Research ArticleCancer

Sporadic activation of an oxidative stress–dependent NRF2-p53 signaling network in breast epithelial spheroids and premalignancies

See allHide authors and affiliations

Science Signaling  14 Apr 2020:
Vol. 13, Issue 627, eaba4200
DOI: 10.1126/scisignal.aba4200
  • Fig. 1 Transcriptomic fluctuations of ECM-cultured breast epithelial spheroids reveal a gene cluster associated with heterogeneous NRF2 stabilization in a 3D-specific environment.

    (A) Maximum likelihood inference parameterization (bottom) of a two-state distribution of transcript abundances for the gene cluster from microarray profiles (top) of ECM-attached basal-like MCF10A-5E breast epithelial cells, randomly collected as 10-cell pools (n = 16) from 3D-cultured spheroids after 10 days, extracted from (20). Inferred expression frequencies are the maximum likelihood estimate with 90% confidence interval (CI). (B) Venn diagram summarizing the candidate TFs predicted from four different bioinformatics algorithms (data file S1). (C and D) Quantitative immunofluorescence of (C) hyperphosphorylated RB (pRB, an upstream proxy of active E2F1) and (D) NRF2 in 3D culture with ECM (top), 2D culture (middle), and 2D culture with ECM (bottom). Expression frequencies for a two-state lognormal mixture model (preferred over a one-state model by F test; P < 0.05) were calculated by nonlinear least squares of 60 histogram bins collected from n = 1100 to 1600 of cells quantified from 100 to 200 spheroids from two separate 3D cultures. For each subpanel, representative pseudocolored images are shown in the top right inset and merged (magenta) with DAPI nuclear counterstain (blue) in the bottom right inset. Scale bars, 10 μm.

  • Fig. 2 Transcriptome-wide covariate analysis of the NRF2-associated gene cluster suggests a coordinated adaptive-stress response involving p53.

    (A) Transcripts covarying with the median NRF2-associated fluctuation signature (Fig. 1A, top) (20) measured by 10cRNA-seq (45) of ECM-attached MCF10A-5E cells grown as 3D spheroids (n = 18 10-cell pools from GSE120261). Selected GO enrichment analysis (green and purple) is shown for the transcripts with a Spearman correlation (ρ) greater than 0.5. The complete list of enrichments is available in data file S2. (B) Quantitative immunofluorescence of NRF2 and p53 abundance in ECM-attached MCF10A-5E cells grown as 3D spheroids. Representative pseudocolored images for NRF2 (top left) and p53 (middle left) are shown merged with DAPI nuclear counterstain (bottom left). White arrows indicate concurrent NRF2 and p53 stabilization. Median-scaled two-color average fluorescence intensities are quantified (right) along with the log-scaled and background-subtracted mutual information (MI) with 90% CI for n = 1691 cells segmented from 50 to 100 spheroids from two separate 3D cultures. (C) Genetic perturbation of NRF2 by inducible shRNA knockdown (top) and p53 by inducible expression of a FLAG-tagged carboxy terminal (residues 1 to 13 and 302 to 390) dominant-negative p53 (DNp53; bottom). NRF2 knockdown reduced NRF2 protein abundance to 22 ± 4% of control knockdown (fig. S3B). MCF10A-5E cells were treated with doxycycline (1 μg/ml) for 72 (top) or 24 (bottom) hours and immunoblotted for NRF2 or FLAG with vinculin, tubulin, and p38 used as loading controls and p21 used to confirm efficacy of DNp53. The negative control for shNRF2 was an inducible shGFP, and the negative control for DNp53 was an inducible FLAG-tagged LacZ. (D) Abundance changes in the gene cluster after single and combined perturbations of NRF2 and p53. NQO1 was used as a control for efficacy of shNRF2, and CDKN1A shows efficacy of DNp53. MCF10A-5E cells with or without NRF2 knockdown or DNp53 were treated with doxycycline (1 μg/ml) for 48 hours, grown as 3D spheroids for 10 days, and profiled for the indicated genes by qPCR. Data are log2 geometric mean relative to the negative control (shGFP + FLAG-tagged LacZ), with asterisks indicating statistically significant changes (left and middle columns) or interaction effects (right column) by two-way ANOVA of n = 8 independent 3D-cultured samples and an FDR of 5%. The complete set of transcripts in the gene cluster is shown in fig. S2C. (E) Dual inactivation of NRF2 and p53 causes synergistic proliferative suppression in MCF10A-5E 3D spheroids. Black arrows indicate proliferation-suppressed spheroids. Data are mean percentage of proliferation-suppressed spheroids ± SEM of n = 8 independent 3D-cultured samples after 10 days. Statistical interaction between NRF2 and p53 (Pint) was assessed by two-way ANOVA with replication. Scale bars, 20 μm (B) and 100 μm (E).

