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. 2020 Aug 21;6(34):eaba8968.
doi: 10.1126/sciadv.aba8968. Print 2020 Aug.

Synthetic lethal combination targeting BET uncovered intrinsic susceptibility of TNBC to ferroptosis

Nandini Verma  1 , Yaron Vinik  1 , Ashish Saroha  1 , Nishanth Ulhas Nair  2 , Eytan Ruppin  2 , Gordon Mills  3 , Thomas Karn  4 , Vinay Dubey  1 , Lohit Khera  1 , Harsha Raj  1 , Flavio Maina  5 , Sima Lev  6
Affiliations

Synthetic lethal combination targeting BET uncovered intrinsic susceptibility of TNBC to ferroptosis

Nandini Verma et al. Sci Adv. .

Abstract

Identification of targeted therapies for TNBC is an urgent medical need. Using a drug combination screen reliant on synthetic lethal interactions, we identified clinically relevant combination therapies for different TNBC subtypes. Two drug combinations targeting the BET family were further explored. The first, targeting BET and CXCR2, is specific for mesenchymal TNBC and induces apoptosis, whereas the second, targeting BET and the proteasome, is effective for major TNBC subtypes and triggers ferroptosis. Ferroptosis was induced at low drug doses and was associated with increased cellular iron and decreased glutathione levels, concomitant with reduced levels of GPX4 and key glutathione biosynthesis genes. Further functional studies, analysis of clinical datasets and breast cancer specimens revealed a unique vulnerability of TNBC to ferroptosis inducers, enrichment of ferroptosis gene signature, and differential expression of key proteins that increase labile iron and decrease glutathione levels. This study identified potent combination therapies for TNBC and unveiled ferroptosis as a promising therapeutic strategy.

