human breast cancer cell line mda mb 231  (ATCC)


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    ATCC human breast cancer cell line mda mb 231
    Human Breast Cancer Cell Line Mda Mb 231, supplied by ATCC, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    human breast cancer cell line mda mb 231  (ATCC)


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    ATCC human breast cancer cell line mda mb 231
    Human Breast Cancer Cell Line Mda Mb 231, supplied by ATCC, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    human breast cancer cell lines  (ATCC)


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    ATCC human breast cancer cell lines
    Human Breast Cancer Cell Lines, supplied by ATCC, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    human breast cancer cell line  (ATCC)


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    ATCC human breast cancer cell line
    Human Breast Cancer Cell Line, supplied by ATCC, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    human breast cancer cell lines  (ATCC)


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    ATCC human breast cancer cell lines
    Human Breast Cancer Cell Lines, supplied by ATCC, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    human breast cancer cell lines bt20  (ATCC)


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    ATCC human breast cancer cell lines bt20
    VGLL1 expression drives tumor cell proliferation and invasion. (A) Western blot analysis to assess VGLL1 protein expression in the cell lines PANC1, PANC10.05, Bewo, and PANC1 cells transduced to express either hVGLL1-MYC or empty vector (EV). (B) RT-qPCR analysis of VGLL1 mRNA expression in siScramble- (black) or siVGLL1- (red) treated cells after 48h. (C) RT-qPCR analysis of VGLL1 mRNA expression after retroviral transduction of PANC1 cells with hVGLL1-MYC MG-neo plasmid (blue) or empty MG-neo vector (black). (D, E) Cell proliferation analysis of siScramble- (black) or siVGLL1-treated PANC10.05, <t>BT20,</t> and Bewo cells (red), and PANC1 cells transduced with empty MG-neo vector (black) or hVGLL1-MYC MG-neo plasmid (blue). (F, G) Cell invasion assay results comparing siScramble (black) or siVGLL1-treated PANC10.05, BT20, and Bewo cells (red), and PANC1 cells transduced with empty MG-neo vector (black) or VGLL1-MYC MG-neo plasmid (blue). The indicated cells were plated onto the top of a transwell chamber and after 24 hr incubation, migrated invading cells were stained. Images were taken and quantified using ImageJ, with representative images displayed. *p<0.05, **p<0.01.
    Human Breast Cancer Cell Lines Bt20, supplied by ATCC, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    1) Product Images from "Placental co-transcriptional activator Vestigial-like 1 (VGLL1) drives tumorigenesis via increasing transcription of proliferation and invasion genes"

    Article Title: Placental co-transcriptional activator Vestigial-like 1 (VGLL1) drives tumorigenesis via increasing transcription of proliferation and invasion genes

    Journal: Frontiers in Oncology

    doi: 10.3389/fonc.2024.1403052

    VGLL1 expression drives tumor cell proliferation and invasion. (A) Western blot analysis to assess VGLL1 protein expression in the cell lines PANC1, PANC10.05, Bewo, and PANC1 cells transduced to express either hVGLL1-MYC or empty vector (EV). (B) RT-qPCR analysis of VGLL1 mRNA expression in siScramble- (black) or siVGLL1- (red) treated cells after 48h. (C) RT-qPCR analysis of VGLL1 mRNA expression after retroviral transduction of PANC1 cells with hVGLL1-MYC MG-neo plasmid (blue) or empty MG-neo vector (black). (D, E) Cell proliferation analysis of siScramble- (black) or siVGLL1-treated PANC10.05, BT20, and Bewo cells (red), and PANC1 cells transduced with empty MG-neo vector (black) or hVGLL1-MYC MG-neo plasmid (blue). (F, G) Cell invasion assay results comparing siScramble (black) or siVGLL1-treated PANC10.05, BT20, and Bewo cells (red), and PANC1 cells transduced with empty MG-neo vector (black) or VGLL1-MYC MG-neo plasmid (blue). The indicated cells were plated onto the top of a transwell chamber and after 24 hr incubation, migrated invading cells were stained. Images were taken and quantified using ImageJ, with representative images displayed. *p<0.05, **p<0.01.
    Figure Legend Snippet: VGLL1 expression drives tumor cell proliferation and invasion. (A) Western blot analysis to assess VGLL1 protein expression in the cell lines PANC1, PANC10.05, Bewo, and PANC1 cells transduced to express either hVGLL1-MYC or empty vector (EV). (B) RT-qPCR analysis of VGLL1 mRNA expression in siScramble- (black) or siVGLL1- (red) treated cells after 48h. (C) RT-qPCR analysis of VGLL1 mRNA expression after retroviral transduction of PANC1 cells with hVGLL1-MYC MG-neo plasmid (blue) or empty MG-neo vector (black). (D, E) Cell proliferation analysis of siScramble- (black) or siVGLL1-treated PANC10.05, BT20, and Bewo cells (red), and PANC1 cells transduced with empty MG-neo vector (black) or hVGLL1-MYC MG-neo plasmid (blue). (F, G) Cell invasion assay results comparing siScramble (black) or siVGLL1-treated PANC10.05, BT20, and Bewo cells (red), and PANC1 cells transduced with empty MG-neo vector (black) or VGLL1-MYC MG-neo plasmid (blue). The indicated cells were plated onto the top of a transwell chamber and after 24 hr incubation, migrated invading cells were stained. Images were taken and quantified using ImageJ, with representative images displayed. *p<0.05, **p<0.01.

    Techniques Used: Expressing, Western Blot, Plasmid Preparation, Quantitative RT-PCR, Retroviral, Transduction, Invasion Assay, Incubation, Staining

