PGC-1α supports glutamine metabolism in breast cancer
- Shawn McGuirk†1, 2,
- Simon-Pierre Gravel†1, 2,
- Geneviève Deblois1, 2,
- David J Papadopoli1, 2,
- Brandon Faubert1, 3,
- André Wegner4,
- Karsten Hiller4,
- Daina Avizonis1, 5,
- Uri David Akavia2, 6, 7,
- Russell G Jones1, 3,
- Vincent Giguère1, 2 and
- Julie St-Pierre1, 2Email author
© McGuirk et al.; licensee BioMed Central Ltd. 2013
Received: 19 July 2013
Accepted: 19 November 2013
Published: 5 December 2013
Glutamine metabolism is a central metabolic pathway in cancer. Recently, reductive carboxylation of glutamine for lipogenesis has been shown to constitute a key anabolic route in cancer cells. However, little is known regarding central regulators of the various glutamine metabolic pathways in cancer cells.
The impact of PGC-1α and ERRα on glutamine enzyme expression was assessed in ERBB2+ breast cancer cell lines with quantitative RT-PCR, chromatin immunoprecipitation, and immunoblotting experiments. Glutamine flux was quantified using 13C-labeled glutamine and GC/MS analyses. Functional assays for lipogenesis were performed using 14C-labeled glutamine. The expression of glutamine metabolism genes in breast cancer patients was determined by bioinformatics analyses using The Cancer Genome Atlas.
We show that the transcriptional coactivator PGC-1α, along with the transcription factor ERRα, is a positive regulator of the expression of glutamine metabolism genes in ERBB2+ breast cancer. Indeed, ERBB2+ breast cancer cells with increased expression of PGC-1α display elevated expression of glutamine metabolism genes. Furthermore, ERBB2+ breast cancer cells with reduced expression of PGC-1α or when treated with C29, a pharmacological inhibitor of ERRα, exhibit diminished expression of glutamine metabolism genes. The biological relevance of the control of glutamine metabolism genes by the PGC-1α/ERRα axis is demonstrated by consequent regulation of glutamine flux through the citric acid cycle. PGC-1α and ERRα regulate both the canonical citric acid cycle (forward) and the reductive carboxylation (reverse) fluxes; the latter can be used to support de novo lipogenesis reactions, most notably in hypoxic conditions. Importantly, murine and human ERBB2+ cells lines display a significant dependence on glutamine availability for their growth. Finally, we show that PGC-1α expression is positively correlated with that of the glutamine pathway in ERBB2+ breast cancer patients, and high expression of this pathway is associated with reduced patient survival.
These data reveal that the PGC-1α/ERRα axis is a central regulator of glutamine metabolism in ERBB2+ breast cancer. This novel regulatory link, as well as the marked reduction in patient survival time associated with increased glutamine pathway gene expression, suggests that targeting glutamine metabolism may have therapeutic potential in the treatment of ERBB2+ breast cancer.
KeywordsPGC-1α Glutamine Metabolism Breast cancer Metabolomics
Altered metabolism is an emerging hallmark of cancer cells . The most studied metabolic alteration of cancer cells is their high reliance on glycolysis even if there is sufficient oxygen to support mitochondrial oxidative phosphorylation (Warburg effect). The rapid ATP production of glycolysis is thought to benefit the enhanced proliferation of cancer cells. However, glutamine metabolism has been increasingly recognized as a central metabolic pathway in cancer, and it is thought that the catabolic and anabolic roles of glucose and glutamine cooperate in fuelling tumor growth . The discovery that the oncogene Myc is an important regulator of glutamine metabolism has further strengthened the importance of this metabolic pathway in cancer [3, 4].
Recent studies revealed that reductive carboxylation of glutamine to citrate through reversal of the citric acid cycle (CAC) and the subsequent use of citrate for lipogenesis constitute a key anabolic route in hypoxia in cancer cells, as well as in cancer cells with mitochondrial dysfunctions [5–8]. Hypoxia-induced factor 1 (HIF-1) plays an important role in this metabolic reprogramming, as cells constitutively expressing HIF-1α perform reductive carboxylation of glutamine in normoxia [5, 7]. Clearly, the ability to rely on this metabolic pathway will be a distinct advantage for solid tumors that experience fluctuating levels of oxygen by permitting elevated production of lipids, which are important notably for membrane biogenesis.
