CYP1A1 Regulates Breast Cancer Proliferation and Survival

Cytochrome P450 1A1 (CYP1A1) is an extrahepatic phase I enzyme that metabolizes endogenous and xenobiotic substrates. Prior studies implicating CYP1A1 in cancer have dealt primarily with the metabolic activation of procarcinogens including polycyclic aromatic hydrocarbons and estradiol (1–4). Other studies have focused on associations between CYP1A1 single-nucleotide polymorphisms (SNP) and increased cancer incidence. For example, the A2455G allele has been implicated with increased breast cancer risk in Caucasian populations (4, 5). Nonetheless, lack of associations between SNPs and cancer has been reported, and these discrepancies have been attributed to ethnic variations between populations, variation in sample size, and lack of confirmation of protein expression (6). However, little is known about the roles of CYP1A1 in cancer biology in the absence of xenobiotic exposure.

Under physiologic conditions, CYP1A1 expression is suppressed but it is induced in the presence of substrates via the transcriptional regulation of the aryl hydrocarbon receptor (AhR; ref. 4). In recent years, studies have shown that breast tumors constitutively express CYP1A1 (7, 8). Murray and colleagues profiled the expression levels of 21 CYPs in 170 breast tumors from patients who had not received prior adjuvant treatment. This profiling revealed that CYP1A1 was expressed in about 90% of breast tumors. Even so, the degree of CYP1A1 expression varied among tumors and did not correlate with estrogen receptor (ER)-α levels, tumor grade, or clinical outcome (7). Vinothini and colleagues reported on the expression levels of various xenobiotic-metabolizing enzymes, including CYP1A1, in 60 breast tumors from newly diagnosed patients who had not received prior adjuvant therapy. Their study showed that CYP1A1 levels were: (i) elevated in tumors compared with adjacent breast tissue, (ii) higher in premenopausal compared with postmenopausal patients, and (iii) positively correlated with tumor grade (8). These studies provide evidence that CYP1A1 is expressed to varying degrees in breast tumors and may be associated with cancer biology. Moreover, because of its ubiquitous expression in breast cancer and its ability to metabolize xenobiotics, interest has been shown to exploit CYP1A1 activity for breast cancer therapeutics (9–12). Nonetheless, little is known about the activities of CYP1A1 that may participate in breast cancer progression. Therefore, better understanding the function of CYP1A1 in breast cancer will assist in the development of targeted therapy and improve treatment strategies.

The purpose of this study was to determine the biologic functions and roles in signal transduction of CYP1A1 in breast cancer cells. Toward this goal, we used siRNA to knock down CYP1A1 in the breast cancer lines MCF7 (ER-positive; ER⁺) and MDA-MB-231 (triple negative; ER−/PR−/HER2−). We determined that CYP1A1 knockdown decreases proliferation, decreases colony formation, blocks the cell cycle at G₀–G₁ associated with reduction of cyclin D₁, and increases apoptosis associated with reduction of survivin. CYP1A1 silencing reduces proliferation and survival, at least in part, through increased phosphorylation of AMP-activated protein kinase (AMPK) and reduced phosphorylation of AKT, extracellular signal-regulated kinases (ERK)-1 and 2, and 70 kDa ribosomal protein S6 kinase (P70S6K). Consistent with CYP1A1siRNA results, pharmacologic reduction of CYP1A1 levels by carnosol also impairs proliferation and induces AMPK phosphorylation. Together, these results implicate CYP1A1 in cell proliferation and survival pathways. In addition, modulation studies of CYP1A1 activity via 2,3,7,8-tethachlorodibenzo-p-dioxin (TCDD, inducer) and α-naphthoflavone (inhibitor) indicate that reduction of CYP1A1 expression levels is critical for these biologic effects and cannot be substituted by modulation of its activity alone. The evidence presented here suggests that CYP1A1 silencing is a potential therapeutic strategy for breast cancer independent of ER status.

Minimum essential medium (MEM) and cell culture supplements are from GIBCO/Invitrogen/Life Technologies. Charcoal/dextran-stripped serum and FBS from HyClone. ON-TARGETplus CYP1A1- and NTsiRNA pools (sequences below) are from Thermo Scientific Dharmacon. Oligofectamine, Opti-MEM, SuperScript III First-Strand synthesis system, and SYBR GreenER qPCR SuperMixes for iCycler are from Invitrogen/Life Technology. All primers were purchased from Integrated DNA Technologies. The QiaShredder columns, RNeasy Mini Kit, QuantiTect Reverse Transcription Kit, and RNase-A are from Qiagen. The Wright–Giemsa was purchased from Thermo Fisher Scientific. Carnosol was purchased from Cayman Chemical and dissolved in dimethyl sulfoxide (DMSO) to a final concentration of 40 mmol/L. Anti-actin antibody (HHF-35), MG-132, and compound C are from Calbiochem/EMD Millipore. The tetrazolium salt, propidium iodide, NP-40, cell culture grade DMSO HYBRI-MAX, ethoxyresorufin, α-naphthoflavone, and sodium citrate are from Sigma. TCDD is from AccuStandard. Protease and phosphatase inhibitors are from Sigma and Roche. Human fibronectin (#356008) and the apoptosis detection kit are from BD Pharmingen. Anti-phospho-p70S6 kinase (Thr421/Ser424) is from Millipore. Antibodies raised against total and phosphorylated forms of the following proteins were obtained from Cell Signaling Technology: mTOR (p-Ser2448/clone D9C2), ERK1/2 (p-Thr202/Tyr204), Akt (total clone 40D4 and p-Ser473), LKB1 (total), AMPK (total clone F6 and p-Thr172/clone 40H9), P70S6K (total). Anti-CDK4 is from Santa Cruz Biothecnology. Anti-survivin antibody is from R&D Systems. Anti-CYP1A1 (ab3568) was obtained from Abcam. Anti-GAPDH antibody is from Research Diagnostics/Fitzgerald Industries. The ECL Western blotting detection reagent was purchased from GE Healthcare/Biocompare.