    VGLL1 interacts with common and distinct transcription factors to regulate transcription in tumor cells. (A) Western blot analysis showing relative VGLL1 protein expression either in cell lysates or immunoprecipitated from PANC10.05 and Bewo cells expressing endogenous VGLL1, or PANC1 cells transduced with empty vector (EV) or hVGLL1-MYC plasmid (VGLL1-MYC). Samples without VGLL1 Ab (Beads no Ab) confirmed the specificity of the anti-VGLL1 Ab for IP applications. (B) VGLL1 ChIP-seq analysis was performed on native PANC10.05, BT20, and Bewo tumor cell lines. Homor Motif analysis of the VGLL1 chromatin binding regions revealed several transcription factors (TFs) likely to interact with VGLL1. The Venn diagram shows the common VGLL1 TFs between PANC10.05 (red), BT20 (green) and Bewo (blue) tumor cells. (C–E) ChIP-Atlas was used to compare our results with previously published ChIP-seq data. Each dot represents a different sample (cell line, tissue, etc.) used as a source to pull down individual TFs. Higher enrichment scores indicate higher similarity to the VGLL1 ChIP-seq results. Some samples demonstrated overlap in more than one tumor cell type (black) and others overlapped only with individual tumor cell lines PANC10.05 (red), BT20 (green), Bewo (blue). (F) Table of TFs that were identified in all three tumor cell types. The table contains the TF name and analyzed sample tissue, chromatin motif sequence recognized, percentage of overlapping targets compared to background and p-value. The same color scheme as above indicates the different tumor cell lines analyzed.
    Figure Legend Snippet: VGLL1 interacts with common and distinct transcription factors to regulate transcription in tumor cells. (A) Western blot analysis showing relative VGLL1 protein expression either in cell lysates or immunoprecipitated from PANC10.05 and Bewo cells expressing endogenous VGLL1, or PANC1 cells transduced with empty vector (EV) or hVGLL1-MYC plasmid (VGLL1-MYC). Samples without VGLL1 Ab (Beads no Ab) confirmed the specificity of the anti-VGLL1 Ab for IP applications. (B) VGLL1 ChIP-seq analysis was performed on native PANC10.05, BT20, and Bewo tumor cell lines. Homor Motif analysis of the VGLL1 chromatin binding regions revealed several transcription factors (TFs) likely to interact with VGLL1. The Venn diagram shows the common VGLL1 TFs between PANC10.05 (red), BT20 (green) and Bewo (blue) tumor cells. (C–E) ChIP-Atlas was used to compare our results with previously published ChIP-seq data. Each dot represents a different sample (cell line, tissue, etc.) used as a source to pull down individual TFs. Higher enrichment scores indicate higher similarity to the VGLL1 ChIP-seq results. Some samples demonstrated overlap in more than one tumor cell type (black) and others overlapped only with individual tumor cell lines PANC10.05 (red), BT20 (green), Bewo (blue). (F) Table of TFs that were identified in all three tumor cell types. The table contains the TF name and analyzed sample tissue, chromatin motif sequence recognized, percentage of overlapping targets compared to background and p-value. The same color scheme as above indicates the different tumor cell lines analyzed.

    Techniques Used: Western Blot, Expressing, Immunoprecipitation, Transduction, Plasmid Preparation, ChIP-sequencing, Binding Assay, Sequencing

    VGLL1 regulates transcription of common and unique genes in different tumor cell types. (A) A representative image of the ChIP-seq chromatin peaks detected for all tumor line samples comparing immunoprecipitated VGLL1 (VGLL1 IP) to input cell lysate. (B) Venn diagram shows the number of merged peaks detected and overlap between the 3 cell lines PANC10.05 (red), BT20 (green) and Bewo (blue). (C) Comparison of merged peak regions showing common and unique VGLL1 binding clusters for each tumor cell line. (D) RNA-seq analysis was performed on the indicated tumor cell lines treated with either siVGLL1 or siScramble. Changes in transcript expression for genes associated with VGLL1-binding regions identified in the merged peaks analysis are shown as Volcano plots for each tumor cell line, illustrating genes upregulated (orange) or downregulated (purple) by VGLL1 expression. (E) Representative images of the ChIP-seq chromatin peaks for each tumor cell line are shown for TRIM6-TRIM34, a read-through transcript upregulated by VGLL1 expression (top), NCOA2, a gene whose expression was upregulated by VGLL1 expression (bottom). Green boxes highlight examples of merged peaks present in all 3 tumor cell types and blue boxes indicate peaks not present in all cell lines. (F) GO-enrichment analysis was performed on VGLL1 ChIP-seq target genes modulated in response to VGLL1 knockdown. Upregulated pathways are shown in orange and downregulated pathways are in purple. .
    Figure Legend Snippet: VGLL1 regulates transcription of common and unique genes in different tumor cell types. (A) A representative image of the ChIP-seq chromatin peaks detected for all tumor line samples comparing immunoprecipitated VGLL1 (VGLL1 IP) to input cell lysate. (B) Venn diagram shows the number of merged peaks detected and overlap between the 3 cell lines PANC10.05 (red), BT20 (green) and Bewo (blue). (C) Comparison of merged peak regions showing common and unique VGLL1 binding clusters for each tumor cell line. (D) RNA-seq analysis was performed on the indicated tumor cell lines treated with either siVGLL1 or siScramble. Changes in transcript expression for genes associated with VGLL1-binding regions identified in the merged peaks analysis are shown as Volcano plots for each tumor cell line, illustrating genes upregulated (orange) or downregulated (purple) by VGLL1 expression. (E) Representative images of the ChIP-seq chromatin peaks for each tumor cell line are shown for TRIM6-TRIM34, a read-through transcript upregulated by VGLL1 expression (top), NCOA2, a gene whose expression was upregulated by VGLL1 expression (bottom). Green boxes highlight examples of merged peaks present in all 3 tumor cell types and blue boxes indicate peaks not present in all cell lines. (F) GO-enrichment analysis was performed on VGLL1 ChIP-seq target genes modulated in response to VGLL1 knockdown. Upregulated pathways are shown in orange and downregulated pathways are in purple. .

    Techniques Used: ChIP-sequencing, Immunoprecipitation, Comparison, Binding Assay, RNA Sequencing Assay, Expressing, Knockdown

    VGLL1 expression regulates transcription of genes involved in cellular proliferation and invasion. (A) Global heatmap showing all differentially expressed genes (DEGs) identified from RNAseq analysis of PANC10.05, BT20, and Bewo cells following treatment with either siScramble or siVGLL1. (B) Heatmap showing the top 20 upregulated or downregulated genes in response to VGLL1 knockdown that were common to all three tumor cell lines analyzed. (C) Volcano plots of DEGs identified in each tumor cell line. (D) Results of GO-pathway analysis using the DEGs identified for each tumor cell line. Upregulated genes and pathways are shown in orange and downregulated genes and pathways are indicated in purple.
    Figure Legend Snippet: VGLL1 expression regulates transcription of genes involved in cellular proliferation and invasion. (A) Global heatmap showing all differentially expressed genes (DEGs) identified from RNAseq analysis of PANC10.05, BT20, and Bewo cells following treatment with either siScramble or siVGLL1. (B) Heatmap showing the top 20 upregulated or downregulated genes in response to VGLL1 knockdown that were common to all three tumor cell lines analyzed. (C) Volcano plots of DEGs identified in each tumor cell line. (D) Results of GO-pathway analysis using the DEGs identified for each tumor cell line. Upregulated genes and pathways are shown in orange and downregulated genes and pathways are indicated in purple.

