Response and resistance to BET bromodomain inhibitors in triple-negative breast cancer

Abstract

Triple-negative breast cancer (TNBC) is a heterogeneous and clinically aggressive disease for which there is no targeted therapy1,2,3. BET bromodomain inhibitors, which have shown efficacy in several models of cancer4,5,6, have not been evaluated in TNBC. These inhibitors displace BET bromodomain proteins such as BRD4 from chromatin by competing with their acetyl-lysine recognition modules, leading to inhibition of oncogenic transcriptional programs7,8,9. Here we report the preferential sensitivity of TNBCs to BET bromodomain inhibition in vitro and in vivo, establishing a rationale for clinical investigation and further motivation to understand mechanisms of resistance. In paired cell lines selected for acquired resistance to BET inhibition from previously sensitive TNBCs, we failed to identify gatekeeper mutations, new driver events or drug pump activation. BET-resistant TNBC cells remain dependent on wild-type BRD4, which supports transcription and cell proliferation in a bromodomain-independent manner. Proteomic studies of resistant TNBC identify strong association with MED1 and hyper-phosphorylation of BRD4 attributable to decreased activity of PP2A, identified here as a principal BRD4 serine phosphatase. Together, these studies provide a rationale for BET inhibition in TNBC and present mechanism-based combination strategies to anticipate clinical drug resistance.

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Figure 1: Response to BBIs in breast cancer.
Figure 2: Acquired BBI-resistance in TNBC.
Figure 3: Mechanism of BBI-resistance in TNBCs.
Figure 4: Regulation and relevance of BRD4 phosphorylation.

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Primary accessions

Gene Expression Omnibus

Data deposits

RNA-seq, ChIP-seq, and Chem-seq data have been deposited in the NCBI GEO database with the accession number GSE63584.

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Acknowledgements

We thank D. Silver and members of the Polyak and Bradner laboratories for their critical reading of this manuscript and useful discussions. We thank G. Brown for help with creating the word cloud figures. This work was supported by the NIH DF/HCC SPORE in Breast Cancer CA168504 (K.P., E.P.W., I.E.K., D.D., W.T.B., and J.E.B.), CA080111 (K.P. and M.B.), and CA103867 (C.M.C.), Susan G. Komen Foundation (S.S.), CPRIT RP110471 and RP140367 (C.M.C), Welch Foundation (C.M.C.), US Department of Defense CDMRP BC122003 (S.X.L.) and CA120184 (C.Y.L.), Princess Margaret Cancer Foundation (H.H.H.), Canada Foundation for Innovation and Ontario Research Fund CFI32372 (H.H.H.), NSERC discovery grant RGPIN-2015-04658 (H.H.H.), and the Harvard Ludwig Center for Cancer Research (J.E.B., M.B. and K.P.).

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Authors

Contributions

S.S. performed cell culture, xenograft, ChIP-seq, and RNA-seq experiments, and data analyses. C.Y.L. and C.A.M. performed genomic data analyses. H.H.H. helped with ChIP-seq and RNA-seq experiments and data analyses. R.M.W. performed cell culture, ChIP-seq experiments and data analyses. J.M.R. performed synergy studies. D.P.T. helped with immunofluorescence staining. M.J. and S.J.H. helped with confocal microscopy and image quantification. Y.L. helped with BRD4 ChIP-seq. M.B.E. and G.P. helped with cell cycle studies. E.D. helped with generating and testing BRD4 mutants. J.B. and L.A. performed Chem-seq. H.M., C.D. and J.S.C. conducted proteomic experiments and data analyses. C.O. and M.M. performed drug sensitivity screens. J.Q. synthesized BBI compounds. M.N. generated shRNA constructs. D.D., I.E.K. and E.P.W. generated the TMA and linked to clinical data. H.G., D.G.S. and W.T.B. performed TMA and statistical analyses. J.R. and A.L. performed BH3 profiling and data analyses. C.-M.C. and S.-Y.W. provided phospho-BRD4 antibody. P.K.R. and M.D. generated RNA-seq libraries. K.P. supervised with help from J.E.B., X.S.L., M.B., R.A.Y. and H.L. All authors helped to design the study and write the manuscript.

Corresponding authors

Correspondence to James E. Bradner or Kornelia Polyak.

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Competing interests

J.E.B. and R.A.Y. are founders of Syros Pharmaceuticals, J.E.B. is the founder of Tensha Therapeutics. K.P. receives research support from and is a consultant for Novartis Oncology.