The lines MDA-MB-231 and MCF7 were purchased from American Type Culture Collection and grown at 37°C under 5% CO₂. Unless otherwise indicated, cells were grown and maintained in complete medium (MCF7: MEM, 10% FBS, 1% l-glutamine, 1% penicillin/streptomycin, and 1% HEPES; MDA-MB-231: MEM, 10% FBS, 1% l-glutamine, 1% penicillin/streptomycin, 1% sodium pyruvate, and 2 μg/mL insulin). Because antibiotics reduce transfection efficiency, for all siRNA transfection experiments cells were passaged once in antibiotic-free medium (AFM) before plating for the experiments and maintained in this medium throughout the duration of the experiment. MCF7: 10% charcoal/dextran-stripped serum, phenol red-free MEM, 1% HEPES, and 1% l-glutamine; MDA-MB-231: 10% FBS, phenol red- free MEM, 1% sodium pyruvate, 1% l-glutamine, and 2 μg/mL insulin).

To knock down CYP1A1 or AhR levels, cells were transfected with a pool of siRNA designed by Dharmacon (sequences below). Cells were seeded at 30% confluence on 6-well plate and incubated overnight. Before transfection, cells were washed twice with phenol red-free MEM and 0.8 mL of OptiMEM was added to each well. A transfection solution of 60 nmol/L siRNA suspended in 0.3% oligofectamine/OptiMEM was gently added to the cells (200 μL/well). After overnight incubation, AFM medium was added to obtain 10% serum medium. For transfection quality purposes, a separate well was transfected with siGLO green transfection indicator # D-001630-01. Sequences: human CYP1A1siRNA ON-TARGETplus SMARTpool #L-004790-00-0005: UCGACAAGGUGUUAAGUGA, AAAUGCAGCUGCGCUCUUA, CUACAGGUAUGUGGUGGUA, GAACUGCUUAGCCUAGUCA. ON-TARGETplus Human AhRsiRNA SMART pool # L-004990-00-0005: GCAAGUUAAUGGCAUGUUU, GAACUCAAGCUGUAUGGUA, GCACGAGAGGCUCAGGUUA, GCAACAAGAUGAGUCUAUU. Nontargeting siRNA ON-TARGETplus #1 D-001810-10: UGGUUUACAUGUCGACUAA, UGGUUUACAUGUUGUGUGA, UGGUUUACAUGUUUUCUGA, UGGUUUACAUGUUUUCCUA.

To evaluate CYP1A1 mRNA knockdown efficiency, total RNA was collected in lysis buffer (RLT) and β-mercaptoethanol, passed through a QiaShredder column, and purified using the RNeasy Mini Kit according to the manufacturer's protocol. First-strand cDNA was made using the QuantiTect Reverse Transcription Kit according to the manufacturer's protocol. The quantitative reverse transcriptase PCR (RT-PCR) was prepared using SYBR GreenER qPCR SuperMixes for iCycler and conducted at following temperatures: 50°C for 2 minutes, 95°C for 8.5 minutes, 40 cycles of 95°C for 15 seconds, and 60°C for 1 minute. The comparative C_t value method was used for data analysis (13). Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was used for normalization. Primer sequences: CYP1A1 forward: 5′-GCT GAC TTC ATC CCT ATT CTT CG-3′, reverse: 5′:TTT TGT AGT GCT CCT TGA CCA TCT-3′; GAPDH forward: 5′-GGG AAG GTG AAG GTC GGA GT-3′, reverse: 5′-GAG TTA AAA GCA GCC CTG GTG A-3′.