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Figures

Fig. 1
Fig. 1. Synthetic lethal combination therapies for TNBC subtypes.
(A) Heatmap representation of drug screen results. Inhibitors of the indicated target pairs (fig. S1A) were applied at very low doses (~2 to 20% of IC50 as a single agent, for most cases), and viability of the indicated cell lines (12 TNBC + MCF10A) was measured 72 hours later. Effects on cell viability were calculated as percentage of control untreated cells and marked by color codes; blue, no/low cell death; yellow, high cell death. Drug pairs that reduced cell viability (≥75%) across several cell lines were clustered together according to cell line subtypes. We defined pairs that were potent for mesenchymal cell lines (M/MSL, green), basal-like (BL1/2, blue), and those that were potent in all subtypes but had low effect on MCF10A (≤20%) viability. Toxic combinations affect all cell lines (bottom). Results are mean values of three experiments. Actual screen data are included in table S3. (B) Venn diagram of hits obtained in the screen; mesenchymal (M/MSL)–specific, BL-specific (BL), and generic, which were effective in all subtypes. (C) Scatterplot between ISLE significance scores and drug combination effectiveness. Spearman correlation and P value are shown. Basal breast cancer data (330 patients; METABRIC) were used in the ISLE pipeline. (D) Box plots of BRD4 expression in patients with breast cancer grouped by PAM50. The difference between the basal patients and any other PAM50 group is significant (t test, P value of <0.0001). (E) IHC analysis of BRD4 expression in TNBC and non-TNBC tumors. Staining intensity of BRD4 was scored as described in Materials and Methods. Representative images of BRD4 staining in TNBC (n = 40) and non-TNBC (n = 27) tissues along with a column scatterplot of the H-score distribution among the specimens are shown. The difference between the groups is significant (t test).
Fig. 2
Fig. 2. In vitro validation of drug combinations targeting BET.
(A) Effects of BET and CXCR2 antagonists on cell viability. The indicated BL1/2 (blue) and M/MSL (green) TNBC cell lines and MCF7 (luminal) and MCF10A (normal-like) lines were treated with the indicated doses of the drugs for 72 hours and stained with crystal violet. Representative pictures of reproducible effects from two to three independent experiments are shown. (B, E, and F) Dose-response curves of single agents and drug combinations in the indicated cell lines treated with varying concentrations of JQ1 and SB225022 (B) or JQ1 and BTZ (E and F) for 72 hours. Dose-response curves are presented as means of four (B) or three (E and F) repeats. (C and G) CI was calculated by the CompuSyn software with the Chou-Talalay equation using multiple doses and response points. CI values for three different indicated FA are shown. (D) Effects of BET and proteasome inhibitors on cell viability were assessed by crystal violet staining as described in (A). (H) Effects of drug combinations on spheroid growth. Representative images and viability assay (CellTiter-Blue, bar graph) of day 15 4T1 spheroids (n = 6 spheroids). Control untreated and treated spheroids with single agents at the indicated doses and with the drug combinations are shown. Scale bar, 100 μm.
Fig. 3
Fig. 3. In vivo validation of drug combinations targeting BET.
(A to D) Effects of BET and CXCR2 inhibition on tumor growth. Representative bioluminescence imaging of xenograft tumors at day 41 after bilateral implantation of MDA-MB-231 into the mammary fat pad of nude mice is shown in (A). Mice were randomized into four groups (n = 9 per group) at day 23 and then treated with either vehicle, OTX015 (25 mg/kg, oral), SB225022 (5 mg/kg, IP, 5 days/week), or drug combination. The effects of drugs on tumor size at day 41 are shown by the excised tumors (B; scale bar, 1 cm), and the effects on tumor weight are shown in (C). ***P < 0.001 and *P < 0.05 (t test). The different drug treatments had no significant effects on body weight (D). Mean values ± SD of mice body weight at the indicated time points are shown. (E to G) Effects of BET and proteasome inhibition on tumor growth. Representative bioluminescence imaging of 4T1 allograft mice (E) at day 31 after implantation of 4T1 cells into the mammary fat pad of BALB/c mice is shown. Mice were randomized into four groups (n = 10 to 12 per group) at day 13 and then treated with either vehicle, OTX015 (25 mg/kg, oral), BTZ (0.25 mg/kg, IP, every fourth day), or drug combination. The effects of drugs on tumor size at day 31 are shown by the excised tumors (F; scale bar, 1 cm), and the effects on tumor weight are shown in (G), ***P < 0.001 (t test). (H) The different drugs had no significant effects on body weight. Means ± SD from (n = 10 to 12 per group) mice are shown. (I) Tumor volume curves of 4T1 allograft mice treated with vehicle (control), single drugs, or drug combination, ***P < 0.001 (Wilcoxon test). (J) Effects of drug withdrawal at day 31 on tumor growth were measured for 55 days. Data shown are the means ± SD from five to six tumors at each time point, **P < 0.01; *P < 0.05 (Wilcoxon test).
Fig. 4
Fig. 4. Inhibition of BET and the proteasome triggers ferroptosis cell death.
(A and B) Effects of BET and CXCR2 inhibition (A) or BET and proteasome inhibition (B) on PARP (A and B) and caspase-3 cleavage (A) in the indicated cell lines (blue, BL1; black, M/MSL). Staurosporine (150 nM, 16 hours) was used as a positive control. The cells were treated with low doses of JQ1 and either SB225022 (A) or BTZ (B) for 24 hours as described in Materials and Methods, lysed, and assessed by Western blot (WB) for the indicated proteins. (C) Ferroptosis inhibitors rescue cell death induced by JQ1 and BTZ combination. The indicated cell lines were pretreated with the indicated cell death inhibitors for 1 hour and then for an additional 72 hours in the absence or presence of JQ1 and BTZ (see Materials and Methods). Cell viability (CellTiter-Blue) is presented as percentage of untreated cells. The effects of the inhibitors on their cognate death pathways are shown in fig. S6C. Mean values of three experiments are shown (means ± SD; table S6). (D) Iron chelators rescued cell death induced by JQ1 and BTZ treatment. The indicated TNBC cell lines were treated with JQ1 and BTZ (see Materials and Methods) for 72 