. Black arrows indicate CD8a+ T cell infiltration into the tumor and brain microenvironment. Insets show magnified views of CD8a+ cells within the tumor. Scale bars: 50 µm, for small images. Scale bars: 2.5 mm, for full image. (E) Quantification of CD8a+ T cell infiltration in glioma sections from C. SU056 treatment significantly increased CD8a+ T cell infiltration compared with the control group. (**, P < 0.01, Student’s t-test). (F) Schematic of the treatment regimen for survival studies. Mice bearing intracranial GL261 gliomas treated with SU056 alone, PD-1 blockade alone, or the combination of SU056 and anti– PD-1 starting on day 7. (F) Kaplan–Meier survival curves for GL261 glioma-bearing mice. Mice were randomized into four groups (n = 10 per group): vehicle + IgG (VC + IgG), VC + anti–PD-1, SU056 + IgG, and SU056 + anti–PD-1. The median survival durations for each group were as follows: VC + IgG, 31.5 days; VC + anti–PD-1, 38.5 days; SU056 + IgG, 51.5 days; and SU056 + anti–PD-1, 71.5 days. Statistical comparisons: VC + IgG vs. SU056 + IgG (P =0.0002); and VC + IgG vs. SU056 + anti– PD-1 (P < 0.0001). (H) Schematic of the treatment regimen for survival studies in NPA glioma-bearing mice. Mice treated with SU056, PD-1 blockade, or their combination following tumor implantation. (I) Kaplan–Meier survival curves for NPA glioma-bearing mice treated as in G. Combination therapy with SU056 and PD-1 blockade significantly improved survival compared with single-agent treatments. Mice were randomized into four groups (n = 10 or n=9 per group): vehicle + IgG (VC + IgG), VC + anti–PD-1, SU056 + IgG, and SU056 + anti–PD-1. The median survival durations for each group were as follows: VC + IgG, 20 days; VC + anti–PD-1, 22 days; SU056 + IgG, 32 days; and SU056 + anti–PD-1, 49.5 days. Statistical comparisons: VC + IgG vs. SU056 + IgG (P =0.0003); and VC + IgG vs. SU056 + anti–PD-1 (P < 0.0001). (J) Schematic of the treatment regimen incorporating PD-L1 blockade in NPA glioma-bearing mice. Mice received SU056, PD-L1 blockade, or their combination. (K) Kaplan–Meier survival curves for NPA glioma-bearing mice treated. Mice were randomized into four groups (n = 10 or n=9 per group): vehicle + IgG (VC + IgG), VC + anti-PD-L1, SU056 + IgG, and SU056 + anti-PD-L1. The median survival durations for each group were as follows: VC + IgG, 20 days; VC + anti-PD-L1, 22 days; SU056 + IgG, 32 days; and SU056 + anti-PD-L1, 65 days. Statistical comparisons: VC + IgG vs. SU056 + IgG (P =0.0003); and VC + IgG vs. SU056 + anti-PD-L1 (P < 0.0001).

Journal: bioRxiv

Article Title: Targeting CHEK2-YBX1&YBX3 regulatory hub to potentiate immune checkpoint blockade response in gliomas