Extended data figures and tables

Extended Data Figure 1 BET bromodomain proteins and cell growth in TNBCs.

All error bars represent s.d., n = 3. a, Cellular viability of SUM159 and MDA-MB-231 cells expressing TET-inducible BRD4-targeting or lacZ shRNAs. P values indicate statistical significance of the observed differences (paired t-test). b, Cellular viability four days after transfection of siRNAs targeting BET bromodomain proteins. Asterisks indicate statistical significance (paired t-test) of the marked differences as follows. SUM159: siBRD2 versus siBRD3, P = 0.002; siBRD3 versus siBRD4, P = 0.0006, MDA-MB-231: siBRD2 versus siBRD3, P = 0.006; siBRD2 versus siBRD4, P = 0.002; siBRD3 versus siBRD4, P = 0.016, MDA-MB-468: siBRD2 versus siBRD3, P = 0.0009; siBRD3 versus siBRD4, P = 0.0055, MDA-MB-436: siBRD2 versus siBRD4, P = 0.002; siBRD3 versus siBRD4, P = 0.015, ZR-75-1: siBRD2 versus siBRD3, P = 0.0169; siBRD3 versus siBRD4, P = 0.007. c, Immunoblot analysis of BET bromodomain proteins four days after siRNA transfection. d, Cell cycle profile of SUM159 cells synchronized in G2/M with 100 ng ml−1 nocodazole followed by replating to fresh medium with DMSO or JQ1 (500 nM) added at −1 h or at 3 h after release. Cells were collected at different time points (0, 6, 12 h) after release. e, Immunoblot analysis of the indicated proteins at different time points (0, 3, 6, 12 h) after release of SUM159 cells synchronized with 100 ng ml−1 nocodazole followed by replating to fresh medium with DMSO or JQ1 (500 nM) added at 1 h before or 3 h after release. f, Cell cycle analysis of SUM159 cells following 72 h treatment with JQ1 (500 nM) or downregulation of BRD4 using TET-inducible shRNAs. g, Annexin V staining of SUM159 cells following 72 h treatment with JQ1 (500 nM) downregulation of BRD4 using TET-inducible shRNAs. All error bars represent s.e.m. h, Immunoblot analysis of the indicated proteins in a panel of breast cell lines; colour scheme as in a. For gel source data, see Supplementary Fig. 1.

Extended Data Figure 2 Response to BBIs in TNBCs.

a, Immunoblot analysis of the indicated proteins at different time points following JQ1 treatment (500 nM) in SUM159 cells (top) and at different JQ1 doses for 24 h treatment in SUM159 and MDA-MB-436 cells (bottom). b, Immunoblot analysis of the indicated proteins at different time points following JQ1 treatment (500 nM) in SUM149, SUM159 and MDA-MB-231 cells. c, Haematoxylin and eosin staining of SUM159 cells after 3 days of JQ1 treatment. d, Senescence β-galactosidase staining of SUM159 and MDA-MB-231 cells after 3 days of JQ1 treatment. Scale bars, 100 μm. e, Box plots depict the weights of xenografts 30 days after injection of MDA-MB-231 (2 × 106) and IDC50X (2 × 105) cells into inguinal mammary fat pads of NOG mice; n indicates the number of mice per experiment. P values indicate statistical significance of the observed differences (unpaired t-test). Error bars represent s.e.m. Mice were administered JQ1 (50 mg per kg, daily) or vehicle only (control) for 14 days beginning at day 16 (MDA-MB-231) or 10 (IDC50X) after injection (after tumours reached palpable size). For EL12-58X PDX, mice were implanted with pieces of tissue measuring 1 × 3 × 3 mm into the inguinal mammary fat pads and were administered daily JQ1 (50 mg per kg) for 14 days beginning at day 21 after injection (after tumours reached palpable size). f, Bromodeoxyuridine (BrdU) and luminal (Low MW CK) and basal high (High MW CK) molecular weight cytokeratin staining of EL12-58 xenograft with or without JQ1 treatment. Scale bars, 50 μm. g, Tumour volume of SUM159 cells expressing TET-inducible BRD4-targeting shRNAs. Mice were administered doxycycline or vehicle only (control) for 39 days beginning at day 21 after injection (after tumours reached palpable size). Error bars represent s.d., n = 4 (shBRD4-1 experiment) and n = 5 (shBRD4-2 experiment). h, Haematoxylin and eosin staining and immunofluorescence analysis of basal (basal cytokeratin, cytokeratin 17, pSTAT3, and CD44) and luminal (luminal cytokeratin, cytokeratin 18, and CD24) markers in SUM159 xenografts with or without JQ1 treatment. Scale bars, 100 μm for haematoxylin and eosin and 50 μm for immunofluorescence, respectively. For gel source data, see Supplementary Fig. 1.