To evaluate siRNA specificity for CYP1A1 compared with other CYPs, total mRNA was collected and purified as described above. The cDNA was prepared using the First Strand Synthesis Kit according to the manufacturer's protocol (Invitrogen). Semiquantitative RT-PCR analysis of CYP1A1, CYP1A2, and CYP1B1 was conducted using SuperScript III Reverse Transcriptase (Invitrogen) and Taq Master Mix Kit according to manufacturer's protocol (Qiagen) in a PX2 Thermal Cycler (Thermo; 94°C for 2 minutes, 50 cycles: 94°C/30 seconds, 55°C/30 seconds, 72°C/45 seconds, 72°C for 10 minutes, and 4°C for 5 minutes). The PCR products were resolved in a 1.5% agarose gel and GAPDH was used to normalize samples. Primer sequences [Gene (amplicon size), F = forward primer (5′-3′), R = reverse primer (5′-3′)]: GAPDH (609 bp), F: CAC AGT CCA TGC CAT CAC TGC, R: GGT CTA CAT GGC AAC TGT GAG; CYP1A1 (294 bp), F: CTT CAT CCT GGA GAC CTT CC, R: AAG ACC TCC CAG CGG GCA A; CYP1A2 (371 bp), F: CAA TCA GGT GGT GGT GTC AG, R: GCT CCT GGA CTG TTT TCT GC; CYP1B1 (350 bp), F: TCA ACC GCA ACT TCA GCA ACT T, R: ATA GGG CAG GTT GGG CTG GTC A.

To evaluate protein levels, cell extracts were prepared using radioimmunoprecipitation assay extraction buffer (50 mmol/L Tris, pH 7.5, 150 mmol/L NaCl, 1% NP-40, 0.5% sodium deoxycholate, 0.1% SDS, 2 mmol/L EDTA, pH 8, 2 mmol/L EGTA pH 8, 1 mmol/L DL-dithiothreitol (DTT), 1 mmol/L phenylmethylsulfonylfluoride, 5 μmol/L phenylarsine oxide (PAO), 25 mmol/L NaF, 2 mmol/L Na3VO4, 100 μmol/L leupeptin, 2 μmol/L pepstatin, 2.8 μmol/L Tosyl-L-phenylalanyl-chloromethane (TPCK), 2.7 μmol/L Tosyl-L-lysyl-chloromethane hydrochloride (TLCK), 4.17 μmol/L 4-(2-aminoethyl)-benzenesulfonyl fluoride hydrochloride (AEBSF), 4.17 μmol/L chymostatin, 2 μmol/L aprotinin, 2 μmol/L antipain, 5 mmol/L N-ethyl-maliemide, and 40 μmol/L MG-132) and processed according to standard Western blot analysis. GAPDH was used as loading control and relative protein amounts were quantified by densitometry of X-ray film exposures using an Alpha-Innotec densitometer.

To assess viability, cells were incubated with 0.1 mg/mL of tetrazolium MTT for 2 hours at 37°C under 5% CO₂. The supernatant was replaced with DMSO. Proliferating cells reduce the yellow tetrazolium into DMSO-soluble purple formazan, which was read in a BioTek plate reader at an absorbance of 540 nm.

To assess cell survival, 200 transfected cells were seeded onto fibronectin-coated 6-well plates and incubated for 14 days until visible colonies were observed. Colonies were fixed and stained with Wright–Giemsa and total colony number was counted. Plate preparation: 1 mL fibronectin (10 μg/mL in PBS) incubated overnight at 4°C, then blocked with 3% bovine serum albumin in PBS for 1 hour at room temperature, and rinsed with PBS before use.

To evaluate the cell-cycle distribution, cellular DNA content was measured by propidium iodide staining. Because MCF7 cells form clumps in the presence of ethanol, 2 different methods were used for fixing and staining. MDA-MB-231 method: cells were collected by trypsinization, washed with ice-cold PBS, resuspended in 200 μL of ice-cold 70% ethanol, incubated overnight at 4°C, centrifuged, washed with PBS, and finally resuspended in 0.5 mL of Nicoletti buffer (50 μg/mL propidium iodide, 0.1% sodium citrate, 0.1% Triton X-100, and 1 mg/mL RNase-A in PBS). MCF7 method: cells were washed twice with PBS over ice, scraped off the plate with 1 mL of PBS, collected and centrifuged for 5 minutes, resuspended in 0.5 mL of staining solution (0.1% sodium citrate, 50 μg/mL propidium iodide, 0.01% NP-40, and 1 μg/mL Rnase-A in water), and incubated overnight at 4°C. Following the respective staining methods, propidium iodide content was profiled using a FACScalibur flow cytometer (BD Bioscience). Cell-cycle distribution was determined using the Watson Pragmatic algorithm in the FlowJo software.

To evaluate cell death, cells were collected by trypsinization, washed with PBS, and stained with propidium iodide and Annexin-V/Fluorescein isothiocyanate (FITC) for 15 minutes at room temperature. Stained cells were evaluated using a FACScalibur flow cytometer (BD Bioscience) and the results were analyzed with FlowJo software (Tree Star).

