human gene 1.0 st microarray platform Search Results


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Thermo Fisher microarray analysis
qPCR validation of LCA <t> microarray analysis </t> and changes in gene expression caused by treatment with control compound, anthraquinone-2-carboxylic acid
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Proteintech crabp ii rabbit polyclonal antibody
CRABP-II regulates cholesterol metabolic genes expression through cooperation with HuR. ( A ) Molecular and cellular function analysis by IPA software (Qiagen) based on gene expression microarray profiling. The altered lipid synthesis and accumulation functions upon CRABP-II knockout were listed. ( B ) Heat map of altered cholesterol metabolic genes. ( C, D, E ) Cholesterol metabolic genes expression assessed by Q-PCR. ( F ) Correlation between cholesterol metabolic genes and CRABP-II expression in human pancreatic cancer specimens by Pearson’s product-moment correlation coefficient analysis (PPMCC). Data shown here are combination of Pei Pancreas and Badea Pancrease datasets ( n = 75) from Oncomine. ( G ) Interaction between CRABP-II and HuR identified by co-immuprecipitation (co-IP). GR4000 cell lysis was incubated with anti-CRABP-II rabbit <t>polyclonal</t> antibody and the pull down proteins were separated and blotted with anti-HuR mouse monoclonal antibody. ( H ) Half-life of SREBP-1c mRNA assessed by actinomycin D treatment following with Q-PCR. ( I ) RNA-immunoprecipitation (RIP). The down pulled SREBP-1c mRNA from flagged-CRABP-II transfected CIIKO cells and empty vector transfected cells were assessed by Q-PCR. The actin mRNA was used as control. The experiment was repeated three times and the error bars present standard deviation (SD). **, p < 0.01
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Figure 2. Upregulation of <t>CXCL10</t> and MHC class II in human neutrophils in urine during BCG infusion therapy. (a,b) Comprehensive analysis of mRNA expression in urine-derived neutrophils compared to peripheral blood neutrophils. Blood and urine were collected from three patients after one week from the 6th BCG infusion. Comprehensive analysis of mRNA in neutrophils was performed using a DNA tip microarray. (a) Cluster analysis after adjustment and standardiza- tion. The mRNA expression in neutrophils obtained from urine samples (vertical axis) or periph- eral blood (horizontal axis) was analyzed. White lines indicate the thresholds for genes that are upregulated or downregulated > 2-fold between urine- and blood-derived neutrophils. A relatively higher expression in urine-derived neutrophils is indicated using arrows, including expression for CXCR3 ligands (CXCL9 and CXCL10) and MHC class II (HLA-DRB1, HLA-DPA1, and HLA-DQA1). (b) Volcano plot depicting the differentially expressed genes between peripheral blood-derived and urine-derived neutrophils after the 6th BCG infusion. The horizontal axis denotes the fold change in mRNA expression in neutrophils from the urine and blood, while the vertical axis represents the –log10 (p-value) for a t-test of differences in neutrophils from the blood and urine. These data represent the top 6000 genes of the –log10 (p-value). The gene expressions of CXCR3 ligands (CXCL9, CXCL10, and CXCL11) and MHC class II (HLA-DQA2, HLA-DPA1, and HLA-DQA1) were also detected as characteristic features of urine-derived neutrophils (arrows). (c,d) Representative data of intracellular- stained neutrophilic cells obtained via flow cytometric analysis. The CD33+CD15+ neutrophilic cells in the blood (c) or urine (d) samples were obtained from the same patient who was treated with 4th BCG infusions and are presented as CXCL10 MFI (upper panels) and HLA-DR MFI (lower panels). Gray-closed histograms indicate each background staining, and light blue line histograms denote the staining of CXCL10 or HLA-DR. (e–g) Comparison of intracellular expression of (e,f) CXCL10 and (g) HLA-DR in neutrophilic cells from the blood (open circle) and urine (closed circle) samples. These samples were collected after one week from the 2nd to the 6th BCG infusions (after each infusion). (e) ∆CXCL10 MFI was calculated as follows: ∆CXCL10 MFI = (MFI of PE-conjugated anti-CXCL10 mAb staining) −(MFI of PE-conjugated control IgG staining). (f) The neutrophilic cells
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Type I and II interferon genes have time-dependent IL-1B and IL-36 responses. (A) Interferon gamma receptor 1 ( IFNGR1 ). (B) Interferon gamma receptor 2 ( IFNGR2 ). (C) Interferon <t>alpha</t> and beta receptor subunit 2 ( IFNAR2 ). In panels (A–C) , average FPKM (±1 SE) is shown for each group, and asterisks denote significant differences relative to the control (CTL) treatment at the corresponding time point (paired two-sample t -test; n = 2 or 3 per treatment). (D) Genes with interferon response factor 1 (IRF1) binding sites (5 kb upstream region). The middle 50% of FC estimates is shown for genes with 2+ IRF1 binding sites compared with genes with fewer IRF1 sites (magenta font, horizontal axis: P < 0.05, Wilcoxon rank sum test). The IRF1 position weight matrix is shown (right) along with the IRF1 tetrameric structure (bottom right; NCBI structure database). (E) IFN-induced gene signature scores. IFN-induced genes were identified from microarray studies of IFN-treated keratinocytes (left margin), and the average FC for these genes was calculated in IL-1B/IL-36 experiments (bottom margin). Left margin labels indicate the cytokine concentration (in ml), treatment duration, and GEO series accession number. All cytokine experiments were replicated with at least two samples per treatment. (F) Top 30 IFN-g-induced genes (identified from GSE36287). (G) Top 35 INFa-induced genes (identified from GSE36287). (H) Self-organizing maps (SOMs). The SOM layout was determined only from IFN-g-induced genes (i.e., 2,500 genes most strongly induced by IFN-g, GSE36287). Colors reflect average FC estimates for IFN-g-induced genes assigned to each SOM region (columns 1 and 2 on left). The final column (yellow–blue) displays the mean FC difference for each cytokine with respect to each SOM region (8 h mean FC–24 h mean FC; log 2 scale).
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<t>HDAC1,</t> HDAC2, and HDAC3 were upregulated in breast cancer tissues and correlated with worse prognosis in breast cancer patients. ( a ) Representative immunohistochemical (IHC) staining photos of HDAC1, HDAC2, and HDAC3 in breast specimens. HDAC1, HDAC2, and HDAC3 levels were obviously elevated in the tumor tissues compared to the non‐neoplastic adjacent tissues of patients with invasive ductal carcinoma (IDC). Yellow boxes indicated mammary ducts. Scale bars, 100 μm. ( b ) Representative IHC photos of three different kinds of HDAC3 subcellular localization. Scale bars, 100 μm. ( c – f ) Overall survival (OS) curves of 139 IDC patients with different HDAC1 ( c ) ( ) HDAC1 Low ( ) HDAC1 High ( ) HDAC1 low‐censored ( ) HDAC1 high‐censored, HDAC2 ( d ) ( ) HDAC2 Low ( ) HDAC2 High ( ) HDAC2 low‐censored ( ) HDAC2 high‐censored, cytoplasmic HDAC3 ( e ) ( ) HDAC3 C‐low ( ) HDAC3 C‐high ( ) HDAC3 C‐low‐censored ( ) HDAC3 C‐high‐censored, and nuclear HDAC3 ( f ) levels ( ) HDAC3 N‐low ( ) HDAC3 N‐high ( ) HDAC3 N‐low‐censored ( ) HDAC3 N‐high‐censored. According to another set of criteria in which cases with either high nuclear or cytoplasmic expression were classified into the C‐high/N‐high group and other cases were classified into the Others group, the overall survival curve of the 139 IDC patients was reproduced as Figure 1g ( ) HDAC3 Others ( ) HDAC3 C‐high/N‐high ( ) HDAC3 Others‐censored ( ) HDAC3 C‐high/N‐high‐censored. P values of the Kaplan‐Meier plots in (c‐g) were calculated by log‐rank test in IBM SPSS Statistics 19 software. ( h – j ) Kaplan‐Meier survival curves with log‐rank analysis were used to assess the correlation between HDAC1 ( h ) ( ) HDAC1 Low (≤ 75th percentile) ( ) HDAC1 High (> 75th percentile), HDAC2 ( i ) ( ) HDAC2 Low (≤ 75th percentile) ( ) HDAC2 High (> 75th percentile), and HDAC3 ( j ) ( ) HDAC3 Low (≤ 80th percentile) ( ) HDAC3 High (> 80th percentile) expression and overall survival of 4903 breast cancer patients in the bc‐GenExMiner platform (website: http://bcgenex.centregauducheau.fr ; all DNA microarray data, node mixed, ER mixed; optimized split for HDAC1 and 2, an 80th percentile customized cutoff for HDAC3).