    Techniques Used: Expressing, Knockdown

    human breast cancer cell lines sum-159pt  (ATCC)


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    ATCC human breast cancer cell lines sum-159pt
    Human Breast Cancer Cell Lines Sum 159pt, supplied by ATCC, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    human breast cancer cell lines  (ATCC)


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    ATCC human breast cancer cell lines
    Human Breast Cancer Cell Lines, supplied by ATCC, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    human breast cancer cell line mcf 7  (ATCC)


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    ATCC human breast cancer cell line mcf 7
    CCK-8 assay performed on <t>MCF-7,</t> H358, LNCaP, and HepG2. The control (CTRL) comprised untreated cells, and the solvent used was DMSO. Cells were pretreated overnight with 10 µM of β-HCH and then treated for 48 h with specific TKIs at the concentrations shown on page 3. The values reported in the histograms represent the averages of three independent experiments and are presented as the means and standard deviation. Statistical analysis was performed with GraphPad Prisma software version 8.2.1 (279) using ANOVA followed by Tukey’s post hoc test. Statistically significant differences referring to the CTRL or TKIs are marked with asterisks (ns: not statistically significant, * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001).
    Human Breast Cancer Cell Line Mcf 7, supplied by ATCC, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    1) Product Images from "STAT3 Pathways Contribute to β-HCH Interference with Anticancer Tyrosine Kinase Inhibitors"

    Article Title: STAT3 Pathways Contribute to β-HCH Interference with Anticancer Tyrosine Kinase Inhibitors

    Journal: International Journal of Molecular Sciences

    doi: 10.3390/ijms25116181

    CCK-8 assay performed on MCF-7, H358, LNCaP, and HepG2. The control (CTRL) comprised untreated cells, and the solvent used was DMSO. Cells were pretreated overnight with 10 µM of β-HCH and then treated for 48 h with specific TKIs at the concentrations shown on page 3. The values reported in the histograms represent the averages of three independent experiments and are presented as the means and standard deviation. Statistical analysis was performed with GraphPad Prisma software version 8.2.1 (279) using ANOVA followed by Tukey’s post hoc test. Statistically significant differences referring to the CTRL or TKIs are marked with asterisks (ns: not statistically significant, * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001).
    Figure Legend Snippet: CCK-8 assay performed on MCF-7, H358, LNCaP, and HepG2. The control (CTRL) comprised untreated cells, and the solvent used was DMSO. Cells were pretreated overnight with 10 µM of β-HCH and then treated for 48 h with specific TKIs at the concentrations shown on page 3. The values reported in the histograms represent the averages of three independent experiments and are presented as the means and standard deviation. Statistical analysis was performed with GraphPad Prisma software version 8.2.1 (279) using ANOVA followed by Tukey’s post hoc test. Statistically significant differences referring to the CTRL or TKIs are marked with asterisks (ns: not statistically significant, * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001).

    Techniques Used: CCK-8 Assay, Solvent, Standard Deviation, Software

    CCK-8 assay performed on MCF-7, H358, LNCaP, and HepG2. Cells were incubated with 10 µM of β-HCH, TKIs, and S3I-201, as shown in . Cellular viability decreased after treatment with β-HCH + TKIs + S3I-201 compared with samples treated only with β-HCH + TKIs. The values reported in the histograms represent the averages of three independent experiments and are presented as the means and standard deviation. Statistical analysis was performed with the GraphPad Prisma software using ANOVA followed by Tukey’s post hoc test. Statistically significant differences referring to the CTRL or TKIs are marked with asterisks (ns: not statistically significant, * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001).
    Figure Legend Snippet: CCK-8 assay performed on MCF-7, H358, LNCaP, and HepG2. Cells were incubated with 10 µM of β-HCH, TKIs, and S3I-201, as shown in . Cellular viability decreased after treatment with β-HCH + TKIs + S3I-201 compared with samples treated only with β-HCH + TKIs. The values reported in the histograms represent the averages of three independent experiments and are presented as the means and standard deviation. Statistical analysis was performed with the GraphPad Prisma software using ANOVA followed by Tukey’s post hoc test. Statistically significant differences referring to the CTRL or TKIs are marked with asterisks (ns: not statistically significant, * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001).

    Techniques Used: CCK-8 Assay, Incubation, Standard Deviation, Software

    Immunoblotting evaluating the activation of STAT3 and HER2 in MCF-7 ( A ), STAT3 and EGFR in H358 ( B ), STAT3 and SRC in LNCAP ( C ), and STAT3 and JACK2 in HepG2 ( D ). Total protein extracts were subjected to immunoblot analysis. Immunoblot evidenced that STAT3 phosphorylation (pY705-STAT3), HER2 phosphorylation (pY1248-HER2), JACK2 phosphorylation (pY1007/1008-JAK2), and Src phosphorylation (pY416-Src) increased upon treatment with 10 µM of β-HCH. The increase in STAT3 phosphorylation was upheld even with the combined treatment β-HCH+ TKIs, whereas a decrease in the band intensity occurred in the sample with triple treatment (β-HCH+ TKI+ S3I-201), as evident in the relative densitometry. β-actin was used for housekeeping. Phosphorylation levels referred to the amount of total STAT3, HER2, EGFR, Src, or JAK2 present in each sample and were compared with the control. These images are representative of three independent experiments with similar results. Statistical analysis was performed with the GraphPad Prisma software using ANOVA followed by Tukey’s post hoc test. Statistically significant differences referring to the CTRL or TKIs are marked with asterisks (ns: not statistically significant, ** p < 0.01; *** p < 0.001; **** p < 0.0001).
    Figure Legend Snippet: Immunoblotting evaluating the activation of STAT3 and HER2 in MCF-7 ( A ), STAT3 and EGFR in H358 ( B ), STAT3 and SRC in LNCAP ( C ), and STAT3 and JACK2 in HepG2 ( D ). Total protein extracts were subjected to immunoblot analysis. Immunoblot evidenced that STAT3 phosphorylation (pY705-STAT3), HER2 phosphorylation (pY1248-HER2), JACK2 phosphorylation (pY1007/1008-JAK2), and Src phosphorylation (pY416-Src) increased upon treatment with 10 µM of β-HCH. The increase in STAT3 phosphorylation was upheld even with the combined treatment β-HCH+ TKIs, whereas a decrease in the band intensity occurred in the sample with triple treatment (β-HCH+ TKI+ S3I-201), as evident in the relative densitometry. β-actin was used for housekeeping. Phosphorylation levels referred to the amount of total STAT3, HER2, EGFR, Src, or JAK2 present in each sample and were compared with the control. These images are representative of three independent experiments with similar results. Statistical analysis was performed with the GraphPad Prisma software using ANOVA followed by Tukey’s post hoc test. Statistically significant differences referring to the CTRL or TKIs are marked with asterisks (ns: not statistically significant, ** p < 0.01; *** p < 0.001; **** p < 0.0001).