Extended Data Figure 3 SUM149 JQ1 response.

a, Scatter plots showing the relationship between the genomic binding of BRD4 and Bio-JQ1 (left) or H3K27ac and Bio-JQ1 (right) at all Bio-JQ1 enriched bound regions. Units of genomic occupancy are in rpm per bp. A simple linear regression is drawn in black. Pearson correlation statistics are also shown. b, Box plots showing the log2 fold change in BRD4 with or without JQ1 (left) or H3K27ac with or without JQ1 (right) at Bio-JQ1 bound regions in SUM159 cells. The 12,999 Bio-JQ1 regions are ranked by increasing Bio-JQ1 binding and divided into 10 separate bins (displayed from left to right). The statistical significance of the difference in the mean BRD4 log2 fold change between the weakest and strongest Bio-JQ1 bound region bins is shown (Welch’s t-test; ***P value < 1 × 10−10). c, Box plots showing the log2 fold change in BRD4 with or without JQ1 (left) or H3K27ac with or without JQ1 (right) at BRD4 bound regions in SUM149 cells. The 5,696 BRD4 bound regions are ranked by increasing background subtracted BRD4 binding and divided into 10 separate bins (displayed from left to right). The statistical significance of the difference in the mean BRD4 log2 fold change between the weakest and strongest BRD4 bound region bins is shown (Welch’s t-test; ***P value < 1 × 10−10). d, Ranked plots of enhancers defined in untreated SUM149 cells ranked by increasing BRD4 signal (units rpm). Enhancers are defined as regions of BRD4 binding not contained in promoters. The cut-off discriminating typical from super-enhancers is shown as a dashed grey line. Enhancers associated with TNBC characteristic genes are highlighted. e, Scatter plots showing the relationship between the log2 fold change in gene expression upon 12 h JQ1 treatment in SUM149 (y-axis) and SUM159 (x-axis) cells. A simple linear regression is drawn in red. The Pearson correlation statistic is also shown. f, Box plots showing the log2 fold change in expression relative to DMSO control of either all active genes or super-enhancer (SE)-associated genes upon 12 h JQ1 treatment. The statistical significance of the difference in expression change between all active genes and super-enhancer-associated genes is shown by a Welch’s t-test *P value < 1 × 10−3). g, Heat map showing the expression of genes that are up or down regulated by JQ1 versus DMSO after 24 h treatment. Each row shows the expression of a single gene in either DMSO or JQ1 treated cells at 3, 12, and 24 h after treatment. Expression values are coloured according to fold change relative to the median for each row. Genes are ordered by fold change with or without JQ1 24 h after treatment. h, Heat map showing the expression of genes that are up or down regulated by JQ1 versus DMSO after 12 h treatment in SUM149 and SUM149R cells. Each row shows the expression of a single gene in either DMSO or JQ1 treated cells at 12 h after treatment. Expression values are coloured according to fold change relative to the median for each row. Genes are ordered by fold change with or without JQ1 12 h after treatment in SUM149 cells. i, j, Box plots showing the log2 fold change in expression at genes that are up- (i) or down- (j) regulated by JQ1 versus DMSO after 12 h of treatment in parental SUM149 cells. Log2 fold change in expression is shown for either parental SUM149 (left) or resistant SUM149R (right) cells. k, Top signalling pathways affected by JQ1-induced gene expression changes in SUM159 cells. l, Viable cell numbers of SUM149 (left) and SUM149R (right) cells treated with different doses of JQ1 (2 μM, 10 μM). Error bars represent s.d., n = 3. P values indicate statistical significance of the observed differences (two-way ANOVA with Bonferroni multiple comparison correction).

