DU-145 and 22Rv1 cells were purchased from the American Type Culture Collection (ATCC; Manassas, VA). DU-145 cells were cultured in Gibco DMEM (Thermo Fisher Scientific, Inc., Waltham, MA, USA) and 22Rv1 cells were cultured in Gibco RPMI-1640 (Thermo Fisher Scientific, Inc.) containing 10% fetal calf serum, 100 U/ml penicillin and 100 µg/ml streptomycin in a humidified atmosphere containing 5% CO₂ set at 37°C. Every two days, media were changed to provide cells with optimal growth conditions.

All siRNA oligonucleotides were purchased from GenePharma Co., Ltd. (Shanghai, China). The sequences of all specific siRNAs targeted to human PTEN are displayed in Fig. 1A. The siRNAs were transfected into cells with Lipofectamine 2000 (Invitrogen; Thermo Fisher Scientific, Inc.). In the small interfering RNA (siRNA) data set, prostate cancer cells were divided into 3 groups. The control group was transfected with control siRNA at a dose of 40 nM. The experimental group was transfected with either PTEN siRNA-1 or PTEN siRNA-2 at a dose of 20 or 40 nM. The media of the different groups were replaced by the fresh complete culture media after transfection for 6 h. Recombinant lentiviral vectors were constructed with an Invitrogen ViraPower™ Lentiviral System (Thermo Fisher Scientific, Inc.) in our laboratory. The lentiviral vectors pLKO-Scramble/PTEN shRNA-1/PTEN shRNA-2, PAX2 and PMD2G were transfected into 293T cells using Lipofectamine 2000 (Invitrogen; Thermo Fisher Scientific, Inc.) according to the manufacturer's instructions. DU-145 and 22Rv1 cells were infected with the viral medium from 293T cells 48 h after transfection.

After transfection with siRNAs for 48 h, total RNA was isolated from cells using TRIzol Reagent (Invitrogen; Thermo Fisher Scientific, Inc.), and then complementary DNA (cDNA) was synthesized using AMV reverse transcriptase (Promega Corporation, Madison, WI, USA) according to the manufacturer's instructions. The cDNA was used as a template for quantitative real-time PCR using an ABI Prism 7500 real-time PCR instrument (Applied Biosystems; Thermo Fisher Scientific, Inc.). The primer sequences for PTEN and β-actin were as follows: PTEN forward primer, 5′-CGACGGGAAGACAAGTTCAT-3′ and reverse, 5′-AGGTTTCCTCTGGTCCTGGT-3′; β-actin forward primer, 5′-CGCGAGAAGATGACCCAGAT-3′ and reverse, 5′-GTACGGCCAGAGGCGTACAG-3′. The following thermocycling conditions were maintained: 95°C for 3 min; 95°C for 10 sec and 58°C for 30 sec for 39 cycles; and melting curve analysis using an increase from 65.0 to 95.0°C in 0.5°C increments for 5 sec. Independent experiments were repeated three times. The relative expression levels of mRNA were analyzed using Bio-Rad CFX Manager v3.1 software (Bio-Rad Laboratories, Inc., Hercules, CA, USA) with the 2^−∆∆Cq method (12).

After transfection with siRNAs for 48 h, cells were lysed in cell lysis buffer containing 20 mM Tris-HCl, 0.5 M NaCl, 0.25% Triton X-100, 1 mM EDTA, 1 mM EGTA, 10 mM β-glycophosphate, 300 µM Na₃VO₄, 10 mM NaF, 1 mM benzamidine, 2 µM PMSF and 1 mM DTT. Protein concentrations were determined by a BCA protein assay (Thermo Fisher Scientific, Inc.). Proteins were subjected to 10% SDS-PAGE, transferred on to nitrocellulose membranes, blocked in 5% BSA, and followed by washing with TBS with Tween-20. The blots were then incubated with primary antibodies for 12 h at 4°C followed by incubation with the secondary antibody for 2 h at room temperature. The following primary antibodies were used: polyclonal rabbit anti-human phospho-Akt (Ser473) (dilution, 1:1,000; cat. no. 9271S), polyclonal rabbit anti-human Akt (dilution, 1:1,000; cat. no. 9272S), polyclonal rabbit anti-human PTEN (dilution, 1:1,000; cat. no. 9552S), polyclonal rabbit anti-human HK1 (dilution, 1:1,000; cat. no. 2024S), polyclonal rabbit anti-human HK2 (dilution, 1:1,000; cat. no. 2106S), polyclonal rabbit anti-human PKM1/2 (dilution, 1:1,000; cat. no. 3186S), polyclonal rabbit anti-human PKM2 (dilution, 1:1,000; cat. no. 3198S), polyclonal rabbit anti-human LDHA (dilution, 1:1,000; cat. no. 2012S), polyclonal rabbit anti-human PDH (dilution, 1:1,000; cat. no. 3205S), polyclonal rabbit anti-human PFKP (dilution, 1:1,000; cat. no. 5412S) all from Cell Signaling Technology, Inc. (Danvers, MA, USA), and monoclonal rabbit anti-human PCB (dilution, 1:2,000; cat. no. ab126707; Abcam, Cambridge, UK), or polyclonal rabbit anti-human β-actin (dilution, 1:1,000; cat. no. 4970S; Cell Signaling Technology, Inc.). Membranes were then incubated with horesradish peroxidase-conjugated secondary antibody polyclonal goat anti-rabbit IgG (dilution, 1:3,000; cat. no. ab97051; Abcam) for 1 h and visualized with SuperSignal™ West Femto Maximum Sensitivity Substrate (Thermo Fisher Scientific, Inc.) according to the manufacturer's recommended protocol. Quantification was performed using Image J software version 1.45S (National institutes of Health, Bethesda, MD, USA).

