Journal: BMC Biology

Article Title: N6-methyladenosine regulates metabolic remodeling in kidney aging through transcriptional regulator GLIS1

doi: 10.1186/s12915-024-02100-y

Figure Lengend Snippet: The abnormal m6A modification and protein levels of GLIS1 in human aged kidney tissues. A Total m6A RNA levels in the H/aged ( n = 10) and H/control group ( n = 10) detected by m6A methylation quantification kit; B differential methylated mRNA expressions between H/aged (A) and H/control (Y) group by using m6A-mRNA epitranscriptomic microarray analysis ( n = 3); C analysis of significant changes in methylated mRNA expression levels between the H/aged and H/control group; D the Gene Ontology (GO) biological process enrichment analysis pathways of predicted mRNA targets; E enriched m6A modification of GLIS1 in the H/aged and H/control group by MeRIP assay ( n = 4); F , G protein level of GLIS1 in the H/aged and H/control group by western blot, and its semi-quantitative analyses ( n = 6). The data are expressed as the mean ± SD of three independent experiments. *** P < .001 indicates a significant difference versus the H/control group by Student’s t -test

Article Snippet: Human m6A epitranscriptomic microarray and mRNA microarray analyses were performed based on Arraystar’s standard protocols.

Techniques: Modification, Control, Methylation, Microarray, Expressing, Western Blot

Journal: BMC Biology

Article Title: N6-methyladenosine regulates metabolic remodeling in kidney aging through transcriptional regulator GLIS1

doi: 10.1186/s12915-024-02100-y

Figure Lengend Snippet: METTL3 directly interacted with GLIS1 in kidney aging. A The mRNA level of METTL3 in the vector and siMETTL3 group in HK-2 cells by RT-qPCR ( n = 3); B , C protein level of GLIS1 by western blot in the vector and siMETTL3 group in HK-2 cells, and its semi-quantitative analysis ( n = 3); D protein levels of METTL3, METTL14, and WTAP by western blot in the 24-month-old and 6-month-old group ( n = 6); E , F the expression of METTL3 in the 24-month-old and 6-month-old group by IHC assay, and its semi-quantitative analysis ( n = 6), scale bar = 50 μm; G immunostaining for METTL3 (green), with DAPI (blue) counterstaining by IF staining in the 24-month-old and 6-month-old group ( n = 6), scale bar = 50 μm; H immunostaining for METTL3 (green), GLIS1 (red), with DAPI (blue) counterstaining by IF staining in HK-2 cells ( n = 3), scale bar = 50 μm; I , J METTL3 RIP and RT-PCR confirmed the interaction between METTL3 and GLIS1 mRNA, and its semi-quantitative analysis ( n = 3); K the lower m6A level of GLIS1 in siMETTL3 group compared with the vector group in HK-2 cells by using MeRIP-qPCR ( n = 3); L the mRNA level of GLIS1 in the vector and siMETTL3 group in HK-2 cells by RT-qPCR ( n = 3); M mutations at the two putative m6A sites in GLIS1 (A to G); N m6A level of GLIS1 in HK-2 cells with co-expression of siMETTL3 and GLIS1-WT/Muts by MeRIP-qPCR ( n = 3); O the mRNA level of GLIS1 in the vector and GLIS1-Mut3 group by RT-qPCR ( n = 3). The data are expressed as the mean ± SD of three independent experiments. ** P < .01 or *** P < .001 versus the vector group ( A , C , K ) or 6-month-old group ( E ) or IgG group ( J ) by Student’s t -test; ## P < .01, ### P < .001 versus the vector-WT group, ++ P < .01, +++ P < .001 versus the siMETTL3-WT group, ** P < .01 versus vector group by two way-ANOVA ( N )

Article Snippet: Human m6A epitranscriptomic microarray and mRNA microarray analyses were performed based on Arraystar’s standard protocols.