doi: 10.1101/2025.03.09.642289

Figure Lengend Snippet: (A) Schematic representation of the experimental targeting engagement of SU056 timeline. C57BL/6 mice implanted intracranially with GL261 glioma cells, and administration of SUO56 started on day 21. Tumors were collected for WB and IHC analysis between on day 24. (B) Immunoblots of Chk2, Ybx1 and Ybx3 of tumor lysates harvested from brain tumor tissue of mice treated with SU056 or vehicle captisol. (C-D) Representative IHC staining of glioma sections for CD8a in vehicle-treated (C) and SU056-treated (D) mice. Black arrows indicate CD8a+ T cell infiltration into the tumor and brain microenvironment. Insets show magnified views of CD8a+ cells within the tumor. Scale bars: 50 µm, for small images. Scale bars: 2.5 mm, for full image. (E) Quantification of CD8a+ T cell infiltration in glioma sections from C. SU056 treatment significantly increased CD8a+ T cell infiltration compared with the control group. (**, P < 0.01, Student’s t-test). (F) Schematic of the treatment regimen for survival studies. Mice bearing intracranial GL261 gliomas treated with SU056 alone, PD-1 blockade alone, or the combination of SU056 and anti– PD-1 starting on day 7. (F) Kaplan–Meier survival curves for GL261 glioma-bearing mice. Mice were randomized into four groups (n = 10 per group): vehicle + IgG (VC + IgG), VC + anti–PD-1, SU056 + IgG, and SU056 + anti–PD-1. The median survival durations for each group were as follows: VC + IgG, 31.5 days; VC + anti–PD-1, 38.5 days; SU056 + IgG, 51.5 days; and SU056 + anti–PD-1, 71.5 days. Statistical comparisons: VC + IgG vs. SU056 + IgG (P =0.0002); and VC + IgG vs. SU056 + anti– PD-1 (P < 0.0001). (H) Schematic of the treatment regimen for survival studies in NPA glioma-bearing mice. Mice treated with SU056, PD-1 blockade, or their combination following tumor implantation. (I) Kaplan–Meier survival curves for NPA glioma-bearing mice treated as in G. Combination therapy with SU056 and PD-1 blockade significantly improved survival compared with single-agent treatments. Mice were randomized into four groups (n = 10 or n=9 per group): vehicle + IgG (VC + IgG), VC + anti–PD-1, SU056 + IgG, and SU056 + anti–PD-1. The median survival durations for each group were as follows: VC + IgG, 20 days; VC + anti–PD-1, 22 days; SU056 + IgG, 32 days; and SU056 + anti–PD-1, 49.5 days. Statistical comparisons: VC + IgG vs. SU056 + IgG (P =0.0003); and VC + IgG vs. SU056 + anti–PD-1 (P < 0.0001). (J) Schematic of the treatment regimen incorporating PD-L1 blockade in NPA glioma-bearing mice. Mice received SU056, PD-L1 blockade, or their combination. (K) Kaplan–Meier survival curves for NPA glioma-bearing mice treated. Mice were randomized into four groups (n = 10 or n=9 per group): vehicle + IgG (VC + IgG), VC + anti-PD-L1, SU056 + IgG, and SU056 + anti-PD-L1. The median survival durations for each group were as follows: VC + IgG, 20 days; VC + anti-PD-L1, 22 days; SU056 + IgG, 32 days; and SU056 + anti-PD-L1, 65 days. Statistical comparisons: VC + IgG vs. SU056 + IgG (P =0.0003); and VC + IgG vs. SU056 + anti-PD-L1 (P < 0.0001).

Techniques: Western Blot, Immunohistochemistry, Control, Tumor Implantation

Journal: bioRxiv

Article Title: Targeting CHEK2-YBX1&YBX3 regulatory hub to potentiate immune checkpoint blockade response in gliomas

doi: 10.1101/2025.03.09.642289

Figure Lengend Snippet:

Techniques: shRNA, Construct

Journal: Frontiers in Immunology

Article Title: Identification and verification of YBX3 and its regulatory gene HEIH as an oncogenic system: A multidimensional analysis in colon cancer

doi: 10.3389/fimmu.2022.957865

Figure Lengend Snippet: Expression level of YBX3 gene in diverse tumors, normal tissues, and cell lines (* p < 0.05, ** p < 0.01, *** p < 0.001). (A) YBX3 expression profile in unpaired samples among pan-cancer. (B) YBX3 expression in different normal tissues. (C) YBX3 expression in diverse cell lines of different organs. (D) YBX3 expression in The Cancer Genome Atlas tumors and corresponding adjacent normal tissues in paired samples. (E) YBX3 expression in some cancers using data from GTEx databases as controls. ns, non-significant.

Article Snippet: Then, western blot (WB) was performed according to standard procedures with YBX3 primary antibody (ORIGENE, YBX3 rabbit polyclonal antibody, catalog no. TA324558, 1:1,000).

