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ATCC mcf 10a cells

TXNRD(i)s increase redox stress which do not correlate with cell viability. A. Gene set enrichment analysis of Oxidative Stress Response gene set by WikiPathways. NES and nominal p-value were determined by the GSEA software. B. Redox stress quantification using H 2 DCFDA by flow cytometry of MDA-MB-231 (top) (n = 2), HCC1806 (middle) (n = 3), <t>and</t> <t>MCF-10A</t> (bottom) (n = 3) cells. Cells were treated with 10 μM 8VP101 for 0, 2, 6,18, and 24 h, harvested and incubated with 1 μM H 2 DCFDA for 15 min. Representative histograms (left) of measured DCF mean fluorescence intensity (MFI) with the grey peak representing unstained control. Statistical significance was determined by an unpaired t -test relative to 0-h time point. C. Cell viability determined by crystal violet. MDA-MB-231 (top), HCC1806 (middle), and MCF-10A (bottom) cells treated with 10 μM 8VP101 for 24 h. Cells were fixed and stained with crystal violet, then solubilized and absorption values are normalized to vehicle control set as 100 %. Statistical significance was determined by an unpaired t -test. Data is presented as the mean±sem. ∗p ≤ 0.05; ∗∗p ≤ 0.005; ∗∗∗p ≤ 0.001; ∗∗∗∗p ≤ 0.0001; ns: not significant.

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1) Product Images from "Unravelling the anti-cancer mechanisms elicited by non-covalent thioredoxin reductase inhibitors for triple negative breast cancer therapy"

Article Title: Unravelling the anti-cancer mechanisms elicited by non-covalent thioredoxin reductase inhibitors for triple negative breast cancer therapy

Journal: Redox Biology

doi: 10.1016/j.redox.2025.103980

Figure Legend Snippet: TXNRD(i)s increase redox stress which do not correlate with cell viability. A. Gene set enrichment analysis of Oxidative Stress Response gene set by WikiPathways. NES and nominal p-value were determined by the GSEA software. B. Redox stress quantification using H 2 DCFDA by flow cytometry of MDA-MB-231 (top) (n = 2), HCC1806 (middle) (n = 3), and MCF-10A (bottom) (n = 3) cells. Cells were treated with 10 μM 8VP101 for 0, 2, 6,18, and 24 h, harvested and incubated with 1 μM H 2 DCFDA for 15 min. Representative histograms (left) of measured DCF mean fluorescence intensity (MFI) with the grey peak representing unstained control. Statistical significance was determined by an unpaired t -test relative to 0-h time point. C. Cell viability determined by crystal violet. MDA-MB-231 (top), HCC1806 (middle), and MCF-10A (bottom) cells treated with 10 μM 8VP101 for 24 h. Cells were fixed and stained with crystal violet, then solubilized and absorption values are normalized to vehicle control set as 100 %. Statistical significance was determined by an unpaired t -test. Data is presented as the mean±sem. ∗p ≤ 0.05; ∗∗p ≤ 0.005; ∗∗∗p ≤ 0.001; ∗∗∗∗p ≤ 0.0001; ns: not significant.

Techniques Used: Software, Flow Cytometry, Incubation, Fluorescence, Control, Staining

Treatment with TXNRD(i)s inhibits cells proliferation and disrupts cells cycle by inducing G1 arrest and reducing S phase . A. Gene set enrichment analysis of DNA Replication by Gene Ontology Biological Processes. NES and nominal p-value were determined by GSEA software. B. EdU incorporation assay by flow cytometry of MDA-MB-231 cells. Cells were treated with 4 μM or 10 μM 8VP101 for 24 h and loaded with 1 μM EdU for 3 h before harvest and analysis. Representative histograms of EdU incorporation are shown on the left. Statistical significance was determined by an unpaired t -test. C. Gene expression by RT-QPCR in MDA-MB-231 cells treated with 10 μM 8VP101 for 24 h. Relative gene expression is calculated using the ΔΔCt method normalized to β-actin. Statistical significance was determined by an unpaired t -test. D. Cell cycle analysis using PI by flow cytometry of MDA-MB-231 (top), HCC1806 (middle), and MCF-10A (bottom) cells. Cells were treated with 4 μM or 10 μM 8VP101 for 24 h. Statistical significance was determined by Kruskal-Wallis test followed by Dunns test. E. Protein levels of p21 assessed by western blot. MDA-MB-231 cells were treated with 10 μM 8VP101 for 6 h. β-actin was used as the loading control. Data is presented as the mean±sem. ∗p ≤ 0.05; ∗∗p ≤ 0.005; ∗∗∗p ≤ 0.001; ns: not significant.

Figure Legend Snippet: Treatment with TXNRD(i)s inhibits cells proliferation and disrupts cells cycle by inducing G1 arrest and reducing S phase . A. Gene set enrichment analysis of DNA Replication by Gene Ontology Biological Processes. NES and nominal p-value were determined by GSEA software. B. EdU incorporation assay by flow cytometry of MDA-MB-231 cells. Cells were treated with 4 μM or 10 μM 8VP101 for 24 h and loaded with 1 μM EdU for 3 h before harvest and analysis. Representative histograms of EdU incorporation are shown on the left. Statistical significance was determined by an unpaired t -test. C. Gene expression by RT-QPCR in MDA-MB-231 cells treated with 10 μM 8VP101 for 24 h. Relative gene expression is calculated using the ΔΔCt method normalized to β-actin. Statistical significance was determined by an unpaired t -test. D. Cell cycle analysis using PI by flow cytometry of MDA-MB-231 (top), HCC1806 (middle), and MCF-10A (bottom) cells. Cells were treated with 4 μM or 10 μM 8VP101 for 24 h. Statistical significance was determined by Kruskal-Wallis test followed by Dunns test. E. Protein levels of p21 assessed by western blot. MDA-MB-231 cells were treated with 10 μM 8VP101 for 6 h. β-actin was used as the loading control. Data is presented as the mean±sem. ∗p ≤ 0.05; ∗∗p ≤ 0.005; ∗∗∗p ≤ 0.001; ns: not significant.

