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Image Search Results
Journal: Cancer cell
Article Title: Phosphorylation of ETS1 by Src Family Kinases Prevents its Recognition by the COP1 Tumor Suppressor
doi: 10.1016/j.ccr.2014.06.026
Figure Lengend Snippet: (A) Schematics of ETS1 and ETS2.
Article Snippet: Anti-COP1 antibody (A300-894A),
Techniques:
Journal: Cancer cell
Article Title: Phosphorylation of ETS1 by Src Family Kinases Prevents its Recognition by the COP1 Tumor Suppressor
doi: 10.1016/j.ccr.2014.06.026
Figure Lengend Snippet: (A and B) Immunoblot analysis of anti-ETS1 immunoprecipitates or whole cell extracts of MDA-MB-231 cells expressing a DOX-inducible COP1 shRNA treated with increased amounts of dasatinib for 8 hours with or without pretreatment of MG132 (10 μM) for 2 hours (A) or Dox (1μg/mL) for 48 hours (B).
Article Snippet: Anti-COP1 antibody (A300-894A),
Techniques: Western Blot, Expressing, shRNA
Journal: Cancer cell
Article Title: Phosphorylation of ETS1 by Src Family Kinases Prevents its Recognition by the COP1 Tumor Suppressor
doi: 10.1016/j.ccr.2014.06.026
Figure Lengend Snippet: (A and B) Immunoblot analysis (A) and soft agar assay (B) of MDA-MB-231 cells stably expressing shRNAs against GFP or ETS1 (shRNA 2 or 3) and, where indicated, an mRNA encoding venus fluorescent protein (Venus) or an shRNA-resistant (for shRNA 3) mRNA encoding ETS1 (ETS1res). Representative images in (B) are from three biological replicates.
Article Snippet: Anti-COP1 antibody (A300-894A),
Techniques: Western Blot, Soft Agar Assay, Stable Transfection, Expressing, shRNA
Journal: Signal Transduction and Targeted Therapy
Article Title: Single-cell identifies and validates human circulating Treg subtype/state Treg fci in non-small cell lung cancer
doi: 10.1038/s41392-026-02677-6
Figure Lengend Snippet: ETS1 -associated transcriptomic landscape and spatial enrichment of Treg fci subsets in NSCLC and diverse immunopathological settings. a , b Volcano plot showing DEGs identified from scRNA-seq data. a About 1363 DEGs with adjusted p < 0.05 and log 2 FC > 1 between pre-operative Treg fci subsets and post-operative T cells. b About 995 DEGs between pre-operative Treg fci subsets and non-Treg fci T cell populations of NSCLC patients. c Bar plots displaying top 30 DEGs between pre-operative blood-specific T cell subsets and post-operative blood T cells of NSCLC patients. d Heatmap illustrating the expression profiles of the top 30 up-regulated/down-regulated DEGs between pre-operative blood-specific T cell subsets and post-operative blood T cells of NSCLC patients. Box plots comparing spatial distribution of ETS1 ( e ) and ETS1 +Treg fci ( f ) signature scores between central and peripheral tumor regions in NSCLC, based on spatial transcriptomics. g Box plot showing ETS1 exprssion across spatial spots in BRCA, CRC, HCC, OV, PDAC, SCC, analyzed by SpatialTME. h Spatial distribution of ETS1 s in BRCA, CRC, HCC, OV, PDAC, and SCC was analyzed using SpatialTME. Representative spatial transcriptomic heatmaps visualize the regional expression of ETS1 within tissue sections. Representative heatmaps illustrate spatial expression heterogeneity, where red indicates regions of high expression and blue denotes low expression. i Box plots showing ETS1 expression, the identification of 9 out of 16 Treg ciMGPs in healthy donors. * and ** stand for p values less than 0.05 and 0.01, respectively, as compared with the corresponding control groups
Article Snippet: The cells were incubated with
Techniques: Expressing, Spatial Transcriptomics, Control
Journal: Signal Transduction and Targeted Therapy
Article Title: Single-cell identifies and validates human circulating Treg subtype/state Treg fci in non-small cell lung cancer
doi: 10.1038/s41392-026-02677-6