Techniques: Expressing

Associations between HEIH/YBX3 expression and the prognosis in different clinical subgroups of colon cancer. (A) Effect of YBX3 expression on colon cancer of higher pathological stage, cohorts of lymphatic invasion, and CEA >5. (B) Effect of HEIH expression on colon cancer of patients with residual tumor and perineural invasion.

Journal: Frontiers in Immunology

Article Title: Identification and verification of YBX3 and its regulatory gene HEIH as an oncogenic system: A multidimensional analysis in colon cancer

doi: 10.3389/fimmu.2022.957865

Figure Lengend Snippet: Associations between HEIH/YBX3 expression and the prognosis in different clinical subgroups of colon cancer. (A) Effect of YBX3 expression on colon cancer of higher pathological stage, cohorts of lymphatic invasion, and CEA >5. (B) Effect of HEIH expression on colon cancer of patients with residual tumor and perineural invasion.

Article Snippet: Then, western blot (WB) was performed according to standard procedures with YBX3 primary antibody (ORIGENE, YBX3 rabbit polyclonal antibody, catalog no. TA324558, 1:1,000).

Techniques: Expressing

Top 50 genes correlated with YBX3 and HEIH expression in colon adenocarcinoma (COAD). (A) Gene co-expression heat map of the top 50 genes positively correlated with YBX3 in COAD. (B, a–e) Correlation analysis of the top five genes and YBX3 expression of COAD (positively correlated). (C) Gene co-expression heat map of the top 50 genes negatively correlated with YBX3 in COAD. (D, a–e) Correlation analysis of the top five genes and YBX3 expression of COAD (negatively correlated). (E) Gene co-expression heat map of the top 50 genes positively correlated with HEIH in COAD. (F, a–e) Correlation analysis of the top five genes and HEIH expression of COAD (positively correlated). ( G ) Gene co-expression heat map of the top 50 genes negatively correlated with HEIH in COAD. (H, a–e) Correlation analysis of the top five genes and HEIH expression of COAD (negatively correlated).

Journal: Frontiers in Immunology

Article Title: Identification and verification of YBX3 and its regulatory gene HEIH as an oncogenic system: A multidimensional analysis in colon cancer

doi: 10.3389/fimmu.2022.957865

Figure Lengend Snippet: Top 50 genes correlated with YBX3 and HEIH expression in colon adenocarcinoma (COAD). (A) Gene co-expression heat map of the top 50 genes positively correlated with YBX3 in COAD. (B, a–e) Correlation analysis of the top five genes and YBX3 expression of COAD (positively correlated). (C) Gene co-expression heat map of the top 50 genes negatively correlated with YBX3 in COAD. (D, a–e) Correlation analysis of the top five genes and YBX3 expression of COAD (negatively correlated). (E) Gene co-expression heat map of the top 50 genes positively correlated with HEIH in COAD. (F, a–e) Correlation analysis of the top five genes and HEIH expression of COAD (positively correlated). ( G ) Gene co-expression heat map of the top 50 genes negatively correlated with HEIH in COAD. (H, a–e) Correlation analysis of the top five genes and HEIH expression of COAD (negatively correlated).

Article Snippet: Then, western blot (WB) was performed according to standard procedures with YBX3 primary antibody (ORIGENE, YBX3 rabbit polyclonal antibody, catalog no. TA324558, 1:1,000).

Techniques: Expressing

Protein–protein interaction (PPI) network construction and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of differentially expressed genes (DEGs) between HEIH/YBX3 high-expression and low-expression groups in COAD. (A) Volcano map of DEGs of HEIH expression in COAD (red: upregulation; blue: downregulation). (B) GO and KEGG pathway enrichment analyses of DEGs of HEIH in the form of a chordal graph. (C, a) Hub genes of PPI network (ranking first) and MCODE2 components identified in the gene lists. (C, b) Enrichment analysis of the hub gene network. (D, a) Hub genes of PPI network (ranking second) and MCODE2 components identified in the gene lists. (D, b) Enrichment analysis of the hub gene network. (E, a) Hub genes of PPI network (ranking third) and MCODE2 components identified in the gene lists. (E, b) Enrichment analysis of the hub gene network. (F) Volcano map of DEGs of YBX3 expression in COAD (purple: upregulation; blue: downregulation). (G) GO and KEGG pathway enrichment analyses of DEGs of YBX3 in the form of a chordal graph. (H, a) Hub genes of PPI network (ranking first) and MCODE2 components identified in the gene lists. (H, b) Enrichment analysis of the hub gene network. (I, a) Hub genes of PPI network (ranking second) and MCODE2 components identified in the gene lists. (I, b) Enrichment analysis of the hub gene network. (J, a) Hub genes of PPI network (ranking third) and MCODE2 components identified in the gene lists. (J, b) enrichment analysis of the hub gene network.

