Neurofibromatosis type 2 (NF2) is an autosomal dominant disorder characterized by the development of multiple tumors in the central nervous system, most notably schwannomas, and meningiomas. Mutational inactivation of the NF2 gene encoding the protein Merlin is found in most sporadic and inherited schwannomas, but the molecular mechanisms underlying neoplastic changes in schwannoma cells remain unclear. We report here that Nf2-deficient cells display elevated expression levels of key enzymes involved in lipogenesis and that this upregulation is caused by increased activity of Torc1. Inhibition or knockdown of fatty acid synthase (FASN), the enzyme that catalyzes the formation of palmitic acid from malonyl-CoA, drove NF2-deficient cells into apoptosis. Treatment of NF2-mutant cells with agents that inhibit the production of malonyl-CoA reduced their sensitivity to FASN inhibitors. Collectively, these results suggest that the altered lipid metabolism found in NF2-mutant cells renders them sensitive to elevated levels of malonyl-CoA, as occurs following blockade of FASN, suggesting new targeted strategies in the treatment of NF2-deficient tumors. Cancer Res; 77(18); 5026–38. ©2017 AACR.
Neurofibromatosis type 2 (NF2) is an autosomal dominant cancer predisposition syndrome that occurs due to inactivating mutations in the NF2 gene. NF2 is characterized by formation of multiple low-grade tumors along the peripheral nerves and in the central nervous system (1), and associated with disease manifestations that include benign schwannomas (including bilateral vestibular schwannomas, the hallmark of the disease), meningiomas, and ependymomas. Despite the benign nature of these lesions, NF2 is often fatal due to development of inoperable intracranial tumors. In addition, somatic mutations in the NF2 gene also contribute to malignant mesotheliomas and other tumors (2). To date there is no effective pharmacotherapy for NF2 and the morbidity and mortality of this inherited disorder remains high.
The NF2 gene product, merlin, is a member of the ezrin–moesin–radixin protein family and functions to regulate cell adhesion via receptor tyrosine kinases and integrins (3–7), proliferative and survival signaling via enzymes such as Rac, PAK, AKT, FAK, and MTOR (8–11), and to suppress tumorigenesis via inhibition of the E3 ubiquitin ligase CRL4/DCAF1 complex (12). In addition, Merlin signaling may also impact the MST/YAP contact inhibition signaling pathway (13). Loss of NF2 gene leads to inability of cells to form stable cell:cell junctions (14), and NF2-deficient cells do not show contact growth inhibition (4, 14). Conversely, Merlin overexpression blocks proliferation (15).
Currently, three targeted therapeutic approaches are being investigated for potential use in NF2: angiogenesis inhibitors such as bevacizumab (16, 17), EGFR inhibitors such as erlotinib and lapatinib (18), and MTOR inhibitors such as sirolimus and everolimus (19). While the use of such targeted agents has shown promise in early trials, the redundancy of proliferative, survival, and motility signaling cascades in Merlin-null cells suggests a need to identify additional therapeutic concepts and targets in this disorder.
Recently, there has been revived interest in targeting metabolic enzymes in various malignancies. Most of these efforts have attempted to exploit unique aspects of sugar metabolism in cancer, the so-called Warburg effect. However, cancer cells also require large amounts of lipid for membrane biosynthesis, energy, and signal transduction and such lipids are supplied by de novo fatty acid synthesis (20). Accordingly, enzymes involved in fatty acid metabolism, such as fatty acid synthase (FASN), are commonly upregulated in cancer cells, and inhibiting FASN or other enzymes involved in lipogenesis can induce apoptosis in such cells (21, 22). These data show that enzymes involved in lipid metabolism are potential therapeutic targets against cancers.
In this report, we used Nf2-deficient versus WT cells to screen for metabolic changes caused by Nf2 gene loss. We found that Nf2-deficient fibroblasts and Schwann cells display a variety of metabolic derangements involving lipid metabolism, in particular, a significant elevation of fatty acid levels. Further studies showed that Nf2-deficient cells are selectively sensitive to inhibitors of FASN. We report that siRNA or small-molecule inhibitors of FASN are toxic to Nf2-deficient cells, and that this toxicity appears to be related to a build-up of pro-apoptotic metabolic intermediates, in particular malonyl-CoA. Our findings define a new aspect of NF2 pathobiology that could be used to identify therapeutic agents in this syndrome.
