Effects of canagliflozin on growth and metabolic reprograming in hepatocellular carcinoma cells: Multi-omics analysis of metabolomics and absolute quantification proteomics (iMPAQT)

Dan Nakano; Takumi Kawaguchi; Hideki Iwamoto; Masako Hayakawa; Hironori Koga; Takuji Torimura

doi:10.1371/journal.pone.0232283

. 2020 Apr 28;15(4):e0232283. doi: 10.1371/journal.pone.0232283

Effects of canagliflozin on growth and metabolic reprograming in hepatocellular carcinoma cells: Multi-omics analysis of metabolomics and absolute quantification proteomics (iMPAQT)

Dan Nakano ¹, Takumi Kawaguchi ^1,^*, Hideki Iwamoto ^1,², Masako Hayakawa ², Hironori Koga ^1,², Takuji Torimura ^1,²

Editor: Tatsuo Kanda³

PMCID: PMC7188283 PMID: 32343721

Abstract

Aim

Metabolic reprograming is crucial in the proliferation of hepatocellular carcinoma (HCC). Canagliflozin (CANA), a sodium-glucose cotransporter 2 (SGLT2) inhibitor, affects various metabolisms. We investigated the effects of CANA on proliferation and metabolic reprograming of HCC cell lines using multi-omics analysis of metabolomics and absolute quantification proteomics (iMPAQT).

Methods

The cells were counted 72 hours after treatment with CANA (10 μM; n = 5) or dimethyl sulfoxide (control [CON]; n = 5) in Hep3B and Huh7 cells. In Hep3B cells, metabolomics and iMPAQT were used to evaluate the levels of metabolites and metabolic enzymes in the CANA and CON groups (each n = 5) 48 hours after treatment.

Results

Seventy-two hours after treatment, the number of cells in the CANA group was significantly decreased compared to that in the CON group in Hep3B and Huh7 cells. On multi-omics analysis, there was a significant difference in the levels of 85 metabolites and 68 metabolic enzymes between the CANA and CON groups. For instance, CANA significantly downregulated ATP synthase F1 subunit alpha, a mitochondrial electron transport system protein (CON 297.28±20.63 vs. CANA 251.83±22.83 fmol/10 μg protein; P = 0.0183). CANA also significantly upregulated 3-hydroxybutyrate, a beta-oxidation metabolite (CON 530±14 vs. CANA 854±68 arbitrary units; P<0.001). Moreover, CANA significantly downregulated nucleoside diphosphate kinase 1 (CON 110.30±11.37 vs. CANA 89.14±8.39 fmol/10 μg protein; P = 0.0172).

Conclusions

We found that CANA suppressed the proliferation of HCC cells through alterations in mitochondrial oxidative phosphorylation metabolism, fatty acid metabolism, and purine and pyrimidine metabolism. Thus, CANA may suppress the proliferation of HCC by regulating metabolic reprograming.

Introduction

Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related death worldwide [1]. Although there are several therapeutic options for HCC including oral multikinase inhibiters, the prognosis of patients with HCC is still unsatisfactory [1]. One mechanism of tumor progression and treatment resistance is metabolic reprograming, which promotes adenosine triphosphate (ATP) production to meet the bioenergetic and biosynthetic demands of tumor growth [2]. In HCC, metabolic reprograming is seen in various metabolisms including lipid, amino acid, and purine metabolisms [3–5]. In addition, reprograming of glucose metabolism is involved in the proliferation of HCC [6–8].

Recently, sodium glucose co-transporter 2 (SGLT2), a glucose transporter, has been found to occur not only in renal proximal tubular epithelial cells but also in cancer cells including pancreatic cancer as well as HCC [9]. In addition, a meta-analysis showed that canagliflozin (CANA), a SGLT2 inhibiter (SGLT2i), suppresses gastrointestinal cancers in patients with type 2 diabetes mellitus [10]. Kaji et al. demonstrated that CANA inhibits hepatoma cell growth by suppressing angiogenic activity and chronic inflammation [11]. Moreover, Shiba et al. reported that CANA attenuates the development of HCC by reducing the oxidative stress of adipose tissue in a mouse model of nonalcoholic steatohepatitis [12]. However, the direct effects of SGLT2i on metabolic reprograming in HCC remain unclear.

Metabolomics is the large-scale systematic analysis of metabolites, which is a powerful approach to uncovering detailed information about changes in metabolites [13]. Metabolomics has been applied to the study of HCC and provides new insights into the diagnosis, prognosis, and therapeutic evaluation of HCC [13, 14]. Changes in metabolites are caused by alterations in metabolic enzymes; therefore, proteomics should also be applied to detect metabolic reprograming. Recently, Matsumoto et al. developed a new method for in vitro proteome-assisted multiple reaction monitoring for protein absolute quantification (iMPAQT) [15]. iMPAQT is able to measure the absolute quantity of any human protein in a given pathway of interest with high quantitative accuracy [15]. Although iMPAQT has been used to investigate the therapeutic target of bladder cancer [16], this new proteomics analysis has never been applied to investigate metabolic reprogramming in HCC.

The aim of this study was to investigate the effects of SGLT2i on the proliferation of HCC cell lines. In addition, we investigated the effects of SGLT2i on metabolic reprograming using multi-omics analysis combining metabolomics and iMPAQT analyses.

Methods

Reagents and antibodies

CANA, a SGLT2i, was kindly provided by the Mitsubishi Tanabe Pharma Corporation (Osaka, Japan). All other reagents were purchased from Cell Signaling Technology, Inc. (Danvers, MA) unless otherwise indicated. Antibodies against SGLT2 were purchased from Abcam plc (ab137207 and ab85626, Kenbridge, England), Proteintech Group, Inc. (24654-1-AP, Rosemont, IL), and Cell Signaling Technology, Inc. (#14210). Antibodies against glucose transporter (GLUT) 4, GLUT5, GLUT6, anti-mitochondrial pyruvate dehydrogenase kinase, hydroxymethylglutaryl-CoA lyase, and phosphate- AMP-activated protein kinase (AMPK) α2 (Ser345) were purchased from Abcam plc. Antibodies against GLUT1, GLUT2, GLUT3, caspase8, caspase3, carnitine palmitoyltransferase (CPT) 1A, CPT2, acyl-CoA synthetase long-chain family member/fatty acid-CoA ligase, and solute carrier family 25 member 2 were purchased from Proteintech Group, Inc. Actin antibody was purchased from Sigma-Aldrich Co. LLC (St. Louis, MO). Anti-glyceraldehyde-3-phosphate dehydrogenase antibody was purchased Santa Cruz Biotechnology (Dallas, TX). Jurkat (Human) whole cell lysate was purchased from Abcam plc. Primary human hepatocytes (LHum17003) was purchased from BIOPREDIC International (Saint-Grégoire, France).

Cell lines

Huh7 cells were obtained from HuH7 (JCRB0403) and HLF (JCRB0405) cells were obtained from the JCRB Cell Bank (Tokyo, Japan). Hep3B cells (HB8064) were obtained from the American Type Culture Collection (ATCC-LGC Standards). HAK-1A, HAK-1B, KYN-2, and KMCH-1 were kindly provided from Prof. Hirohisa Yano (Department of Pathology, Kurume University School of Medicine, Kurume, Japan).

Eight hepatoma cell lines such as Huh7, HLF, HepG2, Hep3B, KYN2, KMCH1, HAK1A, and, HAK1B cells were maintained in modified Dulbecco's modified Eagle's medium with L-glutamine and phenol red (Wako, Osaka, Japan), penicillin (10,000 units/mL), and streptomycin (10 mg/mL) at 37°C in a humidified atmosphere contained 5% CO².

Immunoblotting analysis and quantification

After washes with phosphate buffered saline (PBS), cells were lysed in a lysis buffer (RIPA buffer, Thermo Fisher Scientific, Inc., Waltham, MA) containing a protease and phosphatase inhibitor cocktail (Nacalai Tesque, Inc.). Cell lysates were centrifuged at 15,000 rpm × g for 15 minutes at 4°C, and the supernatant was collected. The protein concentration was determined by a protein assay kit (Pierce^TM, Thermo Fisher Scientific, Inc.). The samples were then mixed with an equal volume of 2 × sample loading buffer containing 4 × lithium dodecyl sulfate sample buffer (NuPAGE^® LDS sample buffer, Thermo Fisher Scientific, Inc.) and 2-mercaptoethanol and a sample reducing agent (NuPAGE^® Sample Reducing Agent, Thermo Fisher Scientific, Inc.). The membranes were washed and incubated with horseradish peroxidase-labeled secondary antibodies (GE Healthcare UK Ltd., Buckinghamshire, UK) for 1 hour at room temperature. After several washes, the membranes were incubated with chemiluminescent reagents (ImmunoStar LD, FUJIFILM Wako Pure Chemical Corporation, Tokyo, Japan), and specific bands were visualized by an image analyzer LAS-4000mini (GE Healthcare) as previously described [17]. The quantification of protein expression in western blotting was evaluated using ImageJ software (National Institutes of Health, Bethesda, MD, USA) [18].

Immunofluorescence staining

In this immunofluorescence staining, Huh7 and Hep3B cells were used. Cells were fixed in 4% paraformaldehyde and were incubated at 37°C for 20 minutes. After washes with PBS, cells were treated with 0.1% TritonX (Sigma-Aldrich Co. LLC.) and incubated at 37°C for 5 minutes. Cells were incubated with 3% skim milk in 1 × PBS at room temperature for 20 minutes. Antibodies were diluted in 3% skim milk in PBS. Cells were incubated in primary antibodies for SGLT2 (ab85626, Abcam plc) at 4°C overnight, washed with PBS, and then incubated in fluorescent-dye conjugated secondary antibody at 4°C in the dark, overnight. The nucleus was stained by 4',6-diamidino-2-phenylindole. The mitochondria were stained by an antibody for mitochondrial pyruvate dehydrogenase kinase 1. A fluorescence microscope (BZ-X700; Keyence Corporation, Osaka, Japan) was used to visualize the distribution of immunostaining for SGLT2 as previously described [19].

Isolation of mitochondrial fraction

Mitochondrial fraction was isolated by using Mitochondria Isolation Kit for Cultured Cells (ab110171, Abcam) according to the manufactures’ instruction. Briefly, Hep3B and Huh7 cells were collected with a cell lifter and pelleted by centrifugation at 1,000 g. The cells were freezed and then thaw in order to weaken the cell membranes. The cells were resuspended in Reagent A and, then, were transferred into a pre-cooled Dounce Homogenizer. The homogenates were centrifuged at 1,000 g for 10 minutes at 4°C and save as supernatant #1. The pellet was resuspended in Reagent B and repeated the rupturing. The homogenates were centrifuged and save as supernatant #2. Supernatants #1 and #2 were combined and centrifuged. The pellet was collected and resuspend into 500 μL of Reagent C supplemented with Protease Inhibitors. Freeze the aliquots at -80°C until use.

Effect of CANA on cell proliferation

The Hep3B and Huh7 cells were counted at 0, 24, 48, and 72 hours after treatment with 3, 10, and 30 μM of CANA (n = 5 per condition) or dimethyl sulfoxide (DMSO) (control [CON]; n = 5). Cells were trypsinized after washing with PBS. Then, the number of cells was determined using an automated cell counter (CDA-500; Sysmex Corporation, Kobe, Japan) as previously described [20]. In addition, the Hep3B cells were counted at 0, 24, 48, and 72 hours after treatment with 10 μM of dapagliflozin.

Living cell assessment by reagent SF assay

In this assay, Hep3B cells were used. The living Hep3B cells were counted by using Cell Count Reagent SF (Nacalai Tesque, Inc., Kyoto, Japan) according to the manufacturer’s instructions. This assay is a sensitive colorimetric assay utilizing a highly water-soluble tetrazolium salt, which produces a water-soluble formazan dye upon reduction in the presence of an electron carrier. Briefly, cells were cultured in Dulbecco's modified Eagle medium with 10% fetal bovine serum at 37°C for 2 hours. Then, cells were treated with 3 μM, 10 μM of CANA, or DMSO (CON, each n = 5) and incubated at 37°C for 72 hours. Then, 10 μL of Cell Count Reagent SF was added to each dish, and the cells were incubated for 30 minutes. Then the absorbance was read at 490 nm with a plate reader (BZ-X700; Keyence Corporation), and the number of viable cells was determined using the absorbance value of a previously prepared calibration curve.

Dead cell assessment by trypan blue exclusion assay

In this assay, Hep3B cells were used. Cells were cultured in Dulbecco's modified Eagle's medium with 10% fetal bovine serum at 37°C for 2 hours. Then, cells were treated with 10 μM, 30 μM of CANA, DMSO, or mitomycin (positive control for apoptosis) (each n = 5) and incubated at 37°C for 72 hours. After PBS washes, cells were treated with 1 mL of trypsin ethylenediaminetetraacetic acid (Nacalai Tesque, Inc.) and incubated at 37°C for 5 minutes, and medium was added to make a total of 3 mL. Ten μL of these samples was mixed with 10 μL of GIBCO Trypan Blue Stain, 0.4% (Thermo Fisher Scientific, Inc.). Then, the total and dead cells were counted by BIO RAD TC20 Automated Cell Counter (Bio-Rad Laboratories, Inc. Hercules, CA) as previously described [21].

Evaluation of morphological change of Hep3B and Huh7 cells

Hep3B and Huh7 cells were cultured with in Dulbecco's modified Eagle's medium containing10% fetal bovine serum, and cell morphology was observed by using a phase-contrast microscopy (BZ-X700; Keyence Corporation, Osaka, Japan) 48hours after treated with 3 μM, 10 μM of CANA, or DMSO.

Evaluation of apoptosis

In this assay, Hep3B and Huh7 cells were used. Apoptosis was evaluated by using annexin V (AN)/7-amino-actinomycin D (7AAD) as previously described [22]. Briefly, Hep3B cells were cultured in Dulbecco's modified Eagle medium with 10% fetal bovine serum at 37°C for 2 hours. Then, the cells were treated with CANA (3 μM), DMSO (CON), and mitomycin (positive control for apoptosis) (each n = 3) and incubated at 37°C for 72 hours. The cell suspensions were washed and stained with fluorescein isothiocyanate-labeled AN and 7AAD. A fluorescence microscope (BZ-X700; Keyence Corporation) was used to visualize the distribution of immunostaining for AN and 7AAD. The cells were analyzed using flow cytometry (EPICS profile, Coulter, Hialeah, FL), and the AN−/7AAD−, AN+/7AAD− and AN+/7AAD+ populations, which have been found to correspond to live cells, early apoptotic cells, and both late apoptotic and necrotic cells, respectively, were counted.

Apoptosis was evaluated by immunoblotting in Hep3B and Huh7 cells using antibodies against caspase8, caspase3, and Poly (adenosine diphosphate-ribose) polymerase (PARP).

Cell cycle analysis

In this assay, Huh7 and Hep3B cells were used. After treatment with DMSO or 10 μM of CANA at 37°C for 72 hours, the cells were trypsinized. The cells were fixed in 75% ethanol and PBS for 5 minutes at -20°C and centrifuged at 2,000 rpm × g for 10 minutes at 4°C. The samples were incubated with PBS including RNase and propidium iodide for DNA staining at 37°C for 5 minutes. The DNA content was assessed by monitoring with FACSCalibur (Becton Dickinson, Franklin Lakes, NJ). The flow cytometry data were collected, and cell cycle distributions were analyzed with Cell Quest software (Becton Dickinson) as previously described [23].

