Insulin enhances metabolic capacities of cancer cells by dual regulation of glycolytic enzyme pyruvate kinase M2
- Mohd Askandar Iqbal1,
- Farid Ahmad Siddiqui1,
- Vibhor Gupta1,
- Shilpi Chattopadhyay1,
- Prakasam Gopinath1,
- Bhupender Kumar1,
- Siddharth Manvati1,
- Noor Chaman1 and
- Rameshwar NK Bamezai1Email author
© Iqbal et al.; licensee BioMed Central Ltd. 2013
Received: 27 May 2013
Accepted: 13 June 2013
Published: 9 July 2013
Insulin is tightly associated with cancer progression; however, mechanistic insights into such observations are poorly understood. Recent studies show that metabolic transformation is critical to cancer cell proliferation. Here, we attempt to understand the role of insulin in promotion of cancer metabolism. To this end, the role of insulin in regulating glycolytic enzyme pyruvate kinase M2 (PKM2) was examined.
We observed that insulin up-regulated PKM2 expression, through PI3K/mTOR mediated HIF1α induction, but significantly reduced PKM2 activity independent of this pathway. Drop in PKM2 activity was attributed to subunit dissociation leading to formation of low activity PKM2 oligomers, as assessed by density gradient centrifugation. However, tyrosine 105 phosphorylation of PKM2, known for inhibiting PKM2 activity, remained unaffected on insulin treatment. Interestingly, insulin-induced ROS was found responsible for PKM2 activity reduction. The observed changes in PKM2 status led to augmented cancer metabolism. Insulin-induced PKM2 up-regulation resulted in enhanced aerobic glycolysis as confirmed by PKM2 knockdown studies. Further, PKM2 activity reduction led to characteristic pooling of glycolytic intermediates and increased accumulation of NADPH; suggesting diversion of glucose flux towards macromolecular synthesis, necessary for cancer cell growth.
The study identifies new PKM2-mediated effects of insulin on cancer metabolism, thus, advancing the understanding of insulin’s role in cancer.
KeywordsInsulin Cancer Metabolism Lactate Glycolysis HepG2, PKM2
Pyruvate kinase M2
Mammalian target of rapamycin
Pentose phosphate pathway
Nicotinamide adenine dinucleotide phosphate
Reactive oxygen species
Cancer cell metabolism differs from that of normal cells and is characterized by high glucose uptake and lactate production even in presence of sufficient oxygen, an observation made by Otto Warburg in 1920’s. The phenomenon has been referred to as Warburg effect or aerobic glycolysis which forms the basis of 18fluorodeoxyglucose-positron emission tomography (FDG-PET) – a diagnostic technique used for clinical detection of cancer . Although, inefficient in terms of ATP production, aerobic glycolysis, nonetheless, is vital to maintain macromolecule synthesis needed to produce daughter cells . Further, aerobic glycolysis is believed to provide cancer cells a selective advantage to grow in regions with low oxygen concentration . Considering the significance of aerobic glycolysis to cancer cells, metabolic behaviour is now perceived as a critical target for anti-cancer therapeutics [5, 6]. Among the several glycolytic genes that are up-regulated in cancer , pyruvate kinase is of prime significance because of its key position in glycolytic sequence [8, 9]. It catalyzes the last step of glycolysis i.e. conversion of phosphoenolpyruvate (PEP) to pyruvate with concomitant ATP production . Out of four isoforms of pyruvate kinase (PK) in mammals- L, R, M1 and M2 ; tumor cells predominantly express M2 isoform . Switch to this isoform is considered essential for aerobic glycolysis and tumor growth .
Activity of PKM2 is critical to determine a shift in metabolism required for tumor growth. Decrease in PKM2 activity causes pooling of glycolytic intermediates which are then shunted to pentose phosphate pathway (PPP) for NADPH generation for macromolecular synthesis, essential for cellular growth [8, 9, 11, 13]. Therefore, decreased PKM2 activity is believed to favour rapidly proliferating cancer cells; however, the phenomenology of PKM2 activity regulation by external factors is not well understood. PKM2 exists in highly active (tetramer) and less active (dimer/monomer) oligomeric forms. The ratio of these forms decides the overall PKM2 activity in cellular milieu [11, 14, 15]. In cancer cells, disruption of active PKM2 tetramers results in accumulation of less active PKM2 monomers/dimers, thus, promoting anabolic synthesis [9, 13]. Our previous work has shown how two missense mutations in PKM2 stabilized less active PKM2 form to promote cellular growth and polyploidy .