After 48 h of transfection, all culture media were collected for glucose consumption and lactate production analysis. The concentrations of glucose in culture media were assessed after 24 h using a Glucose Detection Kit (Invitrogen; Thermo Fisher Scientific, Inc.). Briefly, the culture media was mixed with the colorimetric substrate and horseradish peroxidase and the reaction was initiated by the addition of glucose oxidase in a 96-well plate. The reaction was incubated for 30 min at room temperature and the product was assessed by a microplate reader at an absorbance of 560 nm. Glucose consumption was the difference of the glucose concentration between the spent medium and the unused medium. The concentrations of lactate in the culture media were assessed using a Lactate Assay Kit (Jiancheng Bioengineering, Nanjing, China). Briefly, the culture media was mixed with lactate assay buffer in a 96-well plate. Then reaction buffer was added to every well and incubated for 30 min at room temperature. The lactate production was assessed by a microplate reader at an absorbance of 570 nm.

Cells infected with lentivirus containing PTEN shRNA or control shRNA were seeded into 96-well plates in triplicate at a starting density of 1×10⁴ cells/well. Treated cells were washed and incubated with tetrazolium salt (MTT, 100 µg/ml; Sigma-Aldrich; Merck KGaA, Darmstadt, Germany) at 37°C for 4 h. The supernatant was removed, and 150 µl of dimethyl sulfoxide (DMSO) was added to each well. The absorbance (OD) of the reaction solution at 490 nm was recorded.

The siRNA-treated cells were washed twice with room temperature D-Hank's solution, digested with trypsin for 5 min and then collected in a culture tube. The collected solution was centrifuged (4°C, 380 × g, 2 min), and the supernatant was discarded. Next, 500 µl of methyl alcohol (4°C) was added to the tube containing the cell pellet and was vortexed for 30 sec. After three freeze-thaw cycles, the mixture was centrifuged (4°C, 15,000 × g, 10 min). The upper layer was used for organic acid and fatty acid metabolomics analysis.

For organic acid analysis, the supernatant was placed in a 1.5 ml polypropylene centrifuge tube, then 25 µl each of margarate (MGA) and tetracosane (C24) and 40 mg of tropate (TA) were added as internal standards. Subsequently, 50 µl of hydroxylamine hydrochloride, sulfuric acid and saturated ammonium chloride were added to the fouling reaction. The the mixed solution was extracted twice by ether. After centrifugation for 5 min, the supernatant was placed in a 1.5 ml vial. The aliquots were evaporated to dryness in a vacuum concentrator. The final dry residue, 110 µl of a mixture of BSTFA and TMCS (10:1, v:v) were added and dissolved. The solution was then transferred to a 1-ml screw top vial, tightly capped and trimethylsilyl (TMS)-derivatized at 80°C for 30 min. The samples were then ready for GC-MS analysis.

Samples were analyzed using a Gas Chromatography-Mass Spectrometer (GC-MS, 7890–5975; Agilent Technologies, Inc., Santa Clara, CA, USA). The capillary column was a fused-silica DB-5 column (30 m × 0.25 mm i.d.) with a 0.25-µm film thickness of 5% phenylmethylsilicone. Mass spectra were obtained by standard electron impact ionization scanning from m/z 50 to m/z 750 at a rate of 0.35 sec/cycle. The temperature program started at 150°C with an initial hold for 1 min, and the temperature was then increased at a rate of 10°C/min to 285°C with a final hold for 8 min. The temperatures of the injection port and transfer line were both 280°C. The flow rate of the helium carrier was 1.5 ml/min, and the linear velocity was 38.5 m/sec. One ml of the final derivatized aliquot was injected into the GC-MS and analyzed in the split mode (10:1).