To assess CYP1A1 activity, an ethoxyresorufin-O-deethylase (EROD) assay adapted from refs. (14, 15) was used. Cells were plated onto 6-well plates, treated as desired, washed 2 times with 1× PBS, then incubated at 37°C for 60 minutes with 2 mmol/L ethoxyresorufin in buffer (50 mmol/L Tris, 0.1 mol/L NaCl, 6.25 mmol/L MgCl₂, pH 7.8, warmed to 37°C). A 100 μL aliquot of the assay supernatant was transferred to a black-wall clear bottom 96-well plate, and fluorescence was read in a BioTek fluorescence plate reader at excitation λ(530 nm)/emission λ (590 nm). When necessary, fluorescent counts were normalized to total cell number.

All experiments were reproducible and carried out at least in triplicate. Statistical significance (P values) was calculated using 2-tailed Student t test. Equality of variance was determined by F test.

The purpose of this study was to understand the biologic roles of CYP1A1 in MCF7 and MDA-MB-231 breast cancer lines. We chose ER⁺ and triple-negative breast cancer because there is a significant unmet need for new treatments for metastatic hormone therapy refractory and triple-negative breast cancer. To achieve the goal of defining the role of CYP1A1 in breast cancer growth, pooled siRNA was used to knock down CYP1A1 mRNA and protein. To validate the knockdown efficiency, CYP1A1 mRNA and protein levels were measured by quantitative RT-PCR and by Western blot analysis, respectively. Significant reductions of CYP1A1 mRNA and protein levels were observed between 48 and 120 hours. CYP1A1 mRNA levels were reduced by 53% (P = 0.002) in the MCF7 line and by 70% (P = 6 × 10⁻⁶) in MDA-MB-231 line (Fig. 1A, top). CYP1A1 protein levels were reduced by 64% (P = 0.02) in the MCF7 line and by 52% (P = 0.04) in the MDA-MB-231 line (Fig. 1B). Because CYP1A1 shares 73% identity with CYP1A2 and 41% identity with CYP1B1, we also evaluated by semiquantitative RT-PCR whether CYP1A1siRNA alters the mRNA levels of these CYP1 family members. No change was observed in the levels of these CYPs indicating that the biologic effects observed are specifically due to reduction of CYP1A1 (Fig. 1A, bottom).

To investigate the functional roles of CYP1A1 in breast cancer, we determined the effects of CYP1A1 knockdown on 2 “hallmarks of cancer:” uncontrolled cell proliferation and loss of inhibition of cell death. First, we examined the effects of CYP1A1 knockdown on the ability of MCF7 and MDA-MB-231 cells to proliferate. After transfection for 48, 72, and 96 hours, viable cells were measured by MTT assay. CYP1A1siRNA reduces the proliferation of both lines. At 96 hours of transfection with CYP1A1siRNA, proliferation was reduced by approximately 40% for the MCF7 and MDA-MB-231 lines (Fig. 1C; P < 0.001).

To determine the effects of CYP1A1 knockdown on cell survival, we conducted a clonogenic assay to count the cells able to survive and proliferate to form visible colonies. MCF7 and MDA-MB-231 cells were transfected for 48 hours, seeded at low density onto fibronectin-coated plates, and colonies were counted after 2 weeks of culture. Compared with NTsiRNA control, CYP1A1siRNA inhibited colony formation of MCF7 line by 82% (P = 4 × 10⁻⁶) and of MDA-MB-231 line by 56% (P = 0.03; Fig. 1D). Together these results indicate that CYP1A1 silencing impairs proliferation and survival of breast cancer cells.

The AhR localizes to the cytosol of MCF7 cells and translocates to the nucleus upon ligand activation. In contrast, MDA-MB-231 cells display primarily nuclear AhR expression. In both lines, nuclear AhR is responsible for the inducible transcriptional regulation of CYP1A1. Given the important role of AhR in the regulation of CYP1A1, it is possible that the biologic functions of CYP1A1 may be affected by or be dependent on the AhR status. To determine whether AhR is required for the roles of CYP1A1 on cell proliferation, we investigated the impact of siRNA-mediated knockdown of AhR on basal CYP1A1 expression and cell proliferation. Although AhRsiRNA reduces AhR levels by at least 70% (P < 0.05) in both lines, the levels of CYP1A1 remain unaffected (Supplementary Fig. S1A). Therefore, this system allows us to distinguish AhR-specific effects. As assessed by MTT assay, the proliferation of these lines is not impaired by AhR knockdown (Supplementary Fig. S1B), suggesting that the effects of CYP1A1 knockdown on cell proliferation and survival (Fig. 1) may be independent of the AhR expression status of these lines.

The ability of cells to proliferate depends on the balance between cell growth, division, and death. For this reason, we investigated the effect of CYP1A1 knockdown on the ability of MCF7 and MDA-MB-231 lines to progress through the cell cycle. To achieve this goal, cells were transfected for 48 hours, permeabilized, stained with propidium iodide, and cell-cycle distribution was analyzed by flow cytometry. The G₀–G₁ populations of MCF7 and MDA-MB-231 lines increased by 37% (P = 0.001) and 20% (P = 0.003) respectively, consistent with a block in the cell cycle at G₀–G₁ (Fig. 2A).

