Journal: bioRxiv

Article Title: Differential sensitivity to LINE 1-induced damage contributes to the expansion of Tet2-deficient HSCs upon chronic inflammatory stress

doi: 10.1101/2025.07.21.665900

Figure Lengend Snippet: (A) GSEA analysis showing Hallmark gene sets significantly differentially enriched (padj<0.05 and -1.51.5) in WT-LPS vs WT (left) and/or in Tet2 -/- -LPS vs Tet2 -/- (right) comparisons. (B-E) Enrichment plots for E2F TARGETS (B-C) and TNF-α signalling via NF-κB (D-E) hallmark genesets in WT-LPS vs WT (B,D) and Tet2 -/- -LPS vs Tet2 -/- (C,E) conditions. NES: normalized enrichment score. (F-G) violin plot representing TE subfamilies expression for each TE subfamily significantly (p<0.05) differentially expressed in WT-LPS vs WT (F) and Tet2 -/- -LPS vs Tet2 -/- (G) conditions.

Article Snippet: For pathway enrichment analysis and data visualization, we performed Gene Set Enrichment Analysis (GSEA) using the GSEA command line (v 4.3.3, Broad Institute) ( ).

Techniques: Expressing

Journal: Cancer research

Article Title: M 6 A RNA Methylation Regulates Histone Ubiquitination to Support Cancer Growth and Progression

doi: 10.1158/0008-5472.CAN-21-2106

Figure Lengend Snippet: ALKBH5 regulates DNA damage repair events in cancer cells. A, Representative dot plots showing γH2AX-positive cells in scrambled siRNA or ALKBH5 siRNA–transfected U2OS cells. U2OS cells were transfected with scrambled siRNA or ALKBH5 siRNA for 72 hours before flow cytometry analyses. Bar graph shows means ± SEM (n = 3). B, Western blots of scrambled and ALKBH5 siRNA–transfected U2OS cells using antibodies against the indicated proteins. β-Actin was used as the loading control. C, Percent of Annexin V-FITC–positive U2OS cells transfected with scrambled or ALKBH5 siRNA. D, Results of flow cytometry showing γH2AX-positive cells in scrambled siRNA and ALKBH5 siRNA–transfected 143B osteosarcoma cells. Cells were treated with no ionizing radiation (IR) or 10 Gy IR. After 24 hours, cells were stained for γH2AX to estimate unrepaired double-strand breaks. E, Bar graphs show quantification of γH2AX-positive cells shown in D. P values for A, C, and E were calculated using standard Student t tests. Bar graph represents means ± SEM (n = 3). F, GSEA showing enrichment of DNA damage repair pathway in ALKBH5 KD cells compared with scrambled siRNA–transfected 143B cells. G, Results of DR-GFP reporter assay showing DSB-induced HR repair. U2OS-DR-GFP cells were transfected with scrambled siRNA or ALKBH5 siRNAs followed by transfection with a pCAGGS vector expressing I-SceI endonuclease or empty vector as control. I-SceI endonuclease expression induces DSB if repaired by HR results in GFP+ cells as determined by flow cytometry analysis. H, EJ5-GFP reporter assay showing total NHEJ. EJ5-GFP U2OS cells were transfected with scrambled siRNA or ALKBH5 siRNAs followed by transfection with a pCAGGS vector expressing I-SceI endonuclease or empty vector as control. I-SceI endonuclease induced DSB if repaired by NHEJ results in GFP+ cells as determined by flow cytometry. For G and H, bar graphs show means ± SEM (n = 3). P values were calculated using one-way ANOVA followed by Dunnett multiple comparisons test. *, P < 0.05 **, P < 0.01; ****, P < 0.0001.

Article Snippet: Using the differential expression fold change, we also performed Gene Set Enrichment Analysis (GSEA), using the stand-alone package from the Broad Institute (v4.0.3).