    Techniques Used: Western Blot, Activation Assay, Software

    Wound-healing assay conducted on MCF-7 ( A ), H358 ( B ), LNCaP ( C ), and HePG2 ( D ) cell lines. Images were collected immediately after scratching the cell monolayer (T0) and 48 h post-treatment with TKIs. The results show that after 48 h of incubation with specific TKIs +10 µM of β-HCH, the pollutant affected the drug efficacy. Conversely, in the triple treatment (β-HCH+ TKI+ S3I-201), by inhibiting the STAT3 protein, there was a reduction in the cellular migratory capability. These images, representative of three independent experiments with similar results, were captured with a Leica AF6000 Modular System microscope.
    Figure Legend Snippet: Wound-healing assay conducted on MCF-7 ( A ), H358 ( B ), LNCaP ( C ), and HePG2 ( D ) cell lines. Images were collected immediately after scratching the cell monolayer (T0) and 48 h post-treatment with TKIs. The results show that after 48 h of incubation with specific TKIs +10 µM of β-HCH, the pollutant affected the drug efficacy. Conversely, in the triple treatment (β-HCH+ TKI+ S3I-201), by inhibiting the STAT3 protein, there was a reduction in the cellular migratory capability. These images, representative of three independent experiments with similar results, were captured with a Leica AF6000 Modular System microscope.

    Techniques Used: Wound Healing Assay, Incubation, Microscopy

    Clonogenic assay conducted on MCF-7, H358, LNCaP, and HepG2 cell lines. β-HCH induced an increase in colony formation, and in the triple treatment (β-HCH+ TKI+ S3I-201), by inhibiting the STAT3 protein, there was a reduction in cellular colony formation. The cells were pretreated with 10 µM of β-HCH in flasks for 7 days and then seeded at a density of 500 cells/mL in 6-well plates and cotreated for 5 days with specific TKIs, as shown in . After treatments, the colonies formed were evidenced using crystal violet dye (Panel A ) and counted, and the total areas of colonies (expressed as percentages with respect to the control and SD) are shown in the histogram (Panel B ). These images are representative of three independent experiments with similar results. Statistical analysis was performed with the GraphPad Prisma software using ANOVA followed by Tukey’s post hoc test. Statistically significant differences were determined at * p < 0.05; and **** p < 0.0001, ns: not statistically significant.
    Figure Legend Snippet: Clonogenic assay conducted on MCF-7, H358, LNCaP, and HepG2 cell lines. β-HCH induced an increase in colony formation, and in the triple treatment (β-HCH+ TKI+ S3I-201), by inhibiting the STAT3 protein, there was a reduction in cellular colony formation. The cells were pretreated with 10 µM of β-HCH in flasks for 7 days and then seeded at a density of 500 cells/mL in 6-well plates and cotreated for 5 days with specific TKIs, as shown in . After treatments, the colonies formed were evidenced using crystal violet dye (Panel A ) and counted, and the total areas of colonies (expressed as percentages with respect to the control and SD) are shown in the histogram (Panel B ). These images are representative of three independent experiments with similar results. Statistical analysis was performed with the GraphPad Prisma software using ANOVA followed by Tukey’s post hoc test. Statistically significant differences were determined at * p < 0.05; and **** p < 0.0001, ns: not statistically significant.

    Techniques Used: Clonogenic Assay, Software

    human breast cancer cell line  (ATCC)


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    ATCC human breast cancer cell line
    Human Breast Cancer Cell Line, supplied by ATCC, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    Average 86 stars, based on 1 article reviews
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    human breast cancer cell line - by Bioz Stars, 2024-06
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    ATCC human breast cancer cell line mda mb 231
    Human Breast Cancer Cell Line Mda Mb 231, supplied by ATCC, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    ATCC human breast cancer cell lines
    Human Breast Cancer Cell Lines, supplied by ATCC, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    ATCC human breast cancer cell line
    Human Breast Cancer Cell Line, supplied by ATCC, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    86
    ATCC human breast cancer cell lines bt20
    VGLL1 expression drives tumor cell proliferation and invasion. (A) Western blot analysis to assess VGLL1 protein expression in the cell lines PANC1, PANC10.05, Bewo, and PANC1 cells transduced to express either hVGLL1-MYC or empty vector (EV). (B) RT-qPCR analysis of VGLL1 mRNA expression in siScramble- (black) or siVGLL1- (red) treated cells after 48h. (C) RT-qPCR analysis of VGLL1 mRNA expression after retroviral transduction of PANC1 cells with hVGLL1-MYC MG-neo plasmid (blue) or empty MG-neo vector (black). (D, E) Cell proliferation analysis of siScramble- (black) or siVGLL1-treated PANC10.05, <t>BT20,</t> and Bewo cells (red), and PANC1 cells transduced with empty MG-neo vector (black) or hVGLL1-MYC MG-neo plasmid (blue). (F, G) Cell invasion assay results comparing siScramble (black) or siVGLL1-treated PANC10.05, BT20, and Bewo cells (red), and PANC1 cells transduced with empty MG-neo vector (black) or VGLL1-MYC MG-neo plasmid (blue). The indicated cells were plated onto the top of a transwell chamber and after 24 hr incubation, migrated invading cells were stained. Images were taken and quantified using ImageJ, with representative images displayed. *p<0.05, **p<0.01.
    Human Breast Cancer Cell Lines Bt20, supplied by ATCC, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    ATCC human breast cancer cell lines sum-159pt
    VGLL1 expression drives tumor cell proliferation and invasion. (A) Western blot analysis to assess VGLL1 protein expression in the cell lines PANC1, PANC10.05, Bewo, and PANC1 cells transduced to express either hVGLL1-MYC or empty vector (EV). (B) RT-qPCR analysis of VGLL1 mRNA expression in siScramble- (black) or siVGLL1- (red) treated cells after 48h. (C) RT-qPCR analysis of VGLL1 mRNA expression after retroviral transduction of PANC1 cells with hVGLL1-MYC MG-neo plasmid (blue) or empty MG-neo vector (black). (D, E) Cell proliferation analysis of siScramble- (black) or siVGLL1-treated PANC10.05, <t>BT20,</t> and Bewo cells (red), and PANC1 cells transduced with empty MG-neo vector (black) or hVGLL1-MYC MG-neo plasmid (blue). (F, G) Cell invasion assay results comparing siScramble (black) or siVGLL1-treated PANC10.05, BT20, and Bewo cells (red), and PANC1 cells transduced with empty MG-neo vector (black) or VGLL1-MYC MG-neo plasmid (blue). The indicated cells were plated onto the top of a transwell chamber and after 24 hr incubation, migrated invading cells were stained. Images were taken and quantified using ImageJ, with representative images displayed. *p<0.05, **p<0.01.
    Human Breast Cancer Cell Lines Sum 159pt, supplied by ATCC, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    86
    ATCC human breast cancer cell line mcf 7
    CCK-8 assay performed on <t>MCF-7,</t> H358, LNCaP, and HepG2. The control (CTRL) comprised untreated cells, and the solvent used was DMSO. Cells were pretreated overnight with 10 µM of β-HCH and then treated for 48 h with specific TKIs at the concentrations shown on page 3. The values reported in the histograms represent the averages of three independent experiments and are presented as the means and standard deviation. Statistical analysis was performed with GraphPad Prisma software version 8.2.1 (279) using ANOVA followed by Tukey’s post hoc test. Statistically significant differences referring to the CTRL or TKIs are marked with asterisks (ns: not statistically significant, * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001).
    Human Breast Cancer Cell Line Mcf 7, supplied by ATCC, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    Image Search Results