Metabolomic analysis

In this assay, Hep3B cells were used. Cell lysate samples 48 hours after treatment with DMSO (CON) and CANA (10 μM) were used for metabolomic analysis (each n = 5). Metabolome measurements were performed at a service facility of LSI Medience Corporation (Tokyo, Japan) as previously described [24]. Briefly, cell lysate was added to methanol and then mixed for 15 minutes with a shaker at room temperature. After centrifugation at 10,000 g for 10 minutes, the supernatant was dried with nitrogen gas, and the residue was dissolved with 10% acetonitrile aqueous solution. After adding internal standards, they were analyzed with both liquid chromatography mass spectrometry and capillary electrophoresis coupled with mass spectrometry. Tuning and calibration were performed with a standard solution provided by Agilent Technology, and the resolution errors were controlled within 3 ppm. The order of measurement was randomized to minimize the specific error in each group. Quality control samples were prepared by pooling samples.

iMPAQT

In this study, we employed iMPAQT in order to perform a global analysis for absolute quantification of protein expression simultaneously in Hep3B cell both CANA (10 μM) and CON group. The analysis was performed as previously described [15]. Briefly, cells (2 × 10⁶) were lysed with 150 μL of lysis buffer (a solution containing 2% SDS, 7 M urea, and 100 mM Tris-HCl, pH 8.8), and the samples were diluted with an equal volume of water. The protein concentrations of the samples were determined with BCA assays (Bio-Rad Laboratories, Inc., Hercules, CA). To block cysteine/cysteine residues, we treated 200 μg of each sample with 5.0 mM Tris (2-carboxyethyl) phosphine hydrochloride (Thermo Fisher Scientific, Inc.) for 30 minutes at 37°C, then alkylation was performed with 10 mM 2-iodoacetoamide (Sigma-Aldrich Co., LLC., St. Louis, MO) for 30 minutes at room temperature. After these samples were subjected to acetone precipitation, the resulting pellet was resuspended in 100 μL digestion buffer (0.5 M triethylammonium bicarbonate). Each sample was digested with lysyl-endopeptidase (2 μg, Wako) for 3 hours at 37°C. Subsequently, the samples were further digested with trypsin (4 μg, Thermo Fisher Scientific, Inc.) for 14 hours at 37°C. The resulting cell digests were freeze-dried and then labeled with the mTRAQ^® Δ0 (light) reagent (SCIEX Co. Ltd., Ontario, Canada). Each sample was spiked with synthetic peptides (Funakoshi Co. Ltd., Tokyo, Japan) for internal standard, which treated reductive alkylation and mTRAQ^® Δ4 (heavy) labeling (SCIEX Co., Ltd.). The samples were subjected to reverse-phase liquid chromatography followed by multiple reaction monitoring analysis. Experiments using mass spectrometry and pretreatment were performed by the service provider Kyusyu Pro Search LLP (Fukuoka, Japan).

Statistical analysis

All data are expressed as the mean ± SD. Comparisons between any two groups were performed using the Wilcoxon rank-sum test. Comparisons among multiple groups were made using one-way analyses of variance, followed by Fisher’s protected least-significant-difference post-hoc test. These statistical analysis were performed using JMP Pro® 13 (SAS Institute Inc., Cary, NC). A P value <0.05 was considered statistically significant.

Results

Expression of SGLT2

In immunoblotting, expression of SGLT2 was seen in Hep3B and Huh7 cells, and the expression was confirmed by 4 different antibodies against SGLT2 (Fig 1A). We also investigated expression of SGLT2 in 8 hepatoma cell lines such as Huh7, HLF, HepG2, Hep3B, KYN2, KMCH1, HAK1A, and, HAK1B cell lines by western blotting. SGLT2 occurred in the 8 hepatoma cell lines (S1 Fig). In addition, we investigated expression of SGLT2 in Jurkat cells as a SGLT2-positive sample and primary human hepatocytes. Expression of SGLT2 was seen in the both cells, although the expression was weak in primary human hepatocytes.

In immunostaining, expression of SGLT2 was seen in the cytoplasm of Hep3B and Huh7 cells (Fig 1B). SGLT2 co-localized with mitochondrial pyruvate dehydrogenase kinase 1 in Hep3B and Huh7 cells in double immunostaining (Fig 1C). Expression of SGLT2 was also detected in the mitochondrial fraction of Hep3B and Huh7 cells. On the other hand, expression of SGLT2 was weak in cytoplasmic fraction of Hep3B and Huh7 cells (Fig 1D). Expression of SGLT2 was not detected in the negative control examination, which lacks primary antibody for SGLT2 (Fig 1D) In immunoblotting, expression of SGLT1 and GLUT1, 2, 3, 5, and 6 was seen in Hep3B and Huh7 cells (S2 Fig).

Effects of CANA on proliferation of Hep3B and Huh7 cells

In Hep3B cells, the number of cells was significantly decreased in the 10 μM and 30 μM CANA group compared to the CON group, and this decreased in a dose-dependent fashion (Fig 2A). Similar findings were also seen in Huh7 cells (Fig 2B). On the other hand, there was no significant difference in cell number between 10 μM dapagliflozin group and CON group in Hep3B cells (S3 Fig).

Fig 2 — Effects of CANA on proliferation of A) Hep3B and B) Huh7 cells. C) Effects of CANA on live cell rate of Hep3B. D) Effects of CANA on the number of dead Hep3B cells. * P<0.01. Abbreviations: CON, control; CANA, canagliflozin.

In the living cell count assay using SF, the live cell rate of Hep3B was significantly decreased in the 10 μM and 30 μM CANA groups compared to the CON group (Fig 2C). In trypan blue staining, the number of dead Hep3B cells was significantly higher in the 30 μM CANA group than in the CON group. However, there was no significant difference in the number of dead cells between the 10 μM CANA and CON groups (Fig 2D).

Effects of CANA on morphological change and apoptosis of Hep3B and Huh7 cells

The impact of CANA on morphological change of Hep3B and Huh7 cells was examined by using phase-contrast-microscope 48 hours after treatment. There was no morphological change in Hep3B and Huh7 cells after 10 μM of CANA treatment (S4 Fig). However, after treatment with 30 μM CANA, there were morphological changes such as spindled and/or rounded shapes in Hep3B and Huh7 cells (S4 Fig).

The impact of apoptosis on the CANA-caused decrease in the number of cells was evaluated by using AN and 7AAD in Hep3B cells. In flow cytometry, the percentages of necrotic cells were 12.1% in the Mitomycin group (Fig 3A; positive control). However, the percentage was 2.03% and 2.34% in the CON and 10 μM CANA groups, respectively (Fig 3B and 3C). There was no significant difference in the percentages of necrotic cells between the CON and 10 μM CANA groups (n = 4; CON 1.90±0.22% vs. CANA 2.59±0.22%, P = 0.067). In immunostaining, the expression of AN and 7AAD was up-regulated in the Mitomycin group (Fig 3D). Meanwhile, the expression of AN and 7AAD was weak in the 10 μM CANA and CON groups (Fig 3E and 3F). In the Mitomycin group, there was an upregulation in p18 cleaved caspase 8, p17 cleaved caspase 3, and cleaved PARP in Hep3B cells. (S5A Fig). Meanwhile, there was no significant difference in the expression of p18 cleaved caspase 8, p17 cleaved caspase 3, and cleaved PARP between the 10 μM CANA and CON groups in Hep3B cells (S5A Fig). Similarly, there was no significant difference in the expression of apoptosis-related molecules including cleaved PARP between the CANA and CON groups in Huh7 cells. (S5B Fig). By treatment with 30 μM CANA, there was an upregulation of cleaved PARP in Hep3B and Huh7 cells.

Fig 3 — Apoptosis was evaluated by flow cytometry using 7AAD and annexin V in the A) Mitomycin group, B) CON group, and C) 10 μM CANA groups. Apoptosis was also evaluated by immunostaining for 7AAD (red) and annexin V (green) in the D) Mitomycin group, E) CON group, and F) 10 μM CANA group. Scale bar = 50 μm. G) Cell cycle distribution was evaluated by flow cytometry. Abbreviations: 7AAD, 7-amino-actinomycin D; CON, control; CANA, canagliflozin.

Effects of CANA on cell cycle in Hep3B and Huh7 cells

At 72 hours after treatment, the percentage of cells in the G2/M phase was 11.7±0.4% in the CON group. Meanwhile, in Hep3B cells, the percentage was significantly increased to 14.8±0.1% and 34.7±0.5% in the 10 μM and 30 μM CANA groups (both P<0.01), respectively (Fig 3G). Similarly, in Huh7 cells, the percentage of G2/M phase was significantly increased with dose-dependent fashion (12.5±0.2% vs. 14.0±0.2% and 19.9±0.7%; CON vs. 10 μM and 30 μM CANA groups; both P<0.01), respectively (Fig 3G).

Effects of CANA on metabolites evaluated by metabolomics

In a metabolomic analysis, the effects of CANA on 225 metabolite levels were evaluated (S1 Table). A significant difference was seen between the CON and CANA groups in 85 metabolites (Fig 4A). Of these, the most altered metabolism was fatty acid metabolism (15 metabolites), followed by valine leucine and isoleucine metabolism (14 metabolites), then purine and pyrimidine metabolism (7 metabolites) (Fig 4A).

Fig 4 — A) The number of significantly altered metabolites between the CANA and CON groups was plotted according to each category of metabolism. B) Volcano plot of differential metabolomics between the CON and CANA groups. Red circle indicates differential metabolites, which determined the condition of >1.5-fold increase with P<0.05 or <0.7-fold decrease with P<0.05. The green circle indicates differential metabolites associated with fatty acid metabolism. The gray circle indicates non-differential metabolites, which determined the condition of ≤1.5-fold increase and ≥0.7-fold decrease with P<0.05 and non-differential metabolites with P≥0.05. Abbreviations: CON, control; CANA, canagliflozin.

The differences in 225 metabolites between the CON and CANA groups are demonstrated by a volcano plot, and significantly altered metabolites are highlighted in red (Fig 5B). The volcano plot shows that metabolites associated with fatty acid elongation such as acetylcarnitine, butyrylcarnicine, and 3-hydroxybutanoate were significantly up-regulated in the CANA group compared to the CON group (green in Fig 5B). In addition, metabolites associated with fatty acid biosynthesis such as erucic acid and myristoleate were significantly up-regulated in the CANA group (green in Fig 5B). Thus, fatty acid metabolism was significantly altered in the CANA group.

Fig 5 — Red line indicates an up-regulated pathway. Red circle indicates an up-regulated metabolite. Blue line indicates a down-regulated pathway. Blue circle indicates a down-regulated metabolite. A) Whole metabolism map. B) Map for oxidative phosphorylation metabolism. C) Map for fatty acid metabolism. Thick blue line indicates SCD pathway. Green rectangle indicates ACAA1 pathways. D) Map for purine and pyrimidine metabolism. Thick blue line indicates NME1 pathways. Abbreviations: NAD+, nicotinamide adenine dinucleotide; SCD, stearoyl-CoA desaturase; ACAA1, acetyl-coenzyme A acyltransferase 1; UDP, uridine diphosphate; RNA, ribonucleic acid; DNA, deoxyribonucleic acid; NME1, nucleoside diphosphate kinase1.

Effects of CANA on expression level of metabolic enzymes by iMPAQT

In iMPAQT, the effects of CANA on the expression levels of 342 metabolic enzymes were evaluated. A significant difference was seen in 68 metabolic enzymes between the CON and CANA groups (S2 Table). Of these, the most altered metabolism was oxidative phosphorylation (11 metabolic enzymes), followed by purine and pyrimidine metabolism (7 metabolic enzymes). In addition, 4 and 3 metabolic enzymes were categorized as fatty acid metabolism and valine leucine and isoleucine metabolism, respectively (Table 1).

Table 1. Effects of CANA on expression level of metabolic enzymes by iMPAQT assay.

Enzyme	Pathway	Control		SGLT2i		P
Enzyme	Pathway	Mean	SD	Mean	SD	P
UQCRQ	Oxidative phosphorylation	28.99	1.38	35.53	1.39	0.0002
NDUFS2	Oxidative phosphorylation	34.84	0.77	39.48	1.26	0.0002
NDUFB7	Oxidative phosphorylation	25.08	2.96	34.58	3.36	0.0028
NDUFA9	Oxidative phosphorylation	41.70	2.44	49.16	2.62	0.0031
COX7A2	Oxidative phosphorylation	83.33	10.93	111.67	9.13	0.0041
NDUFV1	Oxidative phosphorylation	19.95	0.92	23.63	1.75	0.0059
NDUFV2	Oxidative phosphorylation	34.97	1.03	39.36	2.17	0.0065
UQCRC2	Oxidative phosphorylation	51.12	4.56	64.31	5.91	0.0077
NDUFB4	Oxidative phosphorylation	25.42	1.21	28.65	1.58	0.0118
ATP5A1	Oxidative phosphorylation	297.28	20.63	251.83	22.83	0.0183
COX4I1	Oxidative phosphorylation	136.81	5.26	150.79	8.03	0.0195
PRIM2	Purine, Pyrimidine metabolism	5.99	0.14	5.09	0.26	0.0003
RRM1	Purine, Pyrimidine metabolism	23.03	0.71	17.31	2.20	0.0011
ITPA	Purine, Pyrimidine metabolism	27.46	2.17	22.17	1.31	0.0031
ADSS	Purine, Pyrimidine metabolism	26.76	0.86	22.79	2.18	0.0095
NME1	Purine, Pyrimidine metabolism	110.30	11.37	89.14	8.39	0.0172
NT5C2	Purine, Pyrimidine metabolism	21.82	1.06	19.31	1.55	0.0281
PNP	Purine, Pyrimidine metabolism	14.70	1.89	12.23	0.72	0.0408
GPT2	Arginine and proline metabolism	10.41	1.32	19.14	2.32	0.0002
GLUD1	Arginine and proline metabolism	167.21	7.59	129.09	9.27	0.0002
PYCR1	Arginine and proline metabolism	8.82	0.87	11.86	1.35	0.0053
PYCR2	Arginine and proline metabolism	30.88	3.28	36.72	1.49	0.0119
CKB	Arginine and proline metabolism	65.96	8.75	52.52	5.72	0.0331
OAT	Arginine and proline metabolism	16.32	1.10	18.79	1.63	0.0359
SCD	Fatty acid metabolism	90.82	5.18	68.71	5.07	0.0003
ACOT7	Fatty acid metabolism	19.96	1.07	15.44	1.52	0.0012
ACAT2	Fatty acid metabolism	55.37	3.71	40.13	6.47	0.0035
ACAA1	Fatty acid metabolism	35.46	2.40	30.44	2.53	0.0206
PHGDH	Glycine, serine and threonine metabolism	41.67	2.53	67.88	6.00	<0.0001
SHMT2	Glycine, serine and threonine metabolism	155.76	4.86	194.10	13.99	0.0008
PSAT1	Glycine, serine and threonine metabolism	109.65	12.76	170.17	24.36	0.0023
CBS	Glycine, serine and threonine metabolism	59.75	7.89	72.84	6.67	0.0350
PKM2	Glycolysis / Gluconeogenesis	224.14	13.69	190.53	17.28	0.0159
LDHA	Glycolysis / Gluconeogenesis	197.54	11.83	163.32	19.95	0.0184
ENO1	Glycolysis / Gluconeogenesis	614.47	41.47	509.49	62.87	0.0236
GAPDH	Glycolysis / Gluconeogenesis	1642.62	161.94	1369.61	130.00	0.0302
PRPS2	Pentose phosphate pathway	18.68	1.91	15.36	1.20	0.0188
ALDOA	Pentose phosphate pathway	589.18	87.37	460.40	41.25	0.0285
PGM1	Pentose phosphate pathway	8.18	0.59	6.95	0.85	0.0437
GPI	Pentose phosphate pathway	141.05	15.93	118.88	10.23	0.0473
BCAT1	Valine, leucine and isoleucine metabolism	8.62	0.58	12.04	1.55	0.0033
MUT	Valine, leucine and isoleucine metabolism	8.83	0.60	10.54	0.69	0.0055
IVD	Valine, leucine and isoleucine metabolism	42.20	1.69	47.59	4.10	0.0411
LPGAT1	Glycerophospholipid metabolism	47.08	4.29	40.23	3.47	0.0381
LPCAT1	Glycerophospholipid metabolism	10.58	0.96	9.26	0.54	0.0433
HMOX1	Porphyrin and chlorophyll metabolism	20.73	1.31	15.94	1.82	0.0027
HMOX2	Porphyrin and chlorophyll metabolism	19.50	0.42	17.93	1.16	0.0344
TXNRD1	Pyrimidine metabolism	21.63	1.25	33.04	2.47	<0.0001
CTPS	Pyrimidine metabolism	13.09	1.07	10.72	1.46	0.0310
ME1	Pyruvate metabolism	22.97	2.89	28.00	1.70	0.0171
GLO1	Pyruvate metabolism	37.90	7.06	26.46	3.08	0.0179
LIPA	Steroid biosynthesis	7.57	0.76	5.42	0.74	0.0037
FDFT1	Steroid biosynthesis	9.71	1.13	7.34	1.05	0.0153
ASNS	Alanine, aspartate and glutamate metabolism	40.79	3.82	65.41	5.02	0.0001
CMAS	Amino sugar and nucleotide sugar metabolism	37.53	3.21	30.06	2.23	0.0051
WARS	Aminoacyl-tRNA biosynthesis	23.95	2.80	31.26	4.54	0.0253
MAT2A	Cysteine and methionine metabolism	51.83	4.87	39.93	4.37	0.0066
PAFAH1B3	Ether lipid metabolism	23.57	3.71	19.03	1.23	0.0485
GGH	Folate biosynthesis	19.69	1.47	15.73	2.12	0.0155
GMPPA	Fructose and mannose metabolism	13.11	1.29	10.85	0.69	0.0149
IMPA1	Inositol phosphate metabolism	39.71	2.13	35.59	2.52	0.0373
AASDHPPT	Pantothenate and CoA biosynthesis	19.10	1.90	14.65	1.19	0.0041
DCXR	Pentose and glucuronate interconversions	33.75	2.17	40.95	1.17	0.0004
AGL	Starch and sucrose metabolism	3.18	0.30	2.11	0.43	0.0032
TST	Sulfur metabolism	30.86	3.36	24.81	2.70	0.0231
HMGCS1	Synthesis and degradation of ketone bodies	40.51	4.36	22.77	3.58	0.0002
CAT	Tryptophan metabolism	76.11	4.42	61.09	10.95	0.0345