hours in the absence or presence of deferoxamine (DFO) (100 μM) or 2,2′-dipyridyl (10 μM), and cell viability was assessed by crystal violet staining. (E) Representative confocal images of the indicated TNBC cell lines and T47D cells stained with C11-BODIPY (10 μM) as described in Materials and Methods. The cells were treated with cumene hydroperoxide (CH) (100 μM, 3 hours) as a positive control, and either with JQ1 + SB225022 or with JQ1 and BTZ (see Materials and Methods) for 16 hours. Scale bar, 10 μm. (F) Assessment of lipid peroxidation in breast cancer cells in response to BET and proteasome inhibition. TNBC (gray) and non-TNBC (green) cell lines were incubated with JQ1 and BTZ (see Materials and Methods) for 16 hours or with CH (100 μM, 3 hours). Where indicated, glutathione (1 mM; see Materials and Methods) was applied. Lipid peroxidation is shown as the ratio between fluorescence emission at 510 nm (green) and 590 nm (red) (see Materials and Methods). Mean values of three experiments are shown (mean values ± SD; table S7).
Fig. 5
Fig. 5. Effects of BET and proteasome co-inhibition on cellular iron, GSH, and ROS levels.
(A and B) Inhibition of BET and the proteasome increased iron levels (A) and decreased GSH levels (B) in TNBC cell lines. TNBC and non-TNBC (MCF7, SKBR3, T47D, and BT474) cells were incubated with JQ1 and BTZ (see Materials and Methods) for 16 hours, and total iron (A) and reduced GSH (B) levels were measured as described in Materials and Methods. Mean values of three experiments are shown (mean values ± SD; table S8). (C) Inhibition of BET and the proteasome increased ROS in TNBC cells. The indicated breast cancer cells were treated with JQ1 and BTZ (see Materials and Methods) for 12 hours or with tert-butyl hydrogen peroxide (TBHP; 100 μM) for 2 hours. Where indicated, GSH (1 mM) was applied 1 hour before drug treatment. Cells were then incubated with CM-H2DCFDA to measure ROS as described in Materials and Methods. Results are expressed as folds of control in at least three experiments (mean values ± SD; table S9).
Fig. 6
Fig. 6. BET and proteasome inhibition strongly affects GPX4 level and transcription of key ferroptotic genes.
(A) Box plot showing the expression of GPX4 in patients with breast cancer grouped by PAM50. The differences between the BL patients and any other PAM50 groups are significant (t test, P < 0.001). (B and C) Effects of BET and proteasome inhibition on the levels of GPX4 protein (B) and transcript (C). The indicated TNBC cell lines were treated with JQ1, BTZ, or both (see Materials and Methods) for 24 hours. Levels of GPX4 protein were assessed by WB. Intensities of GPX4 bands were quantified, normalized, and presented as fold of control in the bar graph (B). GPX4 mRNA levels were assessed by qPCR. Mean values ± SD of at least two repeats are shown (C). (D) Effects of BET and proteasome inhibition on level of GPX4 protein and transcript in 4T1 tumors. Representative IHC staining of 4T1 tumors treated with OTX015 (25 mg/kg per day, orally), BTZ (0.25 mg/kg, IP, every fourth day), or both to detect protein expression is shown. GPX4 mRNA levels were evaluated by qPCR. Results are mean values ± SD of at least six mice per group. (E) Effects of BET and proteasome inhibition on level of GPX4 transcript and additional key ferroptosis genes. The indicated TNBC cell lines were treated with JQ1 and BTZ (see Materials and Methods) for 24 hours, and mRNA levels of the indicated genes were assessed by qPCR. The results are reported as fold of control. Mean values of at least three independent experiments are shown (mean values ± SD; table S11).
Fig. 7
Fig. 7. TNBCs are vulnerable to ferroptosis and enriched in ferroptosis signature.
(A) Cell viability of the indicated TNBC and non-TNBC cell lines in response to increasing concentrations of Fin56 or erastin. The indicated cells were treated with FIN56 or erastin for 72 hours, and cell viability was measured by MTT assays. Mean values ± SD of three independent experiments are shown. The differences in the area under the curve between the TNBC and non-TNBC are significant (fig. S8A). (B and C) GSEA plot of normalized enrichment score of ferroptosis pathway for either basal versus non-basal patients in the TCGA dataset (B) or TNBC versus non-TNBC cell lines in the CCLE dataset (C). Enrichment is significant, P value/FDR < 0.01. (D and E) Box plots showing the expression of SLC40A1 (D) and ACSL4 (E) in patients with breast cancer grouped by PAM50. The differences between the basal patients and any other PAM50 group are significant (t test, P < 0.001). (F) Heatmap of normalized expression of the ferroptosis gene signature (KEGG, 40 genes) in patients with breast cancer from the TCGA dataset (n = 956). Patients (in columns) are arranged by unsupervised clustering of gene expression. Bar at the top of the heatmap indicates the subtype of each patient (PAM50). Ferroptotic genes that also belong to the iron metabolism or GSH signature are marked. (G and H) Levels of ferroptosis proteins and BRD4 in TNBC and non-TNBC cell lines. The expression levels of the indicated proteins were assessed by WB, and band intensities were quantified by ImageJ software. The relative expression in TNBC compared to non-TNBC is shown in the box plots (H) *P < 0.05, **P < 0.01.
Fig. 8
Fig. 8. IHC analysis of ferroptotic proteins in breast cancer samples.
(A to D) Representative images of IHC analysis of breast cancer specimens from patients with TNBC and non-TNBC patients immunostained with antibodies against GPX4 (A), GSS (B), Ferroportin (FPN) (C), and TfR (TFRC) (D). Approximately 65 breast cancer tissues were immunostained for each protein, and staining intensity was scored as described in Materials and Methods. The H-score of patients with TNBC relative to non-TNBC patients is shown in the scatter graphs. Percentages of tumors with low- or high-intensity scores are shown in the middle or right graphs along with representative images. Overall view of the entire section is shown as an insert for each image. Scale bars, 50 μm. Unpaired two-tailed t test was used to compare differences between H-scores of patients with TNBC and non-TNBC patients. Fisher’s exact test was applied to compare percentage of tumor sections with high or low protein expression between TNBC and non-TNBC groups.
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