Evidences in recent years have suggested a crucial role of insulin in cancer cell growth and survival [17–20]. High levels of endogenous insulin among type-2 diabetics and non-diabetics have also been associated with increased cancer risk in epidemiological studies ; with highest risk for liver and pancreatic cancer [22–24]. Significantly, insulin receptor has been reported to provide resistance to IGF-1R targeted therapies ; emphasizing the importance of targeting insulin signalling. The role of insulin, however, in regulation of cancer cell metabolism is still obscure.
In this study, the role of insulin in promotion of cancer metabolism is examined. We show that insulin promotes cancer metabolism by upregulating PKM2 expression and decreasing its activity. Insulin-induced changes in PKM2 status directly resulted in amplification of cancer-metabolism-specific parameters like glucose uptake, lactate production, glycolytic pooling and macromolecular synthesis. Our results contribute to better understanding of the role of insulin in cancer metabolism and thus cancer progression.
PKM2 is the predominant isoform of pyruvate kinase in cancer cells
Insulin upregulates PKM2 expression in a PI3K/mTOR dependent manner by inducing HIF1α expression
PI3K/mTOR signalling was inhibited to find out if insulin-induced PKM2 up-regulation is PI3K dependent. PI3K is the chief mediator of insulin signalling in liver and is frequently mutated in liver and other cancers [26–28]. As a result of PI3K/mTOR inhibition, PKM2 expression was down-regulated (Figure 2C-E). These results confirmed that insulin regulates PKM2 expression through PI3K/mTOR pathway. To elucidate how PI3K/mTOR promoted PKM2 expression, the role of HIF1α protein, a transcription factor that binds to hypoxia response element (HRE) in PKM2 gene to induce its expression, was examined [29, 30]. Insulin induced HIF1α expression in a PI3K/mTOR sensitive manner, as was evident from the decrease in HIF1α protein after treatment with PI3K/mTOR inhibitors (Figure 2D). Further, to corroborate this observation, HIF1α was silenced as well as induced, using siRNA and cobalt chloride (CoCl2) treatment, respectively, to observe the effect on PKM2 expression [31, 32]. Expectedly, HIF1α silencing led to a decreased PKM2 expression; whereas CoCl2-induced HIF1α accumulation increased PKM2 expression (Figure 2F), confirming that HIF1α is crucial for PKM2 up-regulation. These results demonstrated that insulin upregulates PKM2 expression through PI3K/mTOR dependent induction of HIF1α transcription factor.
Insulin inhibits PKM2 activity, in a PI3K/mTOR independent manner, by promoting subunit dissociation
Evidence for the involvement of ROS in inhibition of PKM2 activity
PKM2 up-regulation is crucial in insulin-induced aerobic glycolysis
Glycolytic intermediates and NADPH accumulated as a result of decreased PKM2 activity
To demonstrate that decreased PKM2 activity is contributing to the observed accumulation of FBP, PEP and NADPH, PI3K/mTOR pathway was inhibited as it increases glucose uptake which might have contributed to observed accumulation. PI3K/mTOR inhibition did not completely block the insulin-induced pooling of FBP, PEP and NADPH. However, pretreatment with ROS scavengers NAC or ascorbate abolished the insulin-induced glycolytic pooling and accumulation of NADPH. These results indicated that insulin promoted accumulation of glycolytic intermediates and NADPH through decreased PKM2 activity.
In recent years, PKM2 has emerged as a key regulator of cancer metabolism. Considering the PKM2-mediated pro-cancerous effects of insulin, our results seemingly provide a mechanistic understanding into insulin’s role in cancer metabolism.
The predominance of PKM2 over other PK isoforms in HepG2, H1299 and PC3 cells (Figure 1 and Additional file 1: Figure S1) [30, 46], indicated the importance of this PK isoform in cancer, and is consistent with the notion that switch to PKM2 isoform is required for cancer progression . The insulin induced-up- regulation of PKM2, with evident increase at as low as 1 nM insulin (Figure 2), is an important observation, since PKM2 has been reported essential for aerobic glycolysis and tumor growth . PI3K-dependence of PKM2 expression supports the notion that PI3K pathway is central to insulin signalling in cancer cells and correlates with high frequency of PI3K mutations in several cancer types, which may lead to increased expression of PKM2 [26, 27]. PI3K/mTOR dependent induction of HIF1α on insulin treatment, and CoCl2-induced concomitant HIF1 α and PKM2 accumulation, along with HIF1α silencing results (with decreased PKM2 expression) clearly suggested that insulin promoted PKM2 expression through HIF1α (Figure 2D and F). Our results are consistent with previous observations of insulin up-regulation of PKM2 in adipocytes  and decreased PKM2 expression on PI3K/mTOR inhibition [44, 48]. These results also explain the recent observation of high PKM2 in PTEN (negative regulator of PI3K pathway) null fatty liver cells . Decreased aerobic glycolysis on PKM2 knock-down in PTEN deficient (hyper-activated PI3K/mTOR signalling) PC3 cells suggested that insulin promoted aerobic glycolysis, at least in part, through PKM2 (Figure 5). Importance of PKM2 in aerobic glycolysis could be realized from the observation that PKM2 transactivates expression of genes like glucose transporter-1 (GLUT1) and lactate dehydrogenase-A (LDHA), required for glucose uptake and lactate production respectively . Apparently, these results present an important mechanism which may underlie insulin’s role in carcinogenesis.