Open in a new tab

Metabolism map showing both CANA-altered metabolites and metabolic enzymes using multi-omics analysis of metabolomics and iMPAQT

In the metabolite map, 85 metabolites and 68 metabolic enzymes altered by CANA were plotted (Fig 5A). We found that the altered metabolites and metabolic enzymes could be classified into the following 4 categories; 1) oxidative phosphorylation metabolism, 2) fatty acid metabolism, 3) purine and pyrimidine metabolism, and 4) valine, leucine, and isoleucine metabolism (Fig 5A).

In oxidative phosphorylation metabolism, CANA significantly upregulated NAD⁺ in metabolomics (red circle in Fig 5B). Although CANA significantly upregulated 10 proteins associated with the electron transport system, including cytochrome c oxidase subunit 7A2, CANA downregulated a protein associated with the electron transport system, including ATP synthase F1 subunit alpha in iMPAQT (blue line in Fig 5B).

In fatty acid metabolism, CANA significantly upregulated 4 metabolites associated with beta-oxidation including butyrylcarnitine, acetylcarnitine, and 3-hydroxybutyrate in metabolomics. Meanwhile, in iMPAQT, CANA significantly downregulated acetyl-coenzyme A acyltransferase 1 (ACAA1), which is a key enzyme regulating beta-oxidation and production of ketone bodies including 3-hydroxybutyrate. CANA also significantly downregulated stearoyl-CoA desaturase (SCD), which is implicated in the regulation of cell growth and differentiation (Fig 5C).

In purine metabolism, CANA significantly upregulated deoxyadenosine, a deoxyribonucleoside, in metabolomics. In addition, CANA significantly downregulated purine nucleoside phosphorylase, which is an enzyme of the nucleotide salvage pathways that produces nucleotide monophosphates (Fig 5D).

In pyrimidine metabolism, CANA significantly upregulated uridine diphosphate (UDP) and uracil on metabolomics. Moreover, in iMPAQT, CANA significantly downregulated RNA recognition motif 1 and nucleoside diphosphate kinase 1 (NME1), which are involved in the synthesis of nucleoside triphosphates, such as guanosine triphosphate, cytidine triphosphate, and uridine triphosphate (Fig 5D). Moreover, CANA significantly downregulated expression of DNA primase, polypeptide 2 (PRIM2), encoding a subunit of primase involved in purine and pyrimidine metabolism, DNA replication, and transcription (Table 1).

In valine, leucine, and isoleucine metabolism, CANA significantly upregulated valine, leucine, threonine, serine, and alanine in metabolomics. On the other hand, CANA downregulated BCAT1 in iMPAQT (S7 Fig).

Effect of CANA on fatty acid metabolism-associated molecules

In Hep3B, there was no marked difference in the protein expression level of CPT1A, CPT2, acyl-CoA synthetase long-chain family member/fatty acid-CoA ligase, solute carrier family 25 member 2, hydroxymethylglutaryl-CoA lyase, fatty acid synthase, and CD36 between the CON and CANA groups (Fig 6). There was no significant difference in the protein expression level of AMPK between the two groups; however, p-AMPKα1 was significantly upregulated and p-AMPKα2 was significantly downregulated in the CANA 10 μM group compared to the CON group. No significant difference was seen in the protein expression level of ACC between the two groups; however, p-ACC was significantly upregulated in the CANA 10 μM group compared to the CON group (Figs 6 and S8). Moreover, in Huh7 cells, we examined changes in phosphorylation of AMPKα1 and ACC. We found that CANA also phosphorylated AMPKα1 and ACC in Huh7 cells (S6 Fig).

Fig 6 — Expression of fatty acid metabolism-associated molecules was evaluated by immunoblotting 48 hours after treatment with CON, 3 μM CANA, and 10 μM CANA. Abbreviations: CPT, carnitine palmitoyltransferase; ACSL/FACL, acyl-CoA synthetase long-chain family member/fatty acid-CoA ligase; SLC25A2, solute carrier family 25 member 2, hydroxymethylglutaryl-CoA lyase; HMGCL, hydroxymethylglutaryl-CoA lyase; FAS, fatty acid synthase; AMPK, AMP-activated protein kinase; ACC, acetyl-CoA carboxylase.

Discussion

In this study, SGLT2 occurred and localized on mitochondria in Hep3B and Huh7 cells. CANA significantly suppressed proliferation of these HCC cell lines. Multi-omics analysis of metabolomics and iMPAQT revealed that CANA mainly altered the following metabolisms; 1) oxidative phosphorylation metabolism, 2) fatty acid metabolism, and 3) purine and pyrimidine metabolism. Moreover, CANA altered phosphorylation of AMPK and ACC, which are sensors of intracellular ATP levels and regulators for beta oxidation. Thus, CANA may suppress proliferation of HCC cell lines via regulation of electron transport systems, beta oxidation, and nucleic acid synthesis.

We demonstrated that SGLT2 occurred in Hep3B and Huh7 cells. In normal tissue, SGLT2 occurs in the renal proximal tubules [25]. Moreover, SGLT2 is known to occur in various cancer cells including several HCC cell lines such as HepG2, Huh7, and JHH7 [26, 27]. Thus, our results were in good agreement with those of previous reports. In normal tissue, SGLT2 is known to localize on the apical membrane in the epithelial cells of the renal proximal tubule and regulate reabsorption of glucose from the glomerular filtrate in the proximal tubule [25]. Meanwhile, SGLT2 localized on the mitochondria of Hep3B and Huh7 cells in this study. Recently, Villani et al. reported that CANA inhibits mitochondrial complex-I in prostate and lung cancer cells [28]. Taken together, these data indicate that SGLT2 may be involved in the mitochondrial function of Hep3B and Huh7 cells.

In our study, we mainly used 10 μM of CANA. In the pharmacokinetic study of CANA of healthy participants, absolute bioavailability concentration was reported to be approximately 3 to 15 μM [29]. Moreover, Kaji et al. used 10 μM of CANA as a clinically comparable dose in in vitro study using Huh7 and HepG2 cells [11]. Thus, 10 μM of CANA is thought to be clinical relevance of the concentration. In this study, 10 μM of CANA caused inhibition of cell proliferation, but not apoptosis, in Hep3B cells. Meanwhile, Kaji et al. previously reported that 10 μM of CANA causes apoptosis in HepG2 cells [11]. It remains unclear why our results were different from the previous results; however, a possibility is the difference in HCC cell lines between the studies. Wild type p53 occurs in HepG2 cells, while we used a Hep3B cell, which is a p53-null HCC cell line. In our study, apoptosis was evaluated by several assays including trypan blue staining, immunostaining for AN and 7AAD, and apoptosis-related molecules such as cleaved PARP. However, apoptosis was not detected in any of these assays in Hep3B and Huh7 cells. In addition, CANA caused G2/M arrest in this study. Thus, we showed that CANA caused inhibition of cell proliferation, but not apoptosis, in these hepatoma cell lines.

To investigate mechanisms for CANA-induced suppression of cell proliferation, we investigated changes in metabolite levels and protein expression of metabolic enzymes using metabolomics and iMPAQT. These two global analyses revealed that CANA did not alter the intracellular glucose level, although CANA is an SGLT2 inhibitor. The reason for this result remains unclear; however, we found that SGLT1 and various GLUT isoforms occurred in Hep3B and Huh7 cells. Since glucose metabolism plays crucial roles in cancer cell viability [30, 31], these glucose transporters may play a role in maintaining glucose homeostasis in Hep3B and Huh7 cells.

Meanwhile, we found that CANA downregulated proteins associated with the electron transport system in Hep3B cells. We also showed that CANA upregulated p-AMPKα1 and downregulated p-AMPKα2. The similar findings were also seen in Huh7 cells. CANA is reported to inhibit electron transport systems and suppress proliferation of prostate cancer cells [28, 32]. In addition, CANA is reported to suppress ATP production in hepatoma cells [11]. Furthermore, CANA is reported to activate hepatic AMPK without alteration of insulin and glucagon signaling [33]. AMPK is known to be activated by up-regulation of p-AMPKα1 and downregulation of p-AMPKα2 [34, 35]. Thus, CANA may impair the mitochondrial electron transport system and ATP production, leading to AMPK activation via up-regulation of p-AMPKα1 and downregulation of p-AMPKα2 (Fig 7).

Fig 7 — Abbreviations: SGLT2, sodium-glucose cotransporter 2; ADP, adenosine diphosphate; ATP, adenosine triphosphate; AMPK, AMP-activated protein kinase; SCD, stearoyl-CoA desaturase; ACC, acetyl-CoA carboxylase; NME1, nucleoside diphosphate kinase1; NDP, nucleotide diphosphate; NTP, nucleotide triphosphate; PRIM2, DNA primase, polypeptide 2; DNA, deoxyribonucleic acid.

In this study, in Hep3B and Huh7 cells we found that CANA upregulated p-ACC, which is a downstream molecule of AMPK. Recently, ACC phosphorylation is reported to inhibit hepatic de novo lipogenesis and HCC proliferation [36]. We also found that CANA downregulated SCD, which is also a downstream molecule of AMPK. Down-regulation of SCD is known to suppress cell proliferation through regulation of monounsaturated fatty acids in prostate cancer cells [37]. Moreover, we found that CANA caused G2/M arrest of Hep3B cells. AMPK is also known to induce G2/M arrest via regulation of p53 and p21 in HepG2 cells [38, 39]. Taken together, CANA might inhibit oxidative phosphorylation and phosphorylation of AMPK, which results in suppression of cell proliferation through the following 3 pathways: 1) ACC phosphorylation, 2) down-regulation of SCD, and 3) G2/M arrest in Hep3B cells (Fig 7).

In our study, we further revealed that CANA affected fatty acid elongation including beta oxidation and up-regulation of butyrylcarnitine, acetylcarnitine, and 3-hydroxybutirate in Hep3B cells. Meanwhile, Liu et al. performed metabolomics and reported that synthesis of ketone bodies and fatty acid oxidation were upregulated in patients with HCC [40]. Ketone bodies are reported to suppress growth of colon and breast cancer cell lines through over-expression of uncoupling protein-2 [41]. Ketone supplementation is reported to decrease tumor cell viability and prolong survival of mice with metastatic brain tumor [42]. Moreover, in iMPAQT, we demonstrated that CANA down-regulated ACAA1, which is a key enzyme regulating beta-oxidation and production of ketone bodies. Since ACAA1 is reported to promote the occurrence and progression of HCC [43, 44], suppression of ACAA1 may inhibit cell proliferation of HCC. Taken together, inhibition of cell proliferation of Hep3B may be caused by CANA-induced alterations in both metabolites and enzymes of fatty acid metabolism (Fig 7).

In this study, we first found that CANA suppressed enzymes regulating nucleotide synthesis using iMPAQT in Hep3B cells. CANA downregulated NME1, an enzyme catalyzing synthetic reaction of uridine triphosphate from UDP [45]. Moreover, in metabolomics, CANA upregulated UDP. NME1 and NME2 are reported to be upregulated in a mouse model of HCC [46]. Thus, these data indicate that CANA downregulates NME1 and inhibits RNA and DNA synthesis, leading to suppression of cell proliferation of Hep3B cells (Fig 7). Moreover, we found a down-regulation of PRIM2, (which encodes a subunit of primase involved in purine and pyrimidine metabolism), DNA replication, and transcription [47]. Thus, CANA may suppress cell proliferation of Hep3B cells by inhibiting of DNA synthesis by down-regulation of NME1 and PRIM2 (Fig 7). In metabolic analysis and iMPAQT analysis were performed only in Hep3B cells and the result may be specific in this cell line. The validation study using the various HCC cell lines is required.

It is unclear that the alterations in of hepatoma cells is CANA specific. In order to solve this issue, we examined the effect of dapagliflozin (10μM), a SGLT2 inhibiter, on cell proliferation in Hep3B. There was no significant difference in cell number between the dapagliflozin and control groups. In previous studies, Obara et al. reported that tofogliflozin, a SGLT2 inhibiter, did not suppress cell number in Huh7 and JHH cells [26]. Hung MH et al. reported that CANA specifically inhibited cell proliferation due to β-catenin-related pathway, which was not seen in the dapagliflozin and empagliflozin groups in Huh7 and Hep3B [48]. Thus, these previous reports along with our additional data suggest that suppression of cell proliferation in hepatoma cells may be CANA specific effect.