Extended Data Figure 4 Characterization of SUM159R cells.

a, Expression of ABC transporters in SUM159 and SUM159R cells. The expression of 29 ABC transporters was analysed based on RNA-seq data on the two cell lines. b, Assay for MDR (multi drug resistance) pumps in SUM159 and SUM159R cells treated with JQ1 alone or together with verapamil based on microscopic examination (left) and FACS (right) of cells labelled with fluorescent MDR substrate. c, Immunoprecipitation analysis of Biotinylated JQ1 (Bio-JQ1) in SUM159 and SUM159R cells with JQ1 treatment at different time points following immunoblot for the indicated proteins. d, Cellular viability of SUM159 and SUM159R cells treated with CXCR2 and JAK2 inhibitors. Error bars represent s.d., n = 3. e, Cellular viability of SUM159, and pool and single cell clones of SUM159R cells treated with different doses of JQ1. Error bars represent s.d., n = 3. f, Tumour weight of xenografts derived from SUM159 and SUM159R cells. Mice were administered JQ1 for 14 (SUM159) and 30 (SUM159R) days beginning at day 14 and 26, respectively, after injection. P values indicate statistical significance of the observed differences (unpaired t-test). Error bars represent s.e.m. g, Immunoblot analysis of BCL-XL expression in SUM159 and SUM159R cells before and after JQ1 3 h treatment (500 nM). h, Dynamic BH3 profiling reveals inverse apoptotic response to JQ1 in SUM149R and SUM159R cells. In parental lines JQ1 increases priming relative to untreated cells indicating an increase in apoptotic propensity. In resistant lines JQ1 reduces priming indicating greater resistance to apoptosis relative to untreated cells. P values indicate statistical significance of the observed differences (two-way ANOVA). Error bars represent s.e.m., n = 5. For gel source data, see Supplementary Fig. 1.

Extended Data Figure 5 BRD4 binding in SUM159R cells.

a, Cellular viability of SUM159 and SUM159R cells transfected with siRNAs targeting bromodomain proteins. Asterisks indicate statistical significance (paired t-test) of the marked differences as follows: SUM159: siBRD2 versus siBRD3, P = 0.013, siBRD3 versus siBRD4, P = 0.0154 and SUM159R: siBRD2 versus siBRD3, P = 0.0159, siBRD2 versus siBRD4, P = 0.0048; siBRD3 versus siBRD4, P = 0.0068. b, Cellular viability of SUM159R cells expressing TET-inducible BRD4-targeting or lacZ shRNAs. All error bars represent s.e.m. P values indicate statistical significance of the observed differences (unpaired t-test). c, Box plot showing the log2 fold change in H3K27ac genomic occupancy at regions bound by Bio-JQ1 in parental SUM159 or resistant SUM159R cells. d, Heat map showing the expression of genes that are up or down regulated by JQ1 versus DMSO after 24 h treatment in parental SUM159 cells. Each row shows the expression of a single gene in either DMSO or JQ1 treated cells at 24 h after treatment in SUM159 cells (left four columns) or SUM159R cells (right four columns). Expression values are coloured according to fold change relative to the median for each row. Genes are ordered by fold change with or without JQ1 24 h after treatment. e, f, Box plots showing the log2 fold change in expression at genes that are up- (e) or down- (f) regulated by JQ1 versus DMSO after 24 h of treatment in parental SUM159 cells. Log2 fold change in expression is shown for either parental SUM159 or resistant SUM159R cells. g, Box plots showing expression of genes that are up- or downregulated by JQ1 versus DMSO after 24 h of treatment in parental SUM159 cells. Expression is shown in DMSO and JQ1-treated conditions in units of FPKM for either parental SUM159 (left) or resistant SUM159R (right) cells. The statistical significance of the difference between gene expression distributions for SUM159 DMSO- and JQ1-treated cells is shown (P < 0.01). The difference between all other distributions are considered non significant (NS). The statistical significance of the difference between SUM159 DMSO gene expression distribution and all other distributions is shown (*P < 1 × 10−3). The difference between all other distributions are considered non-significant. h, Examples of luminal and basal cell-specific genes, and MYC in SUM159 and SUM159R cells. RNA-seq tracks are shown. i, Haematoxylin and eosin staining and immunofluorescence analysis of luminal (CK18 and LMW) and basal (CK17 and HMW) cytokeratins and luminal (VIM and CD24) and basal (CDH1, CD44, and pSTAT3) cell markers in SUM159R xenografts. All error bars represent s.e.m. Scale bars, 100 μm for haematoxylin and eosin and 50 μm for immunofluorescence, respectively.