  • Fig. 3 NRF2-p53 costabilization is enhanced, and shNRF2-induced p53 adaptations are preserved in basal-like premalignancy but have different morphometric consequences.

    (A) Quantitative immunofluorescence of NRF2 and p53 abundance in ECM-attached MCF10DCIS.com cells grown as 3D spheroids. Median-scaled two-color average fluorescence intensities are quantified along with the log-scaled and background-subtracted MI with 90% CI for n = 1832 cells segmented from 70 to 110 spheroids from two separate 3D cultures. (B) Common changes in transcript abundance identified by RNA-seq of MCF10A-5E (5E) and MCF10DCIS.com (DCIS.com) cells grown as 3D spheroids with or without NRF2 knockdown. The negative control for shNRF2 was an inducible shGFP (5E) or shLacZ (DCIS.com). Data are log2-transformed Z scores for genes detected at >5 transcripts per million from n = 4 biological replicates. Enriched gene sets for the BRCA1, ATM, and CHEK2 networks are indicated, with black denoting multiple enrichments. The complete list of enrichments is available in data file S3. (C) Quantification of rounded spheroids (circularity >0.9) in 3D-cultured MCF10DCIS.com cells with or without NRF2 knockdown. The negative control for shNRF2 was an inducible shLacZ. (D) Quantification of large spheroids (size > e8.5 ≈ 5000 μm2) in 3D-cultured MCF10DCIS.com cells with or without p53 disruption. The negative control for p53 constructs was an inducible FLAG-tagged LacZ. (E) Quantification of size and circularity in 3D-cultured MCF10DCIS.com cells with or without NRF2 knockdown, p53 disruption, or both. For (C) to (E), cells with or without inducible perturbations were treated with doxycycline (1 μg/ml) for 48 hours, grown as 3D spheroids for 10 days, imaged by brightfield microscopy, and segmented. For (C) and (D), data are mean ± 90% bootstrap-estimated CI from n = 8 biological replicates, with P values by rank sum test estimated by bootstrapping. For (E), data are means ± SEM of n = 8 biological replicates. Statistical interaction between NRF2 and p53 perturbations (Pint) was assessed by two-way ANOVA with replication. Scale bars, 100 μm.

  • Fig. 4 NRF2-p53 signaling coordination and 3D phenotypes arise from spontaneous and oncogene-induced oxidative stress.