There are several limitations in this study. First limitation is that the impact of alterations in valine, leucine, and isoleucine metabolism remains unclear. There were significant alterations in 14 metabolites and 3 enzymes associated with valine, leucine, and isoleucine metabolism; however, these changes were dispersed and were not associated with a specific pathway in this study. Second, we did not show direct evidence the link between altered pathways and reduced cell proliferation. CANA mainly altered following pathways 1) oxidative phosphorylation/fatty acid metabolism pathway through down-regulation of ATP synthase F1 subunit alpha and 2) purine and pyrimidine metabolism though down-regulation of NME1 and PRIM2. In order to proof the direct evidence, up-regulation of ATP synthase F1 subunit alpha, NME1, and PRIM2 thought to be required. However, there is no available drugs, which activate these three molecules simultaneously. Third, it remains unclear if the effects of CANA on cell proliferation, metabolomics, and proteomics are cancer specific and are SGLT2 dependent. In this study, we could not examine the CANA specificity by knock down of SGLT2 protein by using small interfering RNA in Hep3B cells. However, Huang H et al. previously reported that a SGLT2i did not affect cell proliferation in normal human renal cells [49]. Kaji et al. reported that CANA did not suppress cell proliferation of HLE cells, which were SGLT2-negative cells [11]. However, we do not have normal hepatocytes, which proliferate in vitro and SGLT-2 negative cells. Further study will be focused on the impact of amino acids metabolism on cell proliferation, direct evidence between altered pathways and CANA, and cell specificity of CANA.

Further study is required to investigate the impact of altered valine, leucine, and isoleucine metabolism on CANA-caused suppression of HCC proliferation.

In conclusion, SGLT2 was expressed and localized on mitochondria in Hep3B and Huh7 cells. CANA significantly suppressed proliferation of these cells. Multi-omics analysis of metabolomics and iMPAQT revealed that CANA mainly altered 1) oxidative phosphorylation metabolism, 2) fatty acid metabolism, and 3) purine and pyrimidine metabolism, but not glucose metabolism. CANA also altered phosphorylation of AMPK and ACC, which are sensors of intracellular ATP levels and regulators for beta oxidation. Thus, CANA may suppress proliferation of hepatoma cells via regulation of the electron transport system, beta oxidation, and nucleic acid synthesis.

Supporting information

S1 Fig. Immunoblotting for SGLT2 in Hep3B and Huh7.

Abbreviations: CANA, canagliflozin; SGLT1, sodium-glucose cotransporter 1; GLUT, glucose transporter.

(TIFF)

Click here for additional data file.^{(1.7MB, tiff)}

S2 Fig. Immunoblotting for SGLT1 and GLUT1-6 in Hep3B and Huh7.

Abbreviations: CANA, canagliflozin; SGLT1, sodium-glucose cotransporter 1; GLUT, glucose transporter.

(TIFF)

Click here for additional data file.^{(2.6MB, tiff)}

S3 Fig. Effects of dapagliflozin on proliferation of Hep3B cells.

* P<0.01. Abbreviations: CON, control; DAPA, dapagliflozin.

(TIFF)

Click here for additional data file.^{(785.7KB, tiff)}

S4 Fig. Effects of CANA on morphological change in Hep3B and Huh7 cells.

Scale bar = 50 μm. Abbreviations: CON, control; CANA, canagliflozin.

(TIFF)

Click here for additional data file.^{(6.1MB, tiff)}

S5 Fig. Immunoblotting for apoptosis-related molecules in Hep3B and Huh7 cells.

Abbreviations: CON, control; CANA, canagliflozin; PARP, poly adenosine diphosphate-ribose polymerase.

(TIFF)

Click here for additional data file.^{(2.3MB, tiff)}

S6 Fig. Immunoblotting for fatty acid metabolism-associated molecules in Huh7 cells.

Abbreviations: CON, control; CANA, canagliflozin; AMPK, AMP-activated protein kinase; ACC, acetyl-CoA carboxylase.

(TIFF)

Click here for additional data file.^{(3.4MB, tiff)}

S7 Fig. Metabolism map for valine, leucine, and isoleucine metabolism.

Red line indicates an up-regulated pathway. Red circle indicates an up-regulated metabolite. Blue circle indicates a down-regulated metabolite.

(TIFF)

Click here for additional data file.^{(4MB, tiff)}

S8 Fig. Intensity of protein expression in the 10 μM CANA and CON groups.

Abbreviations: CON, control; CANA, canagliflozin; AMPK, AMP-activated protein kinase; ACC, acetyl-CoA carboxylase.

(TIFF)

Click here for additional data file.^{(903.3KB, tiff)}

S1 Raw image

(PDF)

Click here for additional data file.^{(5.6MB, pdf)}

S1 Table. Effects of CANA on levels of 225 metabolites by metabolomics in Hep3B cells.

(DOCX)

Click here for additional data file.^{(78KB, docx)}

S2 Table. Effects of CANA on expression level of 342 metabolic enzymes by iMPAQT assay in Hep3B cells.

(DOCX)

Click here for additional data file.^{(49.7KB, docx)}

Acknowledgments

We thank Ms. Saori Meifu Division of Gastroenterology, Department of Medicine, Kurume University School of Medicine) for technical assistance with flow cytometry. We would like to thank Editage for English language editing.

Abbreviations

HCC: hepatocellular carcinoma
ATP: adenosine triphosphate
SGLT2: sodium-glucose cotransporter 2
CANA: canagliflozin
SGLT2i: SGLT2 inhibitor
iMPAQT: in vitro proteome-assisted multiple reaction monitoring for protein absolute quantification
GLUT: glucose transporter
AMPK: adenosine monophosphate-activated protein kinase
CPT: carnitine palmitoyl transferase
PBS: phosphate buffered saline
DMSO: dimethyl sulfoxide
CON: control
AN: annexin V
7AAD: 7-amino-actinomycin D
PARP: Poly (adenosine diphosphate-ribose) polymerase
ACAA1: acetyl-Coenzyme A acyltransferase 1
UDP: uridine diphosphate
SCD: stearoyl- CoA desaturase
NME1: nucleoside diphosphate kinase 1
PRIM2: DNA primase, polypeptide 2

Data Availability

All relevant data are within the manuscript and its Supporting Information files.

Funding Statement

This research was supported by Japan Agency for Medical Research and Development (AMED) under Grant Number JP19fk0210040.

References

1.Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(6):394–424. 10.3322/caac.21492 . [DOI] [PubMed] [Google Scholar]
2.Martinez-Outschoorn UE, Peiris-Pages M, Pestell RG, Sotgia F, Lisanti MP. Cancer metabolism: a therapeutic perspective. Nat Rev Clin Oncol. 2017;14(1):11–31. 10.1038/nrclinonc.2016.60 . [DOI] [PubMed] [Google Scholar]
3.Tian Y, Yang B, Qiu W, Hao Y, Zhang Z, Yang B, et al. ER-residential Nogo-B accelerates NAFLD-associated HCC mediated by metabolic reprogramming of oxLDL lipophagy. Nat Commun. 2019;10(1):3391 10.1038/s41467-019-11274-x [DOI] [PMC free article] [PubMed] [Google Scholar]
4.Ma F, Zhu Y, Liu X, Zhou Q, Hong X, Qu C, et al. Dual-Specificity Tyrosine Phosphorylation-Regulated Kinase 3 Loss Activates Purine Metabolism and Promotes Hepatocellular Carcinoma Progression. Hepatology. 2019. 10.1002/hep.30703 . [DOI] [PubMed] [Google Scholar]
5.Xie Q, Fan F, Wei W, Liu Y, Xu Z, Zhai L, et al. Multi-omics analyses reveal metabolic alterations regulated by hepatitis B virus core protein in hepatocellular carcinoma cells. Scientific reports. 2017;7:41089 10.1038/srep41089 [DOI] [PMC free article] [PubMed] [Google Scholar]
6.Liu R, Li Y, Tian L, Shi H, Wang J, Liang Y, et al. Gankyrin drives metabolic reprogramming to promote tumorigenesis, metastasis and drug resistance through activating beta-catenin/c-Myc signaling in human hepatocellular carcinoma. Cancer Lett. 2019;443:34–46. 10.1016/j.canlet.2018.11.030 . [DOI] [PubMed] [Google Scholar]
7.Zhong XY, Yuan XM, Xu YY, Yin M, Yan WW, Zou SW, et al. CARM1 Methylates GAPDH to Regulate Glucose Metabolism and Is Suppressed in Liver Cancer. Cell Rep. 2018;24(12):3207–23. 10.1016/j.celrep.2018.08.066 . [DOI] [PubMed] [Google Scholar]
8.Wani NA, Zhang B, Teng KY, Barajas JM, Motiwala T, Hu P, et al. Reprograming of Glucose Metabolism by Zerumbone Suppresses Hepatocarcinogenesis. Mol Cancer Res. 2018;16(2):256–68. 10.1158/1541-7786.MCR-17-0304 [DOI] [PMC free article] [PubMed] [Google Scholar]
9.Scafoglio C, Hirayama BA, Kepe V, Liu J, Ghezzi C, Satyamurthy N, et al. Functional expression of sodium-glucose transporters in cancer. Proceedings of the National Academy of Sciences of the United States of America. 2015;112(30):E4111–9. 10.1073/pnas.1511698112 [DOI] [PMC free article] [PubMed] [Google Scholar]
10.Tang H, Dai Q, Shi W, Zhai S, Song Y, Han J. SGLT2 inhibitors and risk of cancer in type 2 diabetes: a systematic review and meta-analysis of randomised controlled trials. Diabetologia. 2017;60(10):1862–72. 10.1007/s00125-017-4370-8 . [DOI] [PubMed] [Google Scholar]
11.Kaji K, Nishimura N, Seki K, Sato S, Saikawa S, Nakanishi K, et al. Sodium glucose cotransporter 2 inhibitor canagliflozin attenuates liver cancer cell growth and angiogenic activity by inhibiting glucose uptake. International journal of cancer. 2018;142(8):1712–22. 10.1002/ijc.31193 . [DOI] [PubMed] [Google Scholar]
12.Shiba K, Tsuchiya K, Komiya C, Miyachi Y, Mori K, Shimazu N, et al. Canagliflozin, an SGLT2 inhibitor, attenuates the development of hepatocellular carcinoma in a mouse model of human NASH. Scientific reports. 2018;8(1):2362 10.1038/s41598-018-19658-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
13.Wang X, Zhang A, Sun H. Power of metabolomics in diagnosis and biomarker discovery of hepatocellular carcinoma. Hepatology. 2013;57(5):2072–7. 10.1002/hep.26130 . [DOI] [PubMed] [Google Scholar]
14.Guo W, Tan HY, Wang N, Wang X, Feng Y. Deciphering hepatocellular carcinoma through metabolomics: from biomarker discovery to therapy evaluation. Cancer Manag Res. 2018;10:715–34. 10.2147/CMAR.S156837 [DOI] [PMC free article] [PubMed] [Google Scholar]
15.Matsumoto M, Matsuzaki F, Oshikawa K, Goshima N, Mori M, Kawamura Y, et al. A large-scale targeted proteomics assay resource based on an in vitro human proteome. Nat Methods. 2017;14(3):251–8. 10.1038/nmeth.4116 . [DOI] [PubMed] [Google Scholar]
16.Sugita S, Enokida H, Yoshino H, Miyamoto K, Yonemori M, Sakaguchi T, et al. HRAS as a potential therapeutic target of salirasib RAS inhibitor in bladder cancer. Int J Oncol. 2018;53(2):725–36. 10.3892/ijo.2018.4435 . [DOI] [PubMed] [Google Scholar]
17.Hnasko TS, Hnasko RM. The Western Blot. Methods Mol Biol. 2015;1318:87–96. 10.1007/978-1-4939-2742-5_9 . [DOI] [PubMed] [Google Scholar]
18.Schneider CA, Rasband WS, Eliceiri KW. NIH Image to ImageJ: 25 years of image analysis. Nat Methods. 2012;9(7):671–5. 10.1038/nmeth.2089 [DOI] [PMC free article] [PubMed] [Google Scholar]
19.Odell ID, Cook D. Immunofluorescence techniques. J Invest Dermatol. 2013;133(1):e4 10.1038/jid.2012.455 . [DOI] [PubMed] [Google Scholar]
20.Kawaguchi T, Hayakawa M, Koga H, Torimura T. Effects of fucoidan on proliferation, AMP-activated protein kinase, and downstream metabolism- and cell cycle-associated molecules in poorly differentiated human hepatoma HLF cells. Int J Oncol. 2015;46(5):2216–22. Epub 2015/03/18. 10.3892/ijo.2015.2928 . [DOI] [PubMed] [Google Scholar]
21.Strober W. Trypan blue exclusion test of cell viability. Curr Protoc Immunol. 2001;Appendix 3:Appendix 3B. 10.1002/0471142735.ima03bs21 . [DOI] [PubMed] [Google Scholar]
22.Takahashi R, Shimazaki C, Inaba T, Okano A, Hatsuse M, Okamoto A, et al. A newly developed bisphosphonate, YM529, is a potent apoptosis inducer of human myeloma cells. Leuk Res. 2001;25(1):77–83. 10.1016/s0145-2126(00)00087-4 . [DOI] [PubMed] [Google Scholar]
23.Selvendiran K, Koga H, Ueno T, Yoshida T, Maeyama M, Torimura T, et al. Luteolin promotes degradation in signal transducer and activator of transcription 3 in human hepatoma cells: an implication for the antitumor potential of flavonoids. Cancer Res. 2006;66(9):4826–34. 10.1158/0008-5472.CAN-05-4062 . [DOI] [PubMed] [Google Scholar]
24.Yamamura S, Kawaguchi T, Nakano D, Tomiyasu Y, Yoshinaga S, Doi Y, et al. Profiles of Advanced Hepatic Fibrosis Evaluated by FIB-4 index and Shear Wave Elastography in Health Check-up Examinees. Hepatol Res. 2019. Epub 2019/10/22. 10.1111/hepr.13436 . [DOI] [PubMed] [Google Scholar]
25.Chao EC, Henry RR. SGLT2 inhibition—a novel strategy for diabetes treatment. Nat Rev Drug Discov. 2010;9(7):551–9. 10.1038/nrd3180 . [DOI] [PubMed] [Google Scholar]
26.Obara K, Shirakami Y, Maruta A, Ideta T, Miyazaki T, Kochi T, et al. Preventive effects of the sodium glucose cotransporter 2 inhibitor tofogliflozin on diethylnitrosamine-induced liver tumorigenesis in obese and diabetic mice. Oncotarget. 2017;8(35):58353–63. 10.18632/oncotarget.16874 [DOI] [PMC free article] [PubMed] [Google Scholar]
27.Tahrani AA, Barnett AH, Bailey CJ. SGLT inhibitors in management of diabetes. Lancet Diabetes Endocrinol. 2013;1(2):140–51. 10.1016/S2213-8587(13)70050-0 . [DOI] [PubMed] [Google Scholar]
28.Villani LA, Smith BK, Marcinko K, Ford RJ, Broadfield LA, Green AE, et al. The diabetes medication Canagliflozin reduces cancer cell proliferation by inhibiting mitochondrial complex-I supported respiration. Mol Metab. 2016;5(10):1048–56. 10.1016/j.molmet.2016.08.014 [DOI] [PMC free article] [PubMed] [Google Scholar]
29.Devineni D, Murphy J, Wang SS, Stieltjes H, Rothenberg P, Scheers E, et al. Absolute oral bioavailability and pharmacokinetics of canagliflozin: A microdose study in healthy participants. Clin Pharmacol Drug Dev. 2015;4(4):295–304. 10.1002/cpdd.162 . [DOI] [PubMed] [Google Scholar]
30.Hsu PP, Sabatini DM. Cancer cell metabolism: Warburg and beyond. Cell. 2008;134(5):703–7. 10.1016/j.cell.2008.08.021 . [DOI] [PubMed] [Google Scholar]
31.DeBerardinis RJ, Lum JJ, Hatzivassiliou G, Thompson CB. The biology of cancer: metabolic reprogramming fuels cell growth and proliferation. Cell Metab. 2008;7(1):11–20. 10.1016/j.cmet.2007.10.002 . [DOI] [PubMed] [Google Scholar]
32.Secker PF, Beneke S, Schlichenmaier N, Delp J, Gutbier S, Leist M, et al. Canagliflozin mediated dual inhibition of mitochondrial glutamate dehydrogenase and complex I: an off-target adverse effect. Cell Death Dis. 2018;9(2):226 10.1038/s41419-018-0273-y [DOI] [PMC free article] [PubMed] [Google Scholar]
33.Osataphan S, Macchi C, Singhal G, Chimene-Weiss J, Sales V, Kozuka C, et al. SGLT2 inhibition reprograms systemic metabolism via FGF21-dependent and -independent mechanisms. JCI Insight. 2019;4(5). 10.1172/jci.insight.123130 [DOI] [PMC free article] [PubMed] [Google Scholar]
34.Okamoto S, Asgar NF, Yokota S, Saito K, Minokoshi Y. Role of the alpha2 subunit of AMP-activated protein kinase and its nuclear localization in mitochondria and energy metabolism-related gene expressions in C2C12 cells. Metabolism. 2019;90:52–68. 10.1016/j.metabol.2018.10.003 . [DOI] [PubMed] [Google Scholar]
35.Lopez-Mejia IC, Lagarrigue S, Giralt A, Martinez-Carreres L, Zanou N, Denechaud PD, et al. CDK4 Phosphorylates AMPKalpha2 to Inhibit Its Activity and Repress Fatty Acid Oxidation. Mol Cell. 2017;68(2):336–49 e6. 10.1016/j.molcel.2017.09.034 . [DOI] [PubMed] [Google Scholar]
36.Lally JSV, Ghoshal S, DePeralta DK, Moaven O, Wei L, Masia R, et al. Inhibition of Acetyl-CoA Carboxylase by Phosphorylation or the Inhibitor ND-654 Suppresses Lipogenesis and Hepatocellular Carcinoma. Cell Metab. 2019;29(1):174–82 e5. 10.1016/j.cmet.2018.08.020 [DOI] [PMC free article] [PubMed] [Google Scholar]
37.Fritz V, Benfodda Z, Rodier G, Henriquet C, Iborra F, Avances C, et al. Abrogation of de novo lipogenesis by stearoyl-CoA desaturase 1 inhibition interferes with oncogenic signaling and blocks prostate cancer progression in mice. Mol Cancer Ther. 2010;9(6):1740–54. 10.1158/1535-7163.MCT-09-1064 [DOI] [PMC free article] [PubMed] [Google Scholar]
38.Sanli T, Steinberg GR, Singh G, Tsakiridis T. AMP-activated protein kinase (AMPK) beyond metabolism: a novel genomic stress sensor participating in the DNA damage response pathway. Cancer Biol Ther. 2014;15(2):156–69. 10.4161/cbt.26726 [DOI] [PMC free article] [PubMed] [Google Scholar]
39.Lee CW, Wong LL, Tse EY, Liu HF, Leong VY, Lee JM, et al. AMPK promotes p53 acetylation via phosphorylation and inactivation of SIRT1 in liver cancer cells. Cancer Res. 2012;72(17):4394–404. 10.1158/0008-5472.CAN-12-0429 [DOI] [PMC free article] [PubMed] [Google Scholar]
40.Liu Y, Hong Z, Tan G, Dong X, Yang G, Zhao L, et al. NMR and LC/MS-based global metabolomics to identify serum biomarkers differentiating hepatocellular carcinoma from liver cirrhosis. International journal of cancer. 2014;135(3):658–68. 10.1002/ijc.28706 . [DOI] [PubMed] [Google Scholar]
41.Fine EJ, Miller A, Quadros EV, Sequeira JM, Feinman RD. Acetoacetate reduces growth and ATP concentration in cancer cell lines which over-express uncoupling protein 2. Cancer Cell Int. 2009;9:14 10.1186/1475-2867-9-14 [DOI] [PMC free article] [PubMed] [Google Scholar]
42.Poff AM, Ari C, Arnold P, Seyfried TN, D'Agostino DP. Ketone supplementation decreases tumor cell viability and prolongs survival of mice with metastatic cancer. International journal of cancer. 2014;135(7):1711–20. 10.1002/ijc.28809 [DOI] [PMC free article] [PubMed] [Google Scholar]
43.Yan H, Li Z, Shen Q, Wang Q, Tian J, Jiang Q, et al. Aberrant expression of cell cycle and material metabolism related genes contributes to hepatocellular carcinoma occurrence. Pathol Res Pract. 2017;213(4):316–21. 10.1016/j.prp.2017.01.019 . [DOI] [PubMed] [Google Scholar]
44.Liu F, Li H, Chang H, Wang J, Lu J. Identification of hepatocellular carcinoma-associated hub genes and pathways by integrated microarray analysis. Tumori. 2015;101(2):206–14. 10.5301/tj.5000241 . [DOI] [PubMed] [Google Scholar]
45.Puts GS, Leonard MK, Pamidimukkala NV, Snyder DE, Kaetzel DM. Nuclear functions of NME proteins. Lab Invest. 2018;98(2):211–8. 10.1038/labinvest.2017.109 [DOI] [PMC free article] [PubMed] [Google Scholar]
46.Hindupur SK, Colombi M, Fuhs SR, Matter MS, Guri Y, Adam K, et al. The protein histidine phosphatase LHPP is a tumour suppressor. Nature. 2018;555(7698):678–82. 10.1038/nature26140 [DOI] [PMC free article] [PubMed] [Google Scholar]
47.Zerbe LK, Kuchta RD. The p58 subunit of human DNA primase is important for primer initiation, elongation, and counting. Biochemistry. 2002;41(15):4891–900. 10.1021/bi016030b . [DOI] [PubMed] [Google Scholar]
48.Hung MH, Chen YL, Chen LJ, Chu PY, Hsieh FS, Tsai MH, et al. Canagliflozin inhibits growth of hepatocellular carcinoma via blocking glucose-influx-induced beta-catenin activation. Cell Death Dis. 2019;10(6):420 10.1038/s41419-019-1646-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
49.Kuang H, Liao L, Chen H, Kang Q, Shu X, Wang Y. Therapeutic Effect of Sodium Glucose Co-Transporter 2 Inhibitor Dapagliflozin on Renal Cell Carcinoma. Med Sci Monit. 2017;23:3737–45. 10.12659/MSM.902530 [DOI] [PMC free article] [PubMed] [Google Scholar]