Techniques Used: Software, Flow Cytometry, Gene Expression, Quantitative RT-PCR, Cell Cycle Assay, Western Blot, Control

TXNRD(i)s inhibit TXNRD1 and TXNRD2 enzymes and both enzymes are critical for growth of TNBC cells. A. HCC1806 cells were pretreated with 8VP101 or vehicle control for 1 h, then treated with 10 μM of TRFS-green for 4 h, followed by incubation with MitoTracker-red. Live cells were imaged on a Nikon Ti2E inverted microscope at 20x. Representative images shown. Cytosolic and mitochondrial TXNRD activity on average intensity per cell per field basis was quantified for 4 μM 8VP101 treatment. Average intensity was calculated from n = 3 biological replicates and n = 9 technical replicates. ∗∗∗∗p ≤ 0.0001. B. MDA-MB-231, HCC1806 and MCF-10A cells were transfected with siNeg, siTXNRD1, siTXNRD2, or both siTXNRD1 and siTXNRD2, 10 nM each, and monitored for cell growth every 12 h over 120 h using BioTek BioSpa. Data is shown as fold change normalized to the initial timepoint. Growth curves are averages −/+ sem from n = 3 biological replicates. End-point statistical significance was determined. ∗∗p ≤ 0.005; ∗∗∗p ≤ 0.001; ∗∗∗∗p ≤ 0.0001. C. MDA-MB-231 cells were treated with DMSO, 8VP101 or 9VP19 at 10 μM each and monitored for cells growth as in (B). End-point statistical significance was determined. ∗∗∗∗p ≤ 0.0001. D. Cell cycle analysis using PI by flow cytometry of MDA-MB-231 cells. Cells were transfected with 10 nM siTXNRD1, 10 nM siTXNRD2, or a combination of 10 nM siTXNRD1 and 10 nM siTXNRD2 for 24 h. Statistical significance was determined by Kruskal-Wallis test followed by Dunns test comparing siTXNRD1, siTXNRD2, and both siTXNRD1 and siTXNRD2 to siNeg control. Data is presented as the mean±sem. ∗p ≤ 0.05; ns: not significant.

Figure Legend Snippet: TXNRD(i)s inhibit TXNRD1 and TXNRD2 enzymes and both enzymes are critical for growth of TNBC cells. A. HCC1806 cells were pretreated with 8VP101 or vehicle control for 1 h, then treated with 10 μM of TRFS-green for 4 h, followed by incubation with MitoTracker-red. Live cells were imaged on a Nikon Ti2E inverted microscope at 20x. Representative images shown. Cytosolic and mitochondrial TXNRD activity on average intensity per cell per field basis was quantified for 4 μM 8VP101 treatment. Average intensity was calculated from n = 3 biological replicates and n = 9 technical replicates. ∗∗∗∗p ≤ 0.0001. B. MDA-MB-231, HCC1806 and MCF-10A cells were transfected with siNeg, siTXNRD1, siTXNRD2, or both siTXNRD1 and siTXNRD2, 10 nM each, and monitored for cell growth every 12 h over 120 h using BioTek BioSpa. Data is shown as fold change normalized to the initial timepoint. Growth curves are averages −/+ sem from n = 3 biological replicates. End-point statistical significance was determined. ∗∗p ≤ 0.005; ∗∗∗p ≤ 0.001; ∗∗∗∗p ≤ 0.0001. C. MDA-MB-231 cells were treated with DMSO, 8VP101 or 9VP19 at 10 μM each and monitored for cells growth as in (B). End-point statistical significance was determined. ∗∗∗∗p ≤ 0.0001. D. Cell cycle analysis using PI by flow cytometry of MDA-MB-231 cells. Cells were transfected with 10 nM siTXNRD1, 10 nM siTXNRD2, or a combination of 10 nM siTXNRD1 and 10 nM siTXNRD2 for 24 h. Statistical significance was determined by Kruskal-Wallis test followed by Dunns test comparing siTXNRD1, siTXNRD2, and both siTXNRD1 and siTXNRD2 to siNeg control. Data is presented as the mean±sem. ∗p ≤ 0.05; ns: not significant.

Techniques Used: Control, Incubation, Inverted Microscopy, Activity Assay, Transfection, Cell Cycle Assay, Flow Cytometry

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Journal: Redox Biology

Article Title: Unravelling the anti-cancer mechanisms elicited by non-covalent thioredoxin reductase inhibitors for triple negative breast cancer therapy

doi: 10.1016/j.redox.2025.103980

Figure Lengend Snippet: TXNRD(i)s increase redox stress which do not correlate with cell viability. A. Gene set enrichment analysis of Oxidative Stress Response gene set by WikiPathways. NES and nominal p-value were determined by the GSEA software. B. Redox stress quantification using H 2 DCFDA by flow cytometry of MDA-MB-231 (top) (n = 2), HCC1806 (middle) (n = 3), and MCF-10A (bottom) (n = 3) cells. Cells were treated with 10 μM 8VP101 for 0, 2, 6,18, and 24 h, harvested and incubated with 1 μM H 2 DCFDA for 15 min. Representative histograms (left) of measured DCF mean fluorescence intensity (MFI) with the grey peak representing unstained control. Statistical significance was determined by an unpaired t -test relative to 0-h time point. C. Cell viability determined by crystal violet. MDA-MB-231 (top), HCC1806 (middle), and MCF-10A (bottom) cells treated with 10 μM 8VP101 for 24 h. Cells were fixed and stained with crystal violet, then solubilized and absorption values are normalized to vehicle control set as 100 %. Statistical significance was determined by an unpaired t -test. Data is presented as the mean±sem. ∗p ≤ 0.05; ∗∗p ≤ 0.005; ∗∗∗p ≤ 0.001; ∗∗∗∗p ≤ 0.0001; ns: not significant.

Article Snippet: MCF-10A cells were obtained from ATCC and maintained in DMEM-F12 medium (Gibco, 11330032) supplemented with 10 % fetal bovine serum, 20 ng/mL epithelial growth factor, 0.5 mg/mL hydrocortisone, 100 ng/mL cholera toxin, and 10 μg/mL insulin.

Techniques: Software, Flow Cytometry, Incubation, Fluorescence, Control, Staining

Journal: Redox Biology

Article Title: Unravelling the anti-cancer mechanisms elicited by non-covalent thioredoxin reductase inhibitors for triple negative breast cancer therapy

doi: 10.1016/j.redox.2025.103980

Figure Lengend Snippet: Treatment with TXNRD(i)s inhibits cells proliferation and disrupts cells cycle by inducing G1 arrest and reducing S phase . A. Gene set enrichment analysis of DNA Replication by Gene Ontology Biological Processes. NES and nominal p-value were determined by GSEA software. B. EdU incorporation assay by flow cytometry of MDA-MB-231 cells. Cells were treated with 4 μM or 10 μM 8VP101 for 24 h and loaded with 1 μM EdU for 3 h before harvest and analysis. Representative histograms of EdU incorporation are shown on the left. Statistical significance was determined by an unpaired t -test. C. Gene expression by RT-QPCR in MDA-MB-231 cells treated with 10 μM 8VP101 for 24 h. Relative gene expression is calculated using the ΔΔCt method normalized to β-actin. Statistical significance was determined by an unpaired t -test. D. Cell cycle analysis using PI by flow cytometry of MDA-MB-231 (top), HCC1806 (middle), and MCF-10A (bottom) cells. Cells were treated with 4 μM or 10 μM 8VP101 for 24 h. Statistical significance was determined by Kruskal-Wallis test followed by Dunns test. E. Protein levels of p21 assessed by western blot. MDA-MB-231 cells were treated with 10 μM 8VP101 for 6 h. β-actin was used as the loading control. Data is presented as the mean±sem. ∗p ≤ 0.05; ∗∗p ≤ 0.005; ∗∗∗p ≤ 0.001; ns: not significant.