Techniques: Plasmid Preparation, Quantitative RT-PCR, Western Blot, Expressing, Immunostaining, Staining, Reverse Transcription Polymerase Chain Reaction

Journal: BMC Biology

Article Title: N6-methyladenosine regulates metabolic remodeling in kidney aging through transcriptional regulator GLIS1

doi: 10.1186/s12915-024-02100-y

Figure Lengend Snippet: METTL3 ameliorated age-related renal fibrosis in accelerated aging mouse model. A , B Downregulated protein levels of METTL3, METTL14, and GLIS1 in an accelerated aging mouse model were reversed in the presence of AAV-METTL3, and the upregulated protein levels of P16 INK4A and FN by western blot in the accelerated aging mouse model were reduced by introducing AAV-METTL3 ( n = 6); C the enriched m6A modification of GLIS1 in the control, AAV-Vector and AAV-METTL3 group by MeRIP-qPCR assay ( n = 6); D GLIS1 mRNA levels in the control, AAV-Vector, and AAV-METTL3 group detected by RT-qPCR ( n = 5); E protein levels of GLIS1, P16 INK4A , and FN in the control, AAV-Vector and AAV-METTL3 group by Masson staining and IHC assay and their semi-quantitative analyses ( n = 6), scale bar = 50 μm; F immunostaining for PPARα (red) and CPT1A (green), HK2 (pink), and PDK1 (yellow), with DAPI (blue) counterstaining by IF staining in the control, AAV-Vector, and AAV-METTL3 group ( n = 6), scale bar = 50 μm. The data are expressed as the mean ± SD of three independent experiments. ** P < .01 or *** P < .001 versus the AAV-vector group by one-way ANOVA

Article Snippet: Human m6A epitranscriptomic microarray and mRNA microarray analyses were performed based on Arraystar’s standard protocols.

Techniques: Western Blot, Modification, Control, Plasmid Preparation, Quantitative RT-PCR, Staining, Immunostaining

Journal: BMC Biology

Article Title: N6-methyladenosine regulates metabolic remodeling in kidney aging through transcriptional regulator GLIS1

doi: 10.1186/s12915-024-02100-y

Figure Lengend Snippet: YTHDF1 identified with m6A-meditated GLIS1 mRNA and participated the translation process of GLIS1 protein. A The expression of YTHDF1 in the 24-month-old and 6-month-old group by IHC assay, and its semi-quantitative analysis ( n = 6), scale bar = 50 μm; B immunostaining for YTHDF1 (green), with DAPI (blue) counterstaining by IF staining in the 24-month-old and 6-month-old group ( n = 6), scale bar = 50 μm; C , D protein level of YTHDF1 in the 24-month-old and 6-month-old group by western blot, and its semi-quantitative analysis ( n = 6); E mRNA level of YTHDF1 by RT-qPCR in HK-2 cells within vector or siYTHDF1 ( n = 3); F protein level of GLIS1 in HK-2 cells within vector or siYTHDF1, and its semi-quantitative analysis ( n = 3); G double immunostaining for GLIS1 (red) and YTHDF1 (green) by IF staining in HK-2 cells ( n = 3), scale bar = 50 μm; H , I RIP and RT-PCR assays confirmed the interaction between YTHDF1 and GLIS1 mRNA, and its semi-quantitative analysis ( n = 3); J the expression of GLIS1 with RPL22-FLAG label by ribosomal immunoprecipitation in HK-2 cells ( n = 3); K the mRNA level of GLIS1 by RT-qPCR in HK-2 cells within vector or siYTHDF1 ( n = 3); L , M relative luciferase activity of the GLIS1-WT or GLIS1-Mut 3′UTR luciferase reporter in the vector and siMETTL3 group, n = 3. The data are expressed as the mean ± SD of three independent experiments. ** P < .01 or *** P < .001 versus the 6-month-old group, or vector group, or IgG group by Student’s t -test

Article Snippet: Human m6A epitranscriptomic microarray and mRNA microarray analyses were performed based on Arraystar’s standard protocols.

Techniques: Expressing, Immunostaining, Staining, Western Blot, Quantitative RT-PCR, Plasmid Preparation, Double Immunostaining, Reverse Transcription Polymerase Chain Reaction, Immunoprecipitation, Luciferase, Activity Assay

Journal: BioMed Research International

Article Title: Combined Analysis of the Aberrant Epigenetic Alteration of Pancreatic Ductal Adenocarcinoma

doi: 10.1155/2019/9379864

Figure Lengend Snippet: Literature search of key hypermethylation genes screened by MethylMix criteria.