The compounds were identified by automatically comparing the MS spectra, in-source fragments, and ion features of each peak in the experimental samples with those of reference standards or those available in libraries, such as Mainlib and Publib in the National Institute of Standards and Technology (NIST) library 2.0 (2012) or Wiley 9 (Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim, Germany).

For fatty acid analysis, the supernatant was placed in a polypropylene microtiter plate. Methanolic internal standard solution (150 µl) was added manually. The microtiter plate was gently shaken during the 30 min extraction of acyl-carnitine markers. The methanol extract was then manually transferred to a second polypropylene microtiter plate and dried by a Pressure Blowing Concentrator at 50°C. Butanol-HCl (60 µl) was manually placed in each sample well and the microtiter plate was covered with a thin Teflon sheet under a heavy weight and placed at 70°C in a forced air oven for 15 min. After the plate was removed from the oven, the Pressure Blowing Concentrator removed the remaining butanol-HCl. The butanol-derivatized samples were reconstituted with 100 µl of acetonitrile and water (70:30 by volume), and each plate was covered with aluminum foil. The samples were then ready for LC-MS analysis.

Samples were analyzed using liquid chromatograph-tandem mass spectrum (LC20AD; Shimadzu, Kyoto, Japan; API 4000+; AB-Sciex, Framingham, MA, USA).

A mixture of acetonitrile and water (70:30, v/v) was used as carrier solution at a flow rate of 0.14 ml/min. A step gradient program was developed for the best separation of amino acids: 0.14 ml/min, 0.2 min; 0.03 ml/min, 1 min; 0.3 ml/min, 0.2 min. An 18-µl sample was injected into the carrier solution. Then, the stream was introduced to the ion source for MS/MS without column separation.

The mass spectrum (MS) parameters in positive ion mode (ESI + MODE) were as follows: Heater Temp, 300°C; Capillary Temp, 350°C; Sheath Gas Flow rate, 45 arb; Aux Gas Flow Rate, 15 arb; Sweep Gas Flow Rate, 1 arb; Spray voltage, 3.0 KV. Product Ion Scan modes were defined to analyze fatty acid metabolism. All data acquisition and processing were carried out using Analyst 1.5.2 software (AB-Sciex).

Statistical analysis was performed using SPSS 17.0 software (SPSS, Inc., Chicago, IL, USA). The chi-square test was used to evaluate the significance of the differences in the cell line samples. Statistical significance was assumed at a threshold of P<0.05. Metabolic pathway analysis and enrichment analysis were performed by MBROLE 2.0 (http://csbg.cnb.csic.es/mbrole2/) and KEGGgraph (http://www.bioconductor.org/packages/2.4/bioc/html/KEGGgraph.html). The function of KEGGgraph suggested that > library (KEGG.db), > tmp <- tempfile, > pName <- ‘Phe signaling pathway’, > pId <- mget (pName, KEGGPATHNAME2ID), > retrieveKGML(pId, organism=‘cel’, destfile=tmp, method=‘wget’, quiet=TRUE).

To investigate the metabolic changes in PTEN knockdown prostate cancer, we synthesized two pairs of PTEN siRNAs and a control siRNA (Fig. 1A). After the prostate cancer cell line DU-145 was transfected with 20 or 40 nM siRNAs for 48 h, the endogenous PTEN expression level was detected by quantitative real-time PCR and western blotting. The results revealed that endogenous PTEN was significantly decreased in 22Rv1 and DU-145 cells transfected with 40 nM PTEN siRNAs compared with the control siRNAs (Fig. 1B and C). Furthermore, the phosphorylation of Akt at Serine 473 was significantly increased in DU-145 and 22Rv1 cells that were transfected with 40 nM PTEN siRNAs after 48 h (Fig. 1D). Accompanying the activation of Akt, glucose consumption and lactate production was also significantly increased in PTEN knockdown DU-145 and 22Rv1 cells (Fig. 1E). Therefore, aerobic glycolysis was possibly increased in PTEN knockdown DU-145 and 22Rv1 cells. Furthermore, the expression of metabolic molecules related to glucose metabolism were detected and it was demonstrated that hexokinase HK2, the first key enzyme involved in glycolysis, was upregulated in PTEN knockdown DU-145 and 22Rv1 cells, especially in DU-145 cells (Fig. 1F). Upregulation of HK2 may be one of the contributors to the Warburg effect in PTEN knockdown DU-145 and 22Rv1 cells. Tumor metabolic reprogramming fuels the malignant growth and proliferation of cancer cells (13–15). Therefore, cell viability was increased in DU-145 cells that were infected with lentivirus containing PTEN shRNA compared with control shRNA (Fig. 1G). However, cell viability was not significantly altered in 22Rv1 cells that were infected with lentivirus containing PTEN shRNA. Although the PI3K/AKT/mTOR and RAF/MEK/ERK signaling pathways play an important role in prostate cancer progression, 22Rv1 prostate cancer cells have been revealed to be more dependent on the MEK/ERK pathway (16). Collectively, cell metabolism and cell viability was significantly altered in PTEN-loss DU-145 cells. Thus, metabolism reprogramming occurred, induced by PTEN deficiency in prostate cancer cells.