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OriGene tissuefocus ovarian cancer tissue microarray
<t>HDAC1,</t> HDAC2, and HDAC3 were upregulated in breast cancer tissues and correlated with worse prognosis in breast cancer patients. ( a ) Representative immunohistochemical (IHC) staining photos of HDAC1, HDAC2, and HDAC3 in breast specimens. HDAC1, HDAC2, and HDAC3 levels were obviously elevated in the tumor tissues compared to the non‐neoplastic adjacent tissues of patients with invasive ductal carcinoma (IDC). Yellow boxes indicated mammary ducts. Scale bars, 100 μm. ( b ) Representative IHC photos of three different kinds of HDAC3 subcellular localization. Scale bars, 100 μm. ( c – f ) Overall survival (OS) curves of 139 IDC patients with different HDAC1 ( c ) ( ) HDAC1 Low ( ) HDAC1 High ( ) HDAC1 low‐censored ( ) HDAC1 high‐censored, HDAC2 ( d ) ( ) HDAC2 Low ( ) HDAC2 High ( ) HDAC2 low‐censored ( ) HDAC2 high‐censored, cytoplasmic HDAC3 ( e ) ( ) HDAC3 C‐low ( ) HDAC3 C‐high ( ) HDAC3 C‐low‐censored ( ) HDAC3 C‐high‐censored, and nuclear HDAC3 ( f ) levels ( ) HDAC3 N‐low ( ) HDAC3 N‐high ( ) HDAC3 N‐low‐censored ( ) HDAC3 N‐high‐censored. According to another set of criteria in which cases with either high nuclear or cytoplasmic expression were classified into the C‐high/N‐high group and other cases were classified into the Others group, the overall survival curve of the 139 IDC patients was reproduced as Figure 1g ( ) HDAC3 Others ( ) HDAC3 C‐high/N‐high ( ) HDAC3 Others‐censored ( ) HDAC3 C‐high/N‐high‐censored. P values of the Kaplan‐Meier plots in (c‐g) were calculated by log‐rank test in IBM SPSS Statistics 19 software. ( h – j ) Kaplan‐Meier survival curves with log‐rank analysis were used to assess the correlation between HDAC1 ( h ) ( ) HDAC1 Low (≤ 75th percentile) ( ) HDAC1 High (> 75th percentile), HDAC2 ( i ) ( ) HDAC2 Low (≤ 75th percentile) ( ) HDAC2 High (> 75th percentile), and HDAC3 ( j ) ( ) HDAC3 Low (≤ 80th percentile) ( ) HDAC3 High (> 80th percentile) expression and overall survival of 4903 breast cancer patients in the bc‐GenExMiner platform (website: http://bcgenex.centregauducheau.fr ; all DNA microarray data, node mixed, ER mixed; optimized split for HDAC1 and 2, an 80th percentile customized cutoff for HDAC3).
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Thermo Fisher copy number variation mdh1b hs00985639 cn
<t>HDAC1,</t> HDAC2, and HDAC3 were upregulated in breast cancer tissues and correlated with worse prognosis in breast cancer patients. ( a ) Representative immunohistochemical (IHC) staining photos of HDAC1, HDAC2, and HDAC3 in breast specimens. HDAC1, HDAC2, and HDAC3 levels were obviously elevated in the tumor tissues compared to the non‐neoplastic adjacent tissues of patients with invasive ductal carcinoma (IDC). Yellow boxes indicated mammary ducts. Scale bars, 100 μm. ( b ) Representative IHC photos of three different kinds of HDAC3 subcellular localization. Scale bars, 100 μm. ( c – f ) Overall survival (OS) curves of 139 IDC patients with different HDAC1 ( c ) ( ) HDAC1 Low ( ) HDAC1 High ( ) HDAC1 low‐censored ( ) HDAC1 high‐censored, HDAC2 ( d ) ( ) HDAC2 Low ( ) HDAC2 High ( ) HDAC2 low‐censored ( ) HDAC2 high‐censored, cytoplasmic HDAC3 ( e ) ( ) HDAC3 C‐low ( ) HDAC3 C‐high ( ) HDAC3 C‐low‐censored ( ) HDAC3 C‐high‐censored, and nuclear HDAC3 ( f ) levels ( ) HDAC3 N‐low ( ) HDAC3 N‐high ( ) HDAC3 N‐low‐censored ( ) HDAC3 N‐high‐censored. According to another set of criteria in which cases with either high nuclear or cytoplasmic expression were classified into the C‐high/N‐high group and other cases were classified into the Others group, the overall survival curve of the 139 IDC patients was reproduced as Figure 1g ( ) HDAC3 Others ( ) HDAC3 C‐high/N‐high ( ) HDAC3 Others‐censored ( ) HDAC3 C‐high/N‐high‐censored. P values of the Kaplan‐Meier plots in (c‐g) were calculated by log‐rank test in IBM SPSS Statistics 19 software. ( h – j ) Kaplan‐Meier survival curves with log‐rank analysis were used to assess the correlation between HDAC1 ( h ) ( ) HDAC1 Low (≤ 75th percentile) ( ) HDAC1 High (> 75th percentile), HDAC2 ( i ) ( ) HDAC2 Low (≤ 75th percentile) ( ) HDAC2 High (> 75th percentile), and HDAC3 ( j ) ( ) HDAC3 Low (≤ 80th percentile) ( ) HDAC3 High (> 80th percentile) expression and overall survival of 4903 breast cancer patients in the bc‐GenExMiner platform (website: http://bcgenex.centregauducheau.fr ; all DNA microarray data, node mixed, ER mixed; optimized split for HDAC1 and 2, an 80th percentile customized cutoff for HDAC3).
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<t>HDAC1,</t> HDAC2, and HDAC3 were upregulated in breast cancer tissues and correlated with worse prognosis in breast cancer patients. ( a ) Representative immunohistochemical (IHC) staining photos of HDAC1, HDAC2, and HDAC3 in breast specimens. HDAC1, HDAC2, and HDAC3 levels were obviously elevated in the tumor tissues compared to the non‐neoplastic adjacent tissues of patients with invasive ductal carcinoma (IDC). Yellow boxes indicated mammary ducts. Scale bars, 100 μm. ( b ) Representative IHC photos of three different kinds of HDAC3 subcellular localization. Scale bars, 100 μm. ( c – f ) Overall survival (OS) curves of 139 IDC patients with different HDAC1 ( c ) ( ) HDAC1 Low ( ) HDAC1 High ( ) HDAC1 low‐censored ( ) HDAC1 high‐censored, HDAC2 ( d ) ( ) HDAC2 Low ( ) HDAC2 High ( ) HDAC2 low‐censored ( ) HDAC2 high‐censored, cytoplasmic HDAC3 ( e ) ( ) HDAC3 C‐low ( ) HDAC3 C‐high ( ) HDAC3 C‐low‐censored ( ) HDAC3 C‐high‐censored, and nuclear HDAC3 ( f ) levels ( ) HDAC3 N‐low ( ) HDAC3 N‐high ( ) HDAC3 N‐low‐censored ( ) HDAC3 N‐high‐censored. According to another set of criteria in which cases with either high nuclear or cytoplasmic expression were classified into the C‐high/N‐high group and other cases were classified into the Others group, the overall survival curve of the 139 IDC patients was reproduced as Figure 1g ( ) HDAC3 Others ( ) HDAC3 C‐high/N‐high ( ) HDAC3 Others‐censored ( ) HDAC3 C‐high/N‐high‐censored. P values of the Kaplan‐Meier plots in (c‐g) were calculated by log‐rank test in IBM SPSS Statistics 19 software. ( h – j ) Kaplan‐Meier survival curves with log‐rank analysis were used to assess the correlation between HDAC1 ( h ) ( ) HDAC1 Low (≤ 75th percentile) ( ) HDAC1 High (> 75th percentile), HDAC2 ( i ) ( ) HDAC2 Low (≤ 75th percentile) ( ) HDAC2 High (> 75th percentile), and HDAC3 ( j ) ( ) HDAC3 Low (≤ 80th percentile) ( ) HDAC3 High (> 80th percentile) expression and overall survival of 4903 breast cancer patients in the bc‐GenExMiner platform (website: http://bcgenex.centregauducheau.fr ; all DNA microarray data, node mixed, ER mixed; optimized split for HDAC1 and 2, an 80th percentile customized cutoff for HDAC3).
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Image Search Results


qPCR validation of LCA  microarray analysis  and changes in gene expression caused by treatment with control compound, anthraquinone-2-carboxylic acid

Journal: The Journal of Biological Chemistry

Article Title: Laccaic Acid A Is a Direct, DNA-competitive Inhibitor of DNA Methyltransferase 1 *

doi: 10.1074/jbc.M113.480517

Figure Lengend Snippet: qPCR validation of LCA microarray analysis and changes in gene expression caused by treatment with control compound, anthraquinone-2-carboxylic acid

Article Snippet: Microarray Analysis Total RNA was isolated from 2 × 10 5 cells and used for microarray analysis (University of Iowa DNA Core Facility) in hybridization to Human Gene ST1.0 Array GeneChips (Affymetrix).