The family of peroxisome proliferator activated receptor gamma coactivator 1 (PGC-1) consists of three members, PGC-1α, PGC-1β, and PRC. These transcriptional coactivators play a central role in metabolism [9, 10]. Even though the importance of the PGC-1s in regulating mitochondrial functions and metabolism is well established in general, their roles in regulating cancer metabolism and proliferation have only started to emerge recently. The PGC-1s have been shown to have both pro- and anti-tumorigenesis effects [11, 12]. In breast cancer, PGC-1α has been shown to promote the growth of ERBB2+ tumors in vivo and to regulate their mitochondrial metabolism and angiogenic properties [12, 13]. In this paper, we inquired whether PGC-1α participates in the control of glutamine metabolism in breast cancer. We reveal that PGC-1α increases the expression of glutamine metabolism genes, augments glutamine-mediated forward and reverse CAC fluxes, as well as elevates glutamine-mediated lipogenesis in hypoxia. This PGC-1α-mediated increase in glutamine metabolism will confer an advantage to solid breast cancer tumors experiencing limited nutrients and oxygen supply. Relevance to the human disease is underlined by the findings that PGC-1α expression is positively correlated with that of the glutamine pathway in ERBB2+ breast cancer patients, and that high expression of the glutamine pathway is associated with shorter survival time.
All procedures were conducted in accordance with approved animal protocols by the McGill University Animal Care Committee. Wild-type mice (C57BL/6J) and muscle creatine kinase (mck)-PGC-1α transgenic mice (C57BL/6-Tg(Ckm-Ppargc1a)31Brsp/J) as described in  were purchased from The Jackson Laboratory (Bar Harbor, ME, USA). All animals used were female and were sacrificed at approximately 12 weeks of age.
Stable cell lines Control-1, PGC-1α-1.1, and PGC-1α-1.2 have been described in . These cells were cultured in Dulbecco's Modified Eagle's Medium (DMEM), 10% FBS, 10 μg/mL insulin, 20 mM HEPES, penicillin/streptomycin, 1 μg/mL puromycin, 400 μg/mL G418, at 37°C and 5% CO2. SK-BR-3 and BT-474 were obtained from the American Type Culture Collection (ATCC) and cultured in DMEM supplemented with 10% FBS and penicillin/streptomycin. Hypoxia experiments were performed in a Thermo Scientific (Rockford, IL, USA) Heraeus HERAcell 150 set at 1% O2 and 5% CO2. Pharmacological inhibition of ERRα was performed using Compound 29 (C29) at 5 μM (0.1% DMSO). C29 was synthesized according to .
Total RNA from cultured cells, grown to 50% to 60% confluence in 35 mm plates, was extracted using the Aurum Total RNA Mini Kit (Bio-Rad, Mississauga, Canada) and was reverse transcribed with iScript cDNA Synthesis kit (Bio-Rad). mRNA expression analyses by real-time PCR were performed using iQ SYBR Green Supermix (Bio-Rad) and gene-specific primers with the MyiQ2 Real-Time Detection System (Bio-Rad). Values were normalized to TATA binding protein (Tbp) for murine cell lines or beta-2 microglobulin (B2M) for human cell lines.
Chromatin was prepared from PGC-1α-1.1 cells, using approximately 107 cells per chromatin immunoprecipitation (ChIP). ChIP was performed as described previously  using a specific anti-PGC-1α antibody (Santa Cruz Biotechnology, Inc., Dallas, TX, USA, catalog #sc-13067) or specific anti-ERRα antibody (Epitomics, Burlingame, CA, USA, catalog #2131-1). Quantification of PGC-1α or ERRα ChIP enrichment was performed using real-time PCR using the LightCycler 480 instrument (Roche, Mississauga, Canada) and specific primers for genomic regions. ChIP enrichment was normalized against the control region and further normalized against the IgG control.