High rates of loss of heterozygosity are observed at the 10q23.3 region containing the human PTEN gene in prostate cancer. The phenotypes of PTEN^+/− DU-145 cells are similar to prostate cancers with loss of heterozygosity in the PTEN gene (17–19). In addition, the cell viability induced by PTEN loss increased significantly in DU-145 cells. Therefore, we assessed the changes of key metabolites in PTEN knockdown DU-145 cells by metabolomics analysis. There are several metabolic pathway changes in tumor metabolism reprogramming, such as glycolysis, glutaminolysis, fatty acid de novo synthesis and fatty acid β-oxidation. Accordingly, the changes of key metabolites in these metabolic pathways were assessed in prostate cancer cells DU-145 transfected with PTEN siRNAs.

Since glucose and glutamine are the main energy production and carbon sources for the malignant growth of tumor cells, we assessed the levels of metabolites in glycolysis and glutaminolysis. As revealed in Fig. 2, many organic acids involved in glycolysis and glutaminolysis were significantly increased, such as lactate, pyruvic acid, succinic acid, citric acid, fumaric acid, malic acid, and 2-ketoglutarate. In addition, the level of intracellular glutamine was decreased in PTEN knockdown DU-145 cells. Therefore, PTEN knockdown led to enhanced glycolysis and glutaminolysis in prostate cancer DU-145 cells.

Unlike other epithelial tumors, primary prostate cancer relies on lipid metabolsim more than on aerobic glycolysis (8,9). PTEN loss can lead to the overexpression of fatty acid synthase (FAS) and therefore facilitate cholesterol and fatty acid biosynthesis in prostate cancer (10). To investigate the function of PTEN in lipid metabolism, the metabolite changes in fatty acid de novo synthesis of PTEN knockdown DU-145 cells was analyzed. The results revealed that when PTEN expression was significantly decreased in prostate cancer cells, many fatty acylcarnitines involved in fatty acid de novo synthesis were enhanced, such as decanoyl-carnitine, dodecanoyl-carnitine, tetradecanoyl-carnitine, hexadecanoyl-carnitine, hexadecenoyl-carnitine, octadecanoyl-carnitine (Fig. 3). In parallel with enhanced fatty acid de novo synthesis, fatty acid β-oxidation was also increased in PTEN knockdown prostate cancer DU-145 cells. Compared with the control siRNA-transfected cells, many fatty acylcarnitines involved in fatty acid β-oxidation were significantly increased in DU-145 cells which were transfected with PTEN siRNAs, such as butanoyl-carnitine, hexanoyl-carnitine, hexenoyl-carnitine, hydroxyhexanoyl-carnitine, octenoyl-carnitine, decanoyl-carnitine, dodecanoyl-carnitine, tetradecanoyl-carnitine, hydroxytetradecanoyl-carnitine, hexadecanoyl-carnitine, hexadecenoyl-carnitine, and hydroxyhexadecanoyl-carnitine (Fig. 4). These results confirmed that PTEN loss can lead to the reprogramming of lipid metabolism in prostate cancer cells, including enhancement of fatty acid de novo synthesis and fatty acid β-oxidation, which provides bioenergy and biomolecules to fuel the malignant proliferation of cancer cells.

The key enzyme that initiates the catabolism of branched-chain amino acids is branched-chain amino acid transaminase 1 (BCAT1), which is overexpressed in many types of cancers (20). Compared with healthy tissues, it has been reported that low levels of BCAT activity are present in all models of prostate cancer but the enzymatic levels are significantly altered in prostate cancer (21). Our results revealed that the products of branched-chain amino acid catabolism such as the levels of hydroxyisovaleryl-carnitine, methylbutanoyl-carnitine, and propanoyl-carnitine were increased in DU-145 cells which were transfected with PTEN siRNAs. Therefore, the catabolism of branched-chain amino acids was enhanced in PTEN-loss prostate cancer cell line DU-145 (Fig. 5). Whether the enhancement of BCAA catabolism is related to BCAT1 and the molecular mechanisms driving this still requires further investigation.