Article Snippet: The 4 adjacent nontumor pancreatic tissues and 187 PDAC samples were included in the gene expression profiles, where the mRNA microarray employed IlluminaHiSeq RNA-Seq array, while 10 adjacent nontumor control tissues and 178 PDAC tissues were included in the gene methylation dataset, where the methylation microarray used Illumina HumanMethylation 450 BeadChip.

Techniques: Binding Assay, Protein-Protein interactions

Journal: Molecular Oncology

Article Title: S100A10, a novel biomarker in pancreatic ductal adenocarcinoma

doi: 10.1002/1878-0261.12356

Figure Lengend Snippet: S100A10 protein overexpressed in PDAC compared to PanIN lesions, nonductal stroma, and normal tissue. (A) imagej IHC profiler plugin was used to quantify S100A10 protein expression (see in methods). Briefly, images were color deconvoluted to isolate the brown DAB stain from non‐DAB image. An area of interest (PDAC shown) was manually highlighted and quantified based on pixel intensity and the percentage contribution of each pixel subcategory (0–60, 61–120, 121–180, 181–255; see H ‐scoring in methods). (B) The graph shows the H ‐score the S100A10 protein expression quantified by imagej in six different regions: PanINs stroma, PDAC stroma, normal adjacent to PanINs, normal adjacent to PDAC, PanINs, and PDAC lesions. Each H ‐score was divided by the mean H ‐score of all measurements to yield a mean‐normalized H ‐score ± SEM. Significance was determined using one‐way ANOVA of unmatched samples (nonpaired). Scale bars, 100 μm.

Article Snippet: We also examined S100A10 mRNA levels (microarray z ‐scores) across all 930 human cancer cell lines listed in the CCLE from the Broad Institute ( http://www.ncbi.nlm.nih.gov/protein/GSE36133 ) (Barretina et al ., ).

Techniques: Expressing, Staining

Journal: Molecular Oncology

Article Title: S100A10, a novel biomarker in pancreatic ductal adenocarcinoma

doi: 10.1002/1878-0261.12356

Figure Lengend Snippet: S100A10 mRNA expression is predictive of overall and RFS in four PDAC patient cohorts. Kaplan–Meier (KM) plots of OS (A,C–E) and RFS ( n = 139; B) of PDAC patients based on their S100A10 mRNA expression. Patients in (A,B) are from the TCGA provisional cohort. Patients in (C,D,E) are derived from Chen et al . ( , http://www.ncbi.nlm.nih.gov/protein/GSE57495 ), Moffitt et al . ( , http://www.ncbi.nlm.nih.gov/protein/GSE71729 ), and ICGC. The ternary cutoff was applied to classify the high‐positive, low‐positive, and weak/negative subgroups. P ‐values were adjusted to the Bonferroni‐corrected threshold. Adjusted P ‐value is P ‐value/ K = 0.017 where K = 3 and represents the number of comparisons made (Table ).

Article Snippet: We also examined S100A10 mRNA levels (microarray z ‐scores) across all 930 human cancer cell lines listed in the CCLE from the Broad Institute ( http://www.ncbi.nlm.nih.gov/protein/GSE36133 ) (Barretina et al ., ).