Materials and Methods
Plasmids, antibodies, and reagents
pBabe-NF2 was obtained from Addgene. Anti-Fasn siRNA (M-040091-01-0005), anti-Acaca siRNA (M-063938-01-0005), anti-Mtor (M-065427-00-0005), anti-Rptor (M-058754-01-0005), anti-Rictor (M-064598-01-0005), and non-silencing (D-001206-13-05) siRNA were purchased from Dharmacon. Individual siRNAs against Mtor (SASI_Mm01-00164496 and -00164492), Rictor (-00137732 and -00137730), Rptor (-00055298 and -00334580), Fasn (-00177858 and -00177854), Acaca (-0011590 and -00115905), and Mlycd (-00028572 and -00028576) were purchased from Sigma-Aldrich. Anti-Merlin antibodies were purchased from Abcam (#ab88957). Lipid synthesis and metabolism antibody kit (includes anti-Fasn, -phospho ACC, -ACC, -Lipin1, -ACLY, -phospho ACLY, -ACSL1, and -ACECS1 antibodies), and anti-Casp3 antibodies were purchased from Cell Signaling Technology. Anti-SREBP1 antibodies were purchased from Santa Cruz Biotechnology. Anti-GAPDH antibodies were purchased from EMD-Millipore.
Cerulenin, C75, luteolin, 5-(tetradecyloxy)-2-furoic acid (TOFA) and 5-iodotubercidin were purchased from Enzo Life Sciences. GSK2194069, dimethylsulfoxyde (DMSO), staurosporin, sodium palmitate, 70% perchloric acid, ammonium formate, acetonitrile, acetyl-coenzyme A lithium salt, malonyl coenzyme A lithium salt, propionyl-coenzyme A lithium salt, and poly-L-lysine were purchased from Sigma-Aldrich.
DMEM, DMEM/F12, PBS, N2 supplement, 0.05% trypsin, and Alamar Blue were purchased from Life Technologies. FBS was purchased from Atlanta Biologicals, heregulin-1 from R&D Systems, forskolin and laminin from EMD Millipore, and the WST-1 assay kit from Clontech.
Nf2f/f mouse embryo fibroblasts (MEF) carrying flox site in exon 2 of Nf2 gene (23), FC912 (Nf2f/f) mouse Schwann cells, FH912 (Nf2-deficient) mouse Schwann cells, and SC4-9 (Nf2-deficient) mouse schwannoma cells were a generous gift of Dr. Marco Giovannini (House Ear Institute, CA), obtained in 2012. RT4 rat schwannoma cells were obtained from the ATCC in 2012. All cell lines except FH912 and FC912 were grown in DMEM GlutaMAX with high glucose, 1 mmol/L sodium pyruvate, 0.1 mmol/L non-essential amino acids and 10% FBS at 37°C, 5% CO2. FH912 and FC912 cells were grown in DMEM:F12 with 2 mmol/L forskolin, 10 ng/ml heregulin, and N2 supplement on laminin–poly-L-lysine coated plates. MEF Nf2f/fcells were immortalized with pMSE-SV40LT plasmid. Deletion of the Nf2 gene from MEF Nf2f/fcells was achieved by transfecting these cells with a pMSCV-Cre-GFP plasmid and sorting for GFP-positive cells. Cell line authentication was confirmed by two methods. First, Nf2 deletion was confirmed by PCR genotyping and by immunoblotting (data not shown). Second, the species of origin was confirmed by short tandem repeat profiling. For the re-expression of merlin in Nf2-deficient schwannoma cells SC4-9 cells were transiently transfected with pBabe-NF2-puro plasmid. Control cells were transfected with pBabe-puro plasmid. Merlin expression level was detected by immunoblotting (Supplementary Fig. S1). Untreated plates for growth control were grown in parallel with experimental plates.
Cells were grown in 10-cm culture plates for no longer than 30 passages and allowed to grow for 3–4 passages after thawing before the actual experiments started. Each cell line was tested for Mycoplasma upon thawing every new vial of cells (at the time of 3d passage after thawing) using Mycoplasma growth indicator cultures of Vero cells, detected by fluorescence microscopy using the DNA-specific fluorochrome Hoeschst 33258. Proliferation studies were done in 96-well plates with initial cell density 104 cells per well. Immunoblotting was done in 6-well plates with initial density 2.5 × 105 cells per well. For lipogenesis-related protein immunoblotting cells were grown in serum-free conditions. For mitochondrial respiration assay cells were grown in 96-well plates provided with the analyzer at initial density 4 × 103 cells per well. For RNA extraction cells were grown in 6-cm culture plates until confluent in serum-free conditions. For UPLC-MS/MS and metabolomic studies cells were grown in 30-cm culture plates until confluent.
Primary schwannoma cell cultures: After informed consent, human primary schwannoma tissue samples were collected during operations at Derriford Hospital (Plymouth, United Kingdom) or Southmead Hospital (Bristol, United Kingdom) under local R&D approval Plymouth Hospitals NHS Trust: R&D No: 14/P/056 and North Bristol NHS Trust: R&D No: 3458. All patient studies were conducted in accordance with the Declaration of Helsinki under Institutional Review Board approval. Cells were isolated by digestion using a mixture of collagenase, dispase and mechanical digestion by pipetting. Once digested cells were cultured in growth factor medium (GFM): DMEM, 10% FBS, 100 U/mL pen/strep; 0.5 μmol/L Forskolin; 2.5 μg/mL Amphotericin; 2.5 μg/mL Insulin; 10 nmol/L β1 heregulin, maintained in a humidified atmosphere of 10% CO2 at 37°C on plates coated with both poly-L lysine and laminin. Human schwannoma primary cells (passages 1-4) and used in this study are Merlin-negative. All Schwann cell cultures are S100 positive.
