Journal: Oncotarget

Article Title: EGR1 regulates cellular metabolism and survival in endocrine resistant breast cancer.

doi: 10.18632/oncotarget.18292

Figure Lengend Snippet: Figure 1: Analysis and integration of gene and metabolites in LCC1 (sensitive) and LCC9 (resistant) ER+ breast cancer cells. (A) Heatmap: R package Limma was used for microarray analysis of LCC1 versus LCC9 data; significantly different genes were selected (q-value < 0.1, fold change, FC > 2) to plot the heatmap; there were 3-biological replicates. (B) Principal component analysis: PCA analysis performed for the transcriptomics and metabolomics datasets - MSRC and Metabolon. (C) Integration of differentially expressed genes and putative metabolites comparing LCC9 (resistant) and LCC1 (sensitive) cells. Metabolites are shown as rectangular nodes, and genes as ellipses. Orange nodes are over-expressed; blue nodes are under-expressed; darker color represents a higher fold change (FC). Lowest log2 FC = –5.66, highest log2 FC = 5.89. Grey nodes are those added into the network based on prediction by STITCH. Edge thickness increases with the confidence of the connection as predicted by STITCH. Gene-metabolite connections are shown in grey lines, gene-gene connections are shows as purple lines, and metabolite-metabolite connections are shown as gold lines. EGR1 is significantly decreased in LCC9 cells (log2 FC= –2.33).

Article Snippet: For EGR1 overexpression, EGR1 cDNA (catalog #SC128132) was purchased from Origene and transfected with TransIT-2020 (Mirus).

Techniques: Microarray

Journal: Oncotarget

Article Title: EGR1 regulates cellular metabolism and survival in endocrine resistant breast cancer.

doi: 10.18632/oncotarget.18292

Figure Lengend Snippet: Figure 2: Lower EGR1 levels correlate with lower survival in ER+ breast cancer patients treated with endocrine therapy. (A) and (B) Kaplan-Meier plots were generated using the Symmans et al. and Loi et al. datasets to estimate the number of patients living over time post endocrine treatment (Tamoxifen) with indicated levels of EGR1 expression in their breast tumors; rfs_t (recurrence free survival time) (C) Pre-treatment vs. 90 days post-treatment (Letrozole) comparisons show significantly increased levels of EGR1 expression (p < 0.0001) only in the responder group.

Article Snippet: For EGR1 overexpression, EGR1 cDNA (catalog #SC128132) was purchased from Origene and transfected with TransIT-2020 (Mirus).

Techniques: Generated, Expressing

Journal: Oncotarget

Article Title: EGR1 regulates cellular metabolism and survival in endocrine resistant breast cancer.

doi: 10.18632/oncotarget.18292

Figure Lengend Snippet: Figure 3: EGR1 expression regulate cell proliferation and viability in both endocrine sensitive and resistant ER+ breast cancer cells. (A) Western blot of LCC1 and LCC9 cells showing the effect of EGR1 knockdown (EGR1-siRNA) and its respective control (EGR1-control-siRNA) or EGR1 overexpression (EGR1) or its respective control, empty vector (EV). Cells were transfected with siRNA or cDNA plasmid for 72 h. EGR1 protein appeared as a doublet, perhaps due to phosphorylation. Actin was used as a loading control. (B–C) Quantification of EGR1 protein (normalized to actin) following transfection with EGR1-siRNA compared with control siRNA in LCC1 and LCC9 cells show 2.5- and 3.8-fold reduction, respectively, (B) EGR1 protein in LCC1 and LCC9 cells show 1.4- and 2-fold increase, respectively, with EGR1-cDNA compared with EV, (C, D) EGR1 knockdown in both LCC1 and LCC9 cells significantly decreased cell proliferation at 48 h regardless of TAM or ICI treatment (ANOVA, p < 0.001). (E) EGR1 knockdown significantly decreased cell viability in both LCC1 and LCC9 cells (ANOVA, p < 0.01; *p < 0.01 for cell death in EGR1-siRNA versus control-siRNA for respective cells lines) at 48 h. (F) and (G) EGR1 overexpression for 48 h followed by treatment with TAM or ICI for 3-days or 5-days, respectively. While EGR1 overexpression did not change cell proliferation of either LCC1 or LCC9 cell under control or treatment conditions at 3-days, at 5-days, EGR1 transfected LCC1 and LCC9 cells showed significant decrease in cell proliferation compared with respective cells transfected with EV. At 5-day transfection with EGR1 combined with E2 treatment showed a significant decrease in E2 response compared to EV control (ANOVA, p < 0.05).