    VGLL1 expression drives tumor cell proliferation and invasion. (A) Western blot analysis to assess VGLL1 protein expression in the cell lines PANC1, PANC10.05, Bewo, and PANC1 cells transduced to express either hVGLL1-MYC or empty vector (EV). (B) RT-qPCR analysis of VGLL1 mRNA expression in siScramble- (black) or siVGLL1- (red) treated cells after 48h. (C) RT-qPCR analysis of VGLL1 mRNA expression after retroviral transduction of PANC1 cells with hVGLL1-MYC MG-neo plasmid (blue) or empty MG-neo vector (black). (D, E) Cell proliferation analysis of siScramble- (black) or siVGLL1-treated PANC10.05, BT20, and Bewo cells (red), and PANC1 cells transduced with empty MG-neo vector (black) or hVGLL1-MYC MG-neo plasmid (blue). (F, G) Cell invasion assay results comparing siScramble (black) or siVGLL1-treated PANC10.05, BT20, and Bewo cells (red), and PANC1 cells transduced with empty MG-neo vector (black) or VGLL1-MYC MG-neo plasmid (blue). The indicated cells were plated onto the top of a transwell chamber and after 24 hr incubation, migrated invading cells were stained. Images were taken and quantified using ImageJ, with representative images displayed. *p<0.05, **p<0.01.

    Journal: Frontiers in Oncology

    Article Title: Placental co-transcriptional activator Vestigial-like 1 (VGLL1) drives tumorigenesis via increasing transcription of proliferation and invasion genes

    doi: 10.3389/fonc.2024.1403052

    Figure Lengend Snippet: VGLL1 expression drives tumor cell proliferation and invasion. (A) Western blot analysis to assess VGLL1 protein expression in the cell lines PANC1, PANC10.05, Bewo, and PANC1 cells transduced to express either hVGLL1-MYC or empty vector (EV). (B) RT-qPCR analysis of VGLL1 mRNA expression in siScramble- (black) or siVGLL1- (red) treated cells after 48h. (C) RT-qPCR analysis of VGLL1 mRNA expression after retroviral transduction of PANC1 cells with hVGLL1-MYC MG-neo plasmid (blue) or empty MG-neo vector (black). (D, E) Cell proliferation analysis of siScramble- (black) or siVGLL1-treated PANC10.05, BT20, and Bewo cells (red), and PANC1 cells transduced with empty MG-neo vector (black) or hVGLL1-MYC MG-neo plasmid (blue). (F, G) Cell invasion assay results comparing siScramble (black) or siVGLL1-treated PANC10.05, BT20, and Bewo cells (red), and PANC1 cells transduced with empty MG-neo vector (black) or VGLL1-MYC MG-neo plasmid (blue). The indicated cells were plated onto the top of a transwell chamber and after 24 hr incubation, migrated invading cells were stained. Images were taken and quantified using ImageJ, with representative images displayed. *p<0.05, **p<0.01.

    Article Snippet: Human pancreatic cell lines PANC1 (cat#CRL-1469, RRID: CVCL_0480), PANC10.05 (RRID: CVCL_1639, cat#CRL-2547), Capan1 (RRID: CVCL_0237, cat#HTB-79), Capan2 (RRID: CVCL_0026, cat#HTB-80), SU8686 (RRID: CVCL_3881, cat#CRL-1837) and human breast cancer cell lines BT20 (RRID: CVCL_0178, cat#HTB-19), MDA-MB-468 (RRID: CVCL_0419, cat#HTB-25), MDA-MB-175-VII (RRID: CVCL_1400, cat#HTB-132), and human choriocarcinoma cells, Bewo (RRID: CVCL_0044, cat#CCL-98), were obtained from ATCC and tested negative for mycoplasma contamination.

    Techniques: Expressing, Western Blot, Plasmid Preparation, Quantitative RT-PCR, Retroviral, Transduction, Invasion Assay, Incubation, Staining

    VGLL1 interacts with common and distinct transcription factors to regulate transcription in tumor cells. (A) Western blot analysis showing relative VGLL1 protein expression either in cell lysates or immunoprecipitated from PANC10.05 and Bewo cells expressing endogenous VGLL1, or PANC1 cells transduced with empty vector (EV) or hVGLL1-MYC plasmid (VGLL1-MYC). Samples without VGLL1 Ab (Beads no Ab) confirmed the specificity of the anti-VGLL1 Ab for IP applications. (B) VGLL1 ChIP-seq analysis was performed on native PANC10.05, BT20, and Bewo tumor cell lines. Homor Motif analysis of the VGLL1 chromatin binding regions revealed several transcription factors (TFs) likely to interact with VGLL1. The Venn diagram shows the common VGLL1 TFs between PANC10.05 (red), BT20 (green) and Bewo (blue) tumor cells. (C–E) ChIP-Atlas was used to compare our results with previously published ChIP-seq data. Each dot represents a different sample (cell line, tissue, etc.) used as a source to pull down individual TFs. Higher enrichment scores indicate higher similarity to the VGLL1 ChIP-seq results. Some samples demonstrated overlap in more than one tumor cell type (black) and others overlapped only with individual tumor cell lines PANC10.05 (red), BT20 (green), Bewo (blue). (F) Table of TFs that were identified in all three tumor cell types. The table contains the TF name and analyzed sample tissue, chromatin motif sequence recognized, percentage of overlapping targets compared to background and p-value. The same color scheme as above indicates the different tumor cell lines analyzed.