Primary meningioma and Human meningeal cell (HMC, Catalog #1400, ScienCell Research Laboratories) cultures: All the meningioma tumor samples used were collected under the MOT project involving both Derriford and Southmead Hospitals. The project was granted full ethics approval by the South West research ethics committee (REC number 14/SW/0119). All tumors used in this project were classified as WHO grade 1. Meningioma cells were isolated using a mixture of collagenase, dispase, and mechanical digestion by pipetting. Once digested Meningioma cells were grown in DMEM containing glucose (4.5 g/L), 10% FBS, 100 U/mL penicillin/streptomycin and 1% glutamine. HMC (Sciencell) were grown in the recommended HMC medium (Sciencell) at 37°C and 5% CO2. Human meningioma grade I primary cells (passages 1-4) used in this study are Merlin-negative.
All primary cells were grown in Mycoplasma ExS (PromoCell GmbH) treated incubators. No additional Mycoplasma testing was performed.
Proliferation and viability assays
Proliferation and viability were evaluated by Alamar Blue reagent according to the manufacturer's protocol. For the human schwannoma and meningioma samples immunofluorescence proliferation and viability assays were performed: cells were cultured for 72 hours in GFM with or without GSK2194069 (0.1, 1, and 10 μmol/L). Pretreated cells were fixed using 4% paraformaldehyde (PFA) and permeabilized using 0.2% Triton X-100 before being blocked using 10% normal goat serum. Cells were then incubated with primary antibodies overnight at 4°C at a concentration of 1:100 in 1% BSA PBS. Anti-Ki67 (Dako) was used as a marker or proliferating cells and anti-cleaved caspase-3 (Cell Signaling Technology) was used as a marker or cells undergoing apoptosis. AlexaFluor secondary antibodies goat-anti mouse 594 and goat-anti rabbit 488 were used and DAPI applied as a nuclear stain.
Multitrack imaging was performed using a Zeiss Confocal LSM510. Proliferation and survival assays that were carried out using a ×20 air objective. The appropriate Zeiss image manipulation software (ZEN) was used for editing.
Transfections were done by electroporation using Neon transfection system (Life Technologies) according to the manufacturer's protocol. Transfections were done in 100 μL tips. For DNA transfections, final concentration of 5 μg per reaction was used. For RNA transfections, final concentration of 100 nmol/L was used.
Cells were lysed with RIPA (1% Triton-X100; 10% glycerol; 50 mmol/L HEPES, pH 7.4; 150 mmol/L NaCl; 1.5 mmol/L MgCl2, 1 mmol/L EGTA,1 mmol/L EDTA, 0.1% SDS, 10 mmol/L phenylmethylsulphonyl-fluoride; aprotinin 10 μg/mL, leupeptin 10 μg/mL, pepstatin 10 μg/mL, 10 mmol/L sodium fluoride) for 15 minutes on ice. Proteins of interest were detected by regular immunoblotting using a Lipid synthesis and metabolism antibody kit, anti-cleaved Casp3 rabbit monoclonal antibody, and mouse anti-merlin, anti-βActin, anti-Srebp1 and anti-Gapdh antibodies. Goat anti-rabbit HRP-conjugated and anti-mouse AP-conjugated immunoglobulins were used with Western Chemiluminescent HRP Substrate (Millipore) and ImmunStar AP substrate (Bio-Rad). Bands were visualized on FluorChem E System (ProteinSimple) and analyzed using ImageJ software. Band intensities were normalized to Gapdh or β-actin band intensities.
Cells were grown in serum-free media in 6-cm plates until confluent, and total RNA was extracted using RNeasy Mini Kit (Qiagen). Quantitative RT-PCR reactions were performed using TaqMan probes and primers designed by the manufacturer, using an ABI PRISM 7700 detection system (Applied Biosystems). Results were analyzed using relative standard curve method. For Acacb, comparative Ct method was used. The average of Hprt1, Tbp and Actinb expression was used for normalization. See Supplementary Data for the complete list of primers.
