Clear cell renal cell carcinoma (ccRCC) is the most common subtype of kidney cancer. While the localized form of this disease can be treated surgically, advanced and metastatic stages are resistant to chemotherapies. Although more innovative treatments, such as targeted or immune-based therapies, exist, the need for new therapeutic options remains. ccRCC presents unique metabolic signatures and multiple studies have reported a significant increase in levels of reduced glutathione (GSH) and its precursors in ccRCC tumor samples compared with normal kidney tissues. These observations led us to investigate the effects of blocking the GSH pathway, particularly the gamma-glutamyltransferase 1 (GGT1) enzyme, in multiple ccRCC cell lines. In this study, we provide in vitro and in vivo evidence that GGT1/GSH pathway inhibition impacts ccRCC cell growth, through increased cell-cycle arrest. Of note, GGT1 inhibition also impairs ccRCC cell migration. Finally, pharmacologic GSH pathway inhibition decreases ccRCC cell proliferation and increases sensitivity to standard chemotherapy. Our results suggest that GGT1/GSH pathway inhibition represents a new strategy to overcome ccRCC chemoresistance.

Implications:

GGT1/GSH pathway inhibition represents a promising therapeutic strategy to overcome chemoresistance and inhibit progression of ccRCC tumors.

Kidney cancer is among the ten most common malignancies in both men and women in the United States, and its incidence has increased rapidly in recent years (1). More than 75% of renal cancer diagnoses present as clear cell renal cell carcinoma (ccRCC), a subtype that carries a poor prognosis due to intrinsic resistance to conventional chemotherapy and radiation (2). Interestingly, ccRCC lacks common genetic abnormalities observed in many other human cancers, including those in the PTEN, TP53, and KRAS signaling pathways (3, 4). More than 90% of ccRCC tumors show constitutive activation of the hypoxia-inducible factor (HIF) proteins due to biallelic inactivation of the tumor suppressor von Hippel-Lindau (VHL) gene (4). Histologically, ccRCC is characterized by the “clear-cell” phenotype resulting from lipid and glycogen accumulation, suggesting that altered fatty acid and glucose metabolism play a crucial role in the development of this cancer (5–8).

Different treatment options available for patients with ccRCC include antiangiogenic agents, receptor tyrosine kinase inhibitors, mTOR inhibitors, HIF2α antagonists, and immunotherapy (9). However, only a subset of patients respond to each of these approaches (∼20%; ref. 9–14). Moreover, while localized tumors can be treated by surgical resection, approximately 23% are diagnosed as metastatic disease with a 5-year survival rate of only 10% (2, 7, 14). Therefore, a significant clinical need exists for therapies that will exploit unique vulnerabilities present in all tumors to effectively improve prognosis of more patients with ccRCC.

Deregulated metabolism to produce sufficient energy and synthetic building blocks for cellular proliferation of tumor cells is a hallmark of cancer (15). Interestingly, ccRCC has often been labeled as a metabolic disease due to reprogramming of several metabolic pathways in this cancer. The Cancer Genome Atlas (TCGA) studies of ccRCC tumors show substantial alterations of metabolic pathways relative to healthy kidney to promote biosynthesis and growth (16). In addition, worse patient survival correlates with upregulation of the pentose phosphate pathway and fatty acid synthesis, and downregulation of the tricarboxylic acid (TCA) cycle and urea cycle genes (16, 17). However, because this was only based on transcriptomic data, we and others performed comprehensive metabolomic studies comparing tumor tissues and matched normal samples using LC/MS (3, 18). A striking feature of these findings is the 140-fold increase in the levels of reduced glutathione (GSH) in patient tumor samples (3, 18). GSH is a tripeptide generated from glutamic acid, cysteine, and glycine in two successive ATP-dependent enzymatic steps (Fig. 1A). In cells, GSH can be found in both reduced (GSH) and oxidized (GSSG) forms, and GSH/GSSG ratios are commonly used as an indicator of oxidative stress (19, 20). Interestingly, elevated GSH levels have also been reported to be a major contributing factor to chemoresistance, a significant therapeutic limitation in ccRCC (21, 22).

Figure 1.