Techniques: Transfection, Flow Cytometry, Western Blot, Control, Staining, Reporter Assay, Plasmid Preparation, Expressing

Journal:

Article Title: Early Expression of Stem Cell-Associated Genes Within The CD8 Compartment After Treatment With a Tumor Vaccine

doi: 10.1016/j.cellimm.2010.07.004

Figure Lengend Snippet: (A) Tumor-bearing and tumor-free mice were generated by the subcutaneous inoculation of 106 AGN2a cells or PBS, respectively, on Day 0. Mice were treated with 250μg of anti-CD25 monoclonal antibody intraperitoneally (Day 3) and/or vaccinated with 2×106 AGN2a-4P vaccine cells given subcutaneously on Days 6. CD8+ splenocytes were collected from 5–6 mice on Day 11 by immunomagnetic cell sorting. RNA was extracted and pooled for gene expression profiling on the Affymetrix GeneChip® Mouse Genome 430 2.0 microarray. GSEA was used to analyze the combined gene expression data of two independent experiments. The “Stemcell_Common_Up” gene set was identified as being enriched in treated tumor-free mice relative to treated tumor-bearing mice. The enrichment profiles of the “Stemcell_Common_Up” gene set are shown for mice given No Treatment (B), Vaccine (C) or Vaccine+anti-CD25 (D). For each enrichment profile, a rank ordered gene list was generated between tumor-free and tumor-bearing mice, in which all genes in the microarray were ordered from highest differential expression in tumor-free (left/red end of bar) to the highest differential expression in tumor-bearing (right/blue end of bar). Black lines represent the location of the “Stemcell_Common_Up” genes in the rank ordered gene list. A summing generates a running enrichment score (green line) which yields the overall enrichment of the gene set at the maximum deviation from zero.

Article Snippet: Importantly, this stem cell-related gene set was not enriched in the CD8 + T cells of non-treated tumor-free mice as compared to non-treated tumor-bearing mice (p=0.749, FDR=0.834, ) indicating that this finding is related to the vaccine-induced immune response and not simply a reflection of the presence or absence of tumor. table ft1 table-wrap mode="anchored" t5 caption a7 P value False Discovery Rate No Treatment 0.749 0.834 Vaccine < 0.001 0.003 Vaccine + Anti-CD25 < 0.001 0.019 Open in a separate window caption a8 Enrichment of the “Stemcell_Common_Up” gene set in tumor-free mice relative to tumor-bearing mice Gene Set Enrichment Analysis (GSEA) was used to examine coordinated changes in the gene expression profile of tumor-free and tumor-bearing mice after undergoing treatment with vaccine ± anti-CD25.

Techniques: Generated, FACS, Gene Expression, Microarray, Quantitative Proteomics

Journal:

Article Title: Early Expression of Stem Cell-Associated Genes Within The CD8 Compartment After Treatment With a Tumor Vaccine

doi: 10.1016/j.cellimm.2010.07.004

Figure Lengend Snippet: The leading edge genes from the “Stemcell_Common_Up” gene set were identified in the comparison of CD8+ T cells from tumor-free and tumor-bearing mice treated with vaccine and anti-CD25. The median expression of the leading edge genes was calculated using GSEA software, and was examined in each treatment group relative to CD8+ T cells from naïve (tumor-free, non-treated) mice. Results were averaged from two independent experiments, normalized and hierarchically clustered using Genesis software [20].

Article Snippet: Importantly, this stem cell-related gene set was not enriched in the CD8 + T cells of non-treated tumor-free mice as compared to non-treated tumor-bearing mice (p=0.749, FDR=0.834, ) indicating that this finding is related to the vaccine-induced immune response and not simply a reflection of the presence or absence of tumor. table ft1 table-wrap mode="anchored" t5 caption a7 P value False Discovery Rate No Treatment 0.749 0.834 Vaccine < 0.001 0.003 Vaccine + Anti-CD25 < 0.001 0.019 Open in a separate window caption a8 Enrichment of the “Stemcell_Common_Up” gene set in tumor-free mice relative to tumor-bearing mice Gene Set Enrichment Analysis (GSEA) was used to examine coordinated changes in the gene expression profile of tumor-free and tumor-bearing mice after undergoing treatment with vaccine ± anti-CD25.