Four types of samples were analyzed: and MEF Nf2−/−, treated with DMSO, MEF Nf2−/−, treated with cerulenin, MEF Nf2f/f, treated with DMSO, and MEF Nf2f/f, treated with cerulenin. Approximately 1 g of cell pellet per sample type was used for analysis. Propionyl-CoA was used as a recovery standard. After the solid-phase extraction, acidified and neutralized samples were put to the Waters Acquity H-class ultra-performance liquid chromatography (UPLC) with the isocratic mobile phase: 50 mmol/L ammonium formate:acetonitrile (30:70, v/v). The eluates were directly introduced into the coupled Thermo triple quadrupole mass spectrometer (TSQ Quantum Access) for quantitative analysis. See Supplementary Data for the complete procedure description.
Mitochondrial respiration measurement
The study was performed in a 96-well format on a Seahorse XF analyzer using the Seahorse Mito Stress Kit (Seahorse Bioscience) according to the manufacturer's protocol. Initial cell density was 4 × 103 cells per well. Upon assay completion cells were lysed and used for protein concentration assay (Bradford). All data were normalized to protein concentrations.
All animal procedures were performed in accordance with Institutional Animal Care and Use Committee guides and regulations. Mouse schwannoma xenografts were performed on female nu/nu mice, n = 5. 3 × 106 SC4-9 cells in Matrigel per mouse were injected subcutaneously. A ×100 stock solution of cerulenin was prepared in DMSO:ethanol (1:4) and stored at −20°C. A working solution in corn oil was prepared daily and given by oral gavage at a dose of 30 or 2 mg/kg/d (cerulenin) and 3 mg/kg/d (GSK2194069) starting day 3 after injection. Mice were sacrificed by cervical dislocation after 4 weeks of treatment.
Six groups of samples were analyzed: non-treated Nf2-deficient mouse Schwann cells FH912 and wild type mouse Schwann cells FC912; nontreated Nf2−/− and Nf2f/f MEFs; and Nf2−/− and Nf2f/f MEFs treated with 5 μmol/L cerulenin for 24 hours. Five samples per sample type were prepared according to Metabolon sample preparation guidelines (Metabolon Inc.).
Half inhibitory concentration
Drugs were added to the cells 4 hours after plating and incubated for 48 hours. For Acaca knockdown, C75 was added next day after transfection and incubated for 48 hours. IC50 was calculated by the following formula: IC50 = a + b ×arctg(1−1/2c) after minimization of quadratic distance between experimental data and a fit curve y = c ×(1−tg((x−a)/b)), where x is the drug concentration, by modifying coefficients a, b, and c.
All IC50 studies were done in quadruplicates and repeated four times. Fasn and Acaca knockdown and ACC1 chemical activation and inhibition experiments were done in quadruplicates and repeated three times. Mlycd knockdown was done in quadruplicates and repeated four times. Lipogenesis immunoblotting and qPCR studies were repeated four times. MTOR signaling and MTOR inactivation experiments were repeated two times. UPLC-MS/MS studies were repeated three times. Mean values and confidence interval 95% were used to build graphs. Statistical significance p was determined by two-tailed Student t test with Welch's correction for increased Casp3 cleavage studies, UPLC-MS/MS, and for in vivo studies; and by the Holm–Sidak method with α = 5% for lipogenesis immunoblotting and qPCR studies. For the schwannoma xenograft FASN expression P value was calculated by the Mann–Whitney test. For human schwannoma samples ANOVA was used. Experiments were performed in at least triplicates using at least three independent batches of cells from different individuals. In a figure, mean ± SEM is given.
Metabolic profiling of Nf2-deficient cells
We performed metabolic profiling of Nf2-deficient MEFs and Schwann cells (FH912) in comparison with WT MEFs (Nf2f/f) and Schwann cells (FC912) to see whether metabolic pathways were altered by loss of the Nf2 gene. Metabolite profiling showed a broad spectrum of changes in Nf2-deficient cells. Specifically, we observed elevated levels of tricarbonic acid (TCA) cycle metabolites in Nf2−/− MEFs (Table 1) and increased levels of long chain and branched fatty acids in both FH912 Schwann cells and Nf2−/− MEFs (Table 2), consistent with increased energy demand in these cells (24–26). An increase in vitamins and cofactors levels was also observed (Supplementary Table S1), especially, nicotinate metabolites involved in electron chain transport (NAD+, NADH, and NADP) and pantothenate metabolites involved in coenzyme A turnover, consistent with an increased energy production in Nf2-deficient cell lines (27). In addition, the level of metabolites associated with glycolysis was decreased in both FH912 Schwann cells and Nf2−/− MEFs (Table 1), as well as a drop in amino acids, including particularly glutamine metabolites (Supplementary Table S2), suggesting that upregulated glutaminolysis supporting the more active TCA cycle. The most profound metabolic alteration, however, was the marked elevation of fatty acid levels in both FH912 cells and Nf2−/− MEFs (Table 2).