Techniques: Biomarker Discovery, Microarray, Gene Expression, Control

CRABP-II regulates cholesterol metabolic genes expression through cooperation with HuR. ( A ) Molecular and cellular function analysis by IPA software (Qiagen) based on gene expression microarray profiling. The altered lipid synthesis and accumulation functions upon CRABP-II knockout were listed. ( B ) Heat map of altered cholesterol metabolic genes. ( C, D, E ) Cholesterol metabolic genes expression assessed by Q-PCR. ( F ) Correlation between cholesterol metabolic genes and CRABP-II expression in human pancreatic cancer specimens by Pearson’s product-moment correlation coefficient analysis (PPMCC). Data shown here are combination of Pei Pancreas and Badea Pancrease datasets ( n = 75) from Oncomine. ( G ) Interaction between CRABP-II and HuR identified by co-immuprecipitation (co-IP). GR4000 cell lysis was incubated with anti-CRABP-II rabbit polyclonal antibody and the pull down proteins were separated and blotted with anti-HuR mouse monoclonal antibody. ( H ) Half-life of SREBP-1c mRNA assessed by actinomycin D treatment following with Q-PCR. ( I ) RNA-immunoprecipitation (RIP). The down pulled SREBP-1c mRNA from flagged-CRABP-II transfected CIIKO cells and empty vector transfected cells were assessed by Q-PCR. The actin mRNA was used as control. The experiment was repeated three times and the error bars present standard deviation (SD). **, p < 0.01

Journal: Journal of Experimental & Clinical Cancer Research : CR

Article Title: Targeting CRABP-II overcomes pancreatic cancer drug resistance by reversing lipid raft cholesterol accumulation and AKT survival signaling

doi: 10.1186/s13046-022-02261-0

Figure Lengend Snippet: CRABP-II regulates cholesterol metabolic genes expression through cooperation with HuR. ( A ) Molecular and cellular function analysis by IPA software (Qiagen) based on gene expression microarray profiling. The altered lipid synthesis and accumulation functions upon CRABP-II knockout were listed. ( B ) Heat map of altered cholesterol metabolic genes. ( C, D, E ) Cholesterol metabolic genes expression assessed by Q-PCR. ( F ) Correlation between cholesterol metabolic genes and CRABP-II expression in human pancreatic cancer specimens by Pearson’s product-moment correlation coefficient analysis (PPMCC). Data shown here are combination of Pei Pancreas and Badea Pancrease datasets ( n = 75) from Oncomine. ( G ) Interaction between CRABP-II and HuR identified by co-immuprecipitation (co-IP). GR4000 cell lysis was incubated with anti-CRABP-II rabbit polyclonal antibody and the pull down proteins were separated and blotted with anti-HuR mouse monoclonal antibody. ( H ) Half-life of SREBP-1c mRNA assessed by actinomycin D treatment following with Q-PCR. ( I ) RNA-immunoprecipitation (RIP). The down pulled SREBP-1c mRNA from flagged-CRABP-II transfected CIIKO cells and empty vector transfected cells were assessed by Q-PCR. The actin mRNA was used as control. The experiment was repeated three times and the error bars present standard deviation (SD). **, p < 0.01

Article Snippet: Antibodies used in this study include: CRABP-II mouse mAbs (Millipore, MAB5488), CRABP-II rabbit polyclonal antibody (Proteintech, 10,225–1-AP), HuR (3A2, Santa Cruz, sc-5261), Flotilin-2 (Santa Cruz, sc-28320), GAPDH (Santa Cruz, sc-365062), and Actin (Santa Cruz, sc-1615), anti-Flag M2 mAb (Sigma, F9291), anti-Flag agarose beads (Clontech, #635,686), Ki67 (SP6, ThermoFisher, RM-9106-S0), ADRP (Novus, NB110-40,877), Caspas3 (Cell Signaling, #9662), PARP (Cell Signaling, #9542), AKT (Cell Signaling, #4691), mTOR (Cell Signaling, #2983), S6 (Cell Signaling, #2217), pAKT (S473, Cell Signaling, #9018), pmTOR (Cell Signaling, #5536), pS6 (Cell Signaling, #4858), and pGSK3β (Cell Signaling, #5558).

Techniques: Expressing, Cell Function Assay, Software, Gene Expression, Microarray, Knock-Out, Co-Immunoprecipitation Assay, Lysis, Incubation, RNA Immunoprecipitation, Transfection, Plasmid Preparation, Control, Standard Deviation

KEY RESOURCES TABLE

Journal: Cell reports

Article Title: Overlapping Activities of Two Neuronal Splicing Factors Switch the GABA Effect from Excitatory to Inhibitory by Regulating REST

doi: 10.1016/j.celrep.2019.03.072

Figure Lengend Snippet: KEY RESOURCES TABLE

Article Snippet: Mouse anti-calbindin D-28K monoclonal antibody (clone CB-955) , Acris Antibodies , Cat# AM08219SU-N; RRID: AB_1954252.

Techniques: Expressing, Plasmid Preparation, Recombinant, SYBR Green Assay, Reporter Assay, Isolation, Staining, Microarray, Clone Assay, Software

Figure 2. Upregulation of CXCL10 and MHC class II in human neutrophils in urine during BCG infusion therapy. (a,b) Comprehensive analysis of mRNA expression in urine-derived neutrophils compared to peripheral blood neutrophils. Blood and urine were collected from three patients after one week from the 6th BCG infusion. Comprehensive analysis of mRNA in neutrophils was performed using a DNA tip microarray. (a) Cluster analysis after adjustment and standardiza- tion. The mRNA expression in neutrophils obtained from urine samples (vertical axis) or periph- eral blood (horizontal axis) was analyzed. White lines indicate the thresholds for genes that are upregulated or downregulated > 2-fold between urine- and blood-derived neutrophils. A relatively higher expression in urine-derived neutrophils is indicated using arrows, including expression for CXCR3 ligands (CXCL9 and CXCL10) and MHC class II (HLA-DRB1, HLA-DPA1, and HLA-DQA1). (b) Volcano plot depicting the differentially expressed genes between peripheral blood-derived and urine-derived neutrophils after the 6th BCG infusion. The horizontal axis denotes the fold change in mRNA expression in neutrophils from the urine and blood, while the vertical axis represents the –log10 (p-value) for a t-test of differences in neutrophils from the blood and urine. These data represent the top 6000 genes of the –log10 (p-value). The gene expressions of CXCR3 ligands (CXCL9, CXCL10, and CXCL11) and MHC class II (HLA-DQA2, HLA-DPA1, and HLA-DQA1) were also detected as characteristic features of urine-derived neutrophils (arrows). (c,d) Representative data of intracellular- stained neutrophilic cells obtained via flow cytometric analysis. The CD33+CD15+ neutrophilic cells in the blood (c) or urine (d) samples were obtained from the same patient who was treated with 4th BCG infusions and are presented as CXCL10 MFI (upper panels) and HLA-DR MFI (lower panels). Gray-closed histograms indicate each background staining, and light blue line histograms denote the staining of CXCL10 or HLA-DR. (e–g) Comparison of intracellular expression of (e,f) CXCL10 and (g) HLA-DR in neutrophilic cells from the blood (open circle) and urine (closed circle) samples. These samples were collected after one week from the 2nd to the 6th BCG infusions (after each infusion). (e) ∆CXCL10 MFI was calculated as follows: ∆CXCL10 MFI = (MFI of PE-conjugated anti-CXCL10 mAb staining) −(MFI of PE-conjugated control IgG staining). (f) The neutrophilic cells