    Journal: Frontiers in Oncology

    Article Title: Placental co-transcriptional activator Vestigial-like 1 (VGLL1) drives tumorigenesis via increasing transcription of proliferation and invasion genes

    doi: 10.3389/fonc.2024.1403052

    Figure Lengend Snippet: VGLL1 interacts with common and distinct transcription factors to regulate transcription in tumor cells. (A) Western blot analysis showing relative VGLL1 protein expression either in cell lysates or immunoprecipitated from PANC10.05 and Bewo cells expressing endogenous VGLL1, or PANC1 cells transduced with empty vector (EV) or hVGLL1-MYC plasmid (VGLL1-MYC). Samples without VGLL1 Ab (Beads no Ab) confirmed the specificity of the anti-VGLL1 Ab for IP applications. (B) VGLL1 ChIP-seq analysis was performed on native PANC10.05, BT20, and Bewo tumor cell lines. Homor Motif analysis of the VGLL1 chromatin binding regions revealed several transcription factors (TFs) likely to interact with VGLL1. The Venn diagram shows the common VGLL1 TFs between PANC10.05 (red), BT20 (green) and Bewo (blue) tumor cells. (C–E) ChIP-Atlas was used to compare our results with previously published ChIP-seq data. Each dot represents a different sample (cell line, tissue, etc.) used as a source to pull down individual TFs. Higher enrichment scores indicate higher similarity to the VGLL1 ChIP-seq results. Some samples demonstrated overlap in more than one tumor cell type (black) and others overlapped only with individual tumor cell lines PANC10.05 (red), BT20 (green), Bewo (blue). (F) Table of TFs that were identified in all three tumor cell types. The table contains the TF name and analyzed sample tissue, chromatin motif sequence recognized, percentage of overlapping targets compared to background and p-value. The same color scheme as above indicates the different tumor cell lines analyzed.

    Article Snippet: Human pancreatic cell lines PANC1 (cat#CRL-1469, RRID: CVCL_0480), PANC10.05 (RRID: CVCL_1639, cat#CRL-2547), Capan1 (RRID: CVCL_0237, cat#HTB-79), Capan2 (RRID: CVCL_0026, cat#HTB-80), SU8686 (RRID: CVCL_3881, cat#CRL-1837) and human breast cancer cell lines BT20 (RRID: CVCL_0178, cat#HTB-19), MDA-MB-468 (RRID: CVCL_0419, cat#HTB-25), MDA-MB-175-VII (RRID: CVCL_1400, cat#HTB-132), and human choriocarcinoma cells, Bewo (RRID: CVCL_0044, cat#CCL-98), were obtained from ATCC and tested negative for mycoplasma contamination.

    Techniques: Western Blot, Expressing, Immunoprecipitation, Transduction, Plasmid Preparation, ChIP-sequencing, Binding Assay, Sequencing

    VGLL1 regulates transcription of common and unique genes in different tumor cell types. (A) A representative image of the ChIP-seq chromatin peaks detected for all tumor line samples comparing immunoprecipitated VGLL1 (VGLL1 IP) to input cell lysate. (B) Venn diagram shows the number of merged peaks detected and overlap between the 3 cell lines PANC10.05 (red), BT20 (green) and Bewo (blue). (C) Comparison of merged peak regions showing common and unique VGLL1 binding clusters for each tumor cell line. (D) RNA-seq analysis was performed on the indicated tumor cell lines treated with either siVGLL1 or siScramble. Changes in transcript expression for genes associated with VGLL1-binding regions identified in the merged peaks analysis are shown as Volcano plots for each tumor cell line, illustrating genes upregulated (orange) or downregulated (purple) by VGLL1 expression. (E) Representative images of the ChIP-seq chromatin peaks for each tumor cell line are shown for TRIM6-TRIM34, a read-through transcript upregulated by VGLL1 expression (top), NCOA2, a gene whose expression was upregulated by VGLL1 expression (bottom). Green boxes highlight examples of merged peaks present in all 3 tumor cell types and blue boxes indicate peaks not present in all cell lines. (F) GO-enrichment analysis was performed on VGLL1 ChIP-seq target genes modulated in response to VGLL1 knockdown. Upregulated pathways are shown in orange and downregulated pathways are in purple. .

    Journal: Frontiers in Oncology

    Article Title: Placental co-transcriptional activator Vestigial-like 1 (VGLL1) drives tumorigenesis via increasing transcription of proliferation and invasion genes

    doi: 10.3389/fonc.2024.1403052

    Figure Lengend Snippet: VGLL1 regulates transcription of common and unique genes in different tumor cell types. (A) A representative image of the ChIP-seq chromatin peaks detected for all tumor line samples comparing immunoprecipitated VGLL1 (VGLL1 IP) to input cell lysate. (B) Venn diagram shows the number of merged peaks detected and overlap between the 3 cell lines PANC10.05 (red), BT20 (green) and Bewo (blue). (C) Comparison of merged peak regions showing common and unique VGLL1 binding clusters for each tumor cell line. (D) RNA-seq analysis was performed on the indicated tumor cell lines treated with either siVGLL1 or siScramble. Changes in transcript expression for genes associated with VGLL1-binding regions identified in the merged peaks analysis are shown as Volcano plots for each tumor cell line, illustrating genes upregulated (orange) or downregulated (purple) by VGLL1 expression. (E) Representative images of the ChIP-seq chromatin peaks for each tumor cell line are shown for TRIM6-TRIM34, a read-through transcript upregulated by VGLL1 expression (top), NCOA2, a gene whose expression was upregulated by VGLL1 expression (bottom). Green boxes highlight examples of merged peaks present in all 3 tumor cell types and blue boxes indicate peaks not present in all cell lines. (F) GO-enrichment analysis was performed on VGLL1 ChIP-seq target genes modulated in response to VGLL1 knockdown. Upregulated pathways are shown in orange and downregulated pathways are in purple. .

    Article Snippet: Human pancreatic cell lines PANC1 (cat#CRL-1469, RRID: CVCL_0480), PANC10.05 (RRID: CVCL_1639, cat#CRL-2547), Capan1 (RRID: CVCL_0237, cat#HTB-79), Capan2 (RRID: CVCL_0026, cat#HTB-80), SU8686 (RRID: CVCL_3881, cat#CRL-1837) and human breast cancer cell lines BT20 (RRID: CVCL_0178, cat#HTB-19), MDA-MB-468 (RRID: CVCL_0419, cat#HTB-25), MDA-MB-175-VII (RRID: CVCL_1400, cat#HTB-132), and human choriocarcinoma cells, Bewo (RRID: CVCL_0044, cat#CCL-98), were obtained from ATCC and tested negative for mycoplasma contamination.