PLoS One. doi: 10.1371/journal.pone.0232283.r001

Decision Letter 0

Tatsuo Kanda

24 Dec 2019

PONE-D-19-33203

Effects of Canagliflozin on Growth and Metabolic Reprograming in Hepatocellular Carcinoma Cells: Multi-Omics Analysis of Metabolomics and Absolute Quantification Proteomics (iMPAQT)

PLOS ONE

Dear Dr. Takumi Kawaguchi,

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Reviewer #2: Partly

Reviewer #3: No

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Reviewer #1: The authors tried to evaluate the effects of Canagliflozin (CANA) on growth and metabolic reprogramming in HCC cells and found that the CANA suppressed the proliferation of HCC cells through alterations in mitochondrial oxidative phosphorylation metabolism, fatty acid metabolism, and purine and pyrimidine metabolism. The paper is well written and organized. They designed the study based on the previous findings of SGLT2 inhibitor’s anti-tumor effect and further evaluated the direct mechanism toward HCC cells using iMPAQT technique.

Comments;

CANA (10uM) was used for metabolomics experiment. Was the significant decrease of 30uM due to cytotoxic effect of the drug? Have the authors studied any of the significant proteins in CANA (30uM), i.e., was there any dose dependency in protein expression?

SGLT2 was expressed in the mitochondria of Hep3B and Huh7 cells. Was SGLT2 expressed in normal hepatocyte or only in cancer cells? Expression levels in normal hepatocyte and its localization will be of great interest. If possible, CANA’s effect on commercially available human primary hepatocyte culture or PXB mouse primary culture could be studied.

Some of the experiments were only studied in Hep3B cell. For instance, how was the cell cycle experiment in Huh7 cell?

Was there any morphological change after CANA treatment?

Reviewer #2: In the present study, the anti-cancer role of SGLT2 inhibitor, canagliflozin (CANA) is examined using SGLT2 expressing liver cancer cell lines. Several metabolic pathways were affected by canagliflozin using combined analysis of metabolites and metabolic enzymes. Mitochondrial localization of SGLT2 is suggested to have some role. Although the findings are potentially interesting, there are several points which need to be addressed.

1. Major point is that although CANA affected metabolome and several specific pathways, no direct evidence is presented for the link between altered pathways and reduced cell proliferation.

2. In Fig. 1a, did the authors confirm if the protein band is SGLT2 specific by using SGLT2-positive and negative control samples?

3. In Fig. 1c, although the immunofluorescence experiments indicate colocalization of SGLT2 and mitochondria, the results are not very convincing. SGLT2 distribution could be confirmed by immunoblot after isolating mitochondrial fraction from cytosolic fraction.

4. In Fig. 2, if the reduced cell proliferation by CANA treatment is dependent on SGLT2 expression, the proliferation of cells not expressing SGLT2 is less affected by CANA treatment.

5. Please mention the clinical relevance of the concentration of the drug used in the present study. Does the drug also affect the normal cell proliferation?

6. Please mention whether the effect of CANA on the mitochondrial function and metabolome is cancer specific and is SGLT2 dependent.

Did the authors examine whether the identified molecules from metabolome analysis were altered in both cell lines used, and other cells such as SGLT2-negative cells and kidney cells?

7. Please specify the cell line used in the experiment in each figure legend for clarity. Please mention the cell line and treatment protocol used in the metabolomics and “iMPACT” analysis in the method section.

8. Please provide all the measurement results in the metabolome and proteome analysis.

Reviewer #3: In this article, the author assessed the effects of canagliflozin (CANA) on proliferation and metabolic reprograming of HCC cell line. They revealed that CANA reduced proliferation of Hep3B and Huh7. They also showed CANA altered mitochondrial oxidative phosphorylation metabolism, fatty acid metabolism, and purine and pyrimidine metabolism in Hep3B

1) Figure 2C, D; Live cell rate is decreased in CANA 10uM group. However, dead cell numbers in CANA 10uM group are not different from those in CON group. It seems that there is discrepancy between these data. Is dead cell rate in CANA 10uM group same with CON group?

2) In the study using iMPAQT, the dose of CANA should be described.

3) Metabolic analysis and iMPAQT analysis is performed only in Hep3B cells. The result may be specific in this cell line. The validation using the other cell line should be included.

4) The data is not shown the alteration in mitochondrial oxidative phosphorylation metabolism, fatty acid metabolism, and purine and pyrimidine metabolism really affects cell proliferation.

**********

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files to be viewed.]

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PLoS One. 2020 Apr 28;15(4):e0232283. doi: 10.1371/journal.pone.0232283.r002

Author response to Decision Letter 0

11 Feb 2020

Responses to the Academic Editor

Thank you for your comments regarding our manuscript (Manuscript PONE-D-19-33203). We appreciate your comments, which have helped us to improve our manuscript. In line with the comments, please find below our point-by-point responses.

1) Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming.

Answer: We ensure that our manuscript meets PLOS ONE's style requirements, including those for file naming.

2) Please provide additional information about the Huh7 and Hep3B cell lines used in this work, including the source, history any quality control testing procedures (authentication, characterisation, and mycoplasma testing).

Answer: We apologize that we did not provide sufficient information about cell lines. Huh7 cells were obtained from HuH7 (JCRB0403) and HLF (JCRB0405) cells were obtained from the JCRB Cell Bank (Tokyo, Japan). Hep3B cells (HB8064) were obtained from the American Type Culture Collection (ATCC-LGC Standards). HAK-1A, HAK-1B, KYN-2, and KMCH-1 were kindly provided from Prof. Hirohisa Yano (Department of Pathology, Kurume University School of Medicine, Kurume, Japan). These cells were checked by quality control testing procedures including authentication, characterisation, and mycoplasma testing. The above information was added in the revised manuscript (Page 7, line 23-Page 8, line 5).

3) To comply with PLOS ONE submission guidelines, in your Methods section, please provide additional information regarding your statistical analyses.

Answer: We apologize that we did not provide sufficient information regarding our statistical analyses. We added additional information regarding our statistical analyses in the revised manuscript (Page 15, line 17-19).

4) We suggest you thoroughly copyedit your manuscript for language usage, spelling, and grammar. If you do not know anyone who can help you do this, you may wish to consider employing a professional scientific editing service.

Answer: This manuscript was edited by Editage. The certificate of English editing was attached in this response letter. In the revised manuscript, following sentence was added “We would like to thank Editage for English language editing.” (Page 39, line 5).

5) At this time, we ask that you please include scale bars on the microscopy images presented in Figures 1 and 3 and refer to the scale bar in the corresponding Figure legend.

Answer: We apologize that we did not provide scale bar. In the revised manuscript, the scale bars and the corresponding figure legends were added (Figures 1B, 1C, 3D, 3E, 3F, and Supplementary Figure 3).

6) Please expand the acronym “AMED” (as indicated in your financial disclosure) so that it states the name of your funders in full.

Answer: We apologize that we did not spell out the acronym “AMED”. In the revised manuscript, the acronym “AMED” was expanded as following: “This research was supported by Japan Agency for Medical Research and Development (AMED) under Grant Number JP19fk0210040.” (Page 39, line 17-18).

7) Thank you for stating the following in the Competing Interests section: 'Takumi Kawaguchi received lecture fees from Mitsubishi Tanabe Pharma Corporation, MSD K.K., and Otsuka Pharmaceutical Co., Ltd. The other authors have no conflicts of interest' Please confirm that this does not alter your adherence to all PLOS ONE policies on sharing data and materials, by including the following statement: "This does not alter our adherence to PLOS ONE policies on sharing data and materials.”

Answer: Takumi Kawaguchi received lecture fees from Mitsubishi Tanabe Pharma Corporation, MSD K.K., and Otsuka Pharmaceutical Co., Ltd. However, this does not alter our adherence to PLOS ONE policies on sharing data and materials. The description was added in the revised main text as well as the cover letter. (Page 39, line 8-11).