    (A and B) NRF2 and p53 stabilization by oxidative stress compared with DNA double-strand breaks. MCF10A-5E cells were treated with 5 μM doxorubicin (double-strand breaks) or 200 μM H2O2 (oxidative stress) for the indicated time points, and NRF2 (magenta) or p53 (green) protein abundance was estimated by quantitative immunoblotting. Data are means ± SEM of n = 3 (A) or 4 (B) independent perturbations. n.s., not significant. (C) Endogenous oxidative stress association with NRF2 stabilization in 3D spheroids. MCF10A-5E cells stably expressing HyPer-2 (67) and mRFP1-NRF2 reporter (NRF2rep) were grown as 3D spheroids for 10 days and imaged by laser scanning confocal microscopy. Representative pseudocolored images for HyPer-2 ratio (top left) and mRFP1-NRF2 reporter (bottom left) are shown. HyPer-2 ratios and mRFP1-NRF2 reporter fluorescence are quantified (right) along with the log-scaled MI with 90% CI for n = 605 cells segmented from 10 to 25 spheroids from four separate 3D cultures. (D) Suppression of endogenous NRF2-p53 coordination during 3D culture with the antioxidant Trolox. Representative pseudocolored images for NRF2 (top left) and p53 (middle left) are shown merged with DAPI nuclear counterstain (bottom left). White arrows indicate concurrent NRF2 and p53 stabilization. The log-scaled and background-subtracted MI (right) is shown with 90% CI estimated from n = 1000 bootstrap replicates. (E) Trolox interference with the synergistic proliferative suppression caused by dual inactivation of NRF2 and p53 in MCF10A-5E cells. Data are mean percentage of proliferation-suppressed spheroids ± SEM of n = 8 independent 3D-cultured samples after 10 days. The overall effect of Trolox on spheroid size is shown in fig. S10. Statistical interaction between Trolox and NRF2-p53 (Pint) was assessed by three-way ANOVA with replication. For (A) and (B), change in protein abundance over time was assessed by one-way ANOVA. For (D) and (E), MCF10A-5E cells cultured for 10 days in 3D with or without 50 μM Trolox supplemented every 2 days. Scale bars, 10 μm (C) and 20 μm (D).

  • Fig. 5 NRF2-p53 pathway coordination and synergistic phenotypes are captured by an integrated systems model of oxidative stress.

    (A) Connecting NRF2 and p53 signaling models (68, 69, 71) through oxidative stress activators and antioxidant target enzymes. Additional cross-talk linking oxidative stress to p53 inhibition (73), p53 to NRF2 through p21 (76), and NRF2 to MDM2 (74, 75) was considered (gray). (B) Simulation strategy for quantifying association between signaling intermediates. The model was challenged with various ROS production rates and randomly sampled at multiple intermediate time points (yellow to blue). Integrated intracellular H2O2 (gray) is used for phenotype predictions related to NRF2 and p53 perturbation. (C) Intracellular H2O2 concentration is associated with a reporter of NRF2 stabilization (NRF2rep) following simulated step increases in ROS production rate as illustrated in (B). (D and E) Coordination of NRF2 and p53 stabilization in the oxidative stress model and in simulations of premalignancy through the computational approach illustrated in (B). (F and G) Modeling NRF2 knockdown by reduced synthesis captures the synergistic oxidative stress profile of cells harboring dual perturbation of the NRF2 and p53 pathways. In (F), transcriptional changes secondary to NRF2 knockdown were added to the model according to the results in Fig. 3B. For (C) to (E), simulated time points are log-scaled and background-subtracted MI with 90% CI for 10 time points from n = 100 random ROS generation rates. For (F) and (G), time-integrated intracellular H2O2 profiles are scaled to the unperturbed simulations and reported as the mean oxidative stress with 90% CI from n = 100 random ROS generation rates. Statistical interaction between shNRF2 and DNp53 perturbations (Pint) was assessed by two-way ANOVA with replication.

  • Fig. 6 NRF2 and p53 are costabilized in breast epithelial tissue and premalignant lesions but uncoupled in TNBC.