Total proteins from cultured cells or muscle tissue were extracted with lysis buffer (50 mM Tris–HCl pH 7.4, 1% Triton X-100, 0.25% sodium deoxycholate, 150 mM NaCl, 1 mM EDTA) with inhibitors (2 μg/mL pepstatin, 1 μg/mL aprotinin, 1 μg/mL leupeptin, 0.2 mM phenylmethylsulfonyl fluoride and 1 mM sodium orthovanadate) and quantified with the Bio-Rad Protein Assay kit (Catalog #500-0006). The blots were incubated according to the manufacturer's instructions with the following primary antibodies: Glud1 (GeneTex, Irvine, CA, USA, GTX88164), Gls (Abcam, Toronto, Canada, AB93434), Got1 (GeneTex, GTX88903), Got2 (GeneTex, GTX88925), Hsp90 (Santa Cruz Biotechnology, sc-101494), and Actin (Santa Cruz Biotechnology, sc-1616) and with horseradish peroxidase-conjugated secondary antibodies (GE Healthcare, Mississauga, Canada, or Santa Cruz Biotechnology). The results were visualized using Western Lightning Plus-ECL (Perkin Elmer, Waltham, MA, USA) or SuperSignal West Femto ECL (Pierce, Rockford, IL, USA). Densitometry analyses were conducted using ImageJ software (NIH).
BT-474 cells were subjected to either 10 nM control siRNA (Dharmacon, Rockford, IL, USA, D-001810-10-05) or a combined 10 nM pool of four siRNA specifically targeting PPARGC1A (Qiagen, Germantown, MD, USA, FlexiTube GeneSolution GS10891). Cells were transfected using calcium phosphate (CaPO4) and incubated for 120 h before extraction.
14C-lipid incorporation assay
Cells were seeded at a density of 400,000 cells per 35 mm plate in standard growth media and conditions. After 24 h, the medium was supplemented with trace amounts of [U-14C]-glutamine (0.094 μCi/mL) and the cells were further incubated either in normoxia (21% O2) or hypoxia (1% O2) for 24 h (Control-1 and PGC-1α-1.1) or 48 h (BT-474). Individual experiments were conducted in triplicate with additional plates for cell counting. Cells were washed with PBS, collected using 0.5% Triton X-100, and stored at −80°C. After thawing, lipids were extracted using chloroform/methanol; the lipid-rich chloroform phase was dried under air and resuspended in 150 μL chloroform. Scintillation counts were measured over 5 minutes per sample using a MicroBeta2 scintillation counter (Perkin-Elmer) and Eco-Lume reagent (MPBio, Solon, OH, USA). Counts were normalized for cell number.
Cellular glutamine uptake was measured using the BioProfile 400 analyzer (Nova Biomedical Corp., Waltham, MA, USA). Following growth under normoxic (21% O2) or hypoxic (1% O2) conditions, media were removed and maintained on ice until analysis. Glutamine uptake was calculated as the difference in glutamine content between culture media and unseeded media incubated in parallel plates and normalized for cell count.
Mass isotopomer distribution analysis
The Cancer Genome Atlas analyses
Breast cancer data, clinical data, and survival data for 732 patients were obtained from The Cancer Genome Atlas (TCGA) . RNAseq data were downloaded from TCGA web portal using the reads per kilobase of exon model per million mapped reads (RPKM) quantification . RPKM data was log2 transformed and expression values lower than 0.25 RPKM were removed. To generate an overall pathway score, all nine genes in the glutamine metabolism pathway were Z-transformed (mean 0 and standard deviation of 1). Mean of zero corrects for the fact that the genes may be expressed at different levels. Transforming the standard deviation to 1 causes the genes to change in the same magnitude, so we can see if the overall pathway is over/underexpressed. If the genes are expressed at different levels, the changes in the pathway will be dominated by the genes that were originally expressed at higher levels. We used the median of Z-scores to generate a pathway score, which was used in correlation and survival analysis.
All statistical analyses were performed using GraphPad Prism (GraphPad Software, Inc., CA, USA), Microsoft Excel (Microsoft Corporation, CA, USA) or Matlab (The Mathworks, Inc., MA, USA). Survival analysis was calculated using an implementation of Kaplan-Meir log rank testing from Matlab Exchange .