8) Please know it is PLOS ONE policy for corresponding authors to declare, on behalf of all authors, all potential competing interests for the purposes of transparency. PLOS defines a competing interest as anything that interferes with, or could reasonably be perceived as interfering with, the full and objective presentation, peer review, editorial decision-making, or publication of research or non-research articles submitted to one of the journals. Competing interests can be financial or non-financial, professional, or personal. Competing interests can arise in relationship to an organization or another person.

Answer: We appreciate for letting us know the PLOS ONE policy. We understand the policy.

9) PLOS ONE now requires that authors provide the original uncropped and unadjusted images underlying all blot or gel results reported in a submission’s figures or Supporting Information files.

Answer: We appreciate for letting us know the requirement for the original uncropped and unadjusted images underlying all blot or gel results. We understand the requirements.

----------

Responses to REVIEWER 1,

1) CANA (10uM) was used for metabolomics experiment. Was the significant decrease of 30uM due to cytotoxic effect of the drug? Have the authors studied any of the significant proteins in CANA (30uM), i.e., was there any dose dependency in protein expression?

Answer: Following your suggestion, we investigated effects of 30 μM of CANA on cell number, morphological changes, and apoptosis in Hep3B and Huh7 cells. At 72 hours after treatment, the number of cells was significantly decreased in the 30 μM CANA group compared to the CON, 3 μM, and 10 μM CANA groups with a dose-dependent fashion (Figure 2A). In phase-contrast-microscopic image, suspended cells were seen in the 30 μM CANA group, while suspended cells were not seen in the CON, 3 μM, and 10 μM CANA groups in Hep3B and Huh7 cells 48 hours after treatment (S3 Fig). In trypan-blue staining assay, the number of dead cells were significantly increased in the 30 μM CANA group compared to that in the CON, and 10 μM CANA groups in Hep3B cells 48 hours after treatment (Figure 2D). Furthermore, upregulation of cleaved Poly (adenosine diphosphate-ribose) polymerase was only seen in 30 μM of CANA, but not in the CON and 10μM CANA groups, indicating the dose dependency of CANA in apoptosis-related protein expression in Hep3B and Huh7 cells (S4A and B Figs). Thus, these results suggested that treatment with 30 μM of CANA significantly decreased cell number due to cytotoxic effect of the drug. The above descriptions were added to the revised manuscript (Page 18, line 8–13; Page 18, line 23-Page 19, line 9).

2) SGLT2 was expressed in the mitochondria of Hep3B and Huh7 cells. Was SGLT2 expressed in normal hepatocyte or only in cancer cells? Expression levels in normal hepatocyte and its localization will be of great interest. If possible, CANA’s effect on commercially available human primary hepatocyte culture or PXB mouse primary culture could be studied.

Answer: We appreciate your comments. As you suggested, we investigated expression of SGLT2 in human primary hepatocytes (LHum17003; BIOPREDIC, Saint-Grégoire, France) and found that expression of SGLT2 was weak (Fig 1D). We have added the results in the revised manuscript (Page 16, line 4-10).

It is great interest to investigate effects of CANA on human primary hepatocyte culture or PXB mouse primary culture. However, we do not have normal hepatocytes, which proliferate in vitro and could not investigate effects of CANA on the proliferation of normal cells. Therefore, this issue was described as a limitation of this study (Page 38, line 10-11).

3) Some of the experiments were only studied in Hep3B cell. For instance, how was the cell cycle experiment in Huh7 cell

Answer: Following your suggestion, we investigated effects of CANA on expression of apoptosis-related molecules and cell cycle in Huh7 cells. Like in Hep3B cells, there was no significant difference in the expression of apoptosis-related molecules including cleaved PARP between the 10 μM CANA and CON groups in Huh7 cells. (S2 Fig A and B). Furthermore, in Huh7 cells, the percentage of G2/M phase was also significantly increased to 12.5±0.2% and 14.0±0.2% in the 10 μM and 30 μM CANA groups (both P<0.01), respectively (Fig 3G). Thus, these experiments in Huh7 cells yielded similar results in Hep3B. These results were added in the revised manuscript (Page 19, line 5–9; Page 20, line 1–4).

4) Was there any morphological change after CANA treatment?

Answer: We appreciate for your valuable comment. Following your suggestion, we examined morphological change of Hep3B and Huh7 cells after CANA treatment by using phase-contrast-microscope. There was no morphological change in Hep3B and Huh 7 cells after 10 μM of CANA treatment (Supplementary Figure 3). However, after treatment of 30 μM CANA, there was morphological changes such as spindled and/or rounded shapes in Hep3B and Huh 7 cells (Supplementary Figure 3). These results were added in the revised manuscript (Page 18, line 8-13).

----------

Responses to REVIEWER 2,

1) Major point is that although CANA affected metabolome and several specific pathways, no direct evidence is presented for the link between altered pathways and reduced cell proliferation.

Answer: We totally agree with your comment. We did not present direct evidence for the link between altered pathways and reduced cell proliferation in this study. In this study, CANA mainly altered following pathways 1) oxidative phosphorylation/fatty acid metabolism pathway through down-regulation of ATP synthase F1 subunit alpha and 2) purine and pyrimidine metabolism though down-regulation of NME1 and PRIM2. In order to proof the direct evidence, up-regulation of ATP synthase F1 subunit alpha, NME1, and PRIM2 thought to be required. However, there is no available drugs, which activate these three molecules simultaneously. Thus, it seems impossible to proof the direct evidence currently. As far as we searched, there is no study, which proof the direct evidence for the link between altered pathways and reduced cell proliferation by up-/down-regulation of multiple pathways [1]. Therefore, we described this issue as a limitation of this study (Page 37, line 22-Page 38, line 5).

2) In Fig. 1a, did the authors confirm if the protein band is SGLT2 specific by using SGLT2-positive and negative control samples?

Answer: We appreciate for your comment. We selected Jurkat cells as a SGLT2-positive sample as previously described [2] and the protein band was detected at the same molecule size of the protein band in Hep3B and Huh7 cells. Although we examined the expression of SGLT2 in 8 hepatoma cell lines and human primary hepatocytes (LHum17003; BIOPREDIC, Saint-Grégoire, France). However, expression of SGLT2 was seen in the all hepatoma cell lines. Even in human primary hepatocytes, weak expression of SGLT2 was observed. Thus, we could not find out SGLT2-negative sample in this study. These results were added in the revised manuscript (Page 16, line 7-10).

3) In Fig. 1c, although the immunofluorescence experiments indicate colocalization of SGLT2 and mitochondria, the results are not very convincing. SGLT2 distribution could be confirmed by immunoblot after isolating mitochondrial fraction from cytosolic fraction.

Answer: Following your suggestion, SGLT2 distribution was investigated by immunoblot after isolating mitochondrial fraction from cytosolic fraction. In Hep3B and Huh7 cells, marked expression of SGLT2 was detected in mitochondrial fraction. On the other hand, expression of SGLT2 was weak cytoplasmic fraction. These data suggested that SGLT2 localized in mitochondria in Hep3B and Huh7 cells (Fig 1D). These results were added in the revised manuscript (Page 16, line 14-16).

4) In Fig. 2, if the reduced cell proliferation by CANA treatment is dependent on SGLT2 expression, the proliferation of cells not expressing SGLT2 is less affected by CANA treatment.

Answer: We appreciate for your valuable comment. As you suggested, we investigated expression of SGLT2 by western blotting and expression of SGLT2 was seen in 8 hepatoma cell lines such as Huh7, HLF, HepG2, Hep3B, KYN2, KMCH1, HAK1A, and, HAK1B cell lines (Supplementary Figure 1). On the other hand, Kaji et al. previously reported that expression of SGLT2 was not seen in HLE cells, a hepatoma cell line [2]. Moreover, they showed that CANA did not suppress cell proliferation of HLE at 10 μM CANA, which is same concentration of our study. These data suggested that effects of CANA treatment on cell proliferation may be dependent on SGLT2 expression. However, we do not have normal hepatocytes, which proliferate in vitro, and, therefore, this issue was described as a limitation of this study (Page 16, line 4–7; Page 38, line 5-11).

5) Please mention the clinical relevance of the concentration of the drug used in the present study. Does the drug also affect the normal cell proliferation?

Answer: We agree with your comment. We did not mention the clinical relevance of the concentration of the drug used in the study. In the pharmacokinetic study of CANA, absolute bioavailability concentration was reported to be approximately 3 to 15 μM [3]. Moreover, Kaji et al. used 10 μM of CANA as a clinically comparable dose in in vitro study using Huh7 and HepG2 cells [2]. We also used 10 μM of CANA in this study, which is thought to be clinical relevance of the concentration. The above description has been added to the revised manuscript (Page 33, line 23-Page 34, line 5).

As you indicated, it is important to investigate effects of CANA on cell proliferation in normal cell. Huang H et al. previously reported that dapagliflozin, a SGLT2i, did not affect cell proliferation in normal human renal cells [4]. However, we do not have normal hepatocytes, which proliferate in vitro, and, therefore, this issue was described as a limitation of this study (Page 38, line 5-11).

6) Please mention whether the effect of CANA on the mitochondrial function and metabolome is cancer specific and is SGLT2 dependent.

Did the authors examine whether the identified molecules from metabolome analysis were altered in both cell lines used, and other cells such as SGLT2-negative cells and kidney cells?

Answer: We appreciate for your valuable comments. Huang H et al. previously reported that dapagliflozin, a SGLT2i, exerts cytotoxic effect in human RCC cell lines, but not in normal human renal cells [4]. However, in this study, we did not evaluate effect of CANA on the mitochondrial function and metabolome in normal hepatocytes and therefore it remains unclear if effects of CANA on the mitochondrial function and metabolome is cancer specific. Moreover, Kaji et al. previously reported that HLE cells, a hepatoma cell line, were SGLT2-negative and showed that cell proliferation of HLE cells was not suppressed by treatment with 10 μM of CANA [2], which is same concentration of our study. These data suggested that effects of CANA treatment on cell proliferation may be dependent on SGLT2 expression. However, we do not have normal hepatocytes, which proliferate in vitro and SGLT2-negative cells. Therefore, this issue was described as a limitation of this study (Page 38, line 5-11).

7) Please specify the cell line used in the experiment in each figure legend for clarity. Please mention the cell line and treatment protocol used in the metabolomics and “iMPACT” analysis in the method section.

Answer: We apologize for insufficient description of this issue. Following your suggestion, we specified the cell line used in the experiment in the main text and each figure legend throughout the manuscript. We also specified the cell line and treatment protocol used in the metabolomics and “iMPACT” analysis in the method section (Page 13, line 18, Page 14, line 12-13).

8) Please provide all the measurement results in the metabolome and proteome analysis.

Answer: We apologize for insufficient description of the results. Following your suggestion, we provided all the measurement results in the metabolomics and “iMPACT” analysis. In the main text, we presented the results for significantly altered metabolites and metabolic enzymes because all the data occupies a large amount of space. All the measurement results were presented as Supplementary Tables (S1 and 2 Tables).

References

1. Yu L, Wu J, Zhai Q, Tian F, Zhao J, Zhang H, et al. Metabolomic analysis reveals the mechanism of aluminum cytotoxicity in HT-29 cells. PeerJ. 2019;7:e7524. doi: 10.7717/peerj.7524. PubMed PMID: 31523502; PubMed Central PMCID: PMCPMC6716502.

2. Kaji K, Nishimura N, Seki K, Sato S, Saikawa S, Nakanishi K, et al. Sodium glucose cotransporter 2 inhibitor canagliflozin attenuates liver cancer cell growth and angiogenic activity by inhibiting glucose uptake. International journal of cancer. 2018;142(8):1712-22. doi: 10.1002/ijc.31193. PubMed PMID: 29205334.

3. Devineni D, Murphy J, Wang SS, Stieltjes H, Rothenberg P, Scheers E, et al. Absolute oral bioavailability and pharmacokinetics of canagliflozin: A microdose study in healthy participants. Clin Pharmacol Drug Dev. 2015;4(4):295-304. doi: 10.1002/cpdd.162. PubMed PMID: 27136910.

4. Kuang H, Liao L, Chen H, Kang Q, Shu X, Wang Y. Therapeutic Effect of Sodium Glucose Co-Transporter 2 Inhibitor Dapagliflozin on Renal Cell Carcinoma. Med Sci Monit. 2017;23:3737-45. doi: 10.12659/msm.902530. PubMed PMID: 28763435; PubMed Central PMCID: PMCPMC5549715.

----------

Responses to REVIEWER 3,

Answer: We apologize for wrong description in vertical line in Figure 2C. In the figure, we examined number of live cells in CANA 10 μM by comparing to the CON group and the result was expressed by %CON. We corrected this mistake in the revised manuscript (Figure 2C and D). Again, we apologize for causing confusion with the wrong description.

2) In the study using iMPAQT, the dose of CANA should be described.

Answer: We apologize for insufficient description in the study using iMPAQT. The dose of CANA (10 μM) was added in the revised manuscript (Page 14, line 12-13).

3) Metabolic analysis and iMPAQT analysis is performed only in Hep3B cells. The result may be specific in this cell line. The validation using the other cell line should be included.

Answer: We totally agree with your comment. Expression of SGLT2 was seen in both Hep3B and Huh 7 cells, and CANA inhibited cell proliferation of both HCC cell lines. We examined changes in phosphorylation of AMPKα1 and ACC and found that CANA phosphorylated AMPKα1 and ACC not only in Hep3B cell, but also in Huh 7 cells (S5 Fig). However, as you indicated, iMPAQT analysis was performed only in Hep3B cells. Therefore, the result may be specific in this cell line. The validation study using the various HCC cell lines should be performed. Unfortunately, we could not conduct the validation study at this moment. Therefore, this issue was described in the Discussion section of the revised manuscript (Page 32 line 7–9; Page 37 line 4-7).

4) The data is not shown the alteration in mitochondrial oxidative phosphorylation metabolism, fatty acid metabolism, and purine and pyrimidine metabolism really affects cell proliferation.

Reference

Attachment

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Click here for additional data file.^{(19.2KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0232283.r003

Decision Letter 1

Tatsuo Kanda

25 Feb 2020

PONE-D-19-33203R1

Effects of Canagliflozin on Growth and Metabolic Reprograming in Hepatocellular Carcinoma Cells: Multi-Omics Analysis of Metabolomics and Absolute Quantification Proteomics (iMPAQT)

PLOS ONE

Dear Prof. Kawaguchi,

We would appreciate receiving your revised manuscript by Apr 10 2020 11:59PM. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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Tatsuo Kanda, M.D., Ph.D.

Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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Reviewer #1: All comments have been addressed

Reviewer #2: (No Response)

Reviewer #3: (No Response)

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2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: (No Response)

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: (No Response)

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4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reviewer #2: (No Response)

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6. Review Comments to the Author

Reviewer #1: The authors have fulfilled each of the major compulsory revisions and modified the manuscript as requested. I have the following further suggestion that in my opinion will improve the quality of the manuscript.

Figure 6 needs statistics (actual p-values).

Page 18 Line 6, Effect of CANA on apoptosis morphological change of Hep3B and Huh7 cells. Needs hyphenation or modification.

Reviewer #2: In the discussion, “it remains unclear if the effects of CANA on cell proliferation, metabolomics, and proteomics are cancer specific and are SGLT2 dependent.”