Article Snippet: For EGR1 overexpression, EGR1 cDNA (catalog #SC128132) was purchased from Origene and transfected with TransIT-2020 (Mirus).

Techniques: Expressing, Western Blot, Knockdown, Control, Over Expression, Plasmid Preparation, Transfection, Phospho-proteomics

Journal: Oncotarget

Article Title: EGR1 regulates cellular metabolism and survival in endocrine resistant breast cancer.

doi: 10.18632/oncotarget.18292

Figure Lengend Snippet: Figure 4: EGR1 knockdown in endocrine resistant cells disrupt fatty acid metabolism pathway. Correlation between estimated log2 fold changes for the EGR1 knockdown experiment (siEGR1 vs. siCtrlEGR1) and the estimated log2 fold changes for the EGR1 siRNA experiment (EGR1 cDNA vs. EV EGR1). The negative correlation indicates agreement a global agreement between the two approaches, as the direction of change is expected to be different when comparing the knockdown to the overexpression experiments.

Article Snippet: For EGR1 overexpression, EGR1 cDNA (catalog #SC128132) was purchased from Origene and transfected with TransIT-2020 (Mirus).

Techniques: Knockdown, Over Expression

Journal: Oncotarget

Article Title: EGR1 regulates cellular metabolism and survival in endocrine resistant breast cancer.

doi: 10.18632/oncotarget.18292

Figure Lengend Snippet: Figure 5: TOLE decreased EGR1 protein in both sensitive and resistant cells and re-sensitize resistant cells to antiestrogens. (A) Western blot analysis of LCC1 and LCC9 cells, treated with vehicle, TOLE (50 μM), TAM (100 nM) or ICI (100 nM) or the combination for 72 h. In LCC1 cells, TOLE, TAM or ICI treatment decreased EGR1 protein levels. However, in LCC9 cells, antiestrogens increased but TOLE deceased EGR1 protein levels. Actin was used as a loading control. (B) Cell proliferation was significantly decreased in both LCC1 and LCC9 with treatment with TOLE at 72 h. Combination of TAM or ICI with TOLE did not show a significant interaction in LCC1 cells. However, cell proliferation was synergistically decreased in LCC9 cells treated with TOLE +TAM (RI = 1.31) or ICI+TOLE (RI = 1.20) within 72 h. ANOVA, p < 0.001; *p < 0.001 for specified treatment and cell line compared to vehicle. Dashed line denotes decrease in relative cell proliferation in each cell line with TOLE alone. (C) In LCC9 cells, knockdown of EGR1 with siRNA showed significant decrease in cell proliferation with 25 or 50 µM TOLE in LCC9 cells suggesting that TOLE-mediated EGR1 downregulation contributes to TOLE-induced decrease in cell proliferation in LCC9 cells. ANOVA, p < 0.05; *p < 0.05 for indicated concentration of TOLE in control-siRNA versus EGR1-siRNA.

Article Snippet: For EGR1 overexpression, EGR1 cDNA (catalog #SC128132) was purchased from Origene and transfected with TransIT-2020 (Mirus).

Techniques: Western Blot, Control, Knockdown, Concentration Assay

Journal: Scientific Reports

Article Title: Transcriptomic analysis identifies a potential target for bevacizumab resistant glioblastoma