Because the cyclin D₁/CDK4 complex regulates the G₁–S transition of the cell cycle (16), we investigated the effects of CYP1A1 knock down on these regulatory proteins. Cyclin D₁ levels were reduced by 74% (P = 0.001) in MCF7 line and by 36% (P = 0.001) in MDA-MB-231 line (Fig. 2B). CDK4 levels were not significantly reduced in both lines, although a trend toward reduction is observed. These results suggest that CYP1A1 knockdown may block the cell cycle, at least in part, through downregulation of cyclin D₁.

To further understand the antiproliferative effects of CYP1A1 silencing, apoptosis was measured by flow cytometry. In this assay, cells were transfected for 48 hours, stained with propidium iodide and Annexin-V/FITC, and analyzed by flow cytometry. CYP1A1 silencing of the MCF7 line correlated with a 50% increase in the early (bottom right) and late (top right quadrant) apoptotic populations (Fig. 3A; P < 0.05). CYP1A1 silencing of the MDA-MB-231 line correlated with a 50% increase in the late apoptotic population (Fig. 3A; P = 0.006).

Survivin is an antiapoptotic protein of the inhibitor of apoptosis family whose importance in breast cancer, including MCF7 and MDA-MB-231 lines, has been established (17, 18). Therefore, to further understand the role of CYP1A1 in apoptosis, we measured the effects of CYP1A1 knockdown on the levels of survivin. Consistent with increased apoptosis, we observed that CYP1A1 knockdown was associated with an 80% reduction of survivin (P = 0.003) in MCF7 line and a 56% reduction (P = 0.04) in MDA-MB-231 line (Fig. 3B).

Because the MAP–ERK kinase (MEK)/ERK and phosphoinositide 3-kinase (PI3K)/AKT signaling pathways promote the growth of breast cancer (19–22), we determined whether CYP1A1 knockdown inhibits ERK1/2 and/or AKT phosphorylation in these lines (Fig. 4). CYP1A1 knockdown reduced phosphorylation of ERK in both lines, most notably by 45% (P = 0.001) in the MCF7 line (Fig. 4). CYP1A1knockdown resulted in reduction of AKT phosphorylation by 45% (P = 0.02) in MCF7 line and by 65% in MDA-MB-231 line (P = 0.004; Fig. 4). These reductions in phosphorylation correlate with downstream inhibition of the protein synthesis regulator P70S6K (23, 24). Phosphorylation of P70S6K was reduced by 53% (P = 0.001) in the MCF7 line and by 37% (P = 0.03) in the MDA-MB-231 line (Fig. 4). These results implicate CYP1A1 upstream of the ERK and PI3K/AKT pathways.

Although reduction of P70S6K phosphorylation caused by CYP1A1 silencing could be related to loss of ERK1/2 and PI3K/AKT signaling, this inhibition could also be due to activation of AMPK, a major regulator of cellular bioenergetics and metabolic tumor suppressor (25). CYP1A1 knockdown increases phosphorylation of AMPK 5.6-fold (P = 0.01) in the MCF7 line and 2.4-fold (P = 0.02) in MDA-MB-231 line (Fig. 4). The activation of AMPK phosphorylation by CYP1A1 silencing in conjunction with concomitant downregulation of ERK1/2 and AKT phosphorylation is consistent with known cross-talk with AMPK (26–28) and potentially places CYP1A1 as a candidate upstream regulator of these kinases. The levels of LKB1, a known regulator of AMPK (29), were determined by Western blot analysis in the MCF7 line. Although an initial marginal reduction of LKB1 by CYP1A1siRNA was observed (48 hours transfection fold change = 0.70, P = 0.047), this reduction was not sustained at longer time points (72–96 hours; 96 hours transfection fold change = 1.01, P = 0.98). This suggests that LKB1-dependent and LKB1-independent mechanisms of AMPK activation may be involved. A possible model summarizing these mechanisms is presented in Fig. 7.

We hypothesized that if AMPK signaling is necessary for the biologic effects of CYP1A1 knockdown, then blocking AMPK activation should abrogate these effects. To test this hypothesis, MCF7 cells were transfected for 24 hours with CYP1A1siRNA, followed by treatment for 24 hours with either vehicle (DMSO) or the AMPK inhibitor compound C (6-[4-(2-Piperidin-1-yl-ethoxy)-phenyl)]-3-pyridin-4-yl-pyyrazolo[1,5-a] pyrimidine; from now on abbreviated as CC). The reverse order of treatment (i.e., 24 hours treatment with DMSO or CC followed by NT/CYP1A1siRNA transfection) was also conducted, leading to similar results. Following treatment, apoptosis was measured by flow cytometry, and the percentage of overall cell death was calculated as follows: ΣDead = % early apoptotic +% late apoptotic +% necrotic populations. It should be noted that because compound C induces cell death in MCF7 line (ref. 30; and confirmed in Fig. 5), the results are interpreted only within the context of treatment (i.e., DMSO or CC) as shown in the diagram on Fig. 5. Therefore, within the context of vehicle treatment CYP1A1siRNA increases cell death [Fig. 5; ΣDead (NTsi+DMSO) = 27% vs. ΣDead (1A1si+DMSO) = 44%; P = 0.01)]. This proapoptotic effect of CYP1A1siRNA in the presence of vehicle is consistent with our results in Fig. 3 and confirms that these effects are due to CYP1A1siRNA and not vehicle treatment.