1. Authors could examine the effects of knockdown/knockout of SGLT2.

2. Please mention if the effects are CANA specific or common features of SGLT2 inhibitors.

Reviewer #3: (No Response)

**********

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PLoS One. 2020 Apr 28;15(4):e0232283. doi: 10.1371/journal.pone.0232283.r004

Author response to Decision Letter 1

9 Apr 2020

Dear Prof. Tatsuo Kanda, M.D., Ph.D.

Thank you very much for your letter dated on February 26, 2016 regarding our manuscript (Manuscript # PONE-D-19-33203R1). We appreciate your comments and those of the reviewers, which have helped us to improve our manuscript.

Enclosed please find the revised manuscript. Our responses to the reviewer’s comments are described in the attached sheet and all changes are indicated with Track Changes in the revised manuscript. We hope that these revisions respond to your comments and the manuscript is now suitable to PLOS ONE.

This research was supported by Japan Agency for Medical Research and Development (AMED) under Grant Number JP19fk0210040. Takumi Kawaguchi received lecture fees from Mitsubishi Tanabe Pharma Corporation, MSD K.K., and Otsuka Pharmaceutical Co., Ltd. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Thank you very much for your kind consideration of our manuscript.

Sincerely Yours,

Takumi Kawaguchi, M.D., Ph.D.

Responses to REVIEWER 1,

1) Figure 6 needs statistics (actual p-values).

Answer: Following your suggestion, we measured intensity of protein expression in the 10 μM CANA and CON groups by using image J. The intensity of p-AMPKα1 in the 10 μM CANA groups was significantly higher than that in the CON group. On the other hand, the intensity of p-AMPKα2 in the 10 μM CANA groups was significantly lower than that in the CON group. These results were added in the Supplementary Figure 8. We appreciate for your suggestion, which have helped us to improve our manuscript. These results were added in the revised manuscript (Page 10, line 21-22).

2) Page 18 Line 6, Effect of CANA on apoptosis morphological change of Hep3B and Huh7 cells. Needs hyphenation or modification.

Answer: We apologized for the typo. As you suggested, we corrected for the grammatical error as following; Effect of CANA on morphological change and apoptosis in Hep3B and Huh7 cells (Page 18, line 9-10).

Responses to REVIEWER 2,

Reviewer #2:

1. In the discussion, “it remains unclear if the effects of CANA on cell proliferation, metabolomics, and proteomics are cancer specific and are SGLT2 dependent.” Authors could examine the effects of knockdown/knockout of SGLT2.

Answer: Following your suggestion, we performed knock down of SGLT2 using small interfering RNA (siRNA) (Silencer® Select s534032 Thermo Fisher), because knock down is reported to be suitable for investigating phenotypic change than knock out [1, 2].

We transfected siRNA for SGLT2 into Hep3B cells according to the manufactures’ instruction. However, there was no significant depletion in protein expression of SGLT2 in the siRNA group compared to the control group (Appendix Figure 1). Although we performed the siRNA experiment twice at different concentration of siRNA (5 nM and 10 nM), no significant difference was seen in protein expression of SGLT2 in the siRNA group compared to the control group (Appendix Figure 1). The reason for the unsuccessful depletion of SGLT2 protein expression remains unclear, a possible explanation is following: Although expression of mRNA for SGLT2 was decreased by siRNA treatment, expression of mRNA for SGLT2 was detected even in Hep3B cells treated with 10 nM of siRNA (Appendix Figure 2). These data suggest that a decrease in mRNA for SGLT2 was not sufficient for depletion of protein expression of SGLT2. Thus, it is difficult to examine effects of SGLT2 on metabolisms and cell proliferation by siRNA for SGLT2 in Hep3B cells at this moment. To clarify this issue, further study will be focused on an alternating approach such as short hairpin RNA, which causes more continuous suppression of target protein than siRNA [3]. This issue was described as a limitation of this study (Page 38, line 17-19).

Method for Appendix Figure 1 and 2

Knockdown of SGLT2 in Hep3B using small interfering RNA (siRNA)

Hep3B cells were seeded into six-well plates at a density of 1×105 cells/well. The cells reached 80% confluence 48 hours after incubation and were transiently transfected with siRNA using Lipofectamine® 2000 (Invitrogen; Thermo Fisher Scientific, Inc.). The sequences for siRNA (Invitrogen; Thermo Fisher Scientific, Inc.) were as follows: Sense, 5′- CCGGAGCUGUAUUCAUCCATT-3′ and anti-sense, 5′- UGGAUGAAUACAGCUCCGGAG-3. Cell transfection was performed, according to the manufactures’ instruction. Briefly, each sequence of 10 μM　siRNA (1.5μL) and 9 μL Lipofectamine® 2000 was diluted in serum-free medium (300 μL) at room temperature for 5 min, mixed together. The mixture was subsequently administered to the Hep3B cells, then the medium was replaced with complete medium. Hep3B cells were seeded into six-well plates at a density of 5×104 cells/well and protein expression of SGLT2 was evaluated at 24, 48, 72, 96, and 120 hours after incubation.

2. Please mention if the effects are CANA specific or common features of SGLT2 inhibitors.

Answer: We appreciate for your comment. As you suggested, we examined the effect of dapagliflozin (10μM), a SGLT2 inhibiter, on cell proliferation in Hep3B. There was no significant difference in cell number between the dapagliflozin and control groups (supplementary figure 3). Moreover, Obara et al. reported that tofogliflozin, a SGLT2 inhibiter, did not suppress cell number in Huh7 and JHH cells [4]. Hung MH et al. reported that CANA specifically inhibited cell proliferation due to β-catenin-related pathway, which was not seen in the dapagliflozin and empagliflozin groups in Huh7 and Hep3B [5]. In this study, CANA-specific mechanism on inhibition of cell proliferation remains unclear; however, these previous reports along with our additional data suggest that suppression of cell proliferation in hepatoma cells may be CANA specific effect. This discussion was added in the revised manuscript (Page 37, line 16-Page38, line 2).

References

1. Ma Z, Zhu P, Shi H, Guo L, Zhang Q, Chen Y, et al. PTC-bearing mRNA elicits a genetic compensation response via Upf3a and COMPASS components. Nature. 2019;568(7751):259-63. doi: 10.1038/s41586-019-1057-y. PubMed PMID: 30944473.

2. El-Brolosy MA, Kontarakis Z, Rossi A, Kuenne C, Gunther S, Fukuda N, et al. Genetic compensation triggered by mutant mRNA degradation. Nature. 2019;568(7751):193-7. doi: 10.1038/s41586-019-1064-z. PubMed PMID: 30944477; PubMed Central PMCID: PMCPMC6707827.

3. Yang X, Wu X, Yang Y, Gu T, Hong L, Zheng E, et al. Improvement of developmental competence of cloned male pig embryos by short hairpin ribonucleic acid (shRNA) vector-based but not small interfering RNA (siRNA)-mediated RNA interference (RNAi) of Xist expression. J Reprod Dev. 2019;65(6):533-9. doi: 10.1262/jrd.2019-070. PubMed PMID: 31631092; PubMed Central PMCID: PMCPMC6923154.

4. Obara K, Shirakami Y, Maruta A, Ideta T, Miyazaki T, Kochi T, et al. Preventive effects of the sodium glucose cotransporter 2 inhibitor tofogliflozin on diethylnitrosamine-induced liver tumorigenesis in obese and diabetic mice. Oncotarget. 2017;8(35):58353-63. doi: 10.18632/oncotarget.16874. PubMed PMID: 28938561; PubMed Central PMCID: PMCPMC5601657.

5. Hung MH, Chen YL, Chen LJ, Chu PY, Hsieh FS, Tsai MH, et al. Canagliflozin inhibits growth of hepatocellular carcinoma via blocking glucose-influx-induced beta-catenin activation. Cell Death Dis. 2019;10(6):420. doi: 10.1038/s41419-019-1646-6. PubMed PMID: 31142735; PubMed Central PMCID: PMCPMC6541593.

Attachment

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Click here for additional data file.^{(224.9KB, pdf)}

PLoS One. doi: 10.1371/journal.pone.0232283.r005

Decision Letter 2

Tatsuo Kanda

13 Apr 2020

Effects of Canagliflozin on Growth and Metabolic Reprograming in Hepatocellular Carcinoma Cells: Multi-Omics Analysis of Metabolomics and Absolute Quantification Proteomics (iMPAQT)

PONE-D-19-33203R2

Dear Prof. Takumi Kawaguchi,

We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements.

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Tatsuo Kanda, M.D., Ph.D.

Academic Editor

PLOS ONE

PLoS One. doi: 10.1371/journal.pone.0232283.r006

Acceptance letter

Tatsuo Kanda

15 Apr 2020

PONE-D-19-33203R2

Effects of Canagliflozin on Growth and Metabolic Reprograming in Hepatocellular Carcinoma Cells: Multi-Omics Analysis of Metabolomics and Absolute Quantification Proteomics (iMPAQT)

Dear Dr. Kawaguchi:

I am pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Fig. Immunoblotting for SGLT2 in Hep3B and Huh7.

Abbreviations: CANA, canagliflozin; SGLT1, sodium-glucose cotransporter 1; GLUT, glucose transporter.

(TIFF)

Click here for additional data file.^{(1.7MB, tiff)}

S2 Fig. Immunoblotting for SGLT1 and GLUT1-6 in Hep3B and Huh7.

Abbreviations: CANA, canagliflozin; SGLT1, sodium-glucose cotransporter 1; GLUT, glucose transporter.

(TIFF)

Click here for additional data file.^{(2.6MB, tiff)}

S3 Fig. Effects of dapagliflozin on proliferation of Hep3B cells.

* P<0.01. Abbreviations: CON, control; DAPA, dapagliflozin.

(TIFF)

Click here for additional data file.^{(785.7KB, tiff)}

S4 Fig. Effects of CANA on morphological change in Hep3B and Huh7 cells.

Scale bar = 50 μm. Abbreviations: CON, control; CANA, canagliflozin.

(TIFF)

Click here for additional data file.^{(6.1MB, tiff)}

S5 Fig. Immunoblotting for apoptosis-related molecules in Hep3B and Huh7 cells.

Abbreviations: CON, control; CANA, canagliflozin; PARP, poly adenosine diphosphate-ribose polymerase.

(TIFF)

Click here for additional data file.^{(2.3MB, tiff)}

S6 Fig. Immunoblotting for fatty acid metabolism-associated molecules in Huh7 cells.

Abbreviations: CON, control; CANA, canagliflozin; AMPK, AMP-activated protein kinase; ACC, acetyl-CoA carboxylase.

(TIFF)

Click here for additional data file.^{(3.4MB, tiff)}

S7 Fig. Metabolism map for valine, leucine, and isoleucine metabolism.

Red line indicates an up-regulated pathway. Red circle indicates an up-regulated metabolite. Blue circle indicates a down-regulated metabolite.

(TIFF)

Click here for additional data file.^{(4MB, tiff)}

S8 Fig. Intensity of protein expression in the 10 μM CANA and CON groups.

Abbreviations: CON, control; CANA, canagliflozin; AMPK, AMP-activated protein kinase; ACC, acetyl-CoA carboxylase.

(TIFF)

Click here for additional data file.^{(903.3KB, tiff)}

S1 Raw image

(PDF)

Click here for additional data file.^{(5.6MB, pdf)}

S1 Table. Effects of CANA on levels of 225 metabolites by metabolomics in Hep3B cells.

(DOCX)

Click here for additional data file.^{(78KB, docx)}

S2 Table. Effects of CANA on expression level of 342 metabolic enzymes by iMPAQT assay in Hep3B cells.

(DOCX)

Click here for additional data file.^{(49.7KB, docx)}

Attachment

Submitted filename: Responses to REVIEWER 3.docx

Click here for additional data file.^{(19.2KB, docx)}

Attachment

Submitted filename: Responses to REVIEWER 2.pdf

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Data Availability Statement

All relevant data are within the manuscript and its Supporting Information files.

[pone.0232283.ref001] 1.Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(6):394–424. 10.3322/caac.21492 . [DOI] [PubMed] [Google Scholar]

[pone.0232283.ref002] 2.Martinez-Outschoorn UE, Peiris-Pages M, Pestell RG, Sotgia F, Lisanti MP. Cancer metabolism: a therapeutic perspective. Nat Rev Clin Oncol. 2017;14(1):11–31. 10.1038/nrclinonc.2016.60 . [DOI] [PubMed] [Google Scholar]

[pone.0232283.ref003] 3.Tian Y, Yang B, Qiu W, Hao Y, Zhang Z, Yang B, et al. ER-residential Nogo-B accelerates NAFLD-associated HCC mediated by metabolic reprogramming of oxLDL lipophagy. Nat Commun. 2019;10(1):3391 10.1038/s41467-019-11274-x [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0232283.ref004] 4.Ma F, Zhu Y, Liu X, Zhou Q, Hong X, Qu C, et al. Dual-Specificity Tyrosine Phosphorylation-Regulated Kinase 3 Loss Activates Purine Metabolism and Promotes Hepatocellular Carcinoma Progression. Hepatology. 2019. 10.1002/hep.30703 . [DOI] [PubMed] [Google Scholar]

[pone.0232283.ref005] 5.Xie Q, Fan F, Wei W, Liu Y, Xu Z, Zhai L, et al. Multi-omics analyses reveal metabolic alterations regulated by hepatitis B virus core protein in hepatocellular carcinoma cells. Scientific reports. 2017;7:41089 10.1038/srep41089 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0232283.ref006] 6.Liu R, Li Y, Tian L, Shi H, Wang J, Liang Y, et al. Gankyrin drives metabolic reprogramming to promote tumorigenesis, metastasis and drug resistance through activating beta-catenin/c-Myc signaling in human hepatocellular carcinoma. Cancer Lett. 2019;443:34–46. 10.1016/j.canlet.2018.11.030 . [DOI] [PubMed] [Google Scholar]

[pone.0232283.ref007] 7.Zhong XY, Yuan XM, Xu YY, Yin M, Yan WW, Zou SW, et al. CARM1 Methylates GAPDH to Regulate Glucose Metabolism and Is Suppressed in Liver Cancer. Cell Rep. 2018;24(12):3207–23. 10.1016/j.celrep.2018.08.066 . [DOI] [PubMed] [Google Scholar]

[pone.0232283.ref008] 8.Wani NA, Zhang B, Teng KY, Barajas JM, Motiwala T, Hu P, et al. Reprograming of Glucose Metabolism by Zerumbone Suppresses Hepatocarcinogenesis. Mol Cancer Res. 2018;16(2):256–68. 10.1158/1541-7786.MCR-17-0304 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0232283.ref009] 9.Scafoglio C, Hirayama BA, Kepe V, Liu J, Ghezzi C, Satyamurthy N, et al. Functional expression of sodium-glucose transporters in cancer. Proceedings of the National Academy of Sciences of the United States of America. 2015;112(30):E4111–9. 10.1073/pnas.1511698112 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0232283.ref010] 10.Tang H, Dai Q, Shi W, Zhai S, Song Y, Han J. SGLT2 inhibitors and risk of cancer in type 2 diabetes: a systematic review and meta-analysis of randomised controlled trials. Diabetologia. 2017;60(10):1862–72. 10.1007/s00125-017-4370-8 . [DOI] [PubMed] [Google Scholar]