doi: 10.1038/s41598-025-20847-4

Figure Lengend Snippet: Elevated expression of nuclear EGR1 in tumors that were poor-responders to bevacizumab therapy. ( a , b ) Sections were reacted with rabbit anti-EGR1 antibody, as described in the Methods. ( a ) Box and dot plot depicting nuclear EGR1 expression in tumors that were poor-responders to bevacizumab (five mouse tumors from two PDXs-G64 and G108), and in tumors that were good-responders to bevacizumab (five mouse tumors from two PDXs-G39 and G59). Mouse ids are color-labeled. H-scores were determined for each sample as described in the Methods. Statistical analysis: linear mixed model ( p = 0.02). ( b ) A representative image is shown of immunohistochemical staining for EGR1 in a tumor that was a poor-responder to bevacizumab and in a tumor that was a good-responder to bevacizumab. Arrows denote EGR1 + nuclei. Scale bar denotes 40 μm. ( c , d ) Sections were reacted with rat mAb anti-EGR1 antibody, as described in the Methods. ( c ) Box and dot plot depicts nuclear EGR1 expression in tumors that were poor-responders to bevacizumab (five mouse tumors from two PDXs-G64 and G108), and nuclear EGR1 expression in tumors that were good-responders to bevacizumab (five mouse tumors from two PDXs-G39 and G59). Mouse ids are color-labeled. Statistical analysis: linear mixed model ( p = 0.03). ( d ) A representative image is shown of immunofluorescence for nuclear EGR1 in a tumor that was a poor-responder to bevacizumab and in a tumor that was a good-responder to bevacizumab. Arrows denote EGR1 + nuclei. Scale bar denotes 20 μm. ( e ) Primary cells from PDX tumors were propagated as neurospheres in neural basal media with EGF and bFGF and harvested for flow cytometry. Cells were stained with a live/dead marker (LIVE/DEAD™ Fixable Violet Kit, Thermo # L34955 ) and then fixed and permeabilized (True Nuclear Buffer Set, BioLegend # 424401), and stained with Alexa Fluor ® 647 anti-EGR1 Antibody (BioLegend # 943906), followed by analysis on a BD Fortessa (BD Biosciences) flow cytometer. A violin plot is shown. Data were analyzed using the FlowJo (v10.10.0) software, as described in the Methods. Mean EGR1 fluorescence intensity in PDX tumors that were poor-responders (897.9) as compared to the mean fluorescent intensity in PDX tumors that were good-responders (673.0) to bevacizumab therapy. Statistical analysis: Student’s two-sided T-Test ( p < 0.001).

Article Snippet: Sections were stained for EGR1 with rat mAb anti-EGR1 (20 μg/ml, R&D Systems #MAB28181) after permeabilization with 0.25% Triton X-100 for 5-min. Rat IgG was substituted for the first antibody as the negative control.

Techniques: Expressing, Labeling, Immunohistochemical staining, Staining, Immunofluorescence, Flow Cytometry, Marker, Software, Fluorescence

Journal: Scientific Reports

Article Title: Transcriptomic analysis identifies a potential target for bevacizumab resistant glioblastoma

doi: 10.1038/s41598-025-20847-4

Figure Lengend Snippet: Elevated Ki67 signal in EGR1 high tumor cells in tumors that were poor-responders to bevacizumab therapy. ( a , b ) FFPE sections were triple-labeled with rat mAb anti-EGR1 antibody, rabbit anti-Ki67 antibody, and mouse anti-human nucleoli antibody, as described in the methods. Frozen sections were triple-labeled with rat mAb anti-EGR1 antibody, mouse anti-Ki67 antibody, and rabbit anti-human nuclei antibody, as described in the Methods. ( a ) Representative images are shown of immunofluorescence for nuclear EGR1, Ki67, human nucleoli and DAPI in a tumor that was a poor-responder to bevacizumab and in a tumor that was a good-responder to bevacizumab. White arrows denote nuclear EGR1 expression and Ki67 expression in human tumor nuclei. Scale bar denotes 30 μm. ( b ) Box plot of Ki67 signal in EGR1 high tumor cells in tumors that were poor-responders to bevacizumab (11 mouse tumors from two PDXs-G64 and G108), and of Ki67 signal in EGR1 high tumor cells in tumors that were good-responders to bevacizumab (8 mouse tumors from two PDXs-G39 and G59). Red line represents least squares mean per group. Statistical analysis: linear mixed model ( p = 0.026). ( c , d ) FFPE sections were double-labeled with rabbit anti-Ki67 antibody and mouse anti-human nucleoli antibody; and frozen sections were double-labeled with mouse anti-Ki67 antibody and rabbit anti-human nuclei antibody, as described in the Methods. ( c ) Representative images are shown of immunofluorescence for Ki67 (pseudo-colored red) and human nucleoli (pseudo-colored magenta) in tumors that were poor-responders to bevacizumab and in tumors that were good-responders to bevacizumab. White arrows denote nuclear Ki67 expression in human tumor nuclei. Scale bar denotes 150 μm. ( d ) Box plot of Ki67 signal in all tumor cells in tumors that were poor-responders to bevacizumab (11 mouse tumors from two PDXs-G64 and G108), and Ki67 signal in all tumor cells in tumors that were good-responders to bevacizumab (8 mouse tumors from two PDXs-G39 and G59). Red line represents least squares mean per group. Statistical analysis: linear mixed model ( p = 0.53). ( e ) Fraction of EGR1 high tumor nuclear area to the total EGR1 + tumor nuclear area in entire tumor sections imaged with the Leica DMB6 B scanning fluorescent microscope. A significant increase in the fraction of EGR1 high tumor nuclear area to the total EGR1 + tumor nuclear area is seen in the poor-responder tumors as compared to the good-responder tumors ( p = 0.026). Statistical analysis: Wilcoxon rank-sum test.