    (A) Immunohistochemistry (top) and immunofluorescence (bottom) for NRF2 and p53 in tumor-adjacent normal breast lobules. Hematoxylin and eosin (H+E, top right) histology is from a serial paraffin section for p53. Images from a tumor-adjacent normal breast duct are shown in fig. S17. (B and C) Multicolor immunofluorescence for NRF2 and p53 in (B) hormone-negative DCIS and (C) TNBC. (D) Quantification of the association between NRF2 and p53 immunoreactivities represented in (A) to (C). (E and F) Median NRF2 and p53 immunoreactivities for the designated tissue type in each clinical case. n.s., not significant (P > 0.05). For (A) to (C), immunofluorescence is shown as representative pseudocolored images for NRF2 (left) and p53 (middle) are shown merged with DAPI nuclear counterstain (right). White arrows indicate concurrent NRF2 and p53 stabilization, and magenta or green arrows indicate stabilization of NRF2 or p53 separately. Scale bars, 20 μm. For (D) to (F) data are means ± SEM of n = 14 cases with tumor-adjacent normal epithelium (Normal), 8 cases with DCIS, and 7 cases with TNBC. Multigroup comparison was made by Kruskal-Wallis rank sum test with Šidák correction for multiple hypothesis testing.

  • Fig. 7 TNBC-specific signatures of the oxidative stress network predict NRF2-p53 coupling and the response to NRF2 perturbations.

    (A) Transcripts per million for the indicated TNBC cell lines scaled to MCF10A cells from the NIH LINCS dataset (91). (B) NRF2-p53 MI and ROS tolerance for TNBC cell lines using the simulation strategy in Fig. 5B. (C to G) Quantification of mean spheroid area with or without NRF2 knockdown in 3D-cultured TNBC cells with higher simulated ROS tolerance and NRF2-p53 MI (C and D) and with lower simulated ROS tolerance and NRF2-p53 MI (E to G). (H) Transcripts per million for the TNBC lines in (A) scaled to clinical cases of TNBC in TCGA (35). (I) Simulated NRF2-p53 MI and ROS tolerance for TNBC tumors. Vertical lines indicate cases with high MI in the lower quartile of ROS tolerance. For (A) and (H), the clustered transcripts were used to adjust the initial conditions of the model simulations for each cell line and tumor. For (B) and (I), ROS tolerance was defined as the integrated intracellular H2O2 concentration in each cell line compared with that of MCF10A-5E cells in response to an increased ROS production rate as in Fig. 5B. For (C) to (G), TNBC cells with or without inducible NRF2 knockdown were treated with doxycycline (1 μg/ml) for 72 hours, grown as 3D spheroids, imaged by brightfield microscopy, and segmented. Data are means ± SEM of n = 4 to 8 biological replicates. The difference between means was assessed by Student’s t test with Šidák correction for multiple hypothesis testing, and the specific p53 mutation of each line is shown (bottom left).

Supplementary Materials

  • stke.sciencemag.org/cgi/content/full/13/627/eaba4200/DC1

    Fig. S1. HIF-1α is not appreciably stabilized in 3D culture.

    Fig. S2. Abundance of the heterogeneously regulated gene cluster is perturbed by NRF2 knockdown or p53 disruption, but not by JUND knockdown or human papillomavirus E7–induced inhibition of RB.

    Fig. S3. NRF2 knockdown and 3D phenotype quantification in MCF10A-5E cells.

    Fig. S4. Proliferation differences and signaling similarities between MCF10A-5E and MCF10DCIS.com cells.

    Fig. S5. NRF2 knockdown causes p53 stabilization in premalignant breast epithelial cell lines.

    Fig. S6. Premalignant breast epithelial cell lines have similar adaptations to NRF2 knockdown in spheroid culture.

    Fig. S7. Representative immunoblot images for the double-strand break and oxidative stress time courses in MCF10A-5E cells.

    Fig. S8. Local niches of NRF2 stabilization in MCF10A-5E 3D spheroids and pubertal murine mammary glands.

    Fig. S9. Description and validation of the HyPer-2 probe for H2O2 and the mRFP1-NRF2 reporter.

    Fig. S10. Antioxidant treatment causes an overall increase in MCF10A-5E spheroid size.

    Fig. S11. Oxidative stress stabilizes NRF2 in the cytoplasm more so than electrophilic stress.

    Fig. S12. Oxidative stress does not measurably inhibit MDM2 induction by stabilized p53.