Decreased PKM2 activity fuels macromolecular synthesis by accumulating glycolytic intermediates that are precursors for PPP. Suppression of PKM2 activity presents yet another dimension of insulin’s role in promotion of cancer metabolism. Rise in peak I with simultaneous fall in peak II suggested subunit dissociation leading to increased formation of low activity oligomeric form of PKM2 (Peak I in Figure 3B), thus justifying the observed decrease in PKM2 activity (Figure 3A). Intriguingly, activity of PKM2 was not affected on PI3K/mTOR inhibition (Figure 3A and Additional file 6: Figure S5), indicating the involvement of other factors in activity regulation. Increased PKM2 activity in ascorbate or NAC pretreated cells suggests the involvement of ROS in activity regulation (Figure 4 and Additional file 4: Figure S4). Reversal of insulin-induced decrease in PKM2 activity by DTT suggests the possibility of ROS-induced oxidation of cysteine residues in PKM2 . Correlation between dose dependent changes in PKM2 activity and ROS production further support our conclusion of ROS mediated PKM2 activity inhibition (Figures 3D and 4C). Notably, ROS induced decrease in PKM2 activity has been linked with ability of lung cancer cells to withstand oxidative stress . However, further research is needed to support this observation in liver and prostate cancer cells.
The decrease in the activity of PKM2, positioned at the end of glycolytic sequence, in cancer cells is suggested to accumulate important glycolytic intermediates required for cellular growth. On the contrary, a decrease in the activity of enzyme, like hexokinase, which appear earlier in glycolytic sequence, does not provide the same advantage to the cancer cells; thus the biosynthetic processes required for cellular growth would be inhibited. Accumulation of glycolytic intermediates PEP and FBP (Figure 6) indicated the diversion of glucose flux towards biosynthetic pathway PPP , an observation which was confirmed when PPP product NADPH accumulated upon insulin treatment (Figure 6B). The decrease in glycolytic pooling and NADPH accumulation on PI3K/mTOR inhibition correlated with glucose uptake regulation by PI3K/mTOR pathway (Figures 5A and 6). Interestingly, metabolite accumulation decreased almost to the levels of untreated control upon treatment with ROS scavengers NAC or ascorbate, suggesting a crucial role of decreased PKM2 activity in insulin-induced metabolite build-up. ROS scavenging increased PKM2 activity which negatively affected metabolite pooling and macromolecular synthesis (Figures 4B and 6).
Materials and methods
Cell culture, drug treatment, knockdown and proliferation studies
HepG2 and PC3 cell lines were procured from the National Centre for Cell Science, Pune, India. H1299 cells were a kind gift from Dr. Uttam Pati, School of Biotechnology, Jawaharlal Nehru University. All the cell lines were maintained in DMEM (Sigma) with 10% heat-inactivated FBS (Biowest, France), 1% penicillin/streptomycin (Sigma) at 37°C and 5% CO2 in a humified atmosphere (Heraeus, UK). Cells were grown in monolayer and passaged routinely two-three times a week. For drug treatment; LY294002 (Sigma) and rapamycin (Sigma) were dissolved in DMSO; single use aliquots were stored at −80°C For insulin treatment: cells were seeded in triplicate at a density of 0.4 million cells/well of six well plates, serum starved for 20–24 hours and then stimulated with insulin (Sigma) in presence or absence of inhibitors. DMSO treated cells were used as mock control. For PKM2 knockdown: short hairpin RNA (shRNA) constructs in lentiviral pGIPZ vector were purchased from Open Biosystems. Control and shRNA containing pGIPZ vectors were transfected using polymer based transfection reagent- Arrestin from Thermo-Scientific, as per manufacturer’s instructions. Knock down efficiency was then checked by real time PCR and Western blotting. For HIF1α silencing: pre-designed siRNA was used and transfected using Lipofectamine (Invitrogen) as per manufacturer’s protocol and efficiency was checked by Western blotting. For proliferation assay: cells were counted before and after 48 hours of transfection, using a hemocytometer.