GSH and its intermediates are significantly increased in ccRCC tumors relative to healthy kidney tissue. A, Schematic depicting the enzymes involved in de novo biosynthesis of GSH. GGT, gamma-glutamyltransferase 1; GCL, glutamate-cysteine ligase; GSS, glutathione synthetase; GPx, glutathione peroxidase; xCT, cysteine transporter; OU749, GGT1 inhibitor. B, Metabolite data (tumor vs. normal) from Hakimi and colleagues (3) were analyzed and plotted. Glutathione is among the most over-represented metabolites. C, Metabolite data (tumor vs. normal) from Li and colleagues (18) were analyzed and plotted. Glutathione is among the most overrepresented metabolites. D, Fold change of intermediate metabolites in GSH synthesis in ccRCC relative to adjacent normal kidney tissue samples, indicating that most of the intermediate metabolites are increased relative to normal tissue. E, GSH abundance in patients stratified according to cancer stage from Hakimi and colleagues' (3) dataset. F, GSH abundance in patients stratified according to cancer stage from Li and colleagues' (18) dataset. Statistical significance was defined as ***, P < 0.001; *, P < 0.05; n.s., not significant.

Figure 1.

GSH and its intermediates are significantly increased in ccRCC tumors relative to healthy kidney tissue. A, Schematic depicting the enzymes involved in de novo biosynthesis of GSH. GGT, gamma-glutamyltransferase 1; GCL, glutamate-cysteine ligase; GSS, glutathione synthetase; GPx, glutathione peroxidase; xCT, cysteine transporter; OU749, GGT1 inhibitor. B, Metabolite data (tumor vs. normal) from Hakimi and colleagues (3) were analyzed and plotted. Glutathione is among the most over-represented metabolites. C, Metabolite data (tumor vs. normal) from Li and colleagues (18) were analyzed and plotted. Glutathione is among the most overrepresented metabolites. D, Fold change of intermediate metabolites in GSH synthesis in ccRCC relative to adjacent normal kidney tissue samples, indicating that most of the intermediate metabolites are increased relative to normal tissue. E, GSH abundance in patients stratified according to cancer stage from Hakimi and colleagues' (3) dataset. F, GSH abundance in patients stratified according to cancer stage from Li and colleagues' (18) dataset. Statistical significance was defined as ***, P < 0.001; *, P < 0.05; n.s., not significant.

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We report here that ccRCC tumors have significantly increased levels of gamma-glutamyltransferase 1 (GGT1) according to TCGA data. GGT1 is a component of the GSH salvage pathway, catalyzing the cleavage of extracellular GSH into its components to provide cysteine for the production of intracellular GSH (Fig. 1A; ref. 23). First, γ-glutamylcysteine is synthesized by a reaction between glutamic acid and cysteine by the enzyme glutamate-cysteine ligase (GCL), forming a γ-peptide bond. The second step is catalyzed by GSH synthetase (GSS), adding glycine to the C-terminus of γ-glutamylcysteine, resulting in the final GSH product. Increased circulating GGT activity is usually an indication of hepatobiliary toxicity, especially cholestasis, and also commonly used to detect liver disease (23–25). In addition, higher serum GGT levels are associated with poor patient prognosis and survival in ccRCC (26), and recent studies report that GGT1 expression is deregulated in patients with ccRCC, leading to a more aggressive phenotype (27, 28). We demonstrate that ccRCC cells are dependent upon the presence of GGT1 for proliferation, migration, and tumor growth. Therefore, modulation of the GSH-based antioxidant system, particularly through GGT1 activity, represents a promising therapeutic strategy to overcome chemoresistance and inhibit progression of ccRCC tumors.

Cell culture

Human ccRCC cell lines (786O, UMRC2, RCC10, A498) and control kidney proximal tubular cells (HK2 and RPTEC–renal cortex proximal tubular epithelial cells) were obtained from ATCC. ccRCC cell lines were cultured in DMEM containing 10% FBS. HK2 cells were grown in keratinocyte-free media (Thermo Fisher Scientific, catalog no. 17005042) and RPTEC cells were grown in DMEM/F12 media with recommended additives from ATCC. These cells were cultured for a maximum of four weeks after which fresh early passage cells were thawed and used for experiments. Mycoplasma testing is routinely performed on these cell lines (every 6 months) and confirmed to be negative for its presence (MycoAlert).

