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Illumina Inc
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Biotechnology Information
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10 ). Data were analyzed for statistical significance using an ordinary one‐way ANOVA (* p < 0.05, ** p < 0.01). H1‐0 levels across two leukemia patient cohorts derived from the (F) PeCan St. Jude database Journal: HemaSphere
Article Title: H1‐0 is a specific mediator of the repressive ETV6::RUNX1 transcriptional landscape in preleukemia and B cell acute lymphoblastic leukemia
doi: 10.1002/hem3.70116
Figure Lengend Snippet: H1‐0 is consistently upregulated in preleukemia and BCP‐ALL expressing ETV6::RUNX1 . (A) Principal component analysis (PCA) plot of ETV6::RUNX1 + (E::R) and wild‐type (WT) hiPSC transcriptome profiles based on all detected genes ( n = 16,328). (B) Hierarchical clustering analysis of differentially expressed genes (absolute fold change > 2 and p < 0.05) between ETV6::RUNX1 + and WT hiPSCs detected by RNA‐seq. (C) H1‐0 expression levels determined by RT‐qPCR in ETV6::RUNX1 + and WT hiPSCs subjected to RNA‐seq. Values were normalized to HW8 WT expression levels as well as to GAPDH expression. (D) Representative Western blot analysis of ETV6::RUNX1, H1‐0, ETV6, and β‐actin levels in ETV6::RUNX1 + and WT hiPSCs. (E) H1‐0 levels in HSCs (CD19‐CD34+CD45RA‐), IL7R+ (CD19‐CD34+CD45RA+IL7R+), and pro‐B (CD19+CD34+) cells differentiated from ETV6::RUNX1 + or reverted MIFF3 hiPSCs, and fetal liver cells. Data are derived from an RNA‐seq dataset by Böiers et al. (accession number E‐MTAB‐6382
Article Snippet: Hence, we analyzed previously published
Techniques: Expressing, RNA Sequencing, Quantitative RT-PCR, Western Blot, Derivative Assay, Microarray, Standard Deviation, Control, shRNA
41 ). Expression is shown for microarray probe 208886_at. Each dot represents a single patient. (D) H1‐0 DNA methylation in different leukemia entities is visualized as a heatmap with each column corresponding to a single patient (accession number GSE49032 Journal: HemaSphere
Article Title: H1‐0 is a specific mediator of the repressive ETV6::RUNX1 transcriptional landscape in preleukemia and B cell acute lymphoblastic leukemia
doi: 10.1002/hem3.70116
Figure Lengend Snippet: ETV6::RUNX1 induces H1‐0 promoter activation . (A) Schematic representation of the H1‐0 locus, including the 512‐bp region (nucleotides −351 to +161 from TSS) encompassing promoter‐like signature EH38E2163184 (ENCODE). The H1‐0 CpG island (CGI) shore and 450K Infinium array probes are indicated. (B) 293T cells were transfected with a vector encoding the H1‐0 promoter‐like signature indicated in (A) , together with the empty pcDNA3.1 vector or pcDNA3.1 expressing either ETV6::RUNX1 or RUNX1, and a vector expressing Renilla luciferase. Luciferase activities were normalized to Renilla luciferase activity and the empty vector control. Data represent mean values of three independent replicates ± standard deviation. Significance was calculated using an ordinary one‐way ANOVA (*** p < 0.001). Representative protein levels of ETV6::RUNX1, RUNX1, and β‐actin determined by Western blot are shown. (C) Pearson correlation of H1‐0 expression and mean DNA methylation of the H1‐0 CGI shore probes cg07141002 and cg01883777 in leukemia patients (accession number GSE49032
Article Snippet: Hence, we analyzed previously published
Techniques: Activation Assay, Transfection, Plasmid Preparation, Expressing, Luciferase, Activity Assay, Control, Standard Deviation, Western Blot, DNA Methylation Assay, Microarray
45 ). B cell precursor fractions are HSCs (CD34+CD19‐IgM‐), pro‐B cells (CD34+CD19+IgM‐), pre‐B cells (CD34‐CD19+IgM‐) and immature B cells (CD34‐CD19+IgM+). (B) H1‐0 expression in healthy B cell precursor stages derived from a published expression microarray dataset (accession number GSE24759 Journal: HemaSphere
Article Title: H1‐0 is a specific mediator of the repressive ETV6::RUNX1 transcriptional landscape in preleukemia and B cell acute lymphoblastic leukemia
doi: 10.1002/hem3.70116
Figure Lengend Snippet: H1‐0 expression decreases during hematopoiesis . (A) H1‐0 expression in ETV6::RUNX1 + BCP‐ALL ( n = 6) and healthy B cell precursor stages derived from a published RNA‐seq dataset (accession number GSE115656
Article Snippet: Hence, we analyzed previously published
Techniques: Expressing, Derivative Assay, RNA Sequencing, Microarray, Standard Deviation
Journal: bioRxiv
Article Title: Epigenetic investigation of multifocal small intestinal neuroendocrine tumours reveals accelerated ageing of tumours and epigenetic alteration of metabolic genes
doi: 10.1101/2024.12.02.626017
Figure Lengend Snippet: In this study, genome-wide DNA methylation of 100 samples from 11 patients was assessed. Each patient had multiple primary small intestinal neuroendocrine tumours (ranging from 2-16 per patient), and a subset of 9 patients had a matched normal small intestinal epithelial sample assessed. A subset of 8 patients also had metastases originating from their SI-NETs (ranging from 1-2 per patient). DNA methylation data was used to assess differential methylation relating to the multifocal tumours, the epigenetic clock was used to assess the ‘timing’ of tumour development and metabolic traits predicted by DNA methylation were compared between samples.
Article Snippet:
Techniques: Genome Wide, DNA Methylation Assay, Methylation
Journal: bioRxiv
Article Title: Epigenetic investigation of multifocal small intestinal neuroendocrine tumours reveals accelerated ageing of tumours and epigenetic alteration of metabolic genes
doi: 10.1101/2024.12.02.626017
Figure Lengend Snippet: (A) Plot of age predictions for normal epithelia samples (green), primary tumours (purple) and metastatic tumours (blue). Chronological age is indicated with the orange points and patients are indicated in order of chronological age. (B) Boxplot of age acceleration difference for the skin and blood clock predictions. (C) Somatic mutation count from tumours correlates with DNA methylation age in the skin and blood clock (p=0.0007).
Article Snippet:
Techniques: Mutagenesis, DNA Methylation Assay