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Image Search Results
Journal: Frontiers in Immunology
Article Title: Multi-omics analysis and experimental validation of the value of monocyte-associated features in prostate cancer prognosis and immunotherapy
doi: 10.3389/fimmu.2024.1426474
Figure Lengend Snippet: CCNA2 identified as the best prognostic gene among monocyte-associated genes. (A, B) Functional analysis of monocyte-related prognostic genes. (C, D) GBM and RandomForest algorithms to screen key prognostic genes in the TCGA-PRAD dataset. (E, F) GBM and RandomForest algorithms to screen key prognostic genes in the GSE16560 dataset. (G, H) KM curves of CCNA2 and ACSM3 in the TCGA-PRAD dataset. (I, J) KM curves of CCNA2 and ACSM3 in the GSE16560 dataset.
Article Snippet: Next,
Techniques: Functional Assay
Journal: Frontiers in Immunology
Article Title: Multi-omics analysis and experimental validation of the value of monocyte-associated features in prostate cancer prognosis and immunotherapy
doi: 10.3389/fimmu.2024.1426474
Figure Lengend Snippet: CCNA2 positively correlates with monocyte infiltration levels. (A) Correlation analysis of CCNA2 and monocyte infiltration levels. (B, C) Analysis of CCNA2 correlation with monocyte markers. (D) Mendelian randomization analysis of high HLA-DR expressing monocytes in relation to prostate cancer. (E–I) Single-cell analysis of the correlation between CCNA2 and immune cell infiltration.
Article Snippet: Next,
Techniques: Expressing, Single-cell Analysis
Journal: Frontiers in Immunology
Article Title: Multi-omics analysis and experimental validation of the value of monocyte-associated features in prostate cancer prognosis and immunotherapy
doi: 10.3389/fimmu.2024.1426474
Figure Lengend Snippet: Functional analysis of CCNA2 in PRAD. (A) KEGG analysis of CCNA2 in PRAD. (B–J) GSEA analysis of CCNA2 in PRAD.
Article Snippet: Next,
Techniques: Functional Assay
Journal: Frontiers in Immunology
Article Title: Multi-omics analysis and experimental validation of the value of monocyte-associated features in prostate cancer prognosis and immunotherapy
doi: 10.3389/fimmu.2024.1426474
Figure Lengend Snippet: CCNA2 has a high binding capacity to PRAD-targeted drugs. (A) Analysis of the binding capacity of CCNA2 to PD1 inhibitors. (B) Analysis of the binding capacity of CCNA2 to bicalutamide. (C) Analysis of the binding capacity of CCNA2 to enzalutamide. (D) Analysis of the binding capacity of CCNA2 to abiraterone.
Article Snippet: Next,
Techniques: Binding Assay
Journal: Frontiers in Immunology
Article Title: Multi-omics analysis and experimental validation of the value of monocyte-associated features in prostate cancer prognosis and immunotherapy
doi: 10.3389/fimmu.2024.1426474
Figure Lengend Snippet: CCNA2 is highly expressed in PRAD and is associated with poor patient prognosis. (A, B) Differential expression of CCNA2 in PRAD. (C) Diagnostic predictive value of CCNA2 in PRAD. (D) KM curve of overall survival of CCNA2 in PRAD. (E) Prognostic predictive value of CCNA2 in PRAD.
Article Snippet: Next,
Techniques: Quantitative Proteomics, Diagnostic Assay
Journal: iScience
Article Title: Preparation for mitosis requires gradual CDK1 activation
doi: 10.1016/j.isci.2025.112292
Figure Lengend Snippet: Cdk1 regulates Cyclin B accumulation in G2 phase (A) Schematic. Cdk1 and Plk1 activities that induce mitosis are detected at the S/G2 border and increase gradually throughout G2 phase. (B) Example of unsynchronized U2OS Cyclin B1-YFP cells growing on micropatterns. Lighter colors indicate higher Cyclin B1-YFP fluorescence. Arrows indicate addition of DMSO or inhibitors. Time lapse 30 min. Scale bar 20 μm. (C) Schematic of the in silico synchronization setup. DMSO-treated cells are synchronized in mitosis (top). The resulting Cyclin B1-YFP fluorescence curve (top right) is used to fit Cyclin B1-YFP fluorescence of individual cells before kinase inhibitor treatment (bottom). (D) Quantification of Cyclin B1-YFP fluorescence of cells growing on micropatterns, treated with DMSO or indicated kinase inhibitors after in silico synchronization as in (B) and (C). Graph shows average and standard error of Cyclin B1-YFP fluorescence (At least 15 cells per condition are showed. Data are representative of 4 additional independent experiments, except for Plk1 inhibitor that is present in 2 additional independent experiments). Please note that only Cyclin B1-YFP fluorescence after kinase inhibitor addition is plotted. (E) Quantification of Cyclin B1, Aurora A, and Aurora B immunofluorescence in 4N U2OS Cdk1as cells after 2 h treatment with 1NMPP1. At least 420 cells per condition are showed. Data are representative of 3 independent experiments. ∗∗∗ p < 0.001, using Student’s t test. Interquartile range and median values are indicated within violin plots.