PGC-1α modulates the expression of enzymes involved in glutamine metabolism in ERBB2/Neu-induced breast cancer cells
PGC-1α/ERRα modulate forward and reverse glutamine flux through the citric acid cycle
To gain insight on the flux of glutamine upon increased PGC-1α expression, α-1.1 and control cells were incubated with [U-13C]-glutamine labelled at all five carbons (Figure 2B). α-ketoglutarate m + 5 is generated from glutamine m + 5 ([U-13C]-glutamine) and serves as an entry point in the CAC, where it can either generate isocitrate m + 5 by reductive carboxylation (reverse flux) or succinate m + 4 by oxidative decarboxylation (forward flux) (Figure 2B). Reverse CAC flux leads to enrichments in citrate m + 5, malate m + 3, and fumarate m + 3, and forward CAC leads to the enrichment of m + 4 metabolites (Figure 2B). Citrate m + 4 and m + 5 can be used for lipid biosynthesis, but citrate generated specifically through reverse CAC (m + 5) plays a central role in glutamine-derived lipogenesis in cancer cells (Figure 2B) [5–7].
We performed glutamine labeling experiments in normoxia and hypoxia given that reductive carboxylation of glutamine is particularly active in hypoxia [5–7]. In normoxia, α-1.1 cells displayed increased entry of glutamine in the CAC as illustrated by elevated amount of m + 5 α-ketoglutarate compared with control (Figure 2C). The α-ketoglutarate can then enter both the forward and reverse CAC reactions. The α-1.1 cells displayed higher forward and reverse CAC activity compared with controls (Figure 2C-F). The elevated forward flux can be seen from the higher amount of m + 4 citrate, malate, and fumarate, while the elevated reverse flux can be observed in the higher amount of m + 5 citrate as well as m + 3 malate and fumarate (Figure 2D-F) [see Additional file 4: Figure S2A]. The reverse flux represented a small fraction of the total CAC flux in normoxia. In hypoxia, there was an increase in the entry of glutamine in the CAC at α-ketoglutarate both for the control and α-1.1 cells compared with normoxia (Figure 2C). In general, hypoxia caused an increase in the reverse flux for both the control and α-1.1 cells (Figure 2D-F) [see Additional file 4: Figure S2A], but the effects were more pronounced in the α-1.1 cells and can be best appreciated when examining the labeling on citrate (Figure 2D). Indeed, α-1.1 cells displayed a large m + 5 labeling on citrate in hypoxia and devoted a larger fraction of their CAC flux for reverse reactions than control cells in hypoxia (Figure 2D). Together, these metabolomics experiments illustrate that PGC-1α can stimulate glutamine-mediated forward and reverse CAC fluxes in normoxia and hypoxia.
PGC-1α increases glutamine-mediated fatty acid biosynthesis and favors proliferation in limited nutrient conditions
Next, we tested the impact of PGC-1α on the sensitivity of ERBB2/Neu-induced breast cancer cells to glutamine deprivation, low glucose, and hypoxia, in order to mimic the environment of solid growing tumors. The growth of both ERBB2/Neu-induced breast cancer cells with increased expression of PGC-1α (α-1.1) and controls was ablated in the absence of glutamine (Figure 4D), illustrating that ERBB2/Neu-induced breast cancer cells require glutamine for their growth. A similar dependency on glutamine was observed with human ERBB2+ breast cancer cell lines [see Additional file 6: Figure S4B,C]. We then tested the impact of PGC-1α on cellular proliferation in low glucose and hypoxia, two conditions that can favor glutamine usage (Figure 4E) [5, 7, 25]. The proliferation of α-1.1 cells was less sensitive to a combination of low glucose and hypoxia than controls as indicated by their smaller reduction in proliferation (Figure 4E). Together, these data demonstrate that glutamine is a key metabolite for the growth of ERBB2/Neu-induced breast cancer cells, and that the PGC-1α-mediated increase in glutamine metabolism is associated with protection against low glucose conditions and hypoxia, two conditions that can favor glutamine metabolism.
Gene expression analyses of PGC-1α and glutamine enzymes in breast cancer patients
In this manuscript, we report that the PGC-1α/ERRα axis is a key regulator of glutamine metabolism in ERBB2+ breast cancer cells. We revealed that PGC-1α/ERRα bind the promoter of glutamine metabolism genes and regulate their expression, which ultimately controls the flux of glutamine in cells. This can contribute to increased lipid biosynthesis, especially under hypoxic conditions. Finally, we demonstrate that the PGC-1α-mediated control of glutamine metabolism has clinical relevance in ERBB2+ breast cancer patients.