Loss of the Nf2 gene renders cells vulnerable to FASN inhibitors
Because metabolic profiling indicated elevated fatty acid metabolism in Nf2−/− cells, we asked whether these cells were sensitive to small-molecule inhibitors of FASN. We found that the FASN inhibitor cerulenin (28) showed consistent selective toxicity against Nf2-deficient MEFs with IC50 ratio of 0.436 ± 0.09, P = 4E−10 (Fig. 1A). The schwannoma cell lines SC4-9 and RT4 were also sensitive to similar levels of this compound. Re-expression of Merlin in SC4-9 cells rendered these cells insensitive to cerulenin (almost 2-fold difference in IC50 values, P < 0.0001; Fig. 1B), indicating that the sensitivity to cerulenin is related to Merlin expression (Merlin expression level is shown on Supplementary Fig. S1A). To ensure that the observed effects were related to FASN inhibition, we asked if Nf2−/− MEFs were more sensitive than Nf2f/f MEFs to knockdown of Fasn. Nf2−/− and Nf2f/f MEFs were transfected with pooled anti-Fasn siRNA or control non-silencing siRNA. Within 24 hours, rounded apoptotic cells were observed in Nf2−/− cells transfected with anti-Fasn siRNA, but not in the control cells or in transfected Nf2f/f MEFs. We observed a significant increase of Casp3 cleavage in anti-Fasn siRNA-transfected (4.14-fold, P = 0.0001) Nf2−/− MEFs, but not in similarly treated Nf2f/f MEFs (Fig. 1C; Supplementary Fig. S1B). Low dose cerulenin treatment also decreased levels of FASN at some degree, and the same trend of cleaved Casp3 increase was observed in Nf2−/− MEFs (2.01-fold, P = 0.022). The same pattern was observed when individual oligos against Fasn and GSK2194069 inhibitor were used (Supplementary Fig. S1C). We also tested the sensitivity of Nf2f/f and Nf2−/− MEFs to three additional small-molecule FASN inhibitors: GSK2194069 (29), C75 (25), and luteolin (25). In each case, loss of Nf2 was associated with higher sensitivity to the FASN inhibitors (Fig. 1D–F).
We next performed xenograft studies on female nu/nu mice using SC4-9 cells. Xenografts were placed in the flanks and the mice were treated with cerulenin (30 mg/kg/d), GSK2194069 (3 mg/kg/d), or vehicle for 28 days. As shown in Fig. 1G, treatment with GSK2194069 caused a nearly two-fold reduction in tumor growth (P = 0.0049), and cerulenin treatment caused a 3-fold reduction (P = 0.00039), consistent with the notion that inhibiting FASN represents a potentially effective strategy for NF2. At the dose given mice tolerated treatment well and did not experience weight loss or skin dryness. Remarkably, much lower doses of cerulenin (2 mg/kg/d) also effectively slowed down the tumor growth (Supplementary Fig. S1D). As has been reported previously (30) treatment with cerulenin was associated with a significant FASN expression decrease detected by immunoblotting of the tumor samples (Supplementary Fig. S1D).
Human primary schwannoma and meningioma cells exhibit similar sensitivity to FASN inhibition
To test whether normal FASN functioning was crucial for human schwannomas and meningiomas as well as for mouse tumors we tested a series of GSK2194069 concentrations on primary human schwannoma and meningioma cells obtained from the tumor samples in comparison with normal human Schwann and meningeal cells. Primary human schwannoma cells showed similar sensitivity compared with Nf2−/− MEFs and mouse schwannoma SC4-9 (IC50 0.68 ± 0.26 μmol/L vs. 0.19 ± 0.45 μmol/L and 0.3 ± 0.09 μmol/L, respectively; Fig. 2A). Remarkably, normal Schwann cells turned to be virtually insensitive to GSK2194069 (Fig. 2A). Primary human meningioma cells also displayed similar sensitivity to the compounds, whereas normal HMCs were much less sensitive (IC50 2.77 ± 1.57 μmol/L vs. 28.79 ± 15.86 μmol/L, respectively; Fig. 2B).
Reversal of the cerulenin effect by blockade of malonyl-CoA synthesis
FASN catalyzes production of palmitic acid, an essential building block for long-chain fatty acids (28, 31). By inhibiting FASN, cerulenin blocks the malonyl-CoA condensation step of fatty acid synthesis, causing a deficit in palmitic acid as well as an accumulation of malonyl-CoA (26, 32–35). The toxicity of malonyl-CoA in cancer cells is thought to be mediated by inhibition of carnitine palmitoyltransferase 1-regulated fatty acid β-oxidation, in turn promoting the accumulation of the sphingolipid ceramide followed by the induction of the pro-apoptotic genes such as BNIP3, TRAIL, and DAPK2, effectors in the ceramide-mediated apoptotic pathway (36).