Techniques: Expressing, Derivative Assay

Journal: Molecular Oncology

Article Title: S100A10, a novel biomarker in pancreatic ductal adenocarcinoma

doi: 10.1002/1878-0261.12356

Figure Lengend Snippet: Differentially methylated CpG sites negatively correlate with S100A10 mRNA expression and serve as predictors of survival. (A) Schematic illustration of the human S100A10 gene based on UCSC Ref‐Seq. The genomic distance is approximate but is not drawn to scale. T c SS, transcription start site; T L SS, translation start site; TSS1500, region between 200 bp and 1500 bp upstream of T c SS; TSS200, region 200 bp upstream of T c SS; 5′UTR, 5′ untranslated region. The S100A10 gene is encoded on the negative strand (−), four probes mapped to the opposite positive (+) strand. Five probes were mapped to TSS1500, three to TSS200, and seven probes to the 5′UTR. (B) For normal vs. tumor comparisons, the raw data were extracted from MethHC ( http://methhc.mbc.nctu.edu.tw/php/index.php ), described by Huang et al . . The β‐values of each probe were assessed in 85 PDAC tumors and nine normal tissues (first and third columns). For mRNA vs. methylation correlations, raw β‐values of individual probes were extracted from Maplab Wanderer ( http://maplab.imppc.org/wanderer/ ) (Díez‐Villanueva et al ., ) and plotted against RNA seq V2 (RSEM) expression values of S100A10 in matched patients. Pearson's correlation was used to generate correlation graphs of β‐values and S100A10 mRNA expression (second and fourth columns). β‐Values for the probe cg06786599 were absent for normal samples, and no significant correlation ( P ‐value = 0.1023) between S100A10 tumor mRNA and cg06786599 β‐values was found. Cg06786599 was then excluded from further analysis. Significance was determined using unpaired Tukey test. Data are represented as mean ± SD. Kaplan–Meier (KM) plots of OS ( n = 178; C,F) and RFS ( n = 139; D,G) based on β‐values of the cg13249591 and cg13445177 probes. Overall survival was also assessed in the ICGC cohort was assessed based on the β‐values of both probes (E,H). P ‐values were adjusted to the Bonferroni‐corrected threshold. Adjusted P ‐value is P ‐value/ K = 0.017 where K = 3 and represents the number of comparisons made (Table ).

Article Snippet: We also examined S100A10 mRNA levels (microarray z ‐scores) across all 930 human cancer cell lines listed in the CCLE from the Broad Institute ( http://www.ncbi.nlm.nih.gov/protein/GSE36133 ) (Barretina et al ., ).

Techniques: Methylation, Expressing, RNA Sequencing

Journal: Molecular Oncology

Article Title: S100A10, a novel biomarker in pancreatic ductal adenocarcinoma

doi: 10.1002/1878-0261.12356

Figure Lengend Snippet: S100A10 mRNA and protein expression negatively correlated with promoter methylation in PDAC cell lines. (A) The relationship between S100A10 methylation and mRNA expression in 831 CCLE cell lines. mRNA expression (RNA seq V2 RSEM) and methylation (RRBS β‐values) were extracted from the broad institute CCLE portal ( https://portals.broadinstitute.org/ccle ). S100A10 mRNA (RT‐qPCR; B) and protein expression (C) in three PDAC representative cell lines: Panc 10.05, Panc‐1, and AsPC‐1. (D) S100A10 promoter construct for bisulfite and pyrosequencing covering 24 CpG dinucleotides. (E) Global methylation of the 24 CpGs in the S100A10 promoter. The graph represents the averages of percentages of all 24 sites in each cell line. Significance was determined using one‐way ANOVA. Data are represented as mean ± SD.

Article Snippet: We also examined S100A10 mRNA levels (microarray z ‐scores) across all 930 human cancer cell lines listed in the CCLE from the Broad Institute ( http://www.ncbi.nlm.nih.gov/protein/GSE36133 ) (Barretina et al ., ).

Techniques: Expressing, Methylation, RNA Sequencing, Quantitative RT-PCR, Construct

Journal: Molecular Oncology

Article Title: S100A10, a novel biomarker in pancreatic ductal adenocarcinoma

doi: 10.1002/1878-0261.12356

Figure Lengend Snippet: S100A10 mRNA expression is regulated by differential CpG site methylation. S100A10 mRNA (A,B,C) and protein (D,E,F) changes in Panc 10.05 (A,D), Panc‐1 (B,E), and AsPC‐1 (C,F) in response to 10 μ m decitabine (DAC) for 72 h. Global and CpG‐specific methylation of the 24 CpGs in the S100A10 promoter in Panc 10.05 (G,J), Panc‐1 (H,K), and AsPC‐1 (I,L). Graphs G–I represent the averages of percentages of all 24 sites in each cell line. Graphs J–L represent the percentage methylated of cytosines of a specific CpG site within each sample. Significance was determined using unpaired t ‐tests. Data are represented as mean ± SD.