Article Snippet: Sections were stained for EGR1 with rat mAb anti-EGR1 (20 μg/ml, R&D Systems #MAB28181) after permeabilization with 0.25% Triton X-100 for 5-min. Rat IgG was substituted for the first antibody as the negative control.

Techniques: Labeling, Immunofluorescence, Expressing, Microscopy

Journal: Scientific Reports

Article Title: Transcriptomic analysis identifies a potential target for bevacizumab resistant glioblastoma

doi: 10.1038/s41598-025-20847-4

Figure Lengend Snippet: Expression of α7-nAChR protein directly correlates with nuclear EGR1 protein in poor- and good-responder tumors to bevacizumab therapy. ( a , b ) Sections were double-labeled with rat mAb anti-EGR1 antibody and rabbit anti-α7-nAChR antibody, as described in the Methods. ( a ) Representative images are shown of immunofluorescence for DAPI, α7-nAChR, and nuclear EGR1 in a tumor depicting regions of high and low EGR1 expression. Yellow lines denote regions (ROIs) of representative individual cells used for single-cell analysis. Scale bar denotes 10 μm. ( b ) Scatter plot of nuclear EGR1 expression and α7-nAChR expression in individual cells in tumors that were poor-responders to bevacizumab (5 mouse tumors from two PDXs-G64 and G108), and nuclear EGR expression and α7-nAChR expression in individual cells in tumors that were good-responders to bevacizumab (5 mouse tumors from two PDXs-G39 and G59). Mouse ids are color-labeled. Statistical analysis: Spearman correlation ( p < 0.001). ( c ) Median linear correlation R values for each PDX calculated using Prism software (2 biologic replicates, 2 technical replicates for each PDX).

Article Snippet: Sections were stained for EGR1 with rat mAb anti-EGR1 (20 μg/ml, R&D Systems #MAB28181) after permeabilization with 0.25% Triton X-100 for 5-min. Rat IgG was substituted for the first antibody as the negative control.

Techniques: Expressing, Labeling, Immunofluorescence, Single-cell Analysis, Software

Journal: Scientific Reports

Article Title: Transcriptomic analysis identifies a potential target for bevacizumab resistant glioblastoma

doi: 10.1038/s41598-025-20847-4

Figure Lengend Snippet: Elevated EGR1 mRNA levels were associated with a shorter survival and upregulation of angiogenesis-blood vessel genes in female recurrent GBM patients from the GLASS database. ( a , b ) The overall survival difference between low EGR1 mRNA expression (< mean) and high EGR1 mRNA expression (≥mean) in males and females with recurrent tumors is significant ( P = 0.031 and P = 0.024, respectively; statistical analysis: Log-Rank test). ( c ) When stratified by sex in recurrent tumors, higher EGR1 mRNA levels correlated with shorter overall survival in males and females ( R = −0.25, P = 0.012 and R = −0.18, P = 0.043, respectively; statistical analyses: Pearson Correlation). ( d , e ) When recurrent tumors with methylation of the MGMT promotor were stratified by sex, there was a difference in overall survival between low EGR1 mRNA expression (< mean) and high EGR1 mRNA expression (≥mean) only in females ( P = 0.0062; statistical analysis: Log-Rank test). ( f ) When tumors with methylation of the MGMT promotor were stratified by sex, EGR1 mRNA levels correlated with overall survival only in females ( P = 0.0089; statistical analyses: Pearson Correlation). ( g ) Log 2 expression of genes in the GO-Angiogenesis-Blood Vessel geneset that are downstream targets of EGR1 in recurrent GBM patients shows upregulation in patients with elevated levels of EGR1 mRNA ( p < 0.001; statistical analyses: Student T-test). ( h ) Heatmap of concordant GO-Angiogenesis-Blood Vessel genes that are downstream targets of EGR1 shows upregulation in tumors with elevated levels of EGR1 mRNA. Data gathered from GLASS database through cBioPortal and filtered for GBM tumors (247 patients with recurrent tumor information, of which 89 patients also had MGMT promoter methylation status data). Plots generated and stratified using ggsurv and ggplot2 in R.

Article Snippet: Sections were stained for EGR1 with rat mAb anti-EGR1 (20 μg/ml, R&D Systems #MAB28181) after permeabilization with 0.25% Triton X-100 for 5-min. Rat IgG was substituted for the first antibody as the negative control.

Techniques: Expressing, Methylation, Generated