Journal: Biomedicines

Article Title: Intracellular Major Histocompatibility Complex Class II and C-X-C Motif Chemokine Ligand 10-Expressing Neutrophils Indicate the State of Anti-Tumor Activity Induced by Bacillus Calmette-Guérin .

doi: 10.3390/biomedicines11113062

Figure Lengend Snippet: Figure 2. Upregulation of CXCL10 and MHC class II in human neutrophils in urine during BCG infusion therapy. (a,b) Comprehensive analysis of mRNA expression in urine-derived neutrophils compared to peripheral blood neutrophils. Blood and urine were collected from three patients after one week from the 6th BCG infusion. Comprehensive analysis of mRNA in neutrophils was performed using a DNA tip microarray. (a) Cluster analysis after adjustment and standardiza- tion. The mRNA expression in neutrophils obtained from urine samples (vertical axis) or periph- eral blood (horizontal axis) was analyzed. White lines indicate the thresholds for genes that are upregulated or downregulated > 2-fold between urine- and blood-derived neutrophils. A relatively higher expression in urine-derived neutrophils is indicated using arrows, including expression for CXCR3 ligands (CXCL9 and CXCL10) and MHC class II (HLA-DRB1, HLA-DPA1, and HLA-DQA1). (b) Volcano plot depicting the differentially expressed genes between peripheral blood-derived and urine-derived neutrophils after the 6th BCG infusion. The horizontal axis denotes the fold change in mRNA expression in neutrophils from the urine and blood, while the vertical axis represents the –log10 (p-value) for a t-test of differences in neutrophils from the blood and urine. These data represent the top 6000 genes of the –log10 (p-value). The gene expressions of CXCR3 ligands (CXCL9, CXCL10, and CXCL11) and MHC class II (HLA-DQA2, HLA-DPA1, and HLA-DQA1) were also detected as characteristic features of urine-derived neutrophils (arrows). (c,d) Representative data of intracellular- stained neutrophilic cells obtained via flow cytometric analysis. The CD33+CD15+ neutrophilic cells in the blood (c) or urine (d) samples were obtained from the same patient who was treated with 4th BCG infusions and are presented as CXCL10 MFI (upper panels) and HLA-DR MFI (lower panels). Gray-closed histograms indicate each background staining, and light blue line histograms denote the staining of CXCL10 or HLA-DR. (e–g) Comparison of intracellular expression of (e,f) CXCL10 and (g) HLA-DR in neutrophilic cells from the blood (open circle) and urine (closed circle) samples. These samples were collected after one week from the 2nd to the 6th BCG infusions (after each infusion). (e) ∆CXCL10 MFI was calculated as follows: ∆CXCL10 MFI = (MFI of PE-conjugated anti-CXCL10 mAb staining) −(MFI of PE-conjugated control IgG staining). (f) The neutrophilic cells

Article Snippet: The antibodies used in this study were as follows: fluorescein isothiocyanate (FITC)anti-human CD14 mAb (MφP9), phycoerythrin (PE)-anti-human CD16 mAb (3G8), and allophycocyanin (APC)-anti-human human leukocyte antigen DR isotype (HLA-DR) mAb (G46-6) from BD Biosciences; FITC-anti-human CD15 mAb (HI98), APC- or FITC-antihuman CD16 mAb (3G8), brilliant violet 421-anti-human CD33 mAb (WM53), PE-antihuman CD163 mAb (GHI/61), PE-anti-human CD197 mAb (G043H7), PE-anti-human C-X-C motif chemokine ligand 10 (CXCL10) (J034D6), APC-anti-mouse I-A/I-E mAb (M5/114.15.2), FITC-anti-mouse CD45 mAb (30-F11), PerCP-Cy5.5-anti-mouse Ly6C mAb (HK1.4), brilliant violet 421-anti-mouse Ly6G mAb (1A8), brilliant violet 421-anti-mouse Gr-1 mAb (RB6-8C5), and PE-streptavidin from BioLegend; APC-anti latency-associated peptide-1 (LAP; the N-terminal region of transforming growth factor-β1 precursor) mAb (#27232) and biotin-anti-mouse CXCL10 goat Ab (#BAF466) from R&D systems (Minneapolis, MN, USA); and PE-anti-human GPI-80 mAb (3H9) from MBL (Nagoya, Japan).

Techniques: Expressing, Derivative Assay, Microarray, Staining, Comparison, Control

Figure 3. Effect of BCG on CXCL10 and MHC-II expression in human or mice neutrophilic cells in vitro. Human (a,d) or mouse (b,e) peripheral blood was diluted ten-fold in 10% FCS RPMI1640, or mouse bone marrow cells (4 × 106/mL; c,f) were incubated with or without 4 µg/mL of BCG for 20 h. Following incubation, the expression levels of CXCL10 (a–c) and MHC class II (d–f) in human (CD33+CD15+) or mouse neutrophils (CD45+Ly6G+) were analyzed, as described in Figure S2. Statistical significance was calculated with the paired t-test, * p < 0.05 (n = 3). Abbreviations: BCG, Bacillus Calmette–Guérin; CXCL10, chemokine (C-X-C motif) ligand 10; HLA-DR, human major histocompatibility complex class II cell surface receptor; MFI, mean fluorescence intensity; and I-A/I-E, mouse major histocompatibility complex class II cell surface receptor.

Journal: Biomedicines

Article Title: Intracellular Major Histocompatibility Complex Class II and C-X-C Motif Chemokine Ligand 10-Expressing Neutrophils Indicate the State of Anti-Tumor Activity Induced by Bacillus Calmette-Guérin .

doi: 10.3390/biomedicines11113062

Figure Lengend Snippet: Figure 3. Effect of BCG on CXCL10 and MHC-II expression in human or mice neutrophilic cells in vitro. Human (a,d) or mouse (b,e) peripheral blood was diluted ten-fold in 10% FCS RPMI1640, or mouse bone marrow cells (4 × 106/mL; c,f) were incubated with or without 4 µg/mL of BCG for 20 h. Following incubation, the expression levels of CXCL10 (a–c) and MHC class II (d–f) in human (CD33+CD15+) or mouse neutrophils (CD45+Ly6G+) were analyzed, as described in Figure S2. Statistical significance was calculated with the paired t-test, * p < 0.05 (n = 3). Abbreviations: BCG, Bacillus Calmette–Guérin; CXCL10, chemokine (C-X-C motif) ligand 10; HLA-DR, human major histocompatibility complex class II cell surface receptor; MFI, mean fluorescence intensity; and I-A/I-E, mouse major histocompatibility complex class II cell surface receptor.

Article Snippet: The antibodies used in this study were as follows: fluorescein isothiocyanate (FITC)anti-human CD14 mAb (MφP9), phycoerythrin (PE)-anti-human CD16 mAb (3G8), and allophycocyanin (APC)-anti-human human leukocyte antigen DR isotype (HLA-DR) mAb (G46-6) from BD Biosciences; FITC-anti-human CD15 mAb (HI98), APC- or FITC-antihuman CD16 mAb (3G8), brilliant violet 421-anti-human CD33 mAb (WM53), PE-antihuman CD163 mAb (GHI/61), PE-anti-human CD197 mAb (G043H7), PE-anti-human C-X-C motif chemokine ligand 10 (CXCL10) (J034D6), APC-anti-mouse I-A/I-E mAb (M5/114.15.2), FITC-anti-mouse CD45 mAb (30-F11), PerCP-Cy5.5-anti-mouse Ly6C mAb (HK1.4), brilliant violet 421-anti-mouse Ly6G mAb (1A8), brilliant violet 421-anti-mouse Gr-1 mAb (RB6-8C5), and PE-streptavidin from BioLegend; APC-anti latency-associated peptide-1 (LAP; the N-terminal region of transforming growth factor-β1 precursor) mAb (#27232) and biotin-anti-mouse CXCL10 goat Ab (#BAF466) from R&D systems (Minneapolis, MN, USA); and PE-anti-human GPI-80 mAb (3H9) from MBL (Nagoya, Japan).