Techniques: Comparison, Expressing, Software

Journal:

Article Title: Early Expression of Stem Cell-Associated Genes Within The CD8 Compartment After Treatment With a Tumor Vaccine

doi: 10.1016/j.cellimm.2010.07.004

Figure Lengend Snippet: Enrichment of the “Stemcell_Common_Up” gene set in tumor-free mice relative to tumor-bearing mice Gene Set Enrichment Analysis (GSEA) was used to examine coordinated changes in the gene expression profile of tumor-free and tumor-bearing mice after undergoing treatment with vaccine ± anti-CD25. Gene expression data from two independent experiments was combined and analyzed by GSEA. Of the 1360 gene sets used to interrogate the gene expression data, only the “Stemcell_Common _Up” gene set was found to be consistently enriched in vaccinated tumor-free mice relative to tumor-bearing mice receiving the same treatment. Values above represent the p value and False Discovery Rate (FDR) of the enrichment of the “Stemcell_Common _Up” gene set in each treatment group.

Article Snippet: Importantly, this stem cell-related gene set was not enriched in the CD8 + T cells of non-treated tumor-free mice as compared to non-treated tumor-bearing mice (p=0.749, FDR=0.834, ) indicating that this finding is related to the vaccine-induced immune response and not simply a reflection of the presence or absence of tumor. table ft1 table-wrap mode="anchored" t5 caption a7 P value False Discovery Rate No Treatment 0.749 0.834 Vaccine < 0.001 0.003 Vaccine + Anti-CD25 < 0.001 0.019 Open in a separate window caption a8 Enrichment of the “Stemcell_Common_Up” gene set in tumor-free mice relative to tumor-bearing mice Gene Set Enrichment Analysis (GSEA) was used to examine coordinated changes in the gene expression profile of tumor-free and tumor-bearing mice after undergoing treatment with vaccine ± anti-CD25.

Techniques: Gene Expression

Journal: Breast Cancer Research : BCR

Article Title: Key regulators of lipid metabolism drive endocrine resistance in invasive lobular breast cancer

doi: 10.1186/s13058-018-1041-8

Figure Lengend Snippet: Cholesterol synthesis is predicted to be upregulated in long-term estrogen deprivation (LTED) cells. (a, b) Gene set enrichment analysis (GSEA) of ( a ) E2F activation signature and ( b ) cholesterol biosynthesis signature (Reactome Cholesterol Synthesis) in LTED variants. Differential expression (DE) genes used in GSEA were ranked by log2(fold change). c Growth of parental and LTED cells with treatment of 25-hydroxycholesterol (25-HC) and 27-hydroxycholesterol (27-HC). Parental cells were hormone-deprived before being seeded in hormone-deprived media (charcoal-stripped fetal bovine serum, or CSS). Cells were collected after 5-day treatment. Fold growth was compared with control group (data not shown), which was treated with vehicle (ethanol). Plots are representative of at least two independent experiments. Data are mean ± standard deviation (SD) of six replicates. One-way analysis of variance (ANOVA) followed by Dunnett’s post hoc test for multiple comparisons was used to test the significance between 25-HC/27-HC–treated groups to the control groups (data not shown), * P <0.05, ** P <0.01, *** P <0.001. d The activation z-score of sterol regulatory element-binding proteins (SREBPs) in LTED cells. The upstream regulator analysis was performed in individual LTED cell variants separately with Ingenuity Pathway Analysis (IPA) software. DE genes (absolute log2(fold change) > log2(1.5) and adjusted P value of less than 0.001) and their log2(fold change) were used as input. Upstream regulators with z-score of more than 2 were defined as “activated” (labeled in red). Abbreviation: ES enrichment score.

Article Snippet: GseaPreranked function in Gene Set Enrichment Analysis (GSEA) (version 2.2.2, Broad Institute, Cambridge, MA, USA) was performed using the Reactome cholesterol synthesis signature (Additional file : Table S4), downloaded from the Molecular Signature Database (MsigDB, version 6.0, Broad Institute).

Techniques: Activation Assay, Quantitative Proteomics, Control, Standard Deviation, Binding Assay, Software, Labeling