Lentivirus and making GGT1 KD cell lines

MCG Human GGT1 Sequence-Verified cDNA (clone ID: 4548861) was purchased from Dharmacon. Forward (gatactctcgagatgaagaagaagttagtggtgc) and reverse (gatactgttaactcagtagccggcaggc) primers containing XhoI and HpaI restriction sites, respectively, were designed to clone the GGT1 open-reading frame into retroviral expression plasmid MSCV. A second round of PCR was performed to introduce silent mutations over the shRNA-binding region, using the Q5 Site-Directed Mutagenesis Kit (New England Biolabs, catalog no. E0554S). The knockdown cells lines were made using lentiviruses, generated by transfecting HEK293RT cells with third-generation lentivirus system pRSV-Rev, pMDL, and pCMV-VSV-G plasmids using Fugene6 Transfection Reagent (Promega). The virus was collected 48 hours after transfection. For viral transduction, cells were incubated with medium containing virus for 24 hours and then selected with antibiotics for 3–4 days. The surviving cells were then pooled for downstream analyses. The lentiviral vector pLKO.1 Scramble (plasmid no. 17920) was obtained from Addgene. pLKO.1 lentiviral vectors expressing hairpins against shGGT1_1 (clone ID: TRCN0000036289, sequence TTTCGTGTGGTGCTGTTGTAG) and shGGT1_2 (TRCN0000036293, sequence TTGTAGATGGTGAGGAAGAGG) were obtained from The RNAi Consortium (TRC) at the Broad Institute and GE Dharmacon. Fresh knockdown cell lines were made for the different characterization assays.

Metabolomics analysis

Metabolomics experiments, including mass spectrometry, and analysis of primary ccRCC were performed with Metabolon (Metabolon, Inc.) as described previously (18).

Western blot analysis

Cells were lysed using 40 mmol/L HEPES (pH = 7.4), 2 mmol/L EDTA, 10 mmol/L pyrophosphate, 10 mmol/L glycerophosphate, 1% Triton X-100, and Roche complete ultra protease/phosphatase inhibitor (catalog no. 05892791001). Lysates were then resolved by Tris-Glycine SDS-PAGE and transferred to nitrocellulose membranes (Bio-Rad #162-0115, 0.45-μm pore size for all experiments). Membranes were blocked and incubated overnight in a cold room at 4°C with the indicated primary antibodies diluted in TBS-Tween (20 mmol/L Tris, 135 mmol/L NaCl, and 0.02% Tween 20) supplemented with 5% BSA. Signal was detected using secondary antibodies conjugated with horseradish peroxidase. Membranes were then exposed to ECL reagents. The following antibodies were used: β-actin (Santa Cruz Biotechnology sc 4778) and GGT1 (Abcam, ab109427). All the Western blots were repeated at least twice for each figure.

qRT-PCR

Total RNA was processed and extracted with TRIzol reagent (Thermo Fisher Scientific, catalog no. 15596026) and RNeasy Mini Kit (Qiagen, catalog no. 74104). RT reaction was performed using High-Capacity RNA-to-cDNA Kit (Applied Biosystems, catalog no. 4387406). qRT-PCR were then performed using TaqMan Master Mix (Life Technologies) and a ViiA7 Real-Time PCR Instrument (Applied Biosystems). TaqMan probes were used to quantitate expression of GGT1 (catalog no. hs00980756_m1). Normalization was performed using the housekeeping genes ACTB (catalog no. hs01060665_G1) and TBP (hs00427620_m1). The mRNA was measured in triplicates with each experiment repeated twice.

Cell proliferation assay

Cell proliferation assays were performed using WST-1 Reagent (Sigma-Aldrich, catalog no. 11644807001). ccRCC cells were plated in 96-well plates at 500 cells/well (786O) and 750 cells/well (RCC10), respectively, and allowed to attach overnight (one 96-well plate for each day of the assay). The following day, media were exchanged with 100 μL of complete DMEM or specific media supplemented with drugs used according to each experiment (see figures for exact concentrations used in each experiment). Plated cells were exposed to WST-1 reagent following the manufacturer's protocol; this was considered day 0. The assay was repeated every other day till day 7 and data in each experiment were normalized to the starting cell number at day 0 of the assay. Eight different wells were plated for each condition per experiment and each experiment was repeated at least three times.

Cell survival assay

Cell death was determined using the FITC–Annexin V, PI Kit (catalog no. 556547) from BD Biosciences according to the manufacturer's instructions. Briefly, 2 × 105 RCC10 or 786O cells were plated in triplicates in 6-well plates. Twenty-four hours after plating, cells were treated for 48 hours with either cisplatin (3 μmol/L for 786O cells, 20 μmol/L for RCC10 cells), OU749 (1 mmol/L) or their combination. Flow cytometry was performed using a BD Accuri C6 or a FACSCalibur flow cytometer, and double-negative cells were considered viable. The concentration of cisplatin was decided on the basis of kill curves for 786O and RCC10 cells. Briefly, 5 × 104 cells were plated in duplicate in 6-well plates and exposed to increasing concentrations of cisplatin. Concentrations where less than 50% of the cells were dead (3 μmol/L for 786O cells and 20 μmol/L for RCC10 cells) were chosen to perform the additive experiments.

