Journal: Cell chemical biology

Article Title: Divergent JNK Phosphorylation of HDAC3 in Triple Negative Breast Cancer Cells Determines HDAC Inhibitor Binding and Selectivity

doi: 10.1016/j.chembiol.2017.08.015

Figure Lengend Snippet: A) Western blot analysis of MCF-7 cells labeled in situ with photomate (lane 1 and 4), photomate and SAHA (lane 3 and 5) or DMSO (lane 6), reacted with biotin azide tag, and enriched with streptavidin coated magnetic beads. Blot shows enriched fraction eluted off beads and 2.5% of input recognized by anti-HDAC1, 2 and 3 antibodies. B) Graph of the abundance of each class I HDAC in MCF-7 cells quantified by comparison of MCF-7 lysate to a standard curve of each recombinant class I HDACs; visualized by Western blot (Figure S1). C) MS/MS analysis of photomate enriched fractions, as in A). Pie chart on the right shows total number of proteins identified by MS/MS and the number that were specifically enriched when compared to a DMSO control and were decreased by at least 50% when co-treated with SAHA. On the left, bioinformatic annotation of enriched proteins. All specifically enriched proteins are shown in Table S1. D) Gel based visualization of MCF-7 cells labeled with photomate in situ followed by fractionation into cytosol (right) and nucleus (left). Probe staining is shown above, and antibody recognition of the same gel is shown below. Gels are in grey scale for clarity. E) Western blot analysis of HDAC3 co-immunoprecipitates. MDA-MB-231 cells, or MCF-7 cells were lysed and enriched with polyclonal anti-HDAC3 (Abcam) or rabbit IgG protein A bead conjugates (Lanes 2 and 3 respectively). Eluates were analyzed by western blot along with 10% of Input (Lane 1) and blotted with antibodies for complex components. F) Small interfering RNA knockdown of NCOR1 in MCF-7 cells. MCF-7 cells were transfected with siNCOR1 or siControl, followed by labeling with photomate and electrophoretic separation. Antibody recognition of transfected cells is shown above, followed by gel based visualization of photomate engagement of HDAC1and HDAC3 below. Cells were either incubated with photomate (Lane 1) or photomate and excess SAHA (Lane 2) after transfection. All results are representative of at least 3 independent experiments.

Article Snippet: Rabbit polyclonal anti-c-Jun , Protein Tech , 10024-2-AP.

Techniques: Western Blot, Labeling, In Situ, Magnetic Beads, Comparison, Recombinant, Tandem Mass Spectroscopy, Control, Fractionation, Staining, Small Interfering RNA, Knockdown, Transfection, Incubation

Journal: Cell chemical biology

Article Title: Divergent JNK Phosphorylation of HDAC3 in Triple Negative Breast Cancer Cells Determines HDAC Inhibitor Binding and Selectivity

doi: 10.1016/j.chembiol.2017.08.015

Figure Lengend Snippet: KEY RESOURCES TABLE

Article Snippet: Rabbit polyclonal anti-c-Jun , Protein Tech , 10024-2-AP.

Techniques: Virus, Recombinant, Protease Inhibitor, Bicinchoninic Acid Protein Assay, Software, Blocking Assay

Journal: BMC Biology

Article Title: Machine learning combined with omics-based approaches reveals T-lymphocyte cellular fate imbalance in abdominal aortic aneurysm

doi: 10.1186/s12915-025-02400-x

Figure Lengend Snippet: Identification of TIRS regulatory mechanisms and key biomarkers. A LASSO-based feature selection, with the optimal lambda determined when the partial likelihood deviance reached the minimum value (left). SVM-RFE-based feature selection, with root mean square error (RMSE) reached the minimum value and R -squared reached the max value (mid). Venn diagram presented the intersection of key biomarkers obtained through both algorithms (right). B Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 1 (AAA n = 80 patients, control n = 10 healthy individuals; Student’s t -test). C ROC curve demonstrating the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 1. D Clinical impact plot illustrating the clinical utility of key biomarkers. The “Number high risk” curve closely aligns with the “Number high risk with the event” curve at each threshold probability, indicating exceptional predictive power. E Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 2 (AAA n = 9 patients, control n = 10 healthy individuals; Student’s t -test). F ROC curve validating the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 2. G Clinical impact plot demonstrating the clinical utility of key biomarkers. Again, the “Number high risk” curve is closely aligned with the “Number high risk with the event” curve at each threshold probability, highlighting the biomarkers’ strong predictive power. H Aberrant expression profiles for key biomarkers in Perivascular Adipose Tissue Dataset 3 (dilated n = 30, non-dilated n = 30; Student’s t -test). I ROC curve verifying the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Perivascular Adipose Tissue Dataset 3. J Impact plots reiterated superior predictive performance probability, indicating outstanding predictive capability

Article Snippet: The primary antibodies against FOSB (1:500, catalog No. ab184938, Abcam) and JUNB (1:50, catalog No. 10486–1-AP, Proteintech) were incubated overnight at 4 °C, followed by incubation with horseradish peroxidase conjugated secondary antibodies.

Techniques: Selection, Expressing, Control, Diagnostic Assay

Journal: BMC Biology

Article Title: Machine learning combined with omics-based approaches reveals T-lymphocyte cellular fate imbalance in abdominal aortic aneurysm

doi: 10.1186/s12915-025-02400-x

Figure Lengend Snippet: Verification of key biomarkers. A Abdominal aortic wall and peripheral blood samples obtained from AAA patients. B Aberrant expression profiles for key biomarkers in the abdominal aortic wall (Inhouse Dataset 1; AAA n = 5 patients, control n = 4 healthy individuals). C ROC curve validating the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in the abdominal aortic wall (Inhouse Dataset 1). D Clinical impact plot demonstrating the clinical utility of key biomarkers. The “Number high risk” curve closely aligns with the “Number high risk with the event” curve at each threshold probability, indicating exceptional predictive power. E Aberrant expression profiles for key biomarkers in peripheral blood (Inhouse Dataset 2; AAA n = 24 patients, control n = 15 healthy individuals). F ROC curve validating the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in peripheral blood (Inhouse Dataset 2). G Clinical impact plot illustrating the clinical utility of key biomarkers. Again, the “Number high risk” curve remains closely aligned with the “Number high risk with the event” curve at each threshold probability, highlighting the biomarkers’ strong predictive capability. H Mice were infused with saline or Ang II (1000 ng/kg/min) + BAPN. Gross abdominal aorta images were shown. Scale bar is 1 cm. I Representative images of immunohistochemical stains for elastin fiber (Van Gieson) and representative photomicrographs of hematoxylin and eosin (H&E) staining. Scale bar is 200 μm. J – L Representative immunohistochemical staining of FOSB and JUNB in aortic cross sections. Scale bar is 50 μm. Data are expressed as mean ± SEM (control n = 3 mice, AAA n = 5 or 6 mice). Student’s t -test was utilized to compare continuous variables between the two groups

Article Snippet: The primary antibodies against FOSB (1:500, catalog No. ab184938, Abcam) and JUNB (1:50, catalog No. 10486–1-AP, Proteintech) were incubated overnight at 4 °C, followed by incubation with horseradish peroxidase conjugated secondary antibodies.

Techniques: Expressing, Control, Diagnostic Assay, Saline, Immunohistochemical staining, Staining