Techniques: Expressing, In Vitro, Incubation, Immunopeptidomics, Cell Surface Receptor Assay

Figure 4. Upregulation of CXCL10 and MHC class II in monocytes and neutrophils in peritoneal effusion cells after BCG injections. Mice were injected with B16F10 cells (5 × 104 cells/100 µL/head), and the PECs were collected after two weeks. The PECs induced after one injection of BCG (40 µg/head) after 16 h and the PECs induced after five repeated injections of BCG (40 µg/head) after 16 h from the final injection are presented as “1-shot” and “5-shots”, respectively. These PECs were intracellularly stained with each antibody, and the relative expression (MFI) of CXCL10 and I-A/I-E was analyzed in CD45+Ly6C+ cells and CD45+Ly6G+ cells, respectively. (a–i) Representative flow cytometric analysis of mouse monocytes (Ly6C+ cells) and neutrophils (Ly6G+ cells) via flow cytometry. The (a–c) panels present flow cytometric analysis of the PECs induced 2 weeks after B16F10 cell injection (presented as “Tumor”). The (d–f) panels show representative flow cytometric analysis of the PECs induced 16 h after the administration of BCG (presented as “1-shot). The (g–i) panels indicate representative flow cytometric analyses of the PECs induced via five repeated BCG injections at one-week intervals. The PECs were collected 16 h after the final BCG admin- istration (presented as “5-shots”). The left panels (a,d,g) show CD45+ leukocytes presented with the gates of Ly6C+ cells (monocytic cells) and Ly6G+ cells (neutrophilic cells). (j–l) The number and proportion of myeloid cells (Ly6C+ and Ly6G+ cells) of the PECs. The peritoneal effusion cells obtained after injection of B16F10 cells are presented as “tumor” (open circles). The cells induced 16 h after a single administration of BCG are presented in the group “1-shot” (closed circles). The cells induced via five repeated injections of BCG are presented in the group “5-shots” (closed triangles). The (j) number of the cells in peritoneal fluid were counted using a hemocytometer, and the proportions of (k) Ly6C+ cells and (l) Ly6G+ cells in CD45+ leukocytes were analyzed via flow cytometry. (m–p) The intracellular expression levels of CXCL10 and MHC-II (I-A/I-E) in mouse monocytes (Ly6C+ cells) and neutrophils (Ly6G+ cells) after BCG injection. These PECs were intracellularly stained with each anti- body, and the relative expression (MFI) of (m,n) CXCL10 and (o,p) I-A/I-E was analyzed in (m,o) CD45+Ly6C+ cells and (n,p) CD45+Ly6G+ cells, respectively. Statistical analyses were per- formed using the Kruskal–Wallis test with the Dunn’s post-hoc test. Each bar is presented as the mean of data. * p < 0.05; ** p < 0.01; and ns, not significant. Abbreviations: PECs, peritoneal exudate cells; CXCL10, C-X-C motif chemokine ligand 10; BCG, Bacillus Calmette–Guérin; and MFI, mean fluorescence intensity.

Journal: Biomedicines

Article Title: Intracellular Major Histocompatibility Complex Class II and C-X-C Motif Chemokine Ligand 10-Expressing Neutrophils Indicate the State of Anti-Tumor Activity Induced by Bacillus Calmette-Guérin .

doi: 10.3390/biomedicines11113062

Figure Lengend Snippet: Figure 4. Upregulation of CXCL10 and MHC class II in monocytes and neutrophils in peritoneal effusion cells after BCG injections. Mice were injected with B16F10 cells (5 × 104 cells/100 µL/head), and the PECs were collected after two weeks. The PECs induced after one injection of BCG (40 µg/head) after 16 h and the PECs induced after five repeated injections of BCG (40 µg/head) after 16 h from the final injection are presented as “1-shot” and “5-shots”, respectively. These PECs were intracellularly stained with each antibody, and the relative expression (MFI) of CXCL10 and I-A/I-E was analyzed in CD45+Ly6C+ cells and CD45+Ly6G+ cells, respectively. (a–i) Representative flow cytometric analysis of mouse monocytes (Ly6C+ cells) and neutrophils (Ly6G+ cells) via flow cytometry. The (a–c) panels present flow cytometric analysis of the PECs induced 2 weeks after B16F10 cell injection (presented as “Tumor”). The (d–f) panels show representative flow cytometric analysis of the PECs induced 16 h after the administration of BCG (presented as “1-shot). The (g–i) panels indicate representative flow cytometric analyses of the PECs induced via five repeated BCG injections at one-week intervals. The PECs were collected 16 h after the final BCG admin- istration (presented as “5-shots”). The left panels (a,d,g) show CD45+ leukocytes presented with the gates of Ly6C+ cells (monocytic cells) and Ly6G+ cells (neutrophilic cells). (j–l) The number and proportion of myeloid cells (Ly6C+ and Ly6G+ cells) of the PECs. The peritoneal effusion cells obtained after injection of B16F10 cells are presented as “tumor” (open circles). The cells induced 16 h after a single administration of BCG are presented in the group “1-shot” (closed circles). The cells induced via five repeated injections of BCG are presented in the group “5-shots” (closed triangles). The (j) number of the cells in peritoneal fluid were counted using a hemocytometer, and the proportions of (k) Ly6C+ cells and (l) Ly6G+ cells in CD45+ leukocytes were analyzed via flow cytometry. (m–p) The intracellular expression levels of CXCL10 and MHC-II (I-A/I-E) in mouse monocytes (Ly6C+ cells) and neutrophils (Ly6G+ cells) after BCG injection. These PECs were intracellularly stained with each anti- body, and the relative expression (MFI) of (m,n) CXCL10 and (o,p) I-A/I-E was analyzed in (m,o) CD45+Ly6C+ cells and (n,p) CD45+Ly6G+ cells, respectively. Statistical analyses were per- formed using the Kruskal–Wallis test with the Dunn’s post-hoc test. Each bar is presented as the mean of data. * p < 0.05; ** p < 0.01; and ns, not significant. Abbreviations: PECs, peritoneal exudate cells; CXCL10, C-X-C motif chemokine ligand 10; BCG, Bacillus Calmette–Guérin; and MFI, mean fluorescence intensity.

Article Snippet: The antibodies used in this study were as follows: fluorescein isothiocyanate (FITC)anti-human CD14 mAb (MφP9), phycoerythrin (PE)-anti-human CD16 mAb (3G8), and allophycocyanin (APC)-anti-human human leukocyte antigen DR isotype (HLA-DR) mAb (G46-6) from BD Biosciences; FITC-anti-human CD15 mAb (HI98), APC- or FITC-antihuman CD16 mAb (3G8), brilliant violet 421-anti-human CD33 mAb (WM53), PE-antihuman CD163 mAb (GHI/61), PE-anti-human CD197 mAb (G043H7), PE-anti-human C-X-C motif chemokine ligand 10 (CXCL10) (J034D6), APC-anti-mouse I-A/I-E mAb (M5/114.15.2), FITC-anti-mouse CD45 mAb (30-F11), PerCP-Cy5.5-anti-mouse Ly6C mAb (HK1.4), brilliant violet 421-anti-mouse Ly6G mAb (1A8), brilliant violet 421-anti-mouse Gr-1 mAb (RB6-8C5), and PE-streptavidin from BioLegend; APC-anti latency-associated peptide-1 (LAP; the N-terminal region of transforming growth factor-β1 precursor) mAb (#27232) and biotin-anti-mouse CXCL10 goat Ab (#BAF466) from R&D systems (Minneapolis, MN, USA); and PE-anti-human GPI-80 mAb (3H9) from MBL (Nagoya, Japan).