Matrigel-based spheroid growth assay

Matrigel was used to generate 3D spheroids as described previously (29). A total of 3,000 cells per well were plated in 96-well “low-adherence” plates along with DMEM supplemented with 10% FBS and 2.5% Matrigel. Plates were then centrifuged at 1,800 rpm to promote spheroid formation. Images were taken using the EVOS FL Auto Imaging System every two days for two weeks. Twenty-four wells were plated for each condition per experiment and two biological repeats were performed. Spheroid volume was determined via previously published ImageJ macros (30).

Anchorage-independent growth assay

ccRCC cells (Scr and GGT1 KD) were plated in triplicate 6-well plates (6,000 cells/well) in complete DMEM containing 0.3% agarose (low-melt 2-hydroxyethylagarose, Sigma-Aldrich A4018), onto underlays composed of DMEM containing 0.6% agarose. Additional media were added to the cultures once per week, and colonies counted after three weeks. This experiment was repeated twice.

Cell-cycle analysis

Scr and GGT1 KD cells were plated in 6-cm plates in duplicates and harvested at 80% confluency. Cells were then resuspended in 1× PBS and fixed with 70% ethanol, and incubated overnight at 4°C. The following day, cells were washed with ice-cold PBS and resuspended in 1 mL PBS. They were treated with RNAse (100 μg/mL), stained with PI (20 μg/mL), and then analyzed by flow cytometry using the BD FACSCalibur instrument. For Ki67/PI analysis, the cells were treated with Ki67 (0.25 μg/sample) before staining with PI. This experiment was performed in triplicates and repeated twice.

Migration assay

Cells were grown to confluency in triplicate in 6-well plates. A scratch was made with a 200-μL tip across each well and pictures taken at the starting timepoint, as well as 24 hours postscratch for RCC10 cells and 6 hours postscratch for 786O cells. The percentage of area that was “repaired” was measured using ImageJ software and plotted as the average of the triplicates with standard error (SE). This experiment was repeated three times.

Transwell assay

Cells were plated on 10-cm dishes and serum starved for 24 hours. These were then plated on transwells (8-μm pore size, 24-well format) at a density of 1 × 105 cells per well (total of 5 wells were plated for each condition). The top well was filled with serum-free media and the bottom well with complete media (DMEM containing 10% serum). Plates were incubated for 12–16 hours and fixed with paraformaldehyde followed by methanol. Cells were then stained with diluted Giemsa stain and mounted on a slide to observe the number of cells migrated through the pores. These were then quantified by eye in five different images. The average of these numbers and SE between the samples was calculated and plotted using GraphPad Prism software. The experiment was repeated two times.

Subcutaneous xenografts

All animal experiments and subcutaneous xenografts were approved by the Institutional Animal Care and Use Committee at the University of Pennsylvania (Philadelphia, PA). Twelve female NIH-III nude mice between 4 and 6 weeks old (Charles River Laboratories) were implanted in each flank with 2 × 106 786O cells or 5 × 106 786O control (Scr) or GGT1 KD cells (shGGT1_2). Prior to injection, cells were grown in complete media (DMEM containing 10% FBS) in 15-cm dishes. Cells were then collected and resuspended in ice-cold PBS mixed with Matrigel (BD Biosciences, catalog no. 356234) at a ratio 1:1. The final volume per injection was 200 μL. Tumor volumes were assessed and recorded at the indicated timepoints using caliper measurements. The formula, V = (π/6)(L)(W2), was used to calculate the tumor volume. L being the longer measurement and W being the shorter measurement. Twenty-six days postinjection, mice were sacrificed by CO2 inhalation. Tumors were then harvested for further analyses. For the mice bearing 786O xenografts, tumor growth was closely monitored and when tumor volume reached 100 mm3, mice were randomized and divided into four groups showing similar tumor volumes, control, buthionine sulfoximine (BSO; Sigma-Aldrich, catalog no. B2515), cisplatin (Tocris Bioscience, catalog no. 2251), and BSO + cisplatin (n = 5 per group). BSO (20 mmol/L) was administered by oral delivery in drinking water and cisplatin (3 mg/kg/week) administered intraperitoneally. For the BSO + cisplatin group, mice were pretreated with BSO for 3 days before cisplatin treatment.

IHC

Xenograft tumors were dehydrated using ethanol and embedded in paraffin. Tumors were sectioned for staining and IHC was performed as described previously (6). The antibodies and dilutions used during the IHC process were: 1:100 Ki67 (Abcam, catalog no. Ab15580) and 1:400 cleaved caspase 3 (Cell Signaling Technology, catalog no. 9661).