Article Snippet: We also examined S100A10 mRNA levels (microarray z ‐scores) across all 930 human cancer cell lines listed in the CCLE from the Broad Institute ( http://www.ncbi.nlm.nih.gov/protein/GSE36133 ) (Barretina et al ., ).

Techniques: Expressing, Methylation

Journal: Molecular Oncology

Article Title: S100A10, a novel biomarker in pancreatic ductal adenocarcinoma

doi: 10.1002/1878-0261.12356

Figure Lengend Snippet: S100A10 modulates plasminogen activation and cellular invasiveness in vitro and is regulated by KRAS signaling. (A) Western blot of scramble control and S100A10‐depleted (S100A10 shRNA1) Panc‐1 cells. (B) Cells were equally seeded into a 96‐well plate and cell viability (MTS assay) was measured every day for three consecutive days. The absorbance of the MTS reagent at 490 nm is plotted for each time point. (C) Cells were incubated with 0.5 μ m plasminogen, and plasmin activity was measured as the absorbance of the chromogenic plasmin substrate (S2251) at a wavelength of 405 nm. 5 × 10 3 cells of scramble control and S100A10 shRNA1 Panc‐1 cells were seeded into 96‐well plates. Plasminogen activation (per 1 × 10 5 cells) was then calculated under the following conditions: no plasminogen, with plasminogen, with the lysine analog ACA (100 m m ) and the serine protease Ap (2.2 μ m ). ACA is a lysine analog that prevents plasminogen interaction with the carboxyl terminus. Ap is a serine protease pan‐inhibitor which quenches the generated plasmin confirming the ability of these cells to generate plasmin. (D) The matrigel Boyden chamber invasion assay assesses the ability of cells to invade through a Matrigel barrier (substitute for ECM) in response to a chemoattractant (10% FBS). Invasion assay of scramble control and S100A10 shRNA 1 Panc‐1 cells in the presence/absence of Pg. The results are represented as the number of invading cells per one field of view at 20× magnification. (E) Western blots of S100A10, active RAS, and β‐actin in Panc‐1 (a) and BxPC‐3 (c) treated with 10 μ m of the farnesyltransferase inhibitor Zarnestra for 48 h. A Raf pulldown was performed to measure RAS activity. (F) Quantification of S100A10 protein expression normalized to β‐actin in DMSO‐ and Zarnestra‐treated Panc‐1 and BxPC‐3. (G) Genomic construct setup of the mouse iKRAS pancreatic cancer cells. rtTA is a reverse tetracycline transactivator and is required for doxycycline‐inducible expression of KRAS G12D . Western blot (H) and quantification (I) of S100A10 protein in iKRAS cells in the absence (−Doxy) or presence (+Doxy) of 1 μg·mL −1 doxycycline and Zarnestra (10 μ m ) for 4 days. (J) Plasminogen activation assay of IKRAS cells treated with doxycycline and Zarnestra). (K) Western blot analysis of iKRAS cells treated with doxycycline in the presence/absence of 10 μ m decitabine for 72 h.

Article Snippet: We also examined S100A10 mRNA levels (microarray z ‐scores) across all 930 human cancer cell lines listed in the CCLE from the Broad Institute ( http://www.ncbi.nlm.nih.gov/protein/GSE36133 ) (Barretina et al ., ).

Techniques: Activation Assay, In Vitro, Western Blot, Control, MTS Assay, Incubation, Activity Assay, Generated, Invasion Assay, shRNA, Expressing, Construct

Journal: Molecular Oncology

Article Title: S100A10, a novel biomarker in pancreatic ductal adenocarcinoma

doi: 10.1002/1878-0261.12356

Figure Lengend Snippet: S100A10 depletion in Panc‐1 tumors reduces primary tumor size in vivo . 5 × 10 6 scramble control and S100A10 shRNA 1 Panc‐1 cells were injected intraperitoneally into NOD/SCID mice. Representative images (A) and weight (B) of endpoint tumors (50 days postinjection). RT‐qPCR (C,D) and western blot (E,F) quantification of CCND1 (C,E) and VEGF (D,F).