To evaluate the possibility that cerulenin effects in Nf2−/− cells might be related to reduced palmitic acid availability, we supplemented the growth media of Nf2−/− and Nf2f/f cells with palmitic acid. This addition did not reverse the toxicity of cerulenin (Fig. 3A). We next considered whether lack of fatty acid precursors or accumulation of malonyl-CoA might promote cell death in cerulenin-treated Nf2−/− cells. We therefore knocked down acetyl-CoA carboxylase 1 (ACC1, encoded by Acaca), which catalyzes production of malonyl-CoA from acetyl-CoA to provide building blocks for FASN (Fig. 3B), together with cerulenin treatment. Knockdown of Acaca led to a striking reduction in cerulenin- and GSK2194069-induced toxicity (Fig. 3C; Supplementary Fig. S2A-B). Conversely, we tested the effect and knockdown of malonyl-CoA decarboxylase (MCD, encoded by Mlycd), which catalyzes the conversion of malonyl-CoA back to acetyl-CoA (37). Mlycd knockdown increased the sensitivity of both cell lines to cerulenin and GSK2194069 (Fig. 3D; Supplementary Fig. S2C). Chemical inactivation of ACC1 by TOFA had a similar effect as Acaca knockdown (Fig. 3E), consistent with the idea that elevated levels of malonyl-CoA are toxic to these cells, and suggesting that Nf2−/− cells produce more malonyl-CoA than Nf2f/fcells. Treatment with an ACC activator, 5-iodotubercidin, which blocks an AMP kinase–mediated inhibitory phosphorylation of ACC1 (38), caused an increase in cerulenin toxicity in Nf2f/fcells, but had little effect on cerulenin toxicity in Nf2−/−cells (Fig. 3F). To determine whether malonyl-CoA levels actually differ according to NF2 status, we performed UPLC-MS/MS measurements of intracellular acetyl-CoA and malonyl-CoA in Nf2−/− and Nf2f/f cells (Fig. 3G). These studies showed 50% higher level of acetyl-CoA in non-treated Nf2−/− cells compared with non-treated Nf2f/f cells (P = 0.0497), and a significant increase of both acetyl-CoA (by 47%, P = 0.0003) and malonyl-CoA (by 90%, P = 0.0002) in cerulenin-treated Nf2−/− cells, but not in cerulenin-treated Nf2f/f cells.
Upregulated lipogenesis in Nf2-deficient cells
Consistent with the metabolic profiling data that showed higher levels of fatty acids in Nf2−/− cells (Table 2), the selective toxicity of cerulenin appeared to be related to a greater accumulation of intermediate fatty acid synthesis products in Nf2−/− cells, and we hypothesized that the loss of Nf2 gene might cause a general increase in lipogenesis. We found markedly elevated levels of several key lipogenesis-related proteins in Nf2−/− relative to Nf2f/f cells, including ACC-1 (45%, P = 0.003) and -2 (32%, P = 0.002), FASN (60%, P = 0.0007), SREBP1 (71%, P = 0.0001), Lipin1 (63%, P = 0.0001), ACL (52%, P = 0.0137), and its phosphorylated active form (69%, P = 0.0012), ACECS1 (59%, P = 0.0022), and ACSL1 (60%, P = 0.0006). In addition, we found decreased Ser79 phosphorylation of ACC (59%, P = 0.0032) in Nf2−/− MEFs, an indicator of high activity, as phosphorylation at this site inhibits ACC activity (Fig. 4A; Supplementary Fig. S3; ref. 39). Importantly, reintroduction of Merlin in SC4-9 cells decreased levels of these proteins and restored phosphorylation of ACC (Fig. 4B; Supplementary Fig. S4). Consistent with the immunoblot data, quantitative PCR also showed significantly higher expression of lipogenesis-related genes in Nf2−/− MEFs relative to Nf2f/fMEFs (P < 0.001 for all the genes studied; Fig. 4C). The same trend was observed in SC4-9 cells compared to SC4-9-merlin cells (Fig. 4C). Such an increase, especially of transcription factors SREBP1 and Lipin1, is consistent with our idea of upregulated lipid metabolism in Nf2-deficient cells. The modest effect of 5-iodotubercidin on Nf2−/− cells (Fig. 3F) is consistent with the low phosphorylation, and thus high activity, of ACC in these cells (Fig. 4A). Figure 4D shows additional lipogenic enzyme roles in the fatty acid synthesis. Fasn and Acaca expression is controlled mainly by the transcription factor Sterol regulatory element binding protein 1 (SREBP1; refs. 40, 41), and Lipin1 is a major expression regulator of the rest of lipogenic enzymes (42, 43).