Techniques: Software, Flow Cytometry, Gene Expression, Quantitative RT-PCR, Cell Cycle Assay, Western Blot, Control

Journal: Redox Biology

Article Title: Unravelling the anti-cancer mechanisms elicited by non-covalent thioredoxin reductase inhibitors for triple negative breast cancer therapy

doi: 10.1016/j.redox.2025.103980

Figure Lengend Snippet: TXNRD(i)s inhibit TXNRD1 and TXNRD2 enzymes and both enzymes are critical for growth of TNBC cells. A. HCC1806 cells were pretreated with 8VP101 or vehicle control for 1 h, then treated with 10 μM of TRFS-green for 4 h, followed by incubation with MitoTracker-red. Live cells were imaged on a Nikon Ti2E inverted microscope at 20x. Representative images shown. Cytosolic and mitochondrial TXNRD activity on average intensity per cell per field basis was quantified for 4 μM 8VP101 treatment. Average intensity was calculated from n = 3 biological replicates and n = 9 technical replicates. ∗∗∗∗p ≤ 0.0001. B. MDA-MB-231, HCC1806 and MCF-10A cells were transfected with siNeg, siTXNRD1, siTXNRD2, or both siTXNRD1 and siTXNRD2, 10 nM each, and monitored for cell growth every 12 h over 120 h using BioTek BioSpa. Data is shown as fold change normalized to the initial timepoint. Growth curves are averages −/+ sem from n = 3 biological replicates. End-point statistical significance was determined. ∗∗p ≤ 0.005; ∗∗∗p ≤ 0.001; ∗∗∗∗p ≤ 0.0001. C. MDA-MB-231 cells were treated with DMSO, 8VP101 or 9VP19 at 10 μM each and monitored for cells growth as in (B). End-point statistical significance was determined. ∗∗∗∗p ≤ 0.0001. D. Cell cycle analysis using PI by flow cytometry of MDA-MB-231 cells. Cells were transfected with 10 nM siTXNRD1, 10 nM siTXNRD2, or a combination of 10 nM siTXNRD1 and 10 nM siTXNRD2 for 24 h. Statistical significance was determined by Kruskal-Wallis test followed by Dunns test comparing siTXNRD1, siTXNRD2, and both siTXNRD1 and siTXNRD2 to siNeg control. Data is presented as the mean±sem. ∗p ≤ 0.05; ns: not significant.

Techniques: Control, Incubation, Inverted Microscopy, Activity Assay, Transfection, Cell Cycle Assay, Flow Cytometry

siSPRR3 depletion results in a reduction in the number of nucleoli per nucleus in MCF10A cells. A , siSPRR3 depletion with siGENOME siRNAs reduces the number of nucleoli per nucleus. Images and histograms from a genome-wide screen using Dharmacon/Horizon siGENOME siRNAs . The images show nuclei (Hoechst, blue ) and nucleoli (anti-fibrillarin, red ) after 72 h of treatment with the negative control (siGFP), positive control (siUTP4), or siSPRR3 siRNAs. Histograms show the distribution of cells that have the indicated number of nucleoli per nucleus. Light grey shows the distribution for the negative control, black shows the test condition, and dark grey shows overlap of the two frequencies. B , siSPRR3 depletion with siON-TARGET (siONT) SMARTPool siRNA reduces the number of nucleoli per nucleus. The images show nuclei and nucleoli after 72 h of treatment with the negative control (non-targeting siRNA, siNT), positive control (siUTP4), or siSPRR3 siRNAs. The shading in the histograms is as in A ). The data were collected across four replicates which are pooled in the histogram. C , siSPRR3 depletion with individual siONT SMARTPool siRNAs (deconvolution) reduces the number of nucleoli per nucleus. The images show nuclei and nucleoli after 72 h of treatment with the negative control (siNT), positive control (siNOL11), or representative siSPRR3 individual siRNAs (SPRR3-si1 and SPRR3-si2). The shading in the histograms is as in ( A ). The histograms include all three replicates pooled. The table summarizes each of four individual siONT SMARTPool siRNAs, showing that a reduction in nucleolar number correlates with a loss in cell viability. D , siSPRR3 (custom subpool of SPRR3-si1 and SPRR3-si2) reduces SPRR3 mRNA levels in MCF10A cells. RT-qPCR data of SPRR3 mRNA demonstrating knockdown after 72 h. The data were normalized to 7SL RNA abundance, then to siNT for comparison using the ΔΔC T method. The mean ± SEM are shown alongside individual data points, colored by replicate. E , siSPRR3 (custom subpool of SPRR3-si1 and SPRR3-si2) reduces SPRR3 protein levels in MCF10A cells. Western blot of SPRR3 protein demonstrating decreased levels after 72 h. Protein levels were normalized to total protein (trichloroethanol total protein stain), then to siNT. The mean ± SEM are shown alongside individual data points, colored by replicate. This sample was run on the same Western blot as in . After imaging total protein on the membrane, the blot was cut between 10 to 15 kD markers to stain separately for SPRR3 ( E , above) or RPS28 . Data in ( D and E ) were analyzed by unpaired two-sided Welch's t -tests in GraphPad Prism. ∗, p < 0.05; ∗∗∗, p < 0.001.

Journal: The Journal of Biological Chemistry

Article Title: A high-throughput screen for nucleolar function reveals a role for the signaling protein, SPRR3, in ribosome biogenesis