Extended Data Figure 6 JQ1 response in other breast cancer cell lines.

a, b, Gene tracks depicting BRD4 + DMSO and BRD4 + JQ1 in multiple breast cancer cells at the BCL-xL (a) or SOD2 (b) gene loci. The x-axis shows position along the chromosome with gene structures drawn below. The y-axis shows genomic occupancy in units of rpm per bp. The BCL-xL and SOD2 super-enhancers are shown as a red bar at the top. c, Box plots showing the log2 fold change in BRD4 occupancy with or without JQ1 for all BRD4 bound regions in each cell line for multiple TNBC. Cell lines are ordered by their JQ1 (IC50) and coloured by their sensitivity. d, Gene tracks depicting H3K27AC occupancy at the BCL-xL locus in SUM149 parental (top, light blue) or SUM149R resistant (bottom, dark blue) cells. The x-axis shows position along the chromosome with gene structures drawn below. The y-axis shows genomic occupancy in units of rpm per bp. All error bars represent s.e.m.

Extended Data Figure 7 Word clouds depicting BRD4-associated proteins identified in RIME analysis.

Extended Data Figure 8 Mechanism of BBI-resistance.

a, Immunoblot analysis of BRD4 immunoprecipitates for MED1 in the indicated cell lines with or without JQ1 treatment (5 μM, 3 h). b, Immunoblot analysis of long (BRD4L) and short (BRD4S) forms of BRD4 after transfection of siRNAs. c, Immunoblot analysis of the indicated exogenously expressed Flag-tagged BRD4 proteins in SUM159 and SUM159R cells. d, Immunoblot analysis of pBRD4, BRD4, MED1 and ACTB in the indicated cell lines with or without JQ1 treatment. e, Immunoblot analysis of phospho-BRD4 (pBRD4) and BRD4 in SUM159 and SUM159R cells treated with the indicated doses of CK2, PI3K, and MEK inhibitors for 2 h. f, Immunoblot analysis of CK2 substrates in SUM159 and SUM159R cells following CK2 inhibitor (CX-4945, 10 μM) 3 h treatment. g, Immunoblot analysis of pBRD4 and BRD4 in SUM149 cell line treated with different doses of the indicated PP2A inhibitors for 3 h. ACTB was used as loading control. h, Immunoblot analysis of pBRD4 and BRD4 in the indicated cell lines treated with different doses of phenothiazine for 6 h. i, Immunofluorescence analysis of exogenous Flag-tagged BRD4 proteins (WT, BD, 7D and 7A) in SUM159 cells with or without JQ1 treatment (5 μM, 3 h). Scale bars, 20 μm. For gel source data, see Supplementary Fig. 1.

Extended Data Figure 9 Phospho-BRD4 levels in xenografts and primary TNBC samples.

a, Immunofluorescence analysis of phospho-BRD4 (pBRD4) in SUM159 parental and SUM159R xenografts showing that resistance is associated with higher pBRD4 levels. b, Examples of pBRD4 immunofluorescence in patient tumours depicting variability among different TNBC samples. Scale bars, 50 μm. c. Mean intensity of phospho-BRD4 (pBRD4) in tissue samples from 83 patients with early-stage triple negative breast cancer (TNBC). d, Examples of androgen receptor and basal cytokeratin (bCK, HMW CK) immunofluorescence in TNBC samples. Scale bars, 50 μm. e, Box plot depicting pBRD4 signal intensity in TNBCs tumours with the indicated androgen receptor and bCK expression patterns. None of the differences among groups were significant (ANOVA test P = 0.5413 and Dunnett’s multiple comparisons test was not significant). f, Kaplan–Meier estimates of disease-free survival (DFS) and overall survival (OS) in TNBC subgroups using a median-split of pBRD4 intensity. Disease outcomes were evaluated in 83 of 89 TMA samples. Patients with low pBRD4 had a worse overall prognosis with a five-year RFS of 66.2% (95% confidence interval (CI) 52.7–83.1%), compared to an RFS of 86.4% (95% CI 76.0–98.3%) among patients with high pBRD4 (HR = 2.3, 95% CI 0.98–5.4, P = 0.06). However, with this small sample size this difference did not reach statistical significance, nor did the association of pBRD4 status and overall survival (HR = 2.0, 95% CI 0.67–5.9, P = 0.22). Source data

Extended Data Figure 10 Overcoming BBI-resistance.

ac, Synergy studies of JQ1 with ABT737 (BCL-xl and BCL-2 inhibitor) (a), CX-4945 (CK2 inhibitor) (b) and perphenazine (PP2A activator) (c). Points represent paired values of drug concentrations assessed for synergism. The diagonal line signifies drug additivity. Points above the line represent antagonistic drug combinations, and those below the line represent synergistic drug combinations. Source data

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Shu, S., Lin, C., He, H. et al. Response and resistance to BET bromodomain inhibitors in triple-negative breast cancer. Nature 529, 413–417 (2016). https://doi.org/10.1038/nature16508

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