GSH measurement assay

For Supplementary Fig. S2, GSH ratios were measured using a Promega Kit (V611). Briefly, cells were plated at an equal density in a 96-well plate in duplicates. Total GSH Lysis Reagent was added to one set for the total GSH measurement, or Oxidized Glutathione Lysis Reagent for the GSSG measurement. Luciferin Generation Reagent was then added to all the wells and incubated for 30 minutes. Luminescence was measured after adding Luciferin Detection Reagent and a 15-minute incubation. GSH/GSSG ratios are calculated directly from luminescence measurements. For measuring GSH levels in the tumors, cells were lysed in PBS lysis buffer containing trichloroacetic acid. After neutralization, samples were processed according to manufacturer's instructions (Biovision K264). Each sample was treated with OPA (O-phthaldehye) probe and fluorescence measured at an Ex/Em = 340/420 nm. GSH concentrations were measured according to GSH standards.

For Supplementary Fig. S5, a different Biovision Kit (K264) was used. Briefly, tissue was homogenized on ice with 100 μL of ice cold Glutathione Assay Buffer. These samples were treated with perchloric acid (PCA) to precipitate proteins. PCA was then neutralized by potassium hydroxide and GSH or GSSG levels measured according to the manufacturer's instructions, using an OPA Probe. Samples were read on a fluorescence plate reader equipped with Ex/Em = 340/420 nm, and values plotted and calculated on the basis of normalization to tumor weights prior to homogenization. Each of these assays was repeated twice.

Statistical analysis

Statistical analyses were performed using GraphPad Prism version 7 software, using unpaired Student two-tailed t test. Data are presented as mean ± SEM of at least three independent experiments. Statistical significance was defined as ***, P < 0.001; **, P < 0.01; *, P < 0.05; n.s., not significant.

GSH and its intermediates are significantly enriched in ccRCC tumors relative to healthy kidney tissue

Metabolomic analysis of ccRCC tumors versus normal patient samples from two independently published datasets revealed that reduced GSH is among the most overrepresented metabolites (Fig. 1B and C) in ccRCC, along with increased precursors like cysteine, γ-glutamylcysteine, and γ-glutamylglutamate (Fig. 1D). Moreover, GSH is further elevated in patients with advanced stages of the disease (Fig. 1E and F), suggesting that GSH is important for tumor progression in patients with ccRCC. RNA-seq data from nearly 500 primary ccRCC tumors in TCGA demonstrated that among all the enzymes required for the synthesis and utilization of GSH, GGT1 is significantly upregulated in tumor samples as compared with normal kidney controls (Fig. 2A). mRNA levels of other biosynthetic enzymes, such as glutamyl cysteine ligase catalytic subunit (GCLC), GSS, and glutathione-disulfide reductase (GSR) are either downregulated or not significantly altered between ccRCC and healthy kidney tissue (Supplementary Fig. S1A and S1B). In addition, data from the Cancer Cell Line Encyclopedia (CCLE) indicate that GGT1 expression is highest in human cell lines originating from kidney tumors (Supplementary Fig. S1C).

Figure 2.

GGT1 inhibition reduces proliferation and induces cell-cycle arrest of ccRCC cells in vitro. A,GGT1 mRNA expression in normal kidney tissue and ccRCC tumors, based on TCGA dataset. GGT1 is significantly upregulated in the tumor samples. B, GGT1 protein abundance in 786O and RCC10 ccRCC cell lines following knockdown using two independent shRNAs (shGGT1_1 and shGGT1_2). C, Growth curve of 786O cells, measuring proliferation rates of control (Scr) and GGT1 KD populations. Proliferation was measured by WST-1 assay as described in the Materials and Methods section. D, Growth curve of RCC10 cells, measuring proliferation rate of control (Scr) and GGT1 KD populations. Proliferation was measured by WST-1 assay as described in the Materials and Methods section. E,In vitro Matrigel spheroid growth of control (Scr) and GGT1 KD 786O cells. Pictures were taken using EVOS FL microscope at the indicated timepoints and volume was calculated using ImageJ software and plotted. All volumes were normalized to the day 1 spheroid size, then plotted as arbitrary units (A.U). F,In vitro Matrigel spheroid growth of control (Scr) and GGT1 KD RCC10 cells. Pictures were taken using EVOS FL microscope at the indicated timepoints and volume was calculated using ImageJ software and plotted. All volumes were normalized to the day 1 spheroid size, then plotted as arbitrary units (A.U). G, Anchorage-independent growth capacity of the ccRCC cells was measured by soft-agar colony formation assay. H, Cell-cycle analysis using PI staining of control (Scr) and GGT1 KD 786O cells was measured by flow cytometry. Data are represented as percentage of cells in G1–G0 phase. I, Percentage of control (Scr) and GGT1 KD 786O cells Ki67-negative and PI-positive measured by flow cytometry. Statistical significance was defined as ***, P < 0.001; **, P < 0.01; *, P < 0.05; n.s., not significant.