doi: 10.1016/j.jbc.2026.111132

Figure Lengend Snippet: siSPRR3 depletion results in a reduction in the number of nucleoli per nucleus in MCF10A cells. A , siSPRR3 depletion with siGENOME siRNAs reduces the number of nucleoli per nucleus. Images and histograms from a genome-wide screen using Dharmacon/Horizon siGENOME siRNAs . The images show nuclei (Hoechst, blue ) and nucleoli (anti-fibrillarin, red ) after 72 h of treatment with the negative control (siGFP), positive control (siUTP4), or siSPRR3 siRNAs. Histograms show the distribution of cells that have the indicated number of nucleoli per nucleus. Light grey shows the distribution for the negative control, black shows the test condition, and dark grey shows overlap of the two frequencies. B , siSPRR3 depletion with siON-TARGET (siONT) SMARTPool siRNA reduces the number of nucleoli per nucleus. The images show nuclei and nucleoli after 72 h of treatment with the negative control (non-targeting siRNA, siNT), positive control (siUTP4), or siSPRR3 siRNAs. The shading in the histograms is as in A ). The data were collected across four replicates which are pooled in the histogram. C , siSPRR3 depletion with individual siONT SMARTPool siRNAs (deconvolution) reduces the number of nucleoli per nucleus. The images show nuclei and nucleoli after 72 h of treatment with the negative control (siNT), positive control (siNOL11), or representative siSPRR3 individual siRNAs (SPRR3-si1 and SPRR3-si2). The shading in the histograms is as in ( A ). The histograms include all three replicates pooled. The table summarizes each of four individual siONT SMARTPool siRNAs, showing that a reduction in nucleolar number correlates with a loss in cell viability. D , siSPRR3 (custom subpool of SPRR3-si1 and SPRR3-si2) reduces SPRR3 mRNA levels in MCF10A cells. RT-qPCR data of SPRR3 mRNA demonstrating knockdown after 72 h. The data were normalized to 7SL RNA abundance, then to siNT for comparison using the ΔΔC T method. The mean ± SEM are shown alongside individual data points, colored by replicate. E , siSPRR3 (custom subpool of SPRR3-si1 and SPRR3-si2) reduces SPRR3 protein levels in MCF10A cells. Western blot of SPRR3 protein demonstrating decreased levels after 72 h. Protein levels were normalized to total protein (trichloroethanol total protein stain), then to siNT. The mean ± SEM are shown alongside individual data points, colored by replicate. This sample was run on the same Western blot as in . After imaging total protein on the membrane, the blot was cut between 10 to 15 kD markers to stain separately for SPRR3 ( E , above) or RPS28 . Data in ( D and E ) were analyzed by unpaired two-sided Welch's t -tests in GraphPad Prism. ∗, p < 0.05; ∗∗∗, p < 0.001.

Article Snippet: Human MCF10A breast epithelial cells (#CRL-10317, American Type Culture Collection) were cultured in DMEM/nutrient mixture F-12 (Gibco 11330032) with 5% horse serum (Gibco 16050122), 20 ng/ml epidermal growth factor (Peprotech AF1005), 0.5 μg/ml hydrocortisone (MilliporeSigma H0135), 100 ng/ml cholera toxin (MilliporeSigma C8052), and 10 μg/ml insulin (MilliporeSigma I1882).

Techniques: Genome Wide, Negative Control, Positive Control, Quantitative RT-PCR, Knockdown, Comparison, Western Blot, Staining, Imaging, Membrane

SPRR3 depletion reduces pre-rRNA transcription. A , schematic of the major steps in ribosome biogenesis in human cells. B , SPRR3 depletion inhibits nucleolar rRNA biogenesis. Representative images and quantification of control or SPRR3-depleted MCF10A cells (siONT SMARTpool) following anti-fibrillarin (FBL) staining and 5-EU incorporation. Scale bars are 10 μm. siNT is a non-targeting negative control siRNA. siPOLR1A is a positive control targeting the RNAPI subunit, POLR1A. The overall mean percent inhibition ± SEM is shown for each treatment, with each dot representing one well. Each well in the siSPRR3 condition represents a separate day of testing and control datapoints are distributed across the three testing days. 0% inhibition is determined by the mean value of siNT, and 100% inhibition is set to the mean value of the siPOLR1A positive control. C , RT-qPCR analysis shows decreased 47S/45S pre-rRNA levels upon SPRR3 depletion in MCF10A cells. The mean ± SEM are shown alongside individual data points, colored by replicate. The data were normalized to 7SL RNA abundance, then to siNT for comparison using the ΔΔC T method. D , dual-luciferase reporter assay shows RNAPI promoter activity is reduced after SPRR3 depletion. The mean ± SEM are shown alongside individual data points, colored by replicate. The controls in these data have also been published in , without the inclusion of siSPRR3. All the data in this figure were analyzed by ordinary one-way ANOVA with multiple comparisons against siNT and Holm-Šídák correction in GraphPad Prism. ∗, p < 0.05; ∗∗, p < 0.01; ∗∗∗, p < 0.001.

Journal: The Journal of Biological Chemistry

Article Title: A high-throughput screen for nucleolar function reveals a role for the signaling protein, SPRR3, in ribosome biogenesis

doi: 10.1016/j.jbc.2026.111132

Figure Lengend Snippet: SPRR3 depletion reduces pre-rRNA transcription. A , schematic of the major steps in ribosome biogenesis in human cells. B , SPRR3 depletion inhibits nucleolar rRNA biogenesis. Representative images and quantification of control or SPRR3-depleted MCF10A cells (siONT SMARTpool) following anti-fibrillarin (FBL) staining and 5-EU incorporation. Scale bars are 10 μm. siNT is a non-targeting negative control siRNA. siPOLR1A is a positive control targeting the RNAPI subunit, POLR1A. The overall mean percent inhibition ± SEM is shown for each treatment, with each dot representing one well. Each well in the siSPRR3 condition represents a separate day of testing and control datapoints are distributed across the three testing days. 0% inhibition is determined by the mean value of siNT, and 100% inhibition is set to the mean value of the siPOLR1A positive control. C , RT-qPCR analysis shows decreased 47S/45S pre-rRNA levels upon SPRR3 depletion in MCF10A cells. The mean ± SEM are shown alongside individual data points, colored by replicate. The data were normalized to 7SL RNA abundance, then to siNT for comparison using the ΔΔC T method. D , dual-luciferase reporter assay shows RNAPI promoter activity is reduced after SPRR3 depletion. The mean ± SEM are shown alongside individual data points, colored by replicate. The controls in these data have also been published in , without the inclusion of siSPRR3. All the data in this figure were analyzed by ordinary one-way ANOVA with multiple comparisons against siNT and Holm-Šídák correction in GraphPad Prism. ∗, p < 0.05; ∗∗, p < 0.01; ∗∗∗, p < 0.001.

Techniques: Control, Staining, Negative Control, Positive Control, Inhibition, Quantitative RT-PCR, Comparison, Luciferase, Reporter Assay, Activity Assay

SPRR3 depletion causes reduced global translation (protein synthesis). A , representative image and quantification of puromycin incorporation shows reduced translation after SPRR3 depletion in MCF10A cells. α-puromycin shows puromycin incorporation as a proxy for global protein synthesis. Total protein is the trichloroethanol total protein stain loading control. Images were quantified with Bio-Rad Image Lab. The mean ± SEM are shown alongside individual data points, colored by replicate. siRPL4 is the positive control. Data were normalized to a non-targeting siRNA (siNT), then graphed and analyzed by ordinary one-way ANOVA with multiple comparisons against siNT and Holm-Šídák correction in GraphPad Prism. ∗∗∗, p < 0.001. The control data in this puromycin Western blot have also been published in without the SPRR3 data. B , summary table describing the effects of SPRR3 depletion on ribosome biogenesis and the nucleolus. SPRR3 depletion reduces nucleolar number, nucleolar rRNA biogenesis (5-EU incorporation assay), pre-rRNA transcript levels (RT-qPCR of 47S/45S rRNA), rDNA promoter activity (luciferase reporter assay), and global protein synthesis (puromycin incorporation assay). SPRR3 depletion was found to have no effect on the ratio of 18S to 28S rRNA nor to produce changes in pre-rRNA northern blots, indicating that SPRR3 does not affect rRNA processing. Taken together, this suggests that SPRR3 plays a role in pre-rRNA transcription and nucleolar rRNA biogenesis that is essential to the normal translational activity of ribosomes.