Techniques: Injection, Staining, Expressing, Cytometry

Figure 7. CXCL10 and MHC class II expression in neutrophils induced via BCG was inhibited via partial neutrophil depletion using anti-Ly6G mAbs. BCG (40 µg/100 µL/head) was injected into the peritoneal cavity, following which the antibodies (100 µg/50 µL/head; control mAb, open circle; or anti-Ly6G mAb, closed circle) were injected into the

Journal: Biomedicines

Article Title: Intracellular Major Histocompatibility Complex Class II and C-X-C Motif Chemokine Ligand 10-Expressing Neutrophils Indicate the State of Anti-Tumor Activity Induced by Bacillus Calmette-Guérin .

doi: 10.3390/biomedicines11113062

Figure Lengend Snippet: Figure 7. CXCL10 and MHC class II expression in neutrophils induced via BCG was inhibited via partial neutrophil depletion using anti-Ly6G mAbs. BCG (40 µg/100 µL/head) was injected into the peritoneal cavity, following which the antibodies (100 µg/50 µL/head; control mAb, open circle; or anti-Ly6G mAb, closed circle) were injected into the

Article Snippet: The antibodies used in this study were as follows: fluorescein isothiocyanate (FITC)anti-human CD14 mAb (MφP9), phycoerythrin (PE)-anti-human CD16 mAb (3G8), and allophycocyanin (APC)-anti-human human leukocyte antigen DR isotype (HLA-DR) mAb (G46-6) from BD Biosciences; FITC-anti-human CD15 mAb (HI98), APC- or FITC-antihuman CD16 mAb (3G8), brilliant violet 421-anti-human CD33 mAb (WM53), PE-antihuman CD163 mAb (GHI/61), PE-anti-human CD197 mAb (G043H7), PE-anti-human C-X-C motif chemokine ligand 10 (CXCL10) (J034D6), APC-anti-mouse I-A/I-E mAb (M5/114.15.2), FITC-anti-mouse CD45 mAb (30-F11), PerCP-Cy5.5-anti-mouse Ly6C mAb (HK1.4), brilliant violet 421-anti-mouse Ly6G mAb (1A8), brilliant violet 421-anti-mouse Gr-1 mAb (RB6-8C5), and PE-streptavidin from BioLegend; APC-anti latency-associated peptide-1 (LAP; the N-terminal region of transforming growth factor-β1 precursor) mAb (#27232) and biotin-anti-mouse CXCL10 goat Ab (#BAF466) from R&D systems (Minneapolis, MN, USA); and PE-anti-human GPI-80 mAb (3H9) from MBL (Nagoya, Japan).

Techniques: Expressing, Injection, Control

Type I and II interferon genes have time-dependent IL-1B and IL-36 responses. (A) Interferon gamma receptor 1 ( IFNGR1 ). (B) Interferon gamma receptor 2 ( IFNGR2 ). (C) Interferon alpha and beta receptor subunit 2 ( IFNAR2 ). In panels (A–C) , average FPKM (±1 SE) is shown for each group, and asterisks denote significant differences relative to the control (CTL) treatment at the corresponding time point (paired two-sample t -test; n = 2 or 3 per treatment). (D) Genes with interferon response factor 1 (IRF1) binding sites (5 kb upstream region). The middle 50% of FC estimates is shown for genes with 2+ IRF1 binding sites compared with genes with fewer IRF1 sites (magenta font, horizontal axis: P < 0.05, Wilcoxon rank sum test). The IRF1 position weight matrix is shown (right) along with the IRF1 tetrameric structure (bottom right; NCBI structure database). (E) IFN-induced gene signature scores. IFN-induced genes were identified from microarray studies of IFN-treated keratinocytes (left margin), and the average FC for these genes was calculated in IL-1B/IL-36 experiments (bottom margin). Left margin labels indicate the cytokine concentration (in ml), treatment duration, and GEO series accession number. All cytokine experiments were replicated with at least two samples per treatment. (F) Top 30 IFN-g-induced genes (identified from GSE36287). (G) Top 35 INFa-induced genes (identified from GSE36287). (H) Self-organizing maps (SOMs). The SOM layout was determined only from IFN-g-induced genes (i.e., 2,500 genes most strongly induced by IFN-g, GSE36287). Colors reflect average FC estimates for IFN-g-induced genes assigned to each SOM region (columns 1 and 2 on left). The final column (yellow–blue) displays the mean FC difference for each cytokine with respect to each SOM region (8 h mean FC–24 h mean FC; log 2 scale).

Journal: Frontiers in Immunology

Article Title: RNA-Seq Analysis of IL-1B and IL-36 Responses in Epidermal Keratinocytes Identifies a Shared MyD88-Dependent Gene Signature

doi: 10.3389/fimmu.2018.00080

Figure Lengend Snippet: Type I and II interferon genes have time-dependent IL-1B and IL-36 responses. (A) Interferon gamma receptor 1 ( IFNGR1 ). (B) Interferon gamma receptor 2 ( IFNGR2 ). (C) Interferon alpha and beta receptor subunit 2 ( IFNAR2 ). In panels (A–C) , average FPKM (±1 SE) is shown for each group, and asterisks denote significant differences relative to the control (CTL) treatment at the corresponding time point (paired two-sample t -test; n = 2 or 3 per treatment). (D) Genes with interferon response factor 1 (IRF1) binding sites (5 kb upstream region). The middle 50% of FC estimates is shown for genes with 2+ IRF1 binding sites compared with genes with fewer IRF1 sites (magenta font, horizontal axis: P < 0.05, Wilcoxon rank sum test). The IRF1 position weight matrix is shown (right) along with the IRF1 tetrameric structure (bottom right; NCBI structure database). (E) IFN-induced gene signature scores. IFN-induced genes were identified from microarray studies of IFN-treated keratinocytes (left margin), and the average FC for these genes was calculated in IL-1B/IL-36 experiments (bottom margin). Left margin labels indicate the cytokine concentration (in ml), treatment duration, and GEO series accession number. All cytokine experiments were replicated with at least two samples per treatment. (F) Top 30 IFN-g-induced genes (identified from GSE36287). (G) Top 35 INFa-induced genes (identified from GSE36287). (H) Self-organizing maps (SOMs). The SOM layout was determined only from IFN-g-induced genes (i.e., 2,500 genes most strongly induced by IFN-g, GSE36287). Colors reflect average FC estimates for IFN-g-induced genes assigned to each SOM region (columns 1 and 2 on left). The final column (yellow–blue) displays the mean FC difference for each cytokine with respect to each SOM region (8 h mean FC–24 h mean FC; log 2 scale).

Article Snippet: MYD88-KO KCs including WT KCs were grown in 12-well plates, and cells were treated with recombinant IL-1 beta (10 μg/ml; R&D Systems # 201-LB-025), IL-36 gamma (10 μg/ml; R&D Systems # 6835-IL-010), IFN-gamma (50 μg/ml; R&D Systems # 285-IF-100), IL-17A (20 μg/ml; R&D Systems # 317-ILB-050), and/or TNF-alpha (10 μg/ml; R&D Systems # 210-TA-005) for 8 or 24 h. RNAs were isolated from cell cultures using Qiagen RNeasy plus kit (Cat # 74136).

Techniques: Control, Binding Assay, Microarray, Concentration Assay

HDAC1, HDAC2, and HDAC3 were upregulated in breast cancer tissues and correlated with worse prognosis in breast cancer patients. ( a ) Representative immunohistochemical (IHC) staining photos of HDAC1, HDAC2, and HDAC3 in breast specimens. HDAC1, HDAC2, and HDAC3 levels were obviously elevated in the tumor tissues compared to the non‐neoplastic adjacent tissues of patients with invasive ductal carcinoma (IDC). Yellow boxes indicated mammary ducts. Scale bars, 100 μm. ( b ) Representative IHC photos of three different kinds of HDAC3 subcellular localization. Scale bars, 100 μm. ( c – f ) Overall survival (OS) curves of 139 IDC patients with different HDAC1 ( c ) ( ) HDAC1 Low ( ) HDAC1 High ( ) HDAC1 low‐censored ( ) HDAC1 high‐censored, HDAC2 ( d ) ( ) HDAC2 Low ( ) HDAC2 High ( ) HDAC2 low‐censored ( ) HDAC2 high‐censored, cytoplasmic HDAC3 ( e ) ( ) HDAC3 C‐low ( ) HDAC3 C‐high ( ) HDAC3 C‐low‐censored ( ) HDAC3 C‐high‐censored, and nuclear HDAC3 ( f ) levels ( ) HDAC3 N‐low ( ) HDAC3 N‐high ( ) HDAC3 N‐low‐censored ( ) HDAC3 N‐high‐censored. According to another set of criteria in which cases with either high nuclear or cytoplasmic expression were classified into the C‐high/N‐high group and other cases were classified into the Others group, the overall survival curve of the 139 IDC patients was reproduced as Figure 1g ( ) HDAC3 Others ( ) HDAC3 C‐high/N‐high ( ) HDAC3 Others‐censored ( ) HDAC3 C‐high/N‐high‐censored. P values of the Kaplan‐Meier plots in (c‐g) were calculated by log‐rank test in IBM SPSS Statistics 19 software. ( h – j ) Kaplan‐Meier survival curves with log‐rank analysis were used to assess the correlation between HDAC1 ( h ) ( ) HDAC1 Low (≤ 75th percentile) ( ) HDAC1 High (> 75th percentile), HDAC2 ( i ) ( ) HDAC2 Low (≤ 75th percentile) ( ) HDAC2 High (> 75th percentile), and HDAC3 ( j ) ( ) HDAC3 Low (≤ 80th percentile) ( ) HDAC3 High (> 80th percentile) expression and overall survival of 4903 breast cancer patients in the bc‐GenExMiner platform (website: http://bcgenex.centregauducheau.fr ; all DNA microarray data, node mixed, ER mixed; optimized split for HDAC1 and 2, an 80th percentile customized cutoff for HDAC3).