    Fig. S13. NRF2 perturbations do not detectably alter MDM2 abundance.

    Fig. S14. Calibration of an integrated NRF2-p53 systems model for oxidative stress.

    Fig. S15. Endogenous NRF2 and p21 are not proximity labeled by BirA* fusions of each other.

    Fig. S16. Anti-NRF2 antibody validation for immunohistochemistry.

    Fig. S17. NRF2 and p53 are costabilized in breast epithelial ducts.

    Fig. S18. Low-magnification hematoxylin-eosin images of the tissues and tumors in the work.

    Table S1. qPCR primer sequences.

    Table S2. Parameter summary for the integrated NRF2-p53 computational model.

    Data file S1. Promoter analysis results underlying the summary Venn diagram in Fig. 1B.

    Data file S2. GO enrichment analysis.

    Data file S3. Gene set enrichment analysis of differentially abundant transcripts in MCF10A-5E and MCF10DCIS.com cells upon NRF2 knockdown compared with control.

    Data file S4. NRF2-p53 computational model and associated files.

    References (136151)

  • The PDF file includes:

    • Fig. S1. HIF-1α is not appreciably stabilized in 3D culture.
    • Fig. S2. Abundance of the heterogeneously regulated gene cluster is perturbed by NRF2 knockdown or p53 disruption, but not by JUND knockdown or human papillomavirus E7–induced inhibition of RB.
    • Fig. S3. NRF2 knockdown and 3D phenotype quantification in MCF10A-5E cells.
    • Fig. S4. Proliferation differences and signaling similarities between MCF10A-5E and MCF10DCIS.com cells.
    • Fig. S5. NRF2 knockdown causes p53 stabilization in premalignant breast epithelial cell lines.
    • Fig. S6. Premalignant breast epithelial cell lines have similar adaptations to NRF2 knockdown in spheroid culture.
    • Fig. S7. Representative immunoblot images for the double-strand break and oxidative stress time courses in MCF10A-5E cells.
    • Fig. S8. Local niches of NRF2 stabilization in MCF10A-5E 3D spheroids and pubertal murine mammary glands.
    • Fig. S9. Description and validation of the HyPer-2 probe for H2O2 and the mRFP1-NRF2 reporter.
    • Fig. S10. Antioxidant treatment causes an overall increase in MCF10A-5E spheroid size.
    • Fig. S11. Oxidative stress stabilizes NRF2 in the cytoplasm more so than electrophilic stress.
    • Fig. S12. Oxidative stress does not measurably inhibit MDM2 induction by stabilized p53.
    • Fig. S13. NRF2 perturbations do not detectably alter MDM2 abundance.
    • Fig. S14. Calibration of an integrated NRF2-p53 systems model for oxidative stress.
    • Fig. S15. Endogenous NRF2 and p21 are not proximity labeled by BirA* fusions of each other.
    • Fig. S16. Anti-NRF2 antibody validation for immunohistochemistry.
    • Fig. S17. NRF2 and p53 are costabilized in breast epithelial ducts.
    • Fig. S18. Low-magnification hematoxylin-eosin images of the tissues and tumors in the work.
    • Table S1. qPCR primer sequences.
    • Table S2. Parameter summary for the integrated NRF2-p53 computational model.
    • Legends for data files S1 to S4
    • References (136151)

    [Download PDF]

    Other Supplementary Material for this manuscript includes the following:

    • Data file S1 (Microsoft Excel format). Promoter analysis results underlying the summary Venn diagram in Fig. 1B.
    • Data file S2 (Microsoft Excel format). GO enrichment analysis.
    • Data file S3 (Microsoft Excel format). Gene set enrichment analysis of differentially abundant transcripts in MCF10A-5E and MCF10DCIS.com cells upon NRF2 knockdown compared with control.
    • Data file S4 (.zip format). NRF2-p53 computational model and associated files.

Stay Connected to Science Signaling

Navigate This Article