Journal: Frontiers in Immunology

Article Title: Identification and verification of YBX3 and its regulatory gene HEIH as an oncogenic system: A multidimensional analysis in colon cancer

doi: 10.3389/fimmu.2022.957865

Figure Lengend Snippet: Protein–protein interaction (PPI) network construction and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of differentially expressed genes (DEGs) between HEIH/YBX3 high-expression and low-expression groups in COAD. (A) Volcano map of DEGs of HEIH expression in COAD (red: upregulation; blue: downregulation). (B) GO and KEGG pathway enrichment analyses of DEGs of HEIH in the form of a chordal graph. (C, a) Hub genes of PPI network (ranking first) and MCODE2 components identified in the gene lists. (C, b) Enrichment analysis of the hub gene network. (D, a) Hub genes of PPI network (ranking second) and MCODE2 components identified in the gene lists. (D, b) Enrichment analysis of the hub gene network. (E, a) Hub genes of PPI network (ranking third) and MCODE2 components identified in the gene lists. (E, b) Enrichment analysis of the hub gene network. (F) Volcano map of DEGs of YBX3 expression in COAD (purple: upregulation; blue: downregulation). (G) GO and KEGG pathway enrichment analyses of DEGs of YBX3 in the form of a chordal graph. (H, a) Hub genes of PPI network (ranking first) and MCODE2 components identified in the gene lists. (H, b) Enrichment analysis of the hub gene network. (I, a) Hub genes of PPI network (ranking second) and MCODE2 components identified in the gene lists. (I, b) Enrichment analysis of the hub gene network. (J, a) Hub genes of PPI network (ranking third) and MCODE2 components identified in the gene lists. (J, b) enrichment analysis of the hub gene network.

Article Snippet: Then, western blot (WB) was performed according to standard procedures with YBX3 primary antibody (ORIGENE, YBX3 rabbit polyclonal antibody, catalog no. TA324558, 1:1,000).

Techniques: Expressing

Journal: Frontiers in Immunology

Article Title: Identification and verification of YBX3 and its regulatory gene HEIH as an oncogenic system: A multidimensional analysis in colon cancer

doi: 10.3389/fimmu.2022.957865

Figure Lengend Snippet: Localization, single-cell variation, and expression profile patterns of YBX3. (A) YBX3 protein topology. (B) Immunofluorescence staining of the subcellular distribution of YBX3 within the cytoplasm and nucleus of A-431, PC-3, and U-2 cell lines as adopted from the HPA database. (C) Bar plot of YBX3 mRNA expressions in diverse normal human tissues from the GTEx database. (D) Construction of YBX3-associated disease network.

Article Snippet: Then, western blot (WB) was performed according to standard procedures with YBX3 primary antibody (ORIGENE, YBX3 rabbit polyclonal antibody, catalog no. TA324558, 1:1,000).

Techniques: Expressing, Immunofluorescence, Staining

Journal: Frontiers in Immunology

Article Title: Identification and verification of YBX3 and its regulatory gene HEIH as an oncogenic system: A multidimensional analysis in colon cancer

doi: 10.3389/fimmu.2022.957865

Figure Lengend Snippet: Impact of YBX3 expression on immune/immunosuppressive cells across The Cancer Genome Atlas (TCGA) cancers and on the biomarker value of ICB sub-cohorts and YBX3 expression profile in different immune cells. (A) Correlations between YBX3 expression and infiltration of six immune cell types across all cancer types in TCGA cohorts. (B) Correlations of YBX3 expression with three immunosuppressive cell types in various TCGA cancer types. (C) Biomarker relevance of MXD3 compared to standardized cancer immune evasion biomarkers in immune checkpoint blockade sub-cohorts. (D, E) Presenting YBX3 and HEIH expression profile in different immune cells using scRNA-seq data from GEO database.