Journal: EMBO Molecular Medicine

Article Title: Novel Alzheimer risk genes determine the microglia response to amyloid‐β but not to TAU pathology

doi: 10.15252/emmm.201910606

Figure Lengend Snippet: A Visualization of the pathology load in TAUwt, TAUtg, and APPtg mice at 9M of age. Immunofluorescent staining for X34 (a fluorescent derivative of Congo Red; in magenta), Iba1 (microglia; in green), and TO‐PRO‐3 (nuclei; in blue) has been pseudocolored. Scale bar = 100 μm. B Experimental design for mRNA sequencing using n = 12 per experimental group. C Explanation of the 2 × 2 linear model, where those cells labeled with 1 are compared to the cells labeled with 0. In the age comparison, mRNA expression in all 10‐month‐old (10M) mice is compared to all 4‐month‐old (4M) mice. In the genotype comparison, mRNA expression in all transgenic (TG) mice is compared to all wild‐type (WT) mice. In the age*genotype comparison, we assess which transcripts are differentially expressed in the 10M TG mice compared to all other groups. D Based on Marioni et al , various sets of AD GWAS risk genes were created using different cut‐off P ‐values indicated on the x ‐axis (number of genes within each set is written in gray). Enrichment for AD risk genes was assessed among the different statistical comparisons for APPtg and TAUtg mice (A*G: age*genotype, Gen: genotype), using gene set enrichment analysis (GSEA, Subramanian et al , ). Colors represent the Benjamini–Yekutieli‐adjusted P ‐value for the enrichment; blank means no significant enrichment.

Article Snippet: Using the gene set enrichment analysis preranked module (Broad Institute (Subramanian et al , ; Mootha et al , ), two‐sided testing), enrichment for GWAS genes was tested among all genes, sorted from up‐ to downregulated genes based on signed log10( P ‐value) based on the different statistical comparisons (age, genotype, and age*genotype interaction), for APPtg and TAUtg separately, and performing BY P ‐value adjustment.

Techniques: Staining, Sequencing, Labeling, Comparison, Expressing, Transgenic Assay

Journal: EMBO Molecular Medicine

Article Title: Novel Alzheimer risk genes determine the microglia response to amyloid‐β but not to TAU pathology

doi: 10.15252/emmm.201910606

Figure Lengend Snippet: A Gene set enrichment analysis using Fisher's exact test of GWAS genes from Marioni et al at different P ‐value cut‐offs among the WGCNA‐derived modules in APPtg or TAUtg mice (see also Appendix Figs S2 and S3 ). Colors represent −log10 (Benjamini–Yekutieli‐adjusted P ‐value) for the enrichment. Numbers on the x ‐axis: black = P ‐value cut‐off; gray = size of GWAS gene set. B Log2 fold change (LFC) in TAUtg ( x ‐axis) and APPtg mice ( y ‐axis) after differential expression analysis, assessing the effects of age*genotype interaction. Color code for dots/numbers: gray = genes in hippocampus ( n = 15,824); black = genes in APPtg‐Blue ( n = 4,236); green = genes significantly differentially expressed in APPtg mice ( n = 493); yellow = significantly differentially expressed genes in TAUtg mice ( n = 9); and red = significantly differentially expressed genes in both ( n = 9). C Z ‐score distribution per experimental group for all genes within the APPtg‐Blue module. Boxplots: center line, median; box limits, 25 th –75 th quartiles; and whiskers, 1.5× interquartile range. Empirical P ‐values are Bonferroni‐adjusted (*** P bonf < 0.001) and indicate significant shift in z ‐score distribution (see ). D Gene Ontology (GO) enrichment for genes within the APPtg‐Blue module. The x ‐axis depicts −log10(FDR‐adjusted P ‐value) multiplied by the enrichment score (ES), where the red line represents an −log10(0.049)*(ES = 1). E The “top 18” GWAS genes are prioritized by finding the intersection of genes within the APPtg‐Blue module ( n = 4,236), AD GWAS genes with P < 0.001 in Marioni et al ( n = 314), and significantly differentially expressed genes in the age*genotype comparison of APPtg mice ( n = 798), using the SuperExactTest (Wang et al , ). Numbers in italics are the Benjamini–Yekutieli‐adjusted P ‐values for finding overlap between the different gene sets (see Appendix Table S3).

Article Snippet: Using the gene set enrichment analysis preranked module (Broad Institute (Subramanian et al , ; Mootha et al , ), two‐sided testing), enrichment for GWAS genes was tested among all genes, sorted from up‐ to downregulated genes based on signed log10( P ‐value) based on the different statistical comparisons (age, genotype, and age*genotype interaction), for APPtg and TAUtg separately, and performing BY P ‐value adjustment.

Techniques: Derivative Assay, Quantitative Proteomics, Comparison