    Techniques: ChIP-sequencing, Immunoprecipitation, Comparison, Binding Assay, RNA Sequencing Assay, Expressing, Knockdown

    VGLL1 expression regulates transcription of genes involved in cellular proliferation and invasion. (A) Global heatmap showing all differentially expressed genes (DEGs) identified from RNAseq analysis of PANC10.05, BT20, and Bewo cells following treatment with either siScramble or siVGLL1. (B) Heatmap showing the top 20 upregulated or downregulated genes in response to VGLL1 knockdown that were common to all three tumor cell lines analyzed. (C) Volcano plots of DEGs identified in each tumor cell line. (D) Results of GO-pathway analysis using the DEGs identified for each tumor cell line. Upregulated genes and pathways are shown in orange and downregulated genes and pathways are indicated in purple.

    Journal: Frontiers in Oncology

    Article Title: Placental co-transcriptional activator Vestigial-like 1 (VGLL1) drives tumorigenesis via increasing transcription of proliferation and invasion genes

    doi: 10.3389/fonc.2024.1403052

    Figure Lengend Snippet: VGLL1 expression regulates transcription of genes involved in cellular proliferation and invasion. (A) Global heatmap showing all differentially expressed genes (DEGs) identified from RNAseq analysis of PANC10.05, BT20, and Bewo cells following treatment with either siScramble or siVGLL1. (B) Heatmap showing the top 20 upregulated or downregulated genes in response to VGLL1 knockdown that were common to all three tumor cell lines analyzed. (C) Volcano plots of DEGs identified in each tumor cell line. (D) Results of GO-pathway analysis using the DEGs identified for each tumor cell line. Upregulated genes and pathways are shown in orange and downregulated genes and pathways are indicated in purple.

    Article Snippet: Human pancreatic cell lines PANC1 (cat#CRL-1469, RRID: CVCL_0480), PANC10.05 (RRID: CVCL_1639, cat#CRL-2547), Capan1 (RRID: CVCL_0237, cat#HTB-79), Capan2 (RRID: CVCL_0026, cat#HTB-80), SU8686 (RRID: CVCL_3881, cat#CRL-1837) and human breast cancer cell lines BT20 (RRID: CVCL_0178, cat#HTB-19), MDA-MB-468 (RRID: CVCL_0419, cat#HTB-25), MDA-MB-175-VII (RRID: CVCL_1400, cat#HTB-132), and human choriocarcinoma cells, Bewo (RRID: CVCL_0044, cat#CCL-98), were obtained from ATCC and tested negative for mycoplasma contamination.

    Techniques: Expressing, Knockdown

    CCK-8 assay performed on MCF-7, H358, LNCaP, and HepG2. The control (CTRL) comprised untreated cells, and the solvent used was DMSO. Cells were pretreated overnight with 10 µM of β-HCH and then treated for 48 h with specific TKIs at the concentrations shown on page 3. The values reported in the histograms represent the averages of three independent experiments and are presented as the means and standard deviation. Statistical analysis was performed with GraphPad Prisma software version 8.2.1 (279) using ANOVA followed by Tukey’s post hoc test. Statistically significant differences referring to the CTRL or TKIs are marked with asterisks (ns: not statistically significant, * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001).

    Journal: International Journal of Molecular Sciences

    Article Title: STAT3 Pathways Contribute to β-HCH Interference with Anticancer Tyrosine Kinase Inhibitors

    doi: 10.3390/ijms25116181

    Figure Lengend Snippet: CCK-8 assay performed on MCF-7, H358, LNCaP, and HepG2. The control (CTRL) comprised untreated cells, and the solvent used was DMSO. Cells were pretreated overnight with 10 µM of β-HCH and then treated for 48 h with specific TKIs at the concentrations shown on page 3. The values reported in the histograms represent the averages of three independent experiments and are presented as the means and standard deviation. Statistical analysis was performed with GraphPad Prisma software version 8.2.1 (279) using ANOVA followed by Tukey’s post hoc test. Statistically significant differences referring to the CTRL or TKIs are marked with asterisks (ns: not statistically significant, * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001).

    Article Snippet: The human breast cancer cell line MCF-7, human bronchoalveolar cancer cell line H358, human prostate cancer cell line LNCaP, and human hepatoma cell line HepG2 were obtained from the American Type Culture Collection (ATCC, Manassas, VA, USA).

    Techniques: CCK-8 Assay, Solvent, Standard Deviation, Software

    CCK-8 assay performed on MCF-7, H358, LNCaP, and HepG2. Cells were incubated with 10 µM of β-HCH, TKIs, and S3I-201, as shown in . Cellular viability decreased after treatment with β-HCH + TKIs + S3I-201 compared with samples treated only with β-HCH + TKIs. The values reported in the histograms represent the averages of three independent experiments and are presented as the means and standard deviation. Statistical analysis was performed with the GraphPad Prisma software using ANOVA followed by Tukey’s post hoc test. Statistically significant differences referring to the CTRL or TKIs are marked with asterisks (ns: not statistically significant, * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001).

    Journal: International Journal of Molecular Sciences

    Article Title: STAT3 Pathways Contribute to β-HCH Interference with Anticancer Tyrosine Kinase Inhibitors

    doi: 10.3390/ijms25116181

    Figure Lengend Snippet: CCK-8 assay performed on MCF-7, H358, LNCaP, and HepG2. Cells were incubated with 10 µM of β-HCH, TKIs, and S3I-201, as shown in . Cellular viability decreased after treatment with β-HCH + TKIs + S3I-201 compared with samples treated only with β-HCH + TKIs. The values reported in the histograms represent the averages of three independent experiments and are presented as the means and standard deviation. Statistical analysis was performed with the GraphPad Prisma software using ANOVA followed by Tukey’s post hoc test. Statistically significant differences referring to the CTRL or TKIs are marked with asterisks (ns: not statistically significant, * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001).

    Article Snippet: The human breast cancer cell line MCF-7, human bronchoalveolar cancer cell line H358, human prostate cancer cell line LNCaP, and human hepatoma cell line HepG2 were obtained from the American Type Culture Collection (ATCC, Manassas, VA, USA).

    Techniques: CCK-8 Assay, Incubation, Standard Deviation, Software

    Immunoblotting evaluating the activation of STAT3 and HER2 in MCF-7 ( A ), STAT3 and EGFR in H358 ( B ), STAT3 and SRC in LNCAP ( C ), and STAT3 and JACK2 in HepG2 ( D ). Total protein extracts were subjected to immunoblot analysis. Immunoblot evidenced that STAT3 phosphorylation (pY705-STAT3), HER2 phosphorylation (pY1248-HER2), JACK2 phosphorylation (pY1007/1008-JAK2), and Src phosphorylation (pY416-Src) increased upon treatment with 10 µM of β-HCH. The increase in STAT3 phosphorylation was upheld even with the combined treatment β-HCH+ TKIs, whereas a decrease in the band intensity occurred in the sample with triple treatment (β-HCH+ TKI+ S3I-201), as evident in the relative densitometry. β-actin was used for housekeeping. Phosphorylation levels referred to the amount of total STAT3, HER2, EGFR, Src, or JAK2 present in each sample and were compared with the control. These images are representative of three independent experiments with similar results. Statistical analysis was performed with the GraphPad Prisma software using ANOVA followed by Tukey’s post hoc test. Statistically significant differences referring to the CTRL or TKIs are marked with asterisks (ns: not statistically significant, ** p < 0.01; *** p < 0.001; **** p < 0.0001).