Journal: The Journal of Biological Chemistry

Article Title: A high-throughput screen for nucleolar function reveals a role for the signaling protein, SPRR3, in ribosome biogenesis

doi: 10.1016/j.jbc.2026.111132

Figure Lengend Snippet: SPRR3 depletion causes reduced global translation (protein synthesis). A , representative image and quantification of puromycin incorporation shows reduced translation after SPRR3 depletion in MCF10A cells. α-puromycin shows puromycin incorporation as a proxy for global protein synthesis. Total protein is the trichloroethanol total protein stain loading control. Images were quantified with Bio-Rad Image Lab. The mean ± SEM are shown alongside individual data points, colored by replicate. siRPL4 is the positive control. Data were normalized to a non-targeting siRNA (siNT), then graphed and analyzed by ordinary one-way ANOVA with multiple comparisons against siNT and Holm-Šídák correction in GraphPad Prism. ∗∗∗, p < 0.001. The control data in this puromycin Western blot have also been published in without the SPRR3 data. B , summary table describing the effects of SPRR3 depletion on ribosome biogenesis and the nucleolus. SPRR3 depletion reduces nucleolar number, nucleolar rRNA biogenesis (5-EU incorporation assay), pre-rRNA transcript levels (RT-qPCR of 47S/45S rRNA), rDNA promoter activity (luciferase reporter assay), and global protein synthesis (puromycin incorporation assay). SPRR3 depletion was found to have no effect on the ratio of 18S to 28S rRNA nor to produce changes in pre-rRNA northern blots, indicating that SPRR3 does not affect rRNA processing. Taken together, this suggests that SPRR3 plays a role in pre-rRNA transcription and nucleolar rRNA biogenesis that is essential to the normal translational activity of ribosomes.

Techniques: Staining, Control, Positive Control, Western Blot, Quantitative RT-PCR, Activity Assay, Luciferase, Reporter Assay, Northern Blot

SPRR3 depletion causes the nucleolar stress response in MCF10A and A549 cells. A , schematic of the nucleolar stress response in human cells. Disruption of ribosome biogenesis causes accumulation of free 5S RNP which inhibits the ubiquitin ligase MDM2, leading to accumulation of TP53 and increased transcription of CDKN1A . B , TP53 stabilization after SPRR3 depletion in MCF10A cells. Representative images and quantification of TP53 Western blots after 72h of treatment with siSPRR3. siNOL11 was used as a positive control. TP53 levels were normalized to total protein (trichloroethanol stain), then siNT. C , CDKN1A mRNA levels are elevated after SPRR3 depletion in MCF10A cells. After 72 h of siSPRR3 treatment, CDKN1A mRNA transcript levels were detected with RT-qPCR using primers for CDKN1A mRNA. siNOL11 was used as a positive control. These data were normalized to 7SL RNA abundance, then to siNT for comparison using the ΔΔC T method. D , siSPRR3 reduces SPRR3 mRNA levels in A549 cells. After 72 h of siSPRR3 treatment, SPRR3 transcript levels were detected by RT-qPCR. The data were normalized as in ( C ). E , siSPRR3 reduces SPRR3 protein levels in A549 cells. After 72 h of treatment with siSPRR3, SPRR3 protein levels were detected by Western blot. SPRR3 levels were normalized as in ( B ). F , SPRR3 depletion lowers 47S/45S pre-rRNA levels in A549 cells. Primers to the 5′ ETS of the 47S/45S rRNA were used to detect pre-rRNA levels after 72h of treatment with siSPRR3. siNOL11 was used as a positive control. The data were normalized as in ( C and D ). G , TP53 stabilization after SPRR3 knockdown in A549 cells. Representative images and quantification of TP53 Western blots after 48h or 72h of treatment with siSPRR3 are shown. Protein levels were normalized as in ( B and E ). H , CDKN1A levels are elevated after SPRR3 depletion in A549 cells. After 72 h of treatment with siSPRR3, CDKN1A transcript levels were detected with RT-qPCR using primers for CDKN1A mRNA. siNOL11 was used as a positive control. Data were normalized as in ( C ). The mean ± SEM are shown alongside individual data points. For graphs with two conditions, data were analyzed by unpaired two-sided Welch's t -tests in GraphPad Prism. For graphs with more than two conditions, data were analyzed by ordinary one-way ANOVA with multiple comparisons against siNT and Holm-Šídák correction in GraphPad Prism. ∗, p < 0.05; ∗∗, p < 0.01; ∗∗∗, p < 0.001.

Journal: The Journal of Biological Chemistry

Article Title: A high-throughput screen for nucleolar function reveals a role for the signaling protein, SPRR3, in ribosome biogenesis

doi: 10.1016/j.jbc.2026.111132

Figure Lengend Snippet: SPRR3 depletion causes the nucleolar stress response in MCF10A and A549 cells. A , schematic of the nucleolar stress response in human cells. Disruption of ribosome biogenesis causes accumulation of free 5S RNP which inhibits the ubiquitin ligase MDM2, leading to accumulation of TP53 and increased transcription of CDKN1A . B , TP53 stabilization after SPRR3 depletion in MCF10A cells. Representative images and quantification of TP53 Western blots after 72h of treatment with siSPRR3. siNOL11 was used as a positive control. TP53 levels were normalized to total protein (trichloroethanol stain), then siNT. C , CDKN1A mRNA levels are elevated after SPRR3 depletion in MCF10A cells. After 72 h of siSPRR3 treatment, CDKN1A mRNA transcript levels were detected with RT-qPCR using primers for CDKN1A mRNA. siNOL11 was used as a positive control. These data were normalized to 7SL RNA abundance, then to siNT for comparison using the ΔΔC T method. D , siSPRR3 reduces SPRR3 mRNA levels in A549 cells. After 72 h of siSPRR3 treatment, SPRR3 transcript levels were detected by RT-qPCR. The data were normalized as in ( C ). E , siSPRR3 reduces SPRR3 protein levels in A549 cells. After 72 h of treatment with siSPRR3, SPRR3 protein levels were detected by Western blot. SPRR3 levels were normalized as in ( B ). F , SPRR3 depletion lowers 47S/45S pre-rRNA levels in A549 cells. Primers to the 5′ ETS of the 47S/45S rRNA were used to detect pre-rRNA levels after 72h of treatment with siSPRR3. siNOL11 was used as a positive control. The data were normalized as in ( C and D ). G , TP53 stabilization after SPRR3 knockdown in A549 cells. Representative images and quantification of TP53 Western blots after 48h or 72h of treatment with siSPRR3 are shown. Protein levels were normalized as in ( B and E ). H , CDKN1A levels are elevated after SPRR3 depletion in A549 cells. After 72 h of treatment with siSPRR3, CDKN1A transcript levels were detected with RT-qPCR using primers for CDKN1A mRNA. siNOL11 was used as a positive control. Data were normalized as in ( C ). The mean ± SEM are shown alongside individual data points. For graphs with two conditions, data were analyzed by unpaired two-sided Welch's t -tests in GraphPad Prism. For graphs with more than two conditions, data were analyzed by ordinary one-way ANOVA with multiple comparisons against siNT and Holm-Šídák correction in GraphPad Prism. ∗, p < 0.05; ∗∗, p < 0.01; ∗∗∗, p < 0.001.