Figure Lengend Snippet: Transcriptomic and functional characterization of fci-modulated T cells reveal altered calcium. Signaling and mitochondrial dynamics under co-culture and activation conditions. a Flow cytometric analysis of intracellular calcium (Ca²⁺) levels in T fci-NC , PHA activated T fci-NC , T fci-KD , PHA activated T fci-KD . Representative bar plot showing the intracellular calcium concentration using Fluo4 dye determined by flow cytometry. b Mitochondrial morphology in T fci-NC or T fci-KD treated with vehicle or PHA was visualized by high-content imaging. Scale bar = 50 μm. c , d Mitochondrial respiration of T cells measured using the Seahorse XF Analyzer. c Line graph showing the oxygen consumption rate (OCR) in T fci-NC or T fci-KD treated with vehicle or PHA. d OCR in T fci-NC or T fci-KD co-cultured with HBE or A549 treated with vehicle or PHA. e Transmission electron microscopic (TEM) analysis of mitochondria endoplasmic reticulum contact sites (MERCs) in T fci-NC or T fci-KD with vehicle or PHA. Scale bar = 5 μm. f – i Transcriptomic profiling of T fci-NC or T fci-KD with vehicle or PHA and co-cultured with HBE or A549 assessed by bulk RNA sequencing. Volcano plots illustrating the DEGs defined by a fold change >2 and p < 0.05 highlight upregulated and downregulated transcripts. f Transcriptomic changes between T fci-NC and T fci-KD , PHA treated T fci-NC and PHA treated T fci-KD , vehicle treated T fci-NC and PHA treated T fci-NC , vehicle treated T fci-KD vs. PHA treated T fci-KD . g Transcriptomic changes between T fci-NC and T fci-NC co-cultured with A549, T fci-KD and T fci-KD co-cultured with A549, PHA treated T fci-NC and PHA treated T fci-NC co-cultured with A549, PHA treated T fci-KD and PHA treated T fci-KD co-cultured with A549. h Transcriptomic changes between T fci-NC co-cultured with A549 and PHA treated T fci-NC co-cultured with A549, T fci-KD co-cultured with A549 and PHA treated T fci-KD co-cultured with A549, A549 co-cultured with T fci-NC and A549 co-cultured with PHA treated T fci-NC , A549 co-cultured with T fci-NC and A549 co-cultured with T fci-KD . i Transcriptomic changes between A549 co-cultured with T fci-NC and PHA treated A549 co-cultured with T fci-KD , T fci-NC and T fci-NC co-cultured with HBE, PHA treated T fci-NC and PHA treated T fci-NC co-cultured with HBE, T fci-NC co-cultured with HBE and PHA treated T fci-NC co-cultured with HBE. j Quantitative analysis of proliferation of T fci-NC , PHA activated T fci-NC , T fci-KD , PHA activated T fci-KD tracked every hour for 48 h using the high-content imaging system. k Quantitative analysis of proliferation of T fci-NC , PHA activated T fci-NC , T fci-KD , PHA activated T fci-KD co-cultured with A549 tracked every hour for 48 housing. l Immunohistochemical staining (IHC) of human NSCLC tissue sections to assess expression levels of ETS1 , FOXP3, CTLA4, and IL2RA. Representative images illustrate differential expression patterns within the tumor microenvironment. Scale bar = 40 μm. m Bar plots showing the mRNA expression of ETS family transcription factors ( ETS1 , ETS2, ETV1, ETV4, and ETV6) in T fci-NC and T fci-KD , with or without vehicle or PHA. n Bar plots showing the mRNA expression of Treg fci ciMGPs (FOXP3, CTLA4, IL2RA) in T fci-NC and T fci-KD following lentiviral knockdown of ETS1 . o Bar plot showing the mRNA expression of Treg fci ciMGPs in T fci-NC and T fci-KD following lentiviral overexpression of ETS1 . p TEM was used to evaluate ultrastructural features of MERCs in ETS1 -modulated T cells (T ETS1-NC , T ETS1-KD , T ETS1-OE and T ETS1-OE/fci-KD ). Representative images and quantitative measures of MERCs proportions are presented. Scale bar = 5 μm
Article Snippet: The cells were incubated with
Techniques: Functional Assay, Co-Culture Assay, Activation Assay, Concentration Assay, Flow Cytometry, Imaging, Cell Culture, Transmission Assay, RNA Sequencing, Immunohistochemical staining, Staining, Expressing, Quantitative Proteomics, Knockdown, Over Expression
Journal: Signal Transduction and Targeted Therapy
Article Title: Single-cell identifies and validates human circulating Treg subtype/state Treg fci in non-small cell lung cancer
doi: 10.1038/s41392-026-02677-6