Figure 2.

GGT1 inhibition reduces proliferation and induces cell-cycle arrest of ccRCC cells in vitro. A,GGT1 mRNA expression in normal kidney tissue and ccRCC tumors, based on TCGA dataset. GGT1 is significantly upregulated in the tumor samples. B, GGT1 protein abundance in 786O and RCC10 ccRCC cell lines following knockdown using two independent shRNAs (shGGT1_1 and shGGT1_2). C, Growth curve of 786O cells, measuring proliferation rates of control (Scr) and GGT1 KD populations. Proliferation was measured by WST-1 assay as described in the Materials and Methods section. D, Growth curve of RCC10 cells, measuring proliferation rate of control (Scr) and GGT1 KD populations. Proliferation was measured by WST-1 assay as described in the Materials and Methods section. E,In vitro Matrigel spheroid growth of control (Scr) and GGT1 KD 786O cells. Pictures were taken using EVOS FL microscope at the indicated timepoints and volume was calculated using ImageJ software and plotted. All volumes were normalized to the day 1 spheroid size, then plotted as arbitrary units (A.U). F,In vitro Matrigel spheroid growth of control (Scr) and GGT1 KD RCC10 cells. Pictures were taken using EVOS FL microscope at the indicated timepoints and volume was calculated using ImageJ software and plotted. All volumes were normalized to the day 1 spheroid size, then plotted as arbitrary units (A.U). G, Anchorage-independent growth capacity of the ccRCC cells was measured by soft-agar colony formation assay. H, Cell-cycle analysis using PI staining of control (Scr) and GGT1 KD 786O cells was measured by flow cytometry. Data are represented as percentage of cells in G1–G0 phase. I, Percentage of control (Scr) and GGT1 KD 786O cells Ki67-negative and PI-positive measured by flow cytometry. Statistical significance was defined as ***, P < 0.001; **, P < 0.01; *, P < 0.05; n.s., not significant.

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GGT1 inhibition reduces proliferation and induces cell-cycle arrest of ccRCC cells in vitro

GGT1 is an enzyme localized and bound to the plasma membrane, which catalyzes the degradation of extracellular GSH. This favors the production of constituent amino acids for the synthesis of intracellular GSH. GGT1 also has the ability to catalyze the transfer of the glutamyl moiety of GSH, linked through the glutamate γ-carboxylic acid to acceptor molecules including amino acids and peptides (Fig. 1A). Moreover, GGT1 inhibition results in reduced intracellular cysteine, making GGT1 enzymatic action important for the maintenance of intracellular GSH (31, 32). To determine the functions of GGT1 in ccRCC, we used two different shRNAs with varied efficacy (shGGT1_1 and shGGT1_2) to knockdown (KD) GGT1 in 786O and RCC10 ccRCC cells and confirmed decreased protein abundance by Western blot analysis (Fig. 2B). These lines had the highest GGT1 levels among the ccRCC cell lines examined relative to HK2-immortalized renal epithelial cells (Supplementary Fig. S2A and S2B), and were subsequently used for most experiments in this article. Other ccRCC cell lines (i.e., UMRC2 and A498) showed weak or no expression of GGT1, which does not reflect the status of GGT1 expression in kidney tumors. GSH levels also correlated with efficacy of GGT1 knockdown in 786O and RCC10 cells (Supplementary Fig. S2C). Reduced GGT1 levels inhibited proliferation rates in a dose-dependent manner of both cell lines in vitro, dependent upon the efficiency of knockdown (Fig. 2C and D). This phenotype was partially rescued by adding extracellular GSH to the media (Supplementary Fig. S3A), and by overexpression of shRNA-resistant GGT1 protein in both 786O and RCC10 cells harboring shGGT1-2 (Supplementary Fig. S3B and S3C), confirming that proliferation defects are indeed due to reduced GGT1 enzymatic activity. We then embedded the control (Scr) and GGT1 KD cell lines in Matrigel, to form 3D spheroids in vitro and monitored proliferation over time. Spheroid (Fig. 2E and F; Supplementary Fig. S2D) and anchorage-independent growth (Fig. 2G) were significantly decreased in cells with reduced GGT1 expression compared with controls.