Techniques: Disruption, Ubiquitin Proteomics, Western Blot, Positive Control, Staining, Quantitative RT-PCR, Comparison, Knockdown

SPRR3 drives AKT phosphorylation and maintains POLR1A levels. A , AKT phosphorylation at serine 473 (pAKT) is decreased after a 72h SPRR3 depletion in MCF10A cells. Representative images and quantification are shown for pAKT, total AKT, and total protein (measured by trichloroethanol stain). Blots were probed for pAKT, then stripped and re-probed for total AKT. Signal was measured in Bio-Rad Image Lab. pAKT levels were normalized to total protein and total AKT. Total AKT was normalized to total protein, ensuring no significant difference in overall AKT levels upon SPRR3 depletion. B , phosphorylated AKT (pAKT) levels are decreased after 72h SPRR3 depletion in A549 cells. Representative images and quantification are shown for pAKT, total AKT, and total protein (measured by trichloroethanol stain). C , POLR1A levels are decreased upon 72h SPRR3 depletion. Representative image of Western blotting and quantification of POLR1A levels in MCF10A cells. siPOLR1A was used as a positive control. D , summary of effects of siSPRR3 depletion that we have confirmed in both MCF10A cells and A549 cells. For all graphs in this figure, the mean ± SEM are shown alongside individual data points. Data were analyzed by unpaired two-sided Welch's t -tests in GraphPad Prism. ∗, p < 0.05; ∗∗, p < 0.01; ∗∗∗, p < 0.001; ns, not significant.

Journal: The Journal of Biological Chemistry

Article Title: A high-throughput screen for nucleolar function reveals a role for the signaling protein, SPRR3, in ribosome biogenesis

doi: 10.1016/j.jbc.2026.111132

Figure Lengend Snippet: SPRR3 drives AKT phosphorylation and maintains POLR1A levels. A , AKT phosphorylation at serine 473 (pAKT) is decreased after a 72h SPRR3 depletion in MCF10A cells. Representative images and quantification are shown for pAKT, total AKT, and total protein (measured by trichloroethanol stain). Blots were probed for pAKT, then stripped and re-probed for total AKT. Signal was measured in Bio-Rad Image Lab. pAKT levels were normalized to total protein and total AKT. Total AKT was normalized to total protein, ensuring no significant difference in overall AKT levels upon SPRR3 depletion. B , phosphorylated AKT (pAKT) levels are decreased after 72h SPRR3 depletion in A549 cells. Representative images and quantification are shown for pAKT, total AKT, and total protein (measured by trichloroethanol stain). C , POLR1A levels are decreased upon 72h SPRR3 depletion. Representative image of Western blotting and quantification of POLR1A levels in MCF10A cells. siPOLR1A was used as a positive control. D , summary of effects of siSPRR3 depletion that we have confirmed in both MCF10A cells and A549 cells. For all graphs in this figure, the mean ± SEM are shown alongside individual data points. Data were analyzed by unpaired two-sided Welch's t -tests in GraphPad Prism. ∗, p < 0.05; ∗∗, p < 0.01; ∗∗∗, p < 0.001; ns, not significant.

Techniques: Phospho-proteomics, Staining, Western Blot, Positive Control

A. Left, Relative activation of MNRR1 -promoter harboring luciferase reporter is higher in the breast cancer line HTB126 cells as compared to the isogenic control line HTB125 cells (n=6, **p<0.01). Right, MNRR1 protein levels are higher in cells as compared to HTB125 cells analyzed using western blot. GAPDH was probed as loading control. B. Basal mitochondrial oxygen consumption in cells is higher than HTB125 cells (n=10, **<0.01). C. Transcript levels of endogenous MNRR1 are higher in 231 and 468 cells as compared to 10A cells (n=6, *p<0.05 for 231, **p<0.01 for 468 compared to 10A, # p<0.01 comparing 231 vs 468). Actin was used as housekeeping gene in RT-qPCR analysis. D. Left, MNRR1 protein levels are higher in in 231 and 468 cells as compared to 10A cells analyzed using western blot. Actin was probed as loading control. Right, quantitation of MNRR1 protein levels in MCF10A, 231, and 468 cells (n=5, **p<0.01 for 231 and 468 compared to 10A, # p<0.01 comparing 231 vs 468). E. Basal mitochondrial oxygen consumption in cells is higher than MCF10A (n=at least 8, **p<0.01 for 231 and 468 compared to 10A, # p<0.01 comparing 231 vs 468).

Journal: bioRxiv

Article Title: MNRR1 is required for Triple Negative Breast Cancer growth and metastasis and can be targeted by repurposed drugs

doi: 10.64898/2026.01.31.703055

Figure Lengend Snippet: A. Left, Relative activation of MNRR1 -promoter harboring luciferase reporter is higher in the breast cancer line HTB126 cells as compared to the isogenic control line HTB125 cells (n=6, **p<0.01). Right, MNRR1 protein levels are higher in cells as compared to HTB125 cells analyzed using western blot. GAPDH was probed as loading control. B. Basal mitochondrial oxygen consumption in cells is higher than HTB125 cells (n=10, **<0.01). C. Transcript levels of endogenous MNRR1 are higher in 231 and 468 cells as compared to 10A cells (n=6, *p<0.05 for 231, **p<0.01 for 468 compared to 10A, # p<0.01 comparing 231 vs 468). Actin was used as housekeeping gene in RT-qPCR analysis. D. Left, MNRR1 protein levels are higher in in 231 and 468 cells as compared to 10A cells analyzed using western blot. Actin was probed as loading control. Right, quantitation of MNRR1 protein levels in MCF10A, 231, and 468 cells (n=5, **p<0.01 for 231 and 468 compared to 10A, # p<0.01 comparing 231 vs 468). E. Basal mitochondrial oxygen consumption in cells is higher than MCF10A (n=at least 8, **p<0.01 for 231 and 468 compared to 10A, # p<0.01 comparing 231 vs 468).