Even though the importance of glutamine metabolism in cancer cells is well appreciated, much less is known regarding central regulators of glutamine metabolic pathways. Major transcriptional regulators of glutamine metabolism identified so far are c-Myc [3, 4, 26, 27] and HIF-1 [5, 7]. In this study, we reveal that PGC-1α/ERRα are central regulators of glutamine-mediated forward and reverse CAC fluxes. Interestingly, a recent report showed that glutamine reductive carboxylation for lipogenesis is particularly active in brown fat cells , the same cell type where PGC-1α was discovered and which display very high expression of this coactivator . In recent years, PGC-1s/ERRs have been involved in the control of the expression of numerous metabolic pathways in breast cancer cells [12, 22, 30]. Both PGC-1α and ERRα have been shown to promote the growth of ERBB2+ tumors in vivo and to regulate the metabolism of this specific breast cancer subtype [12, 13, 22, 31]. Interestingly, increased expression of PGC-1α reduced the proliferation of ERBB2+ cells in vitro, but promoted tumor growth in vivo by promoting nutrient supply . We show here that ERBB2+ cells are dependent on glutamine for their growth as complete glutamine removal from cell culture severely compromised cell growth. Although the glucose dependence of ERBB2+ cells is well known , the role of glutamine in this system has been largely overlooked. A point supporting the importance of glutamine in ERBB2+ tumors is the observation that ERBB2 signaling elevates c-Myc expression, which is a central regulator of glutamine metabolism . Furthermore, it would not be surprising that the pro-growth effect of PGC-1α and ERRα in ERBB2+ tumors is mediated at least in part through their positive impact on glutamine metabolism. In support of this point, the expression of PGC-1α and that of the glutamine pathway are positively correlated in ERBB2+ breast cancer patients, and high expression of glutamine metabolism enzymes is associated with shorter survival. It is important to emphasize that we do not exclude the possibility that PGC-1α may associate with other transcription factors, in addition to ERRα, to control the expression of glutamine metabolism genes.
In this paper, we reveal that the PGC-1α/ERRα axis is a central regulator of glutamine metabolism in ERBB2+ breast cancer. PGC-1α/ERRα likely regulate similar metabolic programs in diverse cancer types as the metabolic targets of PGC-1α/ERRα in various normal tissues and cancer cells/tumors are similar. The positive or negative impact of PGC-1α/ERRα on tumor growth will depend on the specific metabolic alterations of each tumor. There is significant effort currently underway to associate metabolic signatures to specific oncogenes. Furthermore, it is important to appreciate that the PGC-1α/ERRα axis also regulates the expression of genes not directly associated with metabolism; these genes may be equally or even more important in defining the roles of PGC-1α/ERRα in various cancer types. For example, ERRα regulates the expression of genes located in the ERBB2 amplicon that are involved in signal transduction, cell migration and invasion, as well as tamoxifen resistance . Overall, much remains to be discovered regarding the importance of PGC-1α/ERRα in contributing to the altered metabolism of various cancer types and to link this new metabolic state with clinical outcome. Also, the importance of PGC-1α/ERRα target genes involved in other hallmarks of cancer cells such as migration/invasion, apoptosis, and angiogenesis  needs to be established. That being said, the identification of PGC-1α/ERRα as central regulators of glutamine metabolism may open novel therapeutic avenues for tumors showing strong dependence on this metabolic pathway.
Co-first authors: Shawn McGuirk and Simon-Pierre Gravel.
Citric acid cycle
Reads per kilobase of exon model per million mapped reads
The Cancer Genome Atlas.
We acknowledge salary support from Canderel (to S-P.G.), Michael D'Avirro Fellowship in Molecular Oncology (to S.M.), Canadian Institutes of Health Research (CIHR) (to B.F. and R.G.J.), Fonds de la Recherche en Santé du Québec (FRSQ) (to J.St-P.), McGill Integrated Cancer Research Training Program (MICRTP) (to D.J.P., FRN53888), and US department of Defense Breast Cancer Research Program (to G.D., W81XWH-10-1-0489). This work was supported by grants from the Canadian Institutes of Health Research [grant number MOP-106603 to J.St-P.; MOP-93799 to R.G.J.; MOP-64275 to V.G.] and Terry Fox Foundation [grant number TFF-116128 to J.St-P., R.G.J., V.G., and Metabolomics Core Facility]. We also thank Erzsebet Nagy Kovacs for technical assistance.
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