Journal: Thoracic Cancer

Article Title: Aberrant HDAC3 expression correlates with brain metastasis in breast cancer patients

doi: 10.1111/1759-7714.13561

Figure Lengend Snippet: HDAC1, HDAC2, and HDAC3 were upregulated in breast cancer tissues and correlated with worse prognosis in breast cancer patients. ( a ) Representative immunohistochemical (IHC) staining photos of HDAC1, HDAC2, and HDAC3 in breast specimens. HDAC1, HDAC2, and HDAC3 levels were obviously elevated in the tumor tissues compared to the non‐neoplastic adjacent tissues of patients with invasive ductal carcinoma (IDC). Yellow boxes indicated mammary ducts. Scale bars, 100 μm. ( b ) Representative IHC photos of three different kinds of HDAC3 subcellular localization. Scale bars, 100 μm. ( c – f ) Overall survival (OS) curves of 139 IDC patients with different HDAC1 ( c ) ( ) HDAC1 Low ( ) HDAC1 High ( ) HDAC1 low‐censored ( ) HDAC1 high‐censored, HDAC2 ( d ) ( ) HDAC2 Low ( ) HDAC2 High ( ) HDAC2 low‐censored ( ) HDAC2 high‐censored, cytoplasmic HDAC3 ( e ) ( ) HDAC3 C‐low ( ) HDAC3 C‐high ( ) HDAC3 C‐low‐censored ( ) HDAC3 C‐high‐censored, and nuclear HDAC3 ( f ) levels ( ) HDAC3 N‐low ( ) HDAC3 N‐high ( ) HDAC3 N‐low‐censored ( ) HDAC3 N‐high‐censored. According to another set of criteria in which cases with either high nuclear or cytoplasmic expression were classified into the C‐high/N‐high group and other cases were classified into the Others group, the overall survival curve of the 139 IDC patients was reproduced as Figure 1g ( ) HDAC3 Others ( ) HDAC3 C‐high/N‐high ( ) HDAC3 Others‐censored ( ) HDAC3 C‐high/N‐high‐censored. P values of the Kaplan‐Meier plots in (c‐g) were calculated by log‐rank test in IBM SPSS Statistics 19 software. ( h – j ) Kaplan‐Meier survival curves with log‐rank analysis were used to assess the correlation between HDAC1 ( h ) ( ) HDAC1 Low (≤ 75th percentile) ( ) HDAC1 High (> 75th percentile), HDAC2 ( i ) ( ) HDAC2 Low (≤ 75th percentile) ( ) HDAC2 High (> 75th percentile), and HDAC3 ( j ) ( ) HDAC3 Low (≤ 80th percentile) ( ) HDAC3 High (> 80th percentile) expression and overall survival of 4903 breast cancer patients in the bc‐GenExMiner platform (website: http://bcgenex.centregauducheau.fr ; all DNA microarray data, node mixed, ER mixed; optimized split for HDAC1 and 2, an 80th percentile customized cutoff for HDAC3).

Article Snippet: After serial blocking with hydrogen peroxide and normal horse serum, the tissue chips and sections were incubated with primary monoclonal antibody against HDAC1 (cat. no. 10197‐1‐AP, Proteintech), HDAC2 (cat. no. 12922‐3‐AP, Proteintech) or HDAC3 (cat. no. 10255‐1‐AP, Proteintech) at 4°C overnight.

Techniques: Immunohistochemical staining, Immunohistochemistry, Expressing, Software, Microarray

HDACs expression exhibited different roles in overall survival of IDC patients ( n = 16l)

Journal: Thoracic Cancer

Article Title: Aberrant HDAC3 expression correlates with brain metastasis in breast cancer patients

doi: 10.1111/1759-7714.13561

Figure Lengend Snippet: HDACs expression exhibited different roles in overall survival of IDC patients ( n = 16l)

Article Snippet: After serial blocking with hydrogen peroxide and normal horse serum, the tissue chips and sections were incubated with primary monoclonal antibody against HDAC1 (cat. no. 10197‐1‐AP, Proteintech), HDAC2 (cat. no. 12922‐3‐AP, Proteintech) or HDAC3 (cat. no. 10255‐1‐AP, Proteintech) at 4°C overnight.

Techniques: Expressing

Relationship between clinicopathological characteristics and HDACs expression in IDC patients ( n = 139)

Journal: Thoracic Cancer

Article Title: Aberrant HDAC3 expression correlates with brain metastasis in breast cancer patients

doi: 10.1111/1759-7714.13561

Figure Lengend Snippet: Relationship between clinicopathological characteristics and HDACs expression in IDC patients ( n = 139)

Article Snippet: After serial blocking with hydrogen peroxide and normal horse serum, the tissue chips and sections were incubated with primary monoclonal antibody against HDAC1 (cat. no. 10197‐1‐AP, Proteintech), HDAC2 (cat. no. 12922‐3‐AP, Proteintech) or HDAC3 (cat. no. 10255‐1‐AP, Proteintech) at 4°C overnight.

Techniques: Expressing, Over Expression

HDACs expression exhibited different roles in the onset of brain metastasis of IDC patients ( n = 161)

Journal: Thoracic Cancer

Article Title: Aberrant HDAC3 expression correlates with brain metastasis in breast cancer patients

doi: 10.1111/1759-7714.13561

Figure Lengend Snippet: HDACs expression exhibited different roles in the onset of brain metastasis of IDC patients ( n = 161)

Article Snippet: After serial blocking with hydrogen peroxide and normal horse serum, the tissue chips and sections were incubated with primary monoclonal antibody against HDAC1 (cat. no. 10197‐1‐AP, Proteintech), HDAC2 (cat. no. 12922‐3‐AP, Proteintech) or HDAC3 (cat. no. 10255‐1‐AP, Proteintech) at 4°C overnight.

Techniques: Expressing

The roles of HDACs expression and other clinicopathological characteristics played in the prognosis of breast cancer patients after brain metastasis ( n = 63)

Journal: Thoracic Cancer

Article Title: Aberrant HDAC3 expression correlates with brain metastasis in breast cancer patients

doi: 10.1111/1759-7714.13561

Figure Lengend Snippet: The roles of HDACs expression and other clinicopathological characteristics played in the prognosis of breast cancer patients after brain metastasis ( n = 63)

Article Snippet: After serial blocking with hydrogen peroxide and normal horse serum, the tissue chips and sections were incubated with primary monoclonal antibody against HDAC1 (cat. no. 10197‐1‐AP, Proteintech), HDAC2 (cat. no. 12922‐3‐AP, Proteintech) or HDAC3 (cat. no. 10255‐1‐AP, Proteintech) at 4°C overnight.

Techniques: Expressing

Primers used.

Journal: Innate Immunity

Article Title: Comprehensive analysis of neuronal guidance cue expression regulation during monocyte-to-macrophage differentiation reveals post-transcriptional regulation of semaphorin7A by the RNA-binding protein quaking

doi: 10.1177/1753425920966645

Figure Lengend Snippet: Primers used.

Article Snippet: Membranes were incubated with human SEMA7A Ab (1:10,000, AF 2068; R&D systems) or GAPDH Ab (1:1000, 5174; Cell Signaling Technology) in blocking buffer overnight at 4°C.

Techniques:

Overview of regulated genes and their known relevant function.