Within the context of CC treatment, 2 potential outcomes could be expected depending on whether AMPK is necessary for the proapoptotic effects of CYP1A1siRNA (Fig. 5, Diagram): (i) if AMPK is necessary, then inhibition of AMPK would prevent CYP1A1siRNA-induced apoptosis and thus less cell death would be observed with “1A1si + CC” treatment compared with “NTsi + CC” treatment, (ii) on the other hand, if AMPK in not necessary, then inhibition of AMPK would not abrogate the proapoptotic effects of CYP1A1siRNA but would instead add to the proapoptotic effects of CYP1A1siRNA, thus resulting in an increase in cell death when treated with “1A1si + CC” compared with “NTsi + CC”. Our results agree with the first scenario, 72% total cell death is observed with “NTsi + CC,” whereas 46% total cell death is observed in “1A1si + CC” (Fig. 5; P = 0.003). This reduction of cell death observed for CYP1A1 knockdown cells treated with the AMPK inhibitor (CC) indicates that AMPK is necessary for the effects of CYP1A1siRNA and agrees with our findings showing that CYP1A1siRNA induces AMPK signaling (Fig. 4). Together, these results suggest that AMPK phosphorylation may be repressed by CYP1A1 and reduction of CYP1A1 levels promotes AMPK phosphorylation. In this manner, AMPK may be required for the effects of CYP1A1siRNA on cell death (Fig. 7).

To further test whether CYP1A1 signals, in part, through AMPK, we sought a pharmacologic approach to reduce CYP1A1 levels (31). Carnosol inhibits the AhR, a transcription factor that regulates the inducible and basal expression of CYP1 family members including CYP1A1 (31). Carnosol has been shown to reduce basal CYP1A1 expression in premalignant tongue and bronchial lines and in prostate cancer lines (31–33). Treatment with carnosol inhibits the proliferation of the MCF7 and MDA-MB-231 lines exhibiting IC₅₀ values of approximately 40 μmol/L for both lines (Fig 6A; P < 0.001). We carried out time-course experiments to investigate early effects (i.e., 2–12 hours) of carnosol treatment on CYP1A1 expression and determined that the optimal time for CYP1A1 reduction is 8 hours (Fig. 6B; P < 0.05). Carnosol treatment reduces AhR levels in both lines by more than 50% (Fig. 6B; P < 0.05). In agreement with CYP1A1siRNA results (Fig. 4), treatment of the MCF7 and MDA-MB-231 lines with 40 μmol/L carnosol for 8 hours results in the activation of AMPK (Fig. 6B; P < 0.01). This suggests that CYP1A1 reduction, whether by siRNA or carnosol, is associated with inhibition of proliferation mediated, in part, through activation of AMPK signaling.

Because carnosol inhibits both AhR and CYP1A1 levels, we tested whether the antiproliferative effects of carnosol were mediated through AhR-dependent mechanisms. As previously shown, knockdown of AhR does not reduce basal CYP1A1 levels (Supplementary Fig. S1A), suggesting that carnosol inhibits basal CYP1A1 through an AhR-independent mechanism. Therefore, to better understand these mechanisms, we tested whether AhR is required for the therapeutic effects of carnosol. If so, we would expect AhR knockdown to shift the dose–response curve of carnosol. Treatment of AhR knockdown cells with carnosol does not result in a shift of the dose–response curve (Supplementary Fig. S1C), further supporting that carnosol's effects may be independent of AhR. Therefore, together these results suggest that carnosol's antiproliferative effects are primarily due to CYP1A1 reduction, AMPK activation, and potentially other yet unidentified mechanisms.

To this point, we have focused on the impact of CYP1A1 levels in the biology of breast cancer cells. Nonetheless, for therapeutic development purposes, we should distinguish between the expression levels and the enzymatic activity of CYP1A1. To address this issue, we tested whether inhibition and/or induction of CYP1A1 activity affects breast cancer cell proliferation.

First, the effects of inhibiting CYP1A1 activity on cell proliferation were determined. To achieve this we first evaluated whether CYP1A1siRNA affects the activity of CYP1A1. To test this, cells were transfected with CYP1A1siRNA for 48 hours, and TCDD-induced CYP1A1 activity was measured by EROD assay. CYP1A1 knockdown reduces CYP1A1 EROD activity by 38% (P = 0.04) in MCF7 line, but it is unaffected (P = 0.52) in MDA-MB-231 line (Supplementary Fig. S2A). These results led us to hypothesize that, although reduction of CYP1A1 levels is necessary for impaired proliferation (Fig. 1), this effect on proliferation may not be dependent on the inhibition of CYP1A1 activity. To further test this hypothesis, we measured the effects of inhibiting CYP1A1′s activity on cell proliferation. Cells were treated with 1 μmol/L of α-naphthoflavone, an inhibitor of CYP1A1 activity that does not affect CYP1A1 levels (Supplementary Fig. S2B and data not shown). Inhibition of CYP1A1 activity by α-naphthoflavone does not affect cell proliferation (Supplementary Fig. S2C), supporting the hypothesis that reduction of CYP1A1 levels, but not its activity, is required for impairment of proliferation and survival (Fig. 1).