Article Snippet:
Techniques: Fluorescence, In Silico, Immunofluorescence
Journal: iScience
Article Title: Preparation for mitosis requires gradual CDK1 activation
doi: 10.1016/j.isci.2025.112292
Figure Lengend Snippet: Cdk1 regulates transcription of mitotic factors (A) Quantification of Cyclin B1 immunofluorescence in 4N U2OS cells treated with Cdk1 inhibitor (RO3306), cycloheximide, or both for 2 h. The G2 population was separated in silico based on DAPI. At least 520 cells per condition are showed. Data are representative of 2 independent experiments; ∗∗∗ p < 0.001, using ANOVA. Interquartile range and median values are indicated within violin plots. (B) Schematic of the setup for RNA sequencing. HeLa cells were released after double thymidine synchronization. After 4.5 h Cdk1 inhibitor (RO3306) or DMSO was added. After 2 h cells were harvested for RNA sequencing analysis. (C and D) Volcano plots show log2 fold change between treated (RO3306) and non-treated (DMSO) normalized gene expressions (x axis), plotted versus the p value (y axis). Orange circles represent differentially expressed genes, and blue circles represent genes with similar expression (data from 3 independent experiments). (E) Schematic containing a selection of key components involved in direct, inner, and outer feedback regulating Cdk activity. (F) Gene Ontology and p values based on (C).
Article Snippet:
Techniques: Immunofluorescence, In Silico, RNA Sequencing, Expressing, Selection, Activity Assay
Journal: iScience
Article Title: Preparation for mitosis requires gradual CDK1 activation
doi: 10.1016/j.isci.2025.112292
Figure Lengend Snippet: Mathematical model of the cell cycle (A) Schematic representation of the mathematical model. (B) Model prediction (red line) of protein level dynamics after parameter estimation based on quantitative immunofluorescence of indicated proteins in U2OS cells from Akopyan et al. (blue dots). Please note that experimental data are only used until mitotic entry. The decrease of protein levels in mitosis is added to the model to mark mitosis upon full activation of Cdk1. (C) Model estimation of selected cell-cycle activities. Model time refers to number of calculation steps with a fixed duration. (D) Model prediction of Cyclin B level dynamics after inhibition of Cdk1, Cdk2, or Plk1.
Article Snippet:
Techniques: Immunofluorescence, Activation Assay, Inhibition
Figure 3 . (B) Model prediction of accumulated FoxM activity at mitotic entry after Wee1 inhibition at different time points in G2 phase. 100% denotes mitotic levels in absence of Wee1 inhibition. (C) Model prediction of Cyclin B level at mitotic entry after Wee1 inhibition at different time points in G2 phase. 100% denotes mitotic levels in absence of Wee1 inhibition. Striped line indicates apparent minimum Cyclin B levels at mitotic entry. (D and E) U2OS Cyclin B1-YFP cells were monitored by time-lapse microscopy upon addition of Wee1 inhibitors. Three different inhibitors were used: MK1775 (1 μM), PD0166285 (1 μM), and PD407824 (5 μM). (D) Duration of mitosis (x axis) is plotted versus Cyclin B1-YFP level at mitotic entry (y axis). 100% denotes median mitotic levels in absence of Wee1 inhibition. (E) Duration of mitosis (y axis) is plotted versus estimated time before mitosis should Wee1 inhibitors have not been added (x axis). The estimate is based on Cyclin B1-YFP accumulation of control cells in the same experiment ( Journal: iScience
Article Title: Preparation for mitosis requires gradual CDK1 activation
doi: 10.1016/j.isci.2025.112292
Figure Lengend Snippet: Mitotic duration after Wee1 inhibition depends on when in G2 phase Wee1 inhibitors are added (A) Model prediction of G2 duration after Wee1 inhibition at different time points in G2 phase. Time when Wee1i added same as in (B) and (C). G2 phase starts approximately at model time 740, and 20 model time corresponds approximately to 30 min. How activities change relative to model time is visible in
Article Snippet:
Techniques: Inhibition, Activity Assay, Time-lapse Microscopy, Control
Figure 3 . (B) Model prediction of Cyclin B level, Plk1 level, Plk1 activity, and Cdk1 activity after inhibition of Wee1 at different time points in G2 phase. The dotted line in each graph represents the levels at mitotic entry when Wee1 is not artificially inhibited. Mit indicates mitosis. (C) Flow cytometry analysis of Plk1 levels and Plk1-mediated phosphorylation of TCTP (pTCTP) in mitotic U2OS cells. STLC (10 μM), to block cells in mitosis, was added with or without Wee1i for 2 h before harvest. Graph shows mitotic cells, gated as in Journal: iScience
Article Title: Preparation for mitosis requires gradual CDK1 activation
doi: 10.1016/j.isci.2025.112292
Figure Lengend Snippet: Wee1 inhibition in G2 phase leads to a de-coupling of Cdk1 and Plk1 activities (A) Model prediction of Plk1 activity at mitotic entry after Wee1 inhibition at different time points in G2 phase. 100% denotes mitotic levels in absence of Wee1 inhibition. G2 phase starts approximately at model time 740, and 20 model time corresponds approximately to 30 min. How activities change relative to model time is visible in
Article Snippet:
Techniques: Inhibition, Activity Assay, Flow Cytometry, Phospho-proteomics, Blocking Assay
Journal: iScience
Article Title: Preparation for mitosis requires gradual CDK1 activation
doi: 10.1016/j.isci.2025.112292
Figure Lengend Snippet:
Article Snippet:
Techniques: Recombinant, Gene Expression, RNA Sequencing, Software