Article Snippet: Then, western blot (WB) was performed according to standard procedures with YBX3 primary antibody (ORIGENE, YBX3 rabbit polyclonal antibody, catalog no. TA324558, 1:1,000).

Techniques: Expressing, Biomarker Discovery

Experimental verification of the combination and role of HEIH/YBX3 in colon cancer. (A) lncRNA HEIH pull-down. (B) Enrichment analysis of the pulled-down proteins. (C) Correlation between YBX3 expression in diverse clinical stages and prognosis in the colon cancer cohort. (D) HEIH expression level in various cancer stages quantified by qPCR. (E) YBX3 expression level in various cancer stages quantified by qPCR. (F) In SW620 cell line, lncRNA-HEIH knockdown enhanced the YBX3 expression confirmed by western blot. (G) Immunohistochemical staining of tissue microarray showing the YBX3 expression in different clinical pathological stages in magnifications of ×25, ×100, and ×200, respectively. *P<0.05; **P<0.01; ns, non-significant.

Journal: Frontiers in Immunology

Article Title: Identification and verification of YBX3 and its regulatory gene HEIH as an oncogenic system: A multidimensional analysis in colon cancer

doi: 10.3389/fimmu.2022.957865

Figure Lengend Snippet: Experimental verification of the combination and role of HEIH/YBX3 in colon cancer. (A) lncRNA HEIH pull-down. (B) Enrichment analysis of the pulled-down proteins. (C) Correlation between YBX3 expression in diverse clinical stages and prognosis in the colon cancer cohort. (D) HEIH expression level in various cancer stages quantified by qPCR. (E) YBX3 expression level in various cancer stages quantified by qPCR. (F) In SW620 cell line, lncRNA-HEIH knockdown enhanced the YBX3 expression confirmed by western blot. (G) Immunohistochemical staining of tissue microarray showing the YBX3 expression in different clinical pathological stages in magnifications of ×25, ×100, and ×200, respectively. *P<0.05; **P<0.01; ns, non-significant.

Article Snippet: Then, western blot (WB) was performed according to standard procedures with YBX3 primary antibody (ORIGENE, YBX3 rabbit polyclonal antibody, catalog no. TA324558, 1:1,000).

Techniques: Expressing, Knockdown, Western Blot, Immunohistochemical staining, Staining, Microarray

Expression of dbpA in colorectal tumor and adjacent normal tissue samples.

Journal: International Journal of Molecular Medicine

Article Title: RNAi-mediated downregulation of DNA binding protein A inhibits tumorigenesis in colorectal cancer

doi: 10.3892/ijmm.2016.2662

Figure Lengend Snippet: Expression of dbpA in colorectal tumor and adjacent normal tissue samples.

Article Snippet: Subsequently, the slides were incubated overnight at 4°C with the rabbit polyclonal anti-dbpA antibody (ab48952; Boster Biological Technology, Ltd., Wuhan, China) at a 1:500 dilutions.

Techniques: Expressing

Expression of DNA binding protein A (dbpA) in tissues obtained from patients with colorectal cancer (CRC) and various CRC cell lines using immunohistochemistry (IHC). T, tumor tissues; A, adjacent normal tissues; C, cytoplasm; and T1-T4, invasion depth. (A) dbpA expression in tumors and adjacent normal tissues (×100 magnification). (B) The levels of dbpA expression in different invasion depths (×100 magnification). RT-qPCR analysis of the mRNA expression of the dbpA in various human CRC cell lines. (C) Western blot analysis of dbpA protein levels. GAPDH was used as an internal control. Data are shown as the means ± standard deviation (SD).