Second, the effects of inducing CYP1A1 activity on cell proliferation were determined. Cells were treated with the CYP1A1 inducer TCDD, which results in increased CYP1A1 levels and activity. Treatment with 5 to 20 nmol/L TCDD induces CYP1A1 activity, but does not stimulate cell proliferation (10 nmol/L shown in Supplementary Fig. S2D–S2E). It is noteworthy that the induction of CYP1A1 activity is the greatest in the MCF7 line, when compared with MDA-MB-231, which is likely attributable to differences in AhR status in these lines (Supplementary Fig. S2D). These results suggest that breast cancer lines, MCF7 and MDA-MB-231, have an optimal amount of CYP1A1 protein and further increasing its level or activity may not enhance the proliferative capability of these lines.

Together, our findings suggest that the development of therapeutic strategies to target CYP1A1 should consider the expression levels of the protein and not just its activity. Nonetheless, it remains to be determined whether CYP1A1′s enzymatic activity or a yet unidentified function(s) is mechanistically responsible for the proliferative and survival cell signaling identified in the present studies.

Recent studies showing that CYP1A1 is expressed in breast tumors (7, 8) led us to investigate the functional roles of CYP1A1 in the proliferation, survival, and signal transduction of breast cancer cells. Although CYP1A1 has been extensively studied in context of extrahepatic drug metabolism, little is known about its roles in cancer progression and cancer cell signal transduction in the absence of xenobiotics. In this study, we provide evidence that CYP1A1 silencing impairs proliferation and survival, in part, through activation of AMPK phosphorylation and reduction of AKT, ERK, and P70S6K signaling. These results mean that CYP1A1 is not only involved in the metabolism of xenobiotics, but also has its own role in breast cancer progression.

The PI3K/AKT and the MEK/ERK pathways are critical for breast cancer progression (19–22). Knockdown of CYP1A1 correlates with decreased phosphorylation of AKT (Ser473) and ERK1/2 (Thr202/Tyr204). CYP1A1 silencing also correlates with induction of AMPK tumor suppressor via phosphorylation of Thr172 in the catalytic subunit α. The AKT oncogene promotes proliferation via inhibition of the TSC1/TSC2 complex upstream of the mTOR/P70S6K pathway (34). In contrast, AMPK activates the TSC1/TSC2 complex thereby inhibiting protein synthesis and growth (35, 36). In this manner, AKT and AMPK signaling converge on P70S6K to regulate cell proliferation (24, 37).

The effects of CYP1A1 knockdown on cell proliferation correlate with cell-cycle arrest and increased apoptosis. Our results indicate that cyclin D₁ is suppressed by CYP1A1 knockdown and correlates with a decrease in G₁–S cell-cycle progression. In contrast, in the absence of TCDD induction, AhR knockdown does not seem to significantly affect basal CYP1A1 expression (Supplementary Fig. S1A), cyclin D₁, or cell-cycle profile (38). AKT and ERK1/2 promote G₁–S transition of the cell cycle by stabilizing cyclin D₁, whereas AMPK activation inhibits this transition by decreasing cyclin D₁ levels, (39–42). In addition, AKT and ERK1/2 regulate apoptosis through the antiapoptotic protein survivin (43, 44). Other feedback regulations between AKT, ERK1/2, and AMPK have also been described (26–28, 45). Therefore, based on these previous findings, the effects of CYP1A1 silencing on proliferation, cell cycle, and apoptosis are consistent with inhibition of AKT, ERK1/2, and P70S6K and activation of AMPK signaling. Moreover, our results showing that AMPK inhibition by compound C abrogates CYP1A1siRNA-mediated apoptosis further suggest that CYP1A1 signals through AMPK.

In light of previous findings and the evidence presented in this study, we propose a model where CYP1A1 silencing inhibits AKT and ERK phosphorylation, thereby activating AMPK signaling (Fig. 7; steps 1–4). AMPK activation and concurrent loss of AKT signaling result in the inhibition of mTOR/P70S6K signaling (Fig. 7; steps 5–8), which consequently decreases synthesis of proliferative and prosurvival proteins such as cyclin D₁ and survivin (Fig. 7; step 9). These findings differ from other cytochrome P450 enzymes, such as CYP3A4, which may act primarily through activation of STAT3 and regulation of the G₂–M checkpoint (46). Our model, however, has limitations because it remains to be determined whether CYP1A1 affects these signaling pathways through its enzymatic activity or by other as yet unidentified functions. The results presented suggest that CYP1A1 expression is critical for these biologic functions and the roles of CYP1A1 in cancer cell growth may not be abrogated by inhibition of its measurable (EROD) enzymatic activity alone. Moreover, it is possible that CYP1A1 may be carrying functions distinct from its canonical metabolic functions. Novel hypotheses about nonenzymatic and enzymatic functions of CYP1A1 in cancer cell growth remain to be investigated.