Torc1 signaling is essential for fatty acid synthesis regulation
It has been previously shown that Merlin inhibits MTOR (44). MTOR is a known metabolic sensor and has been shown to regulate SREBP1 (45) and Lipin1 (46). We hypothesized that activated MTOR in Nf2-deficient cells might cause the upregulation of fatty acid synthesis via upregulation of SREBP1 and Lipin1. We confirmed increased MTOR phosphorylation at serine 2448 in Nf2-deficient MEFs (Fig. 5A) and tried chemical and siRNA inactivation of MTOR in Nf2-null and WT MEFs. Chemical inactivation of MTOR either by the dual TORC1 and TORC2 inhibitor Torin1 or by the TORC1 inhibitor Everolimus led to a significant reduction of the cerulenin toxicity in Nf2−/− MEFs (1.5-fold difference in IC50 values, P = 0.027 and 0.0064 respectively), but had a non-significant effect on WT MEFs (Fig. 5B). Immunoblot confirmed a drop in a triglyceride synthesis regulator Lipin1 and a FASN positive regulator SREBP1 protein levels caused by a decrease of MTOR phosphorylation at serine 2448 (Fig. 5B). The same effect was observed for RNAi knockdown of Mtor and TORC1 component Rptor, but not TORC2 component Rictor (Fig. 5C; Supplementary Fig. S5A–S5B). Thus, a key event causing fatty acid synthesis upregulation in Nf2-deficient cells is TORC1 activation in the absence of Merlin.
In this study, we show that cerulenin, an inhibitor of fatty acid synthesis is selectively toxic in cell lines lacking Merlin expression. Cerulenin has activity as an anti-obesity agent (21, 47), but has also shown in vitro efficacy against the proliferation of colon (22), breast (48), and prostate cancer cells (21). Such sensitivity of certain cancer cells to this drug may be due to higher fatty acid synthesis levels compared with normal cells (24–26). Our findings showed that, despite their benign nature, Merlin-null cells have markedly elevated levels of fatty acid synthesis. Such cells displayed significantly higher levels of FASN and also ACC1 and 2, the enzymes that catalyze production of malonyl-CoA from acetyl-CoA. Moreover, Nf2-deficient cells had low levels of ACC phosphorylation, indicating high activity of this enzyme (39). The higher level of ACC expression is consistent with the pronounced rescue effect of TOFA, an ACC inhibitor, on cerulenin-treated Nf2−/− MEFs (Fig. 4E). FASN inhibitors have previously been shown to reduce proliferation of human malignant mesothelioma cells (49), which are often characterized by loss of function mutations in CDKN2A/p14(ARF) and NF2. Gabrielson and colleagues (49) reported that Fasn is overexpressed in 22 of 30 human mesothelioma tissue samples compared with normal tissues, including mesothelium. They found that the growth of orthotopic xenografts of malignant mesothelioma cells was strongly inhibited in mice treated with the Fasn inhibitor C75. In addition, Haase and colleagues (50) reported that Fasn expression was elevated in 70% of atypical grade II and anaplastic grade 3 meningiomas, and that treatment with cerulenin significantly decreased NF2-null meningioma cell survival in vitro and reduced tumor volumes in xenografts. These results, combined with our data in Nf2-null MEFs and Schwann cells, suggest that changes in lipid synthesis may be a general function in cells lacking Merlin.
Inhibitors such as cerulenin have also shown to have efficacy in a number of non–NF2-related cancer cell types in vitro and in preclinical models (24). In some cases, it has been proposed that these effects are mediated by targets other than FASN. For example, cerulenin induces apoptosis in melan-a cells, but these effects appear to be independent of Fasn inhibition, and are instead thought to be mediated by an oxidative stress-associated mechanism that ultimately results in mitochondrial dysfunction (51). FASN inhibitors have also been shown to affect the activity level of the HER2/PI3K/AKT signaling pathway in U2OS cells (52). However, in our studies in the setting of Merlin deficiency, similar cellular and metabolic effects were seen with other three distinct small-molecule FASN inhibitors as well as with Fasn siRNA. Thus, we believe that the effects of cerulenin on Merlin-null cells are related to FASN inhibition, with subsequent build-up of toxic intermediates such as malonyl-CoA, as opposed to off-target effects. This supposition is supported by the loss of cerulenin toxicity in Merlin-null cells when an ACC inhibitor is also added to the cells (Fig. 3E).
As a clinical agent, cerulenin suffers from relatively poor bioavailability. In addition, this compound, as well as the synthetic analog C75, has undesirable side effects that include anorexia and weight loss, most likely due to effects on production of neuropeptide Y in the hypothalamus as well as activation of mitochondrial fatty acid oxidation (24, 47, 53). In our experiments, mice tolerated treatment well, and did not experience weight loss. Still, a decrease in the FASN levels of cerulenin-treated tumors indicates that the drug reached its target in the in vivo studies. Unfortunately, the quality of antibodies against lipogenic enzymes did not allow to confirm their downregulation in the xenograft experiments, and the size of the treated tumors was too small for the HPLC analysis. It is possible that combining Fasn inhibitors with inhibitors of malonyl-CoA decarboxylase or inhibitors of AMP kinase (resulting in ACC activation and accumulation of malonyl CoA), would show additive or synergistic effects in vivo. We showed that activation of MTOR at Ser 2448 in Nf2-null cells is a key element in lipogenesis upregulation in such cells (Fig. 5A–C). As FASN expression is regulated by the transcription factor sterol regulatory element-binding protein 1c (SREBP1c) via the ERK and PI3K/AKT/MTOR pathways (54, 55), modulators of these signaling pathways might also be reasonable candidates to combine with FASN inhibitors.