Journal: Innate Immunity

Article Title: Comprehensive analysis of neuronal guidance cue expression regulation during monocyte-to-macrophage differentiation reveals post-transcriptional regulation of semaphorin7A by the RNA-binding protein quaking

doi: 10.1177/1753425920966645

Figure Lengend Snippet: Overview of regulated genes and their known relevant function.

Article Snippet: Membranes were incubated with human SEMA7A Ab (1:10,000, AF 2068; R&D systems) or GAPDH Ab (1:1000, 5174; Cell Signaling Technology) in blocking buffer overnight at 4°C.

Techniques: Microarray, Expressing, Migration

Regulation of NGC expression by QKI. (a) Heat map of expression of NGCs in monocytes and macrophages determined by RNA-seq from QKI patient and sibling in log2 scale (Lighter blue indicates higher expression; n = 1). (b) Fold change of NGC expression comparing QKI patient’s monocyte and macrophage to her sibling’s. (c) In macrophages treated with GapmeR antisense oligonucleotides, there is a significant positive correlation between QKI and SEMA7A expression measured by quantitative PCR analysis. Gene expression is expressed as copies per GAPDH. QKI: quaking.

Journal: Innate Immunity

Article Title: Comprehensive analysis of neuronal guidance cue expression regulation during monocyte-to-macrophage differentiation reveals post-transcriptional regulation of semaphorin7A by the RNA-binding protein quaking

doi: 10.1177/1753425920966645

Figure Lengend Snippet: Regulation of NGC expression by QKI. (a) Heat map of expression of NGCs in monocytes and macrophages determined by RNA-seq from QKI patient and sibling in log2 scale (Lighter blue indicates higher expression; n = 1). (b) Fold change of NGC expression comparing QKI patient’s monocyte and macrophage to her sibling’s. (c) In macrophages treated with GapmeR antisense oligonucleotides, there is a significant positive correlation between QKI and SEMA7A expression measured by quantitative PCR analysis. Gene expression is expressed as copies per GAPDH. QKI: quaking.

Article Snippet: Membranes were incubated with human SEMA7A Ab (1:10,000, AF 2068; R&D systems) or GAPDH Ab (1:1000, 5174; Cell Signaling Technology) in blocking buffer overnight at 4°C.

Techniques: Expressing, RNA Sequencing, Real-time Polymerase Chain Reaction, Gene Expression

Visualisation of genomic annotations in 3′UTR region of SEMA7A gene. The region in 3′UTR of SEMA7A in the human genome (hg19 Chromosome 15 q24.1, bp 74,701,500–74,703,000) is annotated with aspects of miRNA binding sites, QKI targeting sites (experimental evidence based), QRE ( in silico alignment of ‘ACUAA motif’) and SEMA7A exon. The microRNA binding information was extracted from ‘miRbase’ and was filtered by expression in monocytes/macrophages and miRNA interaction score. Interactions between RNA binding proteins (RBPs) to genomic DNA were obtained from technique duplicates of eCLIP-seq in the myelogenous K562 cells.

Journal: Innate Immunity

Article Title: Comprehensive analysis of neuronal guidance cue expression regulation during monocyte-to-macrophage differentiation reveals post-transcriptional regulation of semaphorin7A by the RNA-binding protein quaking

doi: 10.1177/1753425920966645

Figure Lengend Snippet: Visualisation of genomic annotations in 3′UTR region of SEMA7A gene. The region in 3′UTR of SEMA7A in the human genome (hg19 Chromosome 15 q24.1, bp 74,701,500–74,703,000) is annotated with aspects of miRNA binding sites, QKI targeting sites (experimental evidence based), QRE ( in silico alignment of ‘ACUAA motif’) and SEMA7A exon. The microRNA binding information was extracted from ‘miRbase’ and was filtered by expression in monocytes/macrophages and miRNA interaction score. Interactions between RNA binding proteins (RBPs) to genomic DNA were obtained from technique duplicates of eCLIP-seq in the myelogenous K562 cells.

Article Snippet: Membranes were incubated with human SEMA7A Ab (1:10,000, AF 2068; R&D systems) or GAPDH Ab (1:1000, 5174; Cell Signaling Technology) in blocking buffer overnight at 4°C.

Techniques: Binding Assay, In Silico, Expressing, RNA Binding Assay

RNA-immunoprecipitation showing quaking protein binding to the 3′UTR of SEMA7A. (a) RNA-immunoprecipitation in Hek293T cells overexpression QKI5 using an IgG control or QKI5 Ab. QKI5 and GAPDH mRNA abundance in immune-precipitated fraction was determined by qPCR. Results are presented relative to IgG immunoprecipitation. Data are the mean ± SEM; n = 5; * P < 0.05. (b) RNA-immunoprecipitation in Hek293T cells overexpression QKI5 and 3′UTR of SEMA7A using an IgG control or QKI5 Ab. SEMA7A 3’UTR and GAPDH mRNA abundance in immune-precipitated fraction was determined by qPCR. Results are presented relative to IgG immunoprecipitation. Data are the mean ± SEM; n = 3; * P < 0.05.

Journal: Innate Immunity

Article Title: Comprehensive analysis of neuronal guidance cue expression regulation during monocyte-to-macrophage differentiation reveals post-transcriptional regulation of semaphorin7A by the RNA-binding protein quaking

doi: 10.1177/1753425920966645

Figure Lengend Snippet: RNA-immunoprecipitation showing quaking protein binding to the 3′UTR of SEMA7A. (a) RNA-immunoprecipitation in Hek293T cells overexpression QKI5 using an IgG control or QKI5 Ab. QKI5 and GAPDH mRNA abundance in immune-precipitated fraction was determined by qPCR. Results are presented relative to IgG immunoprecipitation. Data are the mean ± SEM; n = 5; * P < 0.05. (b) RNA-immunoprecipitation in Hek293T cells overexpression QKI5 and 3′UTR of SEMA7A using an IgG control or QKI5 Ab. SEMA7A 3’UTR and GAPDH mRNA abundance in immune-precipitated fraction was determined by qPCR. Results are presented relative to IgG immunoprecipitation. Data are the mean ± SEM; n = 3; * P < 0.05.

Article Snippet: Membranes were incubated with human SEMA7A Ab (1:10,000, AF 2068; R&D systems) or GAPDH Ab (1:1000, 5174; Cell Signaling Technology) in blocking buffer overnight at 4°C.

Techniques: RNA Immunoprecipitation, Protein Binding, Over Expression, Control, Immunoprecipitation

Role for SEMA7A in monocyte differentiation into pro-inflammatory macrophages. (a) Bright field microscope images from THP-I monocytes and macrophages. (b) Representative immunoblot analysis of SEMA7A or ACTB (loading control) in protein lysates of THP-I monocytes and macrophages. (c) Bright field microscope images from THP-I macrophages transduced with anti-SEMA7A shRNA (sh-SEMA7A) or scrambled shRNA (sh-Ctrl). Elongated phenotype indicated by #. (d) Ratio of TNF-α and IL-10 mRNA expression of sh-SEMA7A or sh-Ctrl THP-I macrophages. Data are the mean ± SEM; n = 4; * P < 0.05.

Journal: Innate Immunity

Article Title: Comprehensive analysis of neuronal guidance cue expression regulation during monocyte-to-macrophage differentiation reveals post-transcriptional regulation of semaphorin7A by the RNA-binding protein quaking

doi: 10.1177/1753425920966645

Figure Lengend Snippet: Role for SEMA7A in monocyte differentiation into pro-inflammatory macrophages. (a) Bright field microscope images from THP-I monocytes and macrophages. (b) Representative immunoblot analysis of SEMA7A or ACTB (loading control) in protein lysates of THP-I monocytes and macrophages. (c) Bright field microscope images from THP-I macrophages transduced with anti-SEMA7A shRNA (sh-SEMA7A) or scrambled shRNA (sh-Ctrl). Elongated phenotype indicated by #. (d) Ratio of TNF-α and IL-10 mRNA expression of sh-SEMA7A or sh-Ctrl THP-I macrophages. Data are the mean ± SEM; n = 4; * P < 0.05.

Article Snippet: Membranes were incubated with human SEMA7A Ab (1:10,000, AF 2068; R&D systems) or GAPDH Ab (1:1000, 5174; Cell Signaling Technology) in blocking buffer overnight at 4°C.

Techniques: Microscopy, Western Blot, Control, Transduction, shRNA, Expressing