RNA isolation, cDNA preparation and real time PCR
Cellular RNA was extracted from cell lines using TRIzol (Sigma), according to manufacturer’s protocol. RNA quality was analyzed by A260/A280 absorbance and by electrophoresis on a 1.2% agarose formaldehyde gel. 3–4 μg of total RNA was reverse transcribed into single stranded DNA using cDNA preparation kit (Applied Biosystems, USA). Commercially available Taqman gene expression assay (Applied Biosystems, USA) was used for quantitating mRNA levels of PKM2. β-actin was used as endogenous control. Real time PCR was carried out on ABI Prism 7000 Sequence Detection System (Applied Biosystems). ΔΔCt (Cycle threshold) method of relative quantification was used to calculate fold change in gene expression by SDS 1.1 RQ software (Applied Biosystems).
Cell lysate preparation, protein estimation and Western blotting
Whole cell lysate was prepared by incubating cells, on ice for 30 minutes, in buffer containing 50 mM Tris pH 7.2, 150 mM NaCl, 0.5% sodium deoxycholate, 10% glycerol, 1% Triton X-100, 0.1% SDS, 1 mM DTT, 1 mM PMSF, 5 mM NaF, 1 mM NaV, phosphatase inhibitor cocktail (Sigma), 4 μg/ml aprotinin, 4 μg/ml leupeptin and 4 μg/ml pepstatin (Sigma). The lysate was centrifuged at high speed in a cooling centrifuge (CM 12, Remi, India) for 30 minutes and supernatant was collected in pre-chilled fresh tubes. Protein concentration was estimated using BCA method as per manufacturer protocol (Thermo Scientific). Proteins were separated on 8% SDS-PAGE, transferred to nitrocellulose membrane (mdi) at 4°C (wet transfer) and probed with primary antibodies. Membrane was incubated with appropriate secondary antibody for one hour at room temperature and proteins were detected using Luminata forte (Millipore). Primary antibodies used were: anti-HIF1α (Novus Biologicals, USA), anti PKM2, anti-phospho-PKM2 (Tyr105), anti-AKT, anti-phospho-AKT, anti-phosphoS6, anti-S6 protein and anti-β-actin (Cell Signalling Technology).
PKM2 activity assay and glycerol gradient centrifugation
U/mg = specific enzyme activity per mg of protein.
OD340 = Change in absorbance due to oxidation of NADH in one minute at 340 nm wavelength.
For glycerol gradient experiment, 500 μg of cell lysate protein was loaded on the top of 11-25% glycerol gradient and centrifuged at 45000 rpm for 16 hours at 4°C in SW55Ti rotor (Beckman Coulter) and rest of the procedure was followed as described .
Metabolites, glucose and lactate measurement
Metabolite extract was prepared from 20 million cells in 0.5 ml of chilled 90% ethanol containing 0.2% formic acid and centrifuged at 15000 rpm in a refrigerated centrifuge. Supernatant was dried using nitrogen flow and then reconstituted in 0.2 ml of MilliQ water. PEP was assessed using NADH/LDH coupled assay as mentioned above with 30 ng of recombinant PKM2. FBP was measured as described . For both FBP and PEP, concentration was determined against standard curve. NADPH was analyzed using kit from BioVision- USA, as per the manufacturer’s protocol. For glucose and lactate: media was collected from wells; spun down at high speed to remove any cell debris, deproteinized using TCA, pH was adjusted between 7.0-7.5 and then glucose uptake was analyzed using glucose assay kit (Sigma), according to manufacturer’s protocol. Lactate and was analysed using kit (BioVision, USA) as per manufacturer’s instructions. All the measurements were normalized to cell numbers.
Ascorbate, NAC treatment and ROS analysis
Cells pretreated with or without ascorbate or NAC (Sigma) were incubated with DCFH-DA for 30 minutes in dark at 37°C, followed by insulin stimulation. Cells were then washed with PBS, trypsinized and resuspended in 0.5 ml PBS, kept on ice, in dark until ROS analysis by fluorescence spectrophotometry. Excitation and emission wavelengths used were 500 nm and 510 nm respectively.
Each experiment was performed in triplicate. All experiments were repeated at least 3 times. Significance was calculated using student’s t-test. P value less than 0.05 was considered statistically significant.
RNKB acknowledges University Grants Commission (UGC), Government of India, for providing research funds to NCAHG. MAI acknowledges UGC for providing research fellowship.
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