Article Snippet: We also examined S100A10 mRNA levels (microarray z ‐scores) across all 930 human cancer cell lines listed in the CCLE from the Broad Institute ( http://www.ncbi.nlm.nih.gov/protein/GSE36133 ) (Barretina et al ., ).

Techniques: In Vivo, Control, shRNA, Injection, Quantitative RT-PCR, Western Blot

Journal: Oncotarget

Article Title: Pancreatic cancer-derived exosomes transfer miRNAs to dendritic cells and inhibit RFXAP expression via miR-212-3p

doi:

Figure Lengend Snippet: The miRNA target prediction between 9 PC derived exosomal miRNAs and 208 down-regulated mRNA in dendritic cells. miR-203, miR-101-3p, miR-212-3p and miR-139-5p are the potential regulators that can inhibite RFXAP expression.

Article Snippet: Human genome-wide mRNA microarray (A10201-1-40-56, ribobio, Guangzhou, China) was used for mRNA profiling of iDC and exo-iDC which contains approximately 40 000 transcripts selected from the National Center for Biotechnology Information (NCBI) RefSeq database (Release 56).

Techniques: Derivative Assay, Expressing

Journal: Oncotarget

Article Title: Pancreatic cancer-derived exosomes transfer miRNAs to dendritic cells and inhibit RFXAP expression via miR-212-3p

doi:

Figure Lengend Snippet: A. qRT-PCR indicated that RFXAP mRNA declined by 84.6% after stimulation by PANC-1 derived exosomes. B. Western blot showed RFXAP and MHC II expression were inhibited in exo-iDC. C. There were 5.5 folds changes between iDC and exo-iDC, indicating miR-212-3p was transferred into iDC by exosome.

Article Snippet: Human genome-wide mRNA microarray (A10201-1-40-56, ribobio, Guangzhou, China) was used for mRNA profiling of iDC and exo-iDC which contains approximately 40 000 transcripts selected from the National Center for Biotechnology Information (NCBI) RefSeq database (Release 56).

Techniques: Quantitative RT-PCR, Derivative Assay, Western Blot, Expressing

Journal: Oncotarget

Article Title: Pancreatic cancer-derived exosomes transfer miRNAs to dendritic cells and inhibit RFXAP expression via miR-212-3p

doi:

Figure Lengend Snippet: A. qRT-PCR analysis of relative miR-212-3p expression in PDAC cell lines and gastric cancer cell lines. B. miR-212-3p expression in tumor cells derived exosome. C. qRT-PCR analysis of RFXAP mRNA expression in exosome stimulated iDC. D. Western blot analysis of RFXAP and MHC II expression in tumor exosome stimulated iDC. The expression of RFXAP and MHC II were significantly inhibited by SW1990 and BxPC-3 derived exosome, while SGC-7901 exosome did not. E. Transfection of miR-212-3p inhibitors and mimics to SW1990, BxPC-3 and SGC-7901 exo-iDCs reversed the expression of RFXAP and MHC II.

Article Snippet: Human genome-wide mRNA microarray (A10201-1-40-56, ribobio, Guangzhou, China) was used for mRNA profiling of iDC and exo-iDC which contains approximately 40 000 transcripts selected from the National Center for Biotechnology Information (NCBI) RefSeq database (Release 56).

Techniques: Quantitative RT-PCR, Expressing, Derivative Assay, Western Blot, Transfection

Journal: Pediatric Research

Article Title: DNA methylation of IFI44L as a potential blood biomarker for childhood-onset systemic lupus erythematosus

doi: 10.1038/s41390-024-03135-1

Figure Lengend Snippet: Childhood-onset SLE distinct mRNA expression signature.

Article Snippet: In this study, we obtained mRNA expression microarray (GSE65391) and genome-wide DNA methylation data (GSE118144) related to cSLE from the Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/ ) database in the National Center for Biotechnology Information (NCBI).

Techniques: Expressing