Article Snippet: The HTB125, HTB126, and MCF10A (10A) cells were purchased from ATCC (Manassas, VA, USA) and were grown in ATCC recommended media.

Techniques: Activation Assay, Luciferase, Control, Western Blot, Quantitative RT-PCR, Quantitation Assay

S1A. Protein levels of MNRR1 are higher in HTB126 (breast cancer line) vs HTB125 (isogenic control) cells detected via immunofluorescent staining. DAPI was used to indicate cellular nuclei. Cells were imaged at 60x, and scale bar represents 50μm. S1B. Protein levels of MNRR1 are higher in 231 and 468 (breast cancer lines) vs 10A (normal breast cell line) cells, detected via immunofluorescent staining. DAPI was used to indicate cellular nuclei. Cells were imaged at 60x, and scale bar represents 50μm. S1C. Overview of the high-throughput screening process to identify inhibitors of MNRR1 using the inverted pyramid approach. S1D. Protein levels of MNRR1 are reduced in 468 cells treated with increasing concentrations of MNRR1 inhibitor as analyzed via western blot. GAPDH was probed as loading control. S1E. Level of EMT marker vimentin is reduced in 468 cells overexpressing transcriptionally defective MNRR1 (TD-R1) compared to empty vector (EV). MNRR1 was probed to confirm overexpression and GAPDH was probed as loading control. S1F. Mesenchymal marker N-cadherin is reduced in MNRR1-knockdown (R1-KD) 468 cells as analyzed via western blot. MNRR1 was probed to confirm knockdown, and tubulin was probed as loading control. S1G. ZO-1 levels are increased, and Snail levels are reduced in 231 cells overexpressing transcriptionally defective MNRR1 (TD-R1) compared to empty vector (EV). MNRR1 was probed to confirm overexpression, and Actin was probed as loading control.

Journal: bioRxiv

Article Title: MNRR1 is required for Triple Negative Breast Cancer growth and metastasis and can be targeted by repurposed drugs

doi: 10.64898/2026.01.31.703055

Figure Lengend Snippet: S1A. Protein levels of MNRR1 are higher in HTB126 (breast cancer line) vs HTB125 (isogenic control) cells detected via immunofluorescent staining. DAPI was used to indicate cellular nuclei. Cells were imaged at 60x, and scale bar represents 50μm. S1B. Protein levels of MNRR1 are higher in 231 and 468 (breast cancer lines) vs 10A (normal breast cell line) cells, detected via immunofluorescent staining. DAPI was used to indicate cellular nuclei. Cells were imaged at 60x, and scale bar represents 50μm. S1C. Overview of the high-throughput screening process to identify inhibitors of MNRR1 using the inverted pyramid approach. S1D. Protein levels of MNRR1 are reduced in 468 cells treated with increasing concentrations of MNRR1 inhibitor as analyzed via western blot. GAPDH was probed as loading control. S1E. Level of EMT marker vimentin is reduced in 468 cells overexpressing transcriptionally defective MNRR1 (TD-R1) compared to empty vector (EV). MNRR1 was probed to confirm overexpression and GAPDH was probed as loading control. S1F. Mesenchymal marker N-cadherin is reduced in MNRR1-knockdown (R1-KD) 468 cells as analyzed via western blot. MNRR1 was probed to confirm knockdown, and tubulin was probed as loading control. S1G. ZO-1 levels are increased, and Snail levels are reduced in 231 cells overexpressing transcriptionally defective MNRR1 (TD-R1) compared to empty vector (EV). MNRR1 was probed to confirm overexpression, and Actin was probed as loading control.

Article Snippet: The HTB125, HTB126, and MCF10A (10A) cells were purchased from ATCC (Manassas, VA, USA) and were grown in ATCC recommended media.

Techniques: Control, Staining, High Throughput Screening Assay, Western Blot, Marker, Plasmid Preparation, Over Expression, Knockdown

A. Left, Cell growth of 10A overexpressing MNRR1 is higher that empty vector (EV) overexpressing cells measured using RealTime-Glo™ luminescence assay over 72 hrs (n=5, **p<0.01). Right, Western blot to confirm overexpression of MNRR1 in MCF10A cells. Actin was probed as loading control. B. Cell growth is inversely proportional to increasing concentrations of MNRR1 inhibitor (R1i, lovastatin) in 231 cells treated for 36 h (n= 8, *p<0.05, **p<0.001). C. MNRR1 protein levels are reduced in 231 cells treated with increasing concentrations of R1i (Lovastatin) as confirmed via western blot. GAPDH was probed as loading control. D. 231 cells overexpressing MNRR1 show increased capacity to form mammospheres. Left, representative image of mammospheres. Cells were imaged at 4X, and scale bar represents 100μM. Middle, graph depicting the number of mammospheres formed in MNRR1 overexpressing cells as compared to EV overexpressing cells (n=16, *p<0.05). Right, western blot confirming that markers of mammosphere formation ALDH1A1 and CD44 are higher in the MNRR1 overexpressing cells. GAPDH was probed as loading control.

Journal: bioRxiv

Article Title: MNRR1 is required for Triple Negative Breast Cancer growth and metastasis and can be targeted by repurposed drugs

doi: 10.64898/2026.01.31.703055

Figure Lengend Snippet: A. Left, Cell growth of 10A overexpressing MNRR1 is higher that empty vector (EV) overexpressing cells measured using RealTime-Glo™ luminescence assay over 72 hrs (n=5, **p<0.01). Right, Western blot to confirm overexpression of MNRR1 in MCF10A cells. Actin was probed as loading control. B. Cell growth is inversely proportional to increasing concentrations of MNRR1 inhibitor (R1i, lovastatin) in 231 cells treated for 36 h (n= 8, *p<0.05, **p<0.001). C. MNRR1 protein levels are reduced in 231 cells treated with increasing concentrations of R1i (Lovastatin) as confirmed via western blot. GAPDH was probed as loading control. D. 231 cells overexpressing MNRR1 show increased capacity to form mammospheres. Left, representative image of mammospheres. Cells were imaged at 4X, and scale bar represents 100μM. Middle, graph depicting the number of mammospheres formed in MNRR1 overexpressing cells as compared to EV overexpressing cells (n=16, *p<0.05). Right, western blot confirming that markers of mammosphere formation ALDH1A1 and CD44 are higher in the MNRR1 overexpressing cells. GAPDH was probed as loading control.

Article Snippet: The HTB125, HTB126, and MCF10A (10A) cells were purchased from ATCC (Manassas, VA, USA) and were grown in ATCC recommended media.