Figure Lengend Snippet: Single-cell transcriptomic and metabolomic profiles of human and mouse Treg fci under conditions of either ETS1 inhibition or deletion. The PBMCs from human healthy volunteers treated with vehicle (Vehicle) or ETS1 inhibitor (Inhibitor) for 24 h ( n = 11/group) and mouse white blood cells and lung tissue cells of Ets1 flox/flox (control) and Ets1 flox/floxFOXP3-Cre (Ets1-cKO) conditional knockout mice were isolated and prepared for scRNA-seq. Treg fci were annotated and selected on basis of Treg fci ciMGPs and the differential expression of genes was analyzed. The percentages of Treg fci were calculated by comparing with total human PBMCs ( a ), mouse blood WBCs ( d ), and mouse lung tissue cells ( g ). Representative changes in the top 20 genes or metabolism-associated genes from significantly different expression of genes were detected between human blood Treg fci with ETS1 inhibitor (Treg fci + TK216) and Treg fci with vehicle (Treg fci + V) ( b or c ), between Ets1 conditional knockout mice blood (mice ETS1-cKO ) and wild-type mice blood (mice ETS1-wt ) ( e or f ), and between Ets1 conditional knockout mice lung (mice ETS1-cKO ) and wild-type mice lung (mice ETS1-wt ) ( h or i ). The up- ( j ) or down-( k )regulated gene expression profiles were presented. The expression of IGKC mRNA among 17 Treg subsets was compared between human blood Treg fci +TK216 and Treg fci + V ( l ), between mice ETS1-cKO and mice ETS1-wt blood ( m ), and between mice ETS1-cKO and mice ETS1-wt lung ( n ). * and ** stand for the p values less than 0.05 and 0.01, respectively, when compared with mice ETS1-wt . The number ( o , t ), the distribution volcano plots ( p , u ), the individual levels ( q , v ), Z -scores ( r , w ), and KEGG pathway enrichment analysis bubble plots ( s , x ) of significantly different metabolite levels in mouse lung tissues ( o , p , q , r , s ) or blood plasma ( t , u , u , w , x ) were compared between mice ETS1-cKO and mice ETS1-wt
Article Snippet: The cells were incubated with
Techniques: Single Cell, Metabolomic, Inhibition, Control, Knock-Out, Isolation, Quantitative Proteomics, Expressing, Gene Expression, Clinical Proteomics
Journal: Signal Transduction and Targeted Therapy
Article Title: Single-cell identifies and validates human circulating Treg subtype/state Treg fci in non-small cell lung cancer
doi: 10.1038/s41392-026-02677-6
Figure Lengend Snippet: A multi-layered strategy to dissect the role of regulatory T cells (Tregs) in non-small cell lung cancer (NSCLC) and the mechanistic contribution of ETS1. Data mining from public repositories enabled the systematic characterization of T cell subsets including Tregs, using marker-based profiling. The analyses of NSCLC-related datasets across six computational platforms revealed Treg enrichment, regional overexpression rates (rOER), and prognostic associations in diverse patient cohorts. Cross-tissue and cross-disease comparisons further established the landscape of Treg distribution in 6 pulmonary diseases, 17 tissues, and 31 disease contexts. Integrative approaches combining differentially expressed gene (DEG) screening, gene set variation analysis (GSVA), and cell communication analysis highlighted ETS1 as a candidate regulator of Treg biology. The relevance of Tregs across cancers was confirmed through flow cytometric phenotyping, while functional experiments demonstrated their impact on cytokine secretion, proliferation, and survival. Co-culture assays using NSCLC cells, organoids, and primary cells provided evidence that Tregs modulate tumor cell autophagy. ETS1 expression and activity within Tregs were further dissected using wild-type and knockout models, uncovering ETS1-dependent transcriptional programs. Gene interaction network analysis delineated ETS1-associated pathways, supporting its role as a central regulator of Treg function in NSCLC. This summarizes an integrated workflow spanning bioinformatics, cross-disease profiling, functional validation, and genetic perturbation, converging on ETS1 as a pivotal determinant of Treg-mediated immune regulation in NSCLC. Created with MedPeer (medpeer.cn)
Article Snippet: The cells were incubated with
Techniques: Marker, Over Expression, Functional Assay, Co-Culture Assay, Expressing, Activity Assay, Knock-Out, Biomarker Discovery