Although our findings suggest that upregulated fatty acid synthesis is a key element in cerulenin selectivity against Nf2-deficient cell lines, we also found other metabolic changes that might be useful in designing targeted therapies. For example, we found a significant increase in mitochondrial respiration rate and a drop-in glycolysis metabolites in both FH912 (Nf2−/−) Schwann cells and Nf2−/− MEFs (Table 1 and Supplementary Fig. S6). Thus, Nf2-deficient tumor cells differ in their utilization of glucose compared to typical malignant cancer cells, which are often characterized by aerobic glycolysis. Interestingly, Nf2−/− and control MEFs react differently to cerulenin treatment (Supplementary Table S3). Although cerulenin causes an increase in TCA metabolite level in normal cells, Nf2-deficient cells retain the same level of TCA metabolites. We speculate that normal cells compensate a decrease of energy production from fatty acid oxidation in the presence of cerulenin by upregulating Krebs' cycle. As Nf2−/− MEFs do not demonstrate such compensation, it suggests that there might be an initial fatty acid oxidation impairment in these cells. This supposition is also indirectly confirmed by the decrease in fatty acid oxidation gene expression in Nf2-deficient cells (Supplementary Fig. S7). In addition, we noted a profound drop in amino acid levels, especially in glutamate metabolites, dipeptide, and polypeptide levels in Nf2-null cells (Supplementary Table S2). Such a general decrease in amino acid and peptide levels might indicate an increased demand of building blocks for protein synthesis, which is likely related to the increased growth rate of Nf2-deficient cells. Similarly, a drop-in glutamine level might be evidence of increased glutaminolysis supporting an increased energy demand. It is also of potential interest that Nf2-deficient cells showed an increased level of coenzymes (Supplementary Table S1). This change specifically affected pantothenate and phosphopantetheine levels, and NAD+ and NADH levels. Pantothenate and phosphopantetheine are essential for coenzyme A synthesis, and elevation of their levels is an indication of higher lipid, carbohydrate, and amino acid metabolism rates (56). Such an increase in NAD+ and NADH levels is likely necessary to support greater energy metabolism in Nf2-deficient cells.
In summary, we have shown for the first time that Nf2 deficiency is associated with a profound reprogramming of cellular metabolism, favoring biosynthetic processes and limiting catalytic processes, and that this altered metabolism might be exploited therapeutically. In particular, the increased dependence of Nf2-deficient cells on lipid synthesis suggests that Fasn inhibitors, alone or in combination with other agents that increase malonyl-CoA levels, might be useful in treating NF2-related diseases.
Disclosure of Potential Conflicts of Interest
No potential conflicts of interest were disclosed.
Conception and design: D.S. Stepanova, G. Semenova, A.J. Andrews, J. Chernoff
Development of methodology: D.S. Stepanova, J. Chernoff
Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): D.S. Stepanova, G. Semenova, Y.-M. Kuo, C.O. Hanemann
Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): D.S. Stepanova, Y.-M. Kuo, A.J. Andrews, C.O. Hanemann, J. Chernoff
Writing, review, and/or revision of the manuscript: D.S. Stepanova, G. Semenova, Y.-M. Kuo, C.O. Hanemann, J. Chernoff
Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): Y.-M. Kuo, J. Chernoff
Study supervision: J. Chernoff
Other (have performed some of the experiments): S. Ammoun
We thank Dr. Tyler Jacks (Koch Institute for Integrative Cancer Research at MIT) for the pBabe-NF2 plasmid; Dr. Marco Giovannini (House Ear Institute) for Nf2f/fMEFs, and SC4-9, FH912, and FC912 Schwann cells; Dr. Emmanuelle Nicolas (Fox Chase Cancer Center) for the help with qPCR, Dr. Warren Kruger (Fox Chase Cancer Center) for providing an opportunity to use the Seahorse XF analyzer, and Drs. Erica Golemis and Igor Astsaturov (Fox Chase Cancer Center) for their kind advice on the article preparation.
This work was supported by grants from the NIH (R01 CA148805), DOD (NF050032, NF130108) and CTF to J. Chernoff, and from the NIH (P30 CA006927) to the Fox Chase Cancer Center, a gift from the Galloway family, as well as by an appropriation from the state of Pennsylvania. Human schwannoma and meningioma studies were supported by the Brain Tumor Research charity (C.O. Hanemann).
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