[pone.0232283.ref011] 11.Kaji K, Nishimura N, Seki K, Sato S, Saikawa S, Nakanishi K, et al. Sodium glucose cotransporter 2 inhibitor canagliflozin attenuates liver cancer cell growth and angiogenic activity by inhibiting glucose uptake. International journal of cancer. 2018;142(8):1712–22. 10.1002/ijc.31193 . [DOI] [PubMed] [Google Scholar]

[pone.0232283.ref012] 12.Shiba K, Tsuchiya K, Komiya C, Miyachi Y, Mori K, Shimazu N, et al. Canagliflozin, an SGLT2 inhibitor, attenuates the development of hepatocellular carcinoma in a mouse model of human NASH. Scientific reports. 2018;8(1):2362 10.1038/s41598-018-19658-7 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0232283.ref013] 13.Wang X, Zhang A, Sun H. Power of metabolomics in diagnosis and biomarker discovery of hepatocellular carcinoma. Hepatology. 2013;57(5):2072–7. 10.1002/hep.26130 . [DOI] [PubMed] [Google Scholar]

[pone.0232283.ref014] 14.Guo W, Tan HY, Wang N, Wang X, Feng Y. Deciphering hepatocellular carcinoma through metabolomics: from biomarker discovery to therapy evaluation. Cancer Manag Res. 2018;10:715–34. 10.2147/CMAR.S156837 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0232283.ref015] 15.Matsumoto M, Matsuzaki F, Oshikawa K, Goshima N, Mori M, Kawamura Y, et al. A large-scale targeted proteomics assay resource based on an in vitro human proteome. Nat Methods. 2017;14(3):251–8. 10.1038/nmeth.4116 . [DOI] [PubMed] [Google Scholar]

[pone.0232283.ref016] 16.Sugita S, Enokida H, Yoshino H, Miyamoto K, Yonemori M, Sakaguchi T, et al. HRAS as a potential therapeutic target of salirasib RAS inhibitor in bladder cancer. Int J Oncol. 2018;53(2):725–36. 10.3892/ijo.2018.4435 . [DOI] [PubMed] [Google Scholar]

[pone.0232283.ref017] 17.Hnasko TS, Hnasko RM. The Western Blot. Methods Mol Biol. 2015;1318:87–96. 10.1007/978-1-4939-2742-5_9 . [DOI] [PubMed] [Google Scholar]

[pone.0232283.ref018] 18.Schneider CA, Rasband WS, Eliceiri KW. NIH Image to ImageJ: 25 years of image analysis. Nat Methods. 2012;9(7):671–5. 10.1038/nmeth.2089 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0232283.ref019] 19.Odell ID, Cook D. Immunofluorescence techniques. J Invest Dermatol. 2013;133(1):e4 10.1038/jid.2012.455 . [DOI] [PubMed] [Google Scholar]

[pone.0232283.ref020] 20.Kawaguchi T, Hayakawa M, Koga H, Torimura T. Effects of fucoidan on proliferation, AMP-activated protein kinase, and downstream metabolism- and cell cycle-associated molecules in poorly differentiated human hepatoma HLF cells. Int J Oncol. 2015;46(5):2216–22. Epub 2015/03/18. 10.3892/ijo.2015.2928 . [DOI] [PubMed] [Google Scholar]

[pone.0232283.ref021] 21.Strober W. Trypan blue exclusion test of cell viability. Curr Protoc Immunol. 2001;Appendix 3:Appendix 3B. 10.1002/0471142735.ima03bs21 . [DOI] [PubMed] [Google Scholar]

[pone.0232283.ref022] 22.Takahashi R, Shimazaki C, Inaba T, Okano A, Hatsuse M, Okamoto A, et al. A newly developed bisphosphonate, YM529, is a potent apoptosis inducer of human myeloma cells. Leuk Res. 2001;25(1):77–83. 10.1016/s0145-2126(00)00087-4 . [DOI] [PubMed] [Google Scholar]

[pone.0232283.ref023] 23.Selvendiran K, Koga H, Ueno T, Yoshida T, Maeyama M, Torimura T, et al. Luteolin promotes degradation in signal transducer and activator of transcription 3 in human hepatoma cells: an implication for the antitumor potential of flavonoids. Cancer Res. 2006;66(9):4826–34. 10.1158/0008-5472.CAN-05-4062 . [DOI] [PubMed] [Google Scholar]

[pone.0232283.ref024] 24.Yamamura S, Kawaguchi T, Nakano D, Tomiyasu Y, Yoshinaga S, Doi Y, et al. Profiles of Advanced Hepatic Fibrosis Evaluated by FIB-4 index and Shear Wave Elastography in Health Check-up Examinees. Hepatol Res. 2019. Epub 2019/10/22. 10.1111/hepr.13436 . [DOI] [PubMed] [Google Scholar]

[pone.0232283.ref025] 25.Chao EC, Henry RR. SGLT2 inhibition—a novel strategy for diabetes treatment. Nat Rev Drug Discov. 2010;9(7):551–9. 10.1038/nrd3180 . [DOI] [PubMed] [Google Scholar]

[pone.0232283.ref026] 26.Obara K, Shirakami Y, Maruta A, Ideta T, Miyazaki T, Kochi T, et al. Preventive effects of the sodium glucose cotransporter 2 inhibitor tofogliflozin on diethylnitrosamine-induced liver tumorigenesis in obese and diabetic mice. Oncotarget. 2017;8(35):58353–63. 10.18632/oncotarget.16874 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0232283.ref027] 27.Tahrani AA, Barnett AH, Bailey CJ. SGLT inhibitors in management of diabetes. Lancet Diabetes Endocrinol. 2013;1(2):140–51. 10.1016/S2213-8587(13)70050-0 . [DOI] [PubMed] [Google Scholar]

[pone.0232283.ref028] 28.Villani LA, Smith BK, Marcinko K, Ford RJ, Broadfield LA, Green AE, et al. The diabetes medication Canagliflozin reduces cancer cell proliferation by inhibiting mitochondrial complex-I supported respiration. Mol Metab. 2016;5(10):1048–56. 10.1016/j.molmet.2016.08.014 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0232283.ref029] 29.Devineni D, Murphy J, Wang SS, Stieltjes H, Rothenberg P, Scheers E, et al. Absolute oral bioavailability and pharmacokinetics of canagliflozin: A microdose study in healthy participants. Clin Pharmacol Drug Dev. 2015;4(4):295–304. 10.1002/cpdd.162 . [DOI] [PubMed] [Google Scholar]

[pone.0232283.ref030] 30.Hsu PP, Sabatini DM. Cancer cell metabolism: Warburg and beyond. Cell. 2008;134(5):703–7. 10.1016/j.cell.2008.08.021 . [DOI] [PubMed] [Google Scholar]

[pone.0232283.ref031] 31.DeBerardinis RJ, Lum JJ, Hatzivassiliou G, Thompson CB. The biology of cancer: metabolic reprogramming fuels cell growth and proliferation. Cell Metab. 2008;7(1):11–20. 10.1016/j.cmet.2007.10.002 . [DOI] [PubMed] [Google Scholar]

[pone.0232283.ref032] 32.Secker PF, Beneke S, Schlichenmaier N, Delp J, Gutbier S, Leist M, et al. Canagliflozin mediated dual inhibition of mitochondrial glutamate dehydrogenase and complex I: an off-target adverse effect. Cell Death Dis. 2018;9(2):226 10.1038/s41419-018-0273-y [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0232283.ref033] 33.Osataphan S, Macchi C, Singhal G, Chimene-Weiss J, Sales V, Kozuka C, et al. SGLT2 inhibition reprograms systemic metabolism via FGF21-dependent and -independent mechanisms. JCI Insight. 2019;4(5). 10.1172/jci.insight.123130 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0232283.ref034] 34.Okamoto S, Asgar NF, Yokota S, Saito K, Minokoshi Y. Role of the alpha2 subunit of AMP-activated protein kinase and its nuclear localization in mitochondria and energy metabolism-related gene expressions in C2C12 cells. Metabolism. 2019;90:52–68. 10.1016/j.metabol.2018.10.003 . [DOI] [PubMed] [Google Scholar]

[pone.0232283.ref035] 35.Lopez-Mejia IC, Lagarrigue S, Giralt A, Martinez-Carreres L, Zanou N, Denechaud PD, et al. CDK4 Phosphorylates AMPKalpha2 to Inhibit Its Activity and Repress Fatty Acid Oxidation. Mol Cell. 2017;68(2):336–49 e6. 10.1016/j.molcel.2017.09.034 . [DOI] [PubMed] [Google Scholar]

[pone.0232283.ref036] 36.Lally JSV, Ghoshal S, DePeralta DK, Moaven O, Wei L, Masia R, et al. Inhibition of Acetyl-CoA Carboxylase by Phosphorylation or the Inhibitor ND-654 Suppresses Lipogenesis and Hepatocellular Carcinoma. Cell Metab. 2019;29(1):174–82 e5. 10.1016/j.cmet.2018.08.020 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0232283.ref037] 37.Fritz V, Benfodda Z, Rodier G, Henriquet C, Iborra F, Avances C, et al. Abrogation of de novo lipogenesis by stearoyl-CoA desaturase 1 inhibition interferes with oncogenic signaling and blocks prostate cancer progression in mice. Mol Cancer Ther. 2010;9(6):1740–54. 10.1158/1535-7163.MCT-09-1064 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0232283.ref038] 38.Sanli T, Steinberg GR, Singh G, Tsakiridis T. AMP-activated protein kinase (AMPK) beyond metabolism: a novel genomic stress sensor participating in the DNA damage response pathway. Cancer Biol Ther. 2014;15(2):156–69. 10.4161/cbt.26726 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0232283.ref039] 39.Lee CW, Wong LL, Tse EY, Liu HF, Leong VY, Lee JM, et al. AMPK promotes p53 acetylation via phosphorylation and inactivation of SIRT1 in liver cancer cells. Cancer Res. 2012;72(17):4394–404. 10.1158/0008-5472.CAN-12-0429 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0232283.ref040] 40.Liu Y, Hong Z, Tan G, Dong X, Yang G, Zhao L, et al. NMR and LC/MS-based global metabolomics to identify serum biomarkers differentiating hepatocellular carcinoma from liver cirrhosis. International journal of cancer. 2014;135(3):658–68. 10.1002/ijc.28706 . [DOI] [PubMed] [Google Scholar]

[pone.0232283.ref041] 41.Fine EJ, Miller A, Quadros EV, Sequeira JM, Feinman RD. Acetoacetate reduces growth and ATP concentration in cancer cell lines which over-express uncoupling protein 2. Cancer Cell Int. 2009;9:14 10.1186/1475-2867-9-14 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0232283.ref042] 42.Poff AM, Ari C, Arnold P, Seyfried TN, D'Agostino DP. Ketone supplementation decreases tumor cell viability and prolongs survival of mice with metastatic cancer. International journal of cancer. 2014;135(7):1711–20. 10.1002/ijc.28809 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0232283.ref043] 43.Yan H, Li Z, Shen Q, Wang Q, Tian J, Jiang Q, et al. Aberrant expression of cell cycle and material metabolism related genes contributes to hepatocellular carcinoma occurrence. Pathol Res Pract. 2017;213(4):316–21. 10.1016/j.prp.2017.01.019 . [DOI] [PubMed] [Google Scholar]

[pone.0232283.ref044] 44.Liu F, Li H, Chang H, Wang J, Lu J. Identification of hepatocellular carcinoma-associated hub genes and pathways by integrated microarray analysis. Tumori. 2015;101(2):206–14. 10.5301/tj.5000241 . [DOI] [PubMed] [Google Scholar]

[pone.0232283.ref045] 45.Puts GS, Leonard MK, Pamidimukkala NV, Snyder DE, Kaetzel DM. Nuclear functions of NME proteins. Lab Invest. 2018;98(2):211–8. 10.1038/labinvest.2017.109 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0232283.ref046] 46.Hindupur SK, Colombi M, Fuhs SR, Matter MS, Guri Y, Adam K, et al. The protein histidine phosphatase LHPP is a tumour suppressor. Nature. 2018;555(7698):678–82. 10.1038/nature26140 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0232283.ref047] 47.Zerbe LK, Kuchta RD. The p58 subunit of human DNA primase is important for primer initiation, elongation, and counting. Biochemistry. 2002;41(15):4891–900. 10.1021/bi016030b . [DOI] [PubMed] [Google Scholar]

[pone.0232283.ref048] 48.Hung MH, Chen YL, Chen LJ, Chu PY, Hsieh FS, Tsai MH, et al. Canagliflozin inhibits growth of hepatocellular carcinoma via blocking glucose-influx-induced beta-catenin activation. Cell Death Dis. 2019;10(6):420 10.1038/s41419-019-1646-6 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0232283.ref049] 49.Kuang H, Liao L, Chen H, Kang Q, Shu X, Wang Y. Therapeutic Effect of Sodium Glucose Co-Transporter 2 Inhibitor Dapagliflozin on Renal Cell Carcinoma. Med Sci Monit. 2017;23:3737–45. 10.12659/MSM.902530 [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Effects of canagliflozin on growth and metabolic reprograming in hepatocellular carcinoma cells: Multi-omics analysis of metabolomics and absolute quantification proteomics (iMPAQT)

Dan Nakano

Takumi Kawaguchi

Hideki Iwamoto

Masako Hayakawa

Hironori Koga

Takuji Torimura

Roles

Abstract

Aim

Methods

Results

Conclusions

Introduction

Methods

Reagents and antibodies

Cell lines

Immunoblotting analysis and quantification

Immunofluorescence staining

Isolation of mitochondrial fraction

Effect of CANA on cell proliferation

Living cell assessment by reagent SF assay

Dead cell assessment by trypan blue exclusion assay

Evaluation of morphological change of Hep3B and Huh7 cells

Evaluation of apoptosis

Cell cycle analysis

Metabolomic analysis

iMPAQT

Statistical analysis

Results

Expression of SGLT2

Fig 1. Expression of SGLT2 in Hep3B and Huh7.

Effects of CANA on proliferation of Hep3B and Huh7 cells

Fig 2.

Effects of CANA on morphological change and apoptosis of Hep3B and Huh7 cells

Fig 3. Effects of CANA on apoptosis and cell cycle of Hep3B and Huh7 cells.

Effects of CANA on cell cycle in Hep3B and Huh7 cells

Effects of CANA on metabolites evaluated by metabolomics

Fig 4. Effects of CANA on metabolites evaluated by metabolomics.

Fig 5. Metabolism map showing both CANA-altered metabolites and metabolic enzymes using multi-omics analysis of metabolomics and iMPAQT.

Effects of CANA on expression level of metabolic enzymes by iMPAQT

Table 1. Effects of CANA on expression level of metabolic enzymes by iMPAQT assay.

Metabolism map showing both CANA-altered metabolites and metabolic enzymes using multi-omics analysis of metabolomics and iMPAQT

Effect of CANA on fatty acid metabolism-associated molecules

Fig 6. Effect of CANA on fatty acid metabolism-associated molecules.

Discussion

Fig 7. A scheme for proposed mechanisms for canagliflozin-induced suppression of cell proliferation in Hep3B cell.

Supporting information

Acknowledgments

Abbreviations

Data Availability

Funding Statement

References

Decision Letter 0

Tatsuo Kanda

Roles

Author response to Decision Letter 0

Decision Letter 1

Tatsuo Kanda

Roles

Author response to Decision Letter 1

Decision Letter 2

Tatsuo Kanda

Roles

Acceptance letter

Tatsuo Kanda

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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