Inhibition of the PI3K/AKT and MEK/ERK pathways correlating with CYP1A1 silencing is important because cross-talk between these pathways displays synergistic effects when combined inhibition is used for cancer therapeutics (23). The involvement of CYP1A1 in both pathways suggests that CYP1A1 may be a promising target for cancer therapeutics. Furthermore, because CYP1A1 silencing significantly inhibits proliferation and survival of ER⁺ and triple-negative breast cancer lines, the results presented in this study may have therapeutic implications for breast cancer independent of ER status. The effect of CYP1A1 knockdown on cell death appears to be greater in ER⁺ MCF7 line than in triple-negative MDA-MB-231 line, whereas both lines appear to be strongly inhibited at the G₁–S checkpoint. Whether strategies to inhibit CYP1A1 would be more effective in ER⁺ compared with triple-negative breast cancer or effective in both remain to be determined.

The widespread expression of CYP1A1 in breast cancer has been exploited as a strategy to activate prodrug compounds to cytotoxic intratumoral metabolites. For example, drugs of the 2-(4-aminophenyl)benzothiazole class such as 5F 203 (Phortress; ref. 47) and aminoflavone drugs (48) exhibit potent antitumor properties in xenograft models and have been moved forward to clinical trials (9, 12, 47, 49). The proposed mechanism of action is that these agents induce and are activated by CYP1A1 into electrophilic metabolites that bind to and damage DNA, thus resulting in tumor growth arrest. Of considerable interest, the benzothiazoles and aminoflavone seem to be active in ER⁺ but not triple-negative breast cancer (10, 47). Our results suggest that an alternative approach to exploit CYP1A1 expression in breast cancer through reduction of basal levels may extend the range of CYP1A1-targeted approaches to triple-negative breast cancer.

Consistent with observations in other cell types (31, 32, 50), our results indicate that carnosol treatment inhibits breast cancer cell proliferation. This inhibition of proliferation in breast cancer lines is associated with reduced CYP1A1 expression and activation of AMPK, which has not been previously described in breast cancer. Although the activation of AMPK phosphorylation by carnosol may be part of a generalized stress response, these results provide new mechanistic information that carnosol is likely to affect bioenergetics in breast cancer in addition to exhibiting antioxidant properties. Our results suggest that the relevant target of carnosol in breast cancer may be reduction of CYP1A1 levels, resulting in AMPK phosphorylation, rather than modulation of AhR. The studies presented here suggest that reduction of CYP1A1 levels is a potential therapeutic strategy for breast cancer and that carnosol may be an approach to actualize this strategy.

In summary, we show that the basal level of CYP1A1, independent of measurable enzymatic (EROD) activity and AhR status, is important for breast cancer proliferation and survival. The identification of widespread expression of CYP1A1 in breast cancer suggests that its therapeutic potential could be exploited either by induction followed by metabolism of prodrugs to DNA-damaging agents (9, 11, 47) or by a new approach of CYP1A1 reduction. Our study suggests that strategies that directly lower CYP1A1 levels using RNA silencing or carnosol may be a potential new approach for breast cancer therapeutics.

No potential conflicts of interest were disclosed.

Conception and design: M. Rodriguez, D.A. Potter

Development of methodology: M. Rodriguez, D.A. Potter

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): M. Rodriguez, D.A. Potter

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): M. Rodriguez, D.A. Potter

Writing, review, and/or revision of the manuscript: M. Rodriguez, D.A. Potter

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): M. Rodriguez, D.A. Potter

Study supervision: D.A. Potter

We would like to thank the expert advice of Drs. Chee-Onn Leong, Tracey D. Bradshaw, Robert Harris, John Falck, Bruce Hammock, Ian Blair, Narayan Avadhani, Douglas Yee, Philip McGlave, Ameeta Kelekar, Ranjana Mitra, Zhijun Guo, and Monica Milani. We also appreciate Drs. James McCarthy, Carol Lange, Kaylee Schwertfeger for helpful discussions and serving on the thesis committee of MR. We also thank Dr. Deepali Sachdev and Dr. Elizabeth Wattenberg for kindly providing the cell cycle and quantitative RT-PCR protocols, respectively. Thanks to Dr. Kaylee Schwertfeger for critical reading of the manuscript.

This study was supported by National Institute of Health grants F31CA144084-02, T32 CA009138-38, and R01CA113570, and by the University of Minnesota OVPR Grant-in-Aid, University of Minnesota Department of Medicine Research Allocation, Masonic Cancer Center Support Grant P30CA077598, and the Randy Shaver Foundation and Community Fund.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.