Techniques: Plasmid Preparation, Luminescence Assay, Western Blot, Over Expression, Control

A. Western blot analysis of 10A cells overexpressing MNRR1 shows increased levels of mesenchymal markers (Beta-catenin, Vimentin, and Slug) as well as reduced levels of epithelial marker ZO-1 when compared to empty vector (EV) -overexpressing cells. These suggest an epithelial to mesenchymal transition (EMT). MNRR1 was probed to confirm overexpression and GAPDH was probed as loading control. B. Transforming growth factor beta (TGF-β) (5 ng/mL) increases the transcript levels of MNRR1 . 18s rRNA was used as a housekeeping gene for the RT-qPCR analysis (n=8, *p<0.05). C. TGF-β increases the protein levels of MNRR1 in 10A cells analyzed using western blot. Tubulin was probed as loading control. D. TGF-β increases the protein levels of mesenchymal marker Slug and the increase is blocked by co-treatment with MNRR1 inhibitor (lovastatin, 10 μM) as analyzed by western blot. MNRR1 was probed to confirm inhibition and GAPDH was probed as loading control. E. Protein levels of the mesenchymal marker Slug are reduced in 231 cells treated with increasing concentrations of the R1i, lovastatin. MNRR1 was probed to confirm inhibition and GAPDH was probed as loading control. F. Left, representative image depicting the reduced invasion capacity of 231 cells by treatment with increasing concentrations of lovastatin. Cells were imaged at 4x, and scale bar represents 100μm. Right, graph shows quantification of cell invasion in 231 cells treated with lovastatin. (n= 4, *p<0.05).

Journal: bioRxiv

Article Title: MNRR1 is required for Triple Negative Breast Cancer growth and metastasis and can be targeted by repurposed drugs

doi: 10.64898/2026.01.31.703055

Figure Lengend Snippet: A. Western blot analysis of 10A cells overexpressing MNRR1 shows increased levels of mesenchymal markers (Beta-catenin, Vimentin, and Slug) as well as reduced levels of epithelial marker ZO-1 when compared to empty vector (EV) -overexpressing cells. These suggest an epithelial to mesenchymal transition (EMT). MNRR1 was probed to confirm overexpression and GAPDH was probed as loading control. B. Transforming growth factor beta (TGF-β) (5 ng/mL) increases the transcript levels of MNRR1 . 18s rRNA was used as a housekeeping gene for the RT-qPCR analysis (n=8, *p<0.05). C. TGF-β increases the protein levels of MNRR1 in 10A cells analyzed using western blot. Tubulin was probed as loading control. D. TGF-β increases the protein levels of mesenchymal marker Slug and the increase is blocked by co-treatment with MNRR1 inhibitor (lovastatin, 10 μM) as analyzed by western blot. MNRR1 was probed to confirm inhibition and GAPDH was probed as loading control. E. Protein levels of the mesenchymal marker Slug are reduced in 231 cells treated with increasing concentrations of the R1i, lovastatin. MNRR1 was probed to confirm inhibition and GAPDH was probed as loading control. F. Left, representative image depicting the reduced invasion capacity of 231 cells by treatment with increasing concentrations of lovastatin. Cells were imaged at 4x, and scale bar represents 100μm. Right, graph shows quantification of cell invasion in 231 cells treated with lovastatin. (n= 4, *p<0.05).

Article Snippet: The HTB125, HTB126, and MCF10A (10A) cells were purchased from ATCC (Manassas, VA, USA) and were grown in ATCC recommended media.

Techniques: Western Blot, Marker, Plasmid Preparation, Over Expression, Control, Quantitative RT-PCR, Inhibition

(A) 3D morphogenesis assays of MCF10A cells expressing Flag-TAZ variants. MCF10A TAZ KO cells were infected with the various Flag-tagged TAZ (F-TAZ) constructs as indicated. These cells, as well as the parental MCF10A cells, were cultured in 3D Matrigel for 7 days and stained for α-integrin (green) as a basolateral marker and GM130 (red) as an apical marker. Nuclei were counterstained with DAPI (blue). Representative confocal images were from three independent experiments. Bar , 40 μm. (B) Quantification of average acinar sizes based on the number of nuclei per acinus. A total of 20–25 acini from three independent experiments were analyzed per cell line. Asterisks depict significant differences between the pairs indicated by the brackets (*, P <0.05; ****, P <10 −4 ; one-way ANOVA and Tukey’s post-hoc test). (C) Anchorage-independent growth in soft agar. MDA-MB-231 TAZ KO cells were infected with the designated F-TAZ constructs as indicated. Following infection, 5,000 cells were plated in 6-well soft agar plates and incubated for 21 days. Parental MDA-MB-231 cells and TAZ KO cells were used as controls. Colonies were stained with 1 mg/ml MTT. Bar , 100 μm. Colony numbers from each cell line expressing different TAZ constructs were counted and are shown in (D). Data are mean ± SEM of three independent experiments. Asterisks represent significant differences between the indicated pairs (****, P <10 −4 ; one-way ANOVA and Dunnett’s post-hoc test).

Journal: bioRxiv

Article Title: Analysis of the assembly, stabilization and maturation of the multiphasic TAZ biomolecular condensates

doi: 10.64898/2026.01.29.702607

Figure Lengend Snippet: (A) 3D morphogenesis assays of MCF10A cells expressing Flag-TAZ variants. MCF10A TAZ KO cells were infected with the various Flag-tagged TAZ (F-TAZ) constructs as indicated. These cells, as well as the parental MCF10A cells, were cultured in 3D Matrigel for 7 days and stained for α-integrin (green) as a basolateral marker and GM130 (red) as an apical marker. Nuclei were counterstained with DAPI (blue). Representative confocal images were from three independent experiments. Bar , 40 μm. (B) Quantification of average acinar sizes based on the number of nuclei per acinus. A total of 20–25 acini from three independent experiments were analyzed per cell line. Asterisks depict significant differences between the pairs indicated by the brackets (*, P <0.05; ****, P <10 −4 ; one-way ANOVA and Tukey’s post-hoc test). (C) Anchorage-independent growth in soft agar. MDA-MB-231 TAZ KO cells were infected with the designated F-TAZ constructs as indicated. Following infection, 5,000 cells were plated in 6-well soft agar plates and incubated for 21 days. Parental MDA-MB-231 cells and TAZ KO cells were used as controls. Colonies were stained with 1 mg/ml MTT. Bar , 100 μm. Colony numbers from each cell line expressing different TAZ constructs were counted and are shown in (D). Data are mean ± SEM of three independent experiments. Asterisks represent significant differences between the indicated pairs (****, P <10 −4 ; one-way ANOVA and Dunnett’s post-hoc test).

Article Snippet: HeLa cells (cat. #CCL-2), MCF10A human mammary epithelial cells (cat. #CRL-10317), MDA-MB-231 human breast cancer epithelial cells (cat. #HTB-26) and 293T human kidney epithelial cells (cat. #CRL-3216) were from American Type Culture Collection (ATCC, Manassas, VA).

Techniques: Expressing, Infection, Construct, Cell Culture, Staining, Marker, Incubation

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