To better characterize proliferation defects observed following GGT1 depletion, we performed flow cytometry–based cell–cycle analysis of 786O and RCC10 cells. A significant increase was observed in the mean percentage of cells arrested in the G1 phase of the cell cycle following GGT1 loss compared with controls (Fig. 2H; Supplementary Fig. S4A–S4C). Furthermore, when stained for Ki67 and propidium iodide (PI), approximately 15% of the shGGT1_2 cell population was Ki67 negative, indicating that they were nonproliferative and arrested in the G0 phase (Fig. 2I; Supplementary Fig. S4C). Collectively, these data indicate that reduced GGT1 expression has an antiproliferative effect by imposing cell-cycle arrest of ccRCC cells.

GGT1 loss affects migration capacity of ccRCC cells in vitro

Because it has also been reported that GSH levels correlate with tumor stage and recurrence of the disease (3), we determined whether GGT1 ablation affected the migration capacity of ccRCC cells in vitro. We plated 786O and RCC10 cells at a confluent level and then performed scratch assays to assess migration capacities over the course of 6 and 24 hours, respectively. We observed a significant difference in the percentage of wound healing between control and GGT1-deficient cells for both ccRCC lines (Fig. 3A and B). Consistent with the wound-healing results, a transwell assay also showed that GGT1 depletion significantly reduces cell motility (Fig. 3C). We concluded that ccRCC cells are dependent on the presence of GGT1 for both proliferation and migration.

Figure 3.

GGT1 knockdown reduces migration capacity of ccRCC cells in vitro. A, Representative images of wound healing 24 hours following scratch of control (Scr) and GGT1 KD RCC10 cells. B, Quantification of the percentage of wound recovery of control (Scr) and GGT1 KD RCC10 and 786O cells (n = 3 wells repeated twice). C, Quantification of the number of control (Scr) and GGT1 KD RCC10 and 786O cells migrated through barriers in transwell migration assays 14 hours following response to attractant. Two independent experiments were carried out in five different wells. Data depicted here are representative of one experiment plotted as mean ± SE per group. Statistical significance was defined as **, P < 0.01; *, P < 0.05; n.s., not significant.

Figure 3.

GGT1 knockdown reduces migration capacity of ccRCC cells in vitro. A, Representative images of wound healing 24 hours following scratch of control (Scr) and GGT1 KD RCC10 cells. B, Quantification of the percentage of wound recovery of control (Scr) and GGT1 KD RCC10 and 786O cells (n = 3 wells repeated twice). C, Quantification of the number of control (Scr) and GGT1 KD RCC10 and 786O cells migrated through barriers in transwell migration assays 14 hours following response to attractant. Two independent experiments were carried out in five different wells. Data depicted here are representative of one experiment plotted as mean ± SE per group. Statistical significance was defined as **, P < 0.01; *, P < 0.05; n.s., not significant.

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GGT1 is required to maintain ccRCC xenograft growth

To assess GGT1 function in ccRCC tumor growth in vivo, we implanted 786O control and GGT1 KD cells subcutaneously into opposing flanks of NIH-III nude mice. Tumor volumes were recorded (Fig. 4A) over the course of the experiment. Tumor weights were also determined at day 26 postinjection (Fig. 4B). We noticed a marked difference in the growth of GGT1 KD tumors relative to controls. Quantitation revealed a significant difference in Ki67 staining between control and GGT1 KD tumors, suggesting that GGT1 is required for ccRCC proliferation in vivo (Fig. 4C and D). Cleaved caspase 3 staining also showed increased rates of cell death, but did not achieve statistical significance (Fig. 4E). As expected, GSH/GSSG ratios were reduced in GGT1 KD tumors compared with controls (Supplementary Fig. S5A). We concluded that GGT1 inhibition results in significant reduction in ccRCC cell proliferation in vivo.

Figure 4.

GGT1 is required to maintain ccRCC xenograft growth in vivo. A, Tumor volume measurements for 786O control (Scr) and GGT1 KD subcutaneous xenografts at indicated timepoints. B, Tumor weights of 786O control (Scr) and GGT1 KD subcutaneous xenografts at day 26 postinjection. C, Representative images of hematoxylin and eosin, Ki67, and cleaved caspase 3 IHC from 786O control (Scr) and GGT1 KD xenograft tumors. Arrows indicate positive staining. Scale bar, 100 μm. D, Quantification of Ki67-positive cells per high-power field (HPF) in control (Scr) and GGT1 KD tumors. E, Quantification of cleaved caspase 3–positive cells per HPF in control (Scr) and GGT1 KD tumors. Statistical significance was defined as ***, P < 0.001; n.s., not significant.

Figure 4.