Journal: International Journal of Molecular Medicine

Article Title: RNAi-mediated downregulation of DNA binding protein A inhibits tumorigenesis in colorectal cancer

doi: 10.3892/ijmm.2016.2662

Figure Lengend Snippet: Expression of DNA binding protein A (dbpA) in tissues obtained from patients with colorectal cancer (CRC) and various CRC cell lines using immunohistochemistry (IHC). T, tumor tissues; A, adjacent normal tissues; C, cytoplasm; and T1-T4, invasion depth. (A) dbpA expression in tumors and adjacent normal tissues (×100 magnification). (B) The levels of dbpA expression in different invasion depths (×100 magnification). RT-qPCR analysis of the mRNA expression of the dbpA in various human CRC cell lines. (C) Western blot analysis of dbpA protein levels. GAPDH was used as an internal control. Data are shown as the means ± standard deviation (SD).

Techniques: Expressing, Binding Assay, Immunohistochemistry, Quantitative RT-PCR, Western Blot, Control, Standard Deviation

Association between dbpA expression and clinicopathologic factors in patient with CRC.

Journal: International Journal of Molecular Medicine

Article Title: RNAi-mediated downregulation of DNA binding protein A inhibits tumorigenesis in colorectal cancer

doi: 10.3892/ijmm.2016.2662

Figure Lengend Snippet: Association between dbpA expression and clinicopathologic factors in patient with CRC.

Techniques: Expressing, Significance Assay

DNA binding protein A (dbpA) knockdown by lentiviral-mediated RNAi. (A) Representative images of SW620 cells transfected with shRNA-dbpA-Lv, shNC-dbpA-Lv, or untransfected cells (CON) for 72 h (×100 magnification). GFP expression indicated that the cells had been successfully infected with the shRNA. (B) RT-qPCR analysis of dbpA mRNA levels in cells treated as in (A). (C) Western blot analysis showing dbpA protein levels in cells treated as in (A). GAPDH was used as an internal control. Data are shown as the means ± standard deviation (SD); ** p<0.01 vs. NC.

Journal: International Journal of Molecular Medicine

Article Title: RNAi-mediated downregulation of DNA binding protein A inhibits tumorigenesis in colorectal cancer

doi: 10.3892/ijmm.2016.2662

Figure Lengend Snippet: DNA binding protein A (dbpA) knockdown by lentiviral-mediated RNAi. (A) Representative images of SW620 cells transfected with shRNA-dbpA-Lv, shNC-dbpA-Lv, or untransfected cells (CON) for 72 h (×100 magnification). GFP expression indicated that the cells had been successfully infected with the shRNA. (B) RT-qPCR analysis of dbpA mRNA levels in cells treated as in (A). (C) Western blot analysis showing dbpA protein levels in cells treated as in (A). GAPDH was used as an internal control. Data are shown as the means ± standard deviation (SD); ** p<0.01 vs. NC.

Techniques: Binding Assay, Knockdown, Transfection, shRNA, Expressing, Infection, Quantitative RT-PCR, Western Blot, Control, Standard Deviation

Effect of DNA binding protein A (dbpA) silencing on SW620 cell proliferation. (A) MTT assay measuring cell proliferation of lentivirus-transfected SW620 cells. (B) Quantification of clone number in SW620 cells transfected with shRNA-dbpA-Lv, shNC-dbpA-Lv, or empty vector-transfected cells (CON). (C) Representative images of colony formation assay for SW620 cells in a 6-well plate. (D) Representative images per colony for SW620 cells under a bright microscope. Data are shown as the means ± standard deviation (SD); * p<0.05, ** p<0.01 vs. NC.

Journal: International Journal of Molecular Medicine

Article Title: RNAi-mediated downregulation of DNA binding protein A inhibits tumorigenesis in colorectal cancer

doi: 10.3892/ijmm.2016.2662

Figure Lengend Snippet: Effect of DNA binding protein A (dbpA) silencing on SW620 cell proliferation. (A) MTT assay measuring cell proliferation of lentivirus-transfected SW620 cells. (B) Quantification of clone number in SW620 cells transfected with shRNA-dbpA-Lv, shNC-dbpA-Lv, or empty vector-transfected cells (CON). (C) Representative images of colony formation assay for SW620 cells in a 6-well plate. (D) Representative images per colony for SW620 cells under a bright microscope. Data are shown as the means ± standard deviation (SD); * p<0.05, ** p<0.01 vs. NC.