    Journal: International Journal of Molecular Sciences

    Article Title: STAT3 Pathways Contribute to β-HCH Interference with Anticancer Tyrosine Kinase Inhibitors

    doi: 10.3390/ijms25116181

    Figure Lengend Snippet: Immunoblotting evaluating the activation of STAT3 and HER2 in MCF-7 ( A ), STAT3 and EGFR in H358 ( B ), STAT3 and SRC in LNCAP ( C ), and STAT3 and JACK2 in HepG2 ( D ). Total protein extracts were subjected to immunoblot analysis. Immunoblot evidenced that STAT3 phosphorylation (pY705-STAT3), HER2 phosphorylation (pY1248-HER2), JACK2 phosphorylation (pY1007/1008-JAK2), and Src phosphorylation (pY416-Src) increased upon treatment with 10 µM of β-HCH. The increase in STAT3 phosphorylation was upheld even with the combined treatment β-HCH+ TKIs, whereas a decrease in the band intensity occurred in the sample with triple treatment (β-HCH+ TKI+ S3I-201), as evident in the relative densitometry. β-actin was used for housekeeping. Phosphorylation levels referred to the amount of total STAT3, HER2, EGFR, Src, or JAK2 present in each sample and were compared with the control. These images are representative of three independent experiments with similar results. Statistical analysis was performed with the GraphPad Prisma software using ANOVA followed by Tukey’s post hoc test. Statistically significant differences referring to the CTRL or TKIs are marked with asterisks (ns: not statistically significant, ** p < 0.01; *** p < 0.001; **** p < 0.0001).

    Article Snippet: The human breast cancer cell line MCF-7, human bronchoalveolar cancer cell line H358, human prostate cancer cell line LNCaP, and human hepatoma cell line HepG2 were obtained from the American Type Culture Collection (ATCC, Manassas, VA, USA).

    Techniques: Western Blot, Activation Assay, Software

    Wound-healing assay conducted on MCF-7 ( A ), H358 ( B ), LNCaP ( C ), and HePG2 ( D ) cell lines. Images were collected immediately after scratching the cell monolayer (T0) and 48 h post-treatment with TKIs. The results show that after 48 h of incubation with specific TKIs +10 µM of β-HCH, the pollutant affected the drug efficacy. Conversely, in the triple treatment (β-HCH+ TKI+ S3I-201), by inhibiting the STAT3 protein, there was a reduction in the cellular migratory capability. These images, representative of three independent experiments with similar results, were captured with a Leica AF6000 Modular System microscope.

    Journal: International Journal of Molecular Sciences

    Article Title: STAT3 Pathways Contribute to β-HCH Interference with Anticancer Tyrosine Kinase Inhibitors

    doi: 10.3390/ijms25116181

    Figure Lengend Snippet: Wound-healing assay conducted on MCF-7 ( A ), H358 ( B ), LNCaP ( C ), and HePG2 ( D ) cell lines. Images were collected immediately after scratching the cell monolayer (T0) and 48 h post-treatment with TKIs. The results show that after 48 h of incubation with specific TKIs +10 µM of β-HCH, the pollutant affected the drug efficacy. Conversely, in the triple treatment (β-HCH+ TKI+ S3I-201), by inhibiting the STAT3 protein, there was a reduction in the cellular migratory capability. These images, representative of three independent experiments with similar results, were captured with a Leica AF6000 Modular System microscope.

    Article Snippet: The human breast cancer cell line MCF-7, human bronchoalveolar cancer cell line H358, human prostate cancer cell line LNCaP, and human hepatoma cell line HepG2 were obtained from the American Type Culture Collection (ATCC, Manassas, VA, USA).

    Techniques: Wound Healing Assay, Incubation, Microscopy

    Clonogenic assay conducted on MCF-7, H358, LNCaP, and HepG2 cell lines. β-HCH induced an increase in colony formation, and in the triple treatment (β-HCH+ TKI+ S3I-201), by inhibiting the STAT3 protein, there was a reduction in cellular colony formation. The cells were pretreated with 10 µM of β-HCH in flasks for 7 days and then seeded at a density of 500 cells/mL in 6-well plates and cotreated for 5 days with specific TKIs, as shown in . After treatments, the colonies formed were evidenced using crystal violet dye (Panel A ) and counted, and the total areas of colonies (expressed as percentages with respect to the control and SD) are shown in the histogram (Panel B ). These images are representative of three independent experiments with similar results. Statistical analysis was performed with the GraphPad Prisma software using ANOVA followed by Tukey’s post hoc test. Statistically significant differences were determined at * p < 0.05; and **** p < 0.0001, ns: not statistically significant.

    Journal: International Journal of Molecular Sciences

    Article Title: STAT3 Pathways Contribute to β-HCH Interference with Anticancer Tyrosine Kinase Inhibitors

    doi: 10.3390/ijms25116181

    Figure Lengend Snippet: Clonogenic assay conducted on MCF-7, H358, LNCaP, and HepG2 cell lines. β-HCH induced an increase in colony formation, and in the triple treatment (β-HCH+ TKI+ S3I-201), by inhibiting the STAT3 protein, there was a reduction in cellular colony formation. The cells were pretreated with 10 µM of β-HCH in flasks for 7 days and then seeded at a density of 500 cells/mL in 6-well plates and cotreated for 5 days with specific TKIs, as shown in . After treatments, the colonies formed were evidenced using crystal violet dye (Panel A ) and counted, and the total areas of colonies (expressed as percentages with respect to the control and SD) are shown in the histogram (Panel B ). These images are representative of three independent experiments with similar results. Statistical analysis was performed with the GraphPad Prisma software using ANOVA followed by Tukey’s post hoc test. Statistically significant differences were determined at * p < 0.05; and **** p < 0.0001, ns: not statistically significant.

    Article Snippet: The human breast cancer cell line MCF-7, human bronchoalveolar cancer cell line H358, human prostate cancer cell line LNCaP, and human hepatoma cell line HepG2 were obtained from the American Type Culture Collection (ATCC, Manassas, VA, USA).

    Techniques: Clonogenic Assay, Software