Techniques: Binding Assay, MTT Assay, Transfection, shRNA, Plasmid Preparation, Colony Assay, Microscopy, Standard Deviation

Effect of DNA binding protein A (dbpA) silencing on cell cycle progression in SW620 cells. (A) Representative images of cell cycle analysis at 72 h by flow cytometry. (B) Cell cycle distribution in SW620 cells transfected with shRNA-dbpA-Lv, shNC-dbpA-Lv, or empty vector. Data are shown as the means ± standard deviation (SD); ** p<0.01 vs. NC.

Journal: International Journal of Molecular Medicine

Article Title: RNAi-mediated downregulation of DNA binding protein A inhibits tumorigenesis in colorectal cancer

doi: 10.3892/ijmm.2016.2662

Figure Lengend Snippet: Effect of DNA binding protein A (dbpA) silencing on cell cycle progression in SW620 cells. (A) Representative images of cell cycle analysis at 72 h by flow cytometry. (B) Cell cycle distribution in SW620 cells transfected with shRNA-dbpA-Lv, shNC-dbpA-Lv, or empty vector. Data are shown as the means ± standard deviation (SD); ** p<0.01 vs. NC.

Techniques: Binding Assay, Cell Cycle Assay, Flow Cytometry, Transfection, shRNA, Plasmid Preparation, Standard Deviation

Apoptosis induction in SW620 cells transfected with short hairpin RNA (shRNA)-DNA binding protein A (dbpA)-Lv, shNC-dbpA-Lv, or empty vector. (A) Cell apoptosis was analyzed by flow cytometry. (B) Cell apoptosis in SW620 cells treated as in (A). Data are shown as the means ± standard deviation (SD); ** p<0.01 vs. NC.

Journal: International Journal of Molecular Medicine

Article Title: RNAi-mediated downregulation of DNA binding protein A inhibits tumorigenesis in colorectal cancer

doi: 10.3892/ijmm.2016.2662

Figure Lengend Snippet: Apoptosis induction in SW620 cells transfected with short hairpin RNA (shRNA)-DNA binding protein A (dbpA)-Lv, shNC-dbpA-Lv, or empty vector. (A) Cell apoptosis was analyzed by flow cytometry. (B) Cell apoptosis in SW620 cells treated as in (A). Data are shown as the means ± standard deviation (SD); ** p<0.01 vs. NC.

Techniques: Transfection, shRNA, Binding Assay, Plasmid Preparation, Flow Cytometry, Standard Deviation

Effect of DNA binding protein A (dbpA) knockdown on tumorigenesis in nude mice. (A) Curve of tumor volume was assessed by caliper measurements. (B) Mass weight of tumor at the 35th day after inoculation. (C) Representative images of mice and tumors from each group. (D) dbpA expression was detected by western blot analysis from isolated tumors. GAPDH was used as an internal control. Data are shown as the means ± standard deviation (SD); * p<0.05, ** p<0.01 vs. NC.

Journal: International Journal of Molecular Medicine

Article Title: RNAi-mediated downregulation of DNA binding protein A inhibits tumorigenesis in colorectal cancer

doi: 10.3892/ijmm.2016.2662

Figure Lengend Snippet: Effect of DNA binding protein A (dbpA) knockdown on tumorigenesis in nude mice. (A) Curve of tumor volume was assessed by caliper measurements. (B) Mass weight of tumor at the 35th day after inoculation. (C) Representative images of mice and tumors from each group. (D) dbpA expression was detected by western blot analysis from isolated tumors. GAPDH was used as an internal control. Data are shown as the means ± standard deviation (SD); * p<0.05, ** p<0.01 vs. NC.

Techniques: Binding Assay, Knockdown, Expressing, Western Blot, Isolation, Control, Standard Deviation

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