GGT1 is required to maintain ccRCC xenograft growth in vivo. A, Tumor volume measurements for 786O control (Scr) and GGT1 KD subcutaneous xenografts at indicated timepoints. B, Tumor weights of 786O control (Scr) and GGT1 KD subcutaneous xenografts at day 26 postinjection. C, Representative images of hematoxylin and eosin, Ki67, and cleaved caspase 3 IHC from 786O control (Scr) and GGT1 KD xenograft tumors. Arrows indicate positive staining. Scale bar, 100 μm. D, Quantification of Ki67-positive cells per high-power field (HPF) in control (Scr) and GGT1 KD tumors. E, Quantification of cleaved caspase 3–positive cells per HPF in control (Scr) and GGT1 KD tumors. Statistical significance was defined as ***, P < 0.001; n.s., not significant.

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Pharmacologic GSH pathway inhibition decreases ccRCC cell proliferation and increases sensitivity to chemotherapy

Recent studies showed that pharmacologic inhibition of GSH synthesis, using the irreversible GCL inhibitor BSO, delays tumor growth in vivo in ccRCC (27, 28). Treating four different ccRCC cell lines with BSO in vitro, we confirmed that GSH pathway inhibition decreases ccRCC proliferation in a dose-dependent manner (Fig. 5A). BSO treatment and decreased proliferation were also accompanied by a reduction of total intracellular GSH levels (Supplementary Fig. S6A and S6B).

Figure 5.

Pharmacologic GSH pathway inhibition decreases ccRCC cell proliferation and increases sensitivity to chemotherapy. A, Growth curves of ccRCC cell lines (786O, RCC10, A498, and UMRC2) following increasing doses of BSO treatment in vitro. B, Percent of viable cells in 786O and RCC10 control (Scr) and GGT1 KD cells alone, or in combination with cisplatin treatment, measured by Annexin V/PI staining. C, Percent of viable cells in 786O and RCC10 cells after treatment with OU749 alone, or in combination with cisplatin, measured by Annexin V/PI staining. Statistical significance was defined as ***, P < 0.001; **, P < 0.01; *, P < 0.05; n.s., not significant.

Figure 5.

Pharmacologic GSH pathway inhibition decreases ccRCC cell proliferation and increases sensitivity to chemotherapy. A, Growth curves of ccRCC cell lines (786O, RCC10, A498, and UMRC2) following increasing doses of BSO treatment in vitro. B, Percent of viable cells in 786O and RCC10 control (Scr) and GGT1 KD cells alone, or in combination with cisplatin treatment, measured by Annexin V/PI staining. C, Percent of viable cells in 786O and RCC10 cells after treatment with OU749 alone, or in combination with cisplatin, measured by Annexin V/PI staining. Statistical significance was defined as ***, P < 0.001; **, P < 0.01; *, P < 0.05; n.s., not significant.

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Apart from its role in aiding cell proliferation and migration, GGT1-overexpressing cells have been reported to be more resistant to chemotherapeutics, correlating with worse survival rates in several other cancer types (25, 33). Interestingly, cisplatin forms adducts with cysteinyl glycine, a byproduct of GGT1 activity, more rapidly than with GSH (23, 24). This suggests that increased GGT1 activity is responsible for chemotherapeutic resistance along with increased metastatic capacity and proliferation of ccRCC. We therefore tested the combination of GGT1 inhibition and cisplatin treatment in 786O and RCC10 cells, and determined that cells with reduced GSH due to GGT1 depletion exhibit enhanced sensitivity to cisplatin, particularly those with more efficient GGT1 knockdown (shGGT1_2). This could be attributed to the levels of GSH reduction achieved by each knockdown and indicates that only cells with very low GSH levels respond to chemotherapeutics (Fig. 5B). Furthermore, a pharmacologic GGT1 inhibitor (OU749) combined with cisplatin further induced additional cell death relative to either drug used independently (Fig. 5C).

Finally, and most importantly, we compared the efficacy of BSO (20 μmol/L) and cisplatin (3 mg/kg/week) combination versus cisplatin or BSO used as single agents in vivo using 786O subcutaneous xenografts (Fig. 6). As predicted, BSO and cisplatin alone significantly decreased tumor growth compared with vehicle-treated animals (Fig. 6A). For the BSO–cisplatin combination, we noticed a trend to slower tumor growth compared with BSO as a single agent. However, tumor weights measured at the experimental endpoint demonstrated that BSO and cisplatin when combined were more potent than either agent alone (Fig. 6B). Although not statistically significant, mice treated with the BSO–cisplatin combination exhibited a trend to inferior tumor weight compared with each on its own. Of note, cisplatin and BSO–cisplatin treatment showed significant toxicity and mice experienced weight loss (Fig. 6C), necessitating the experiment to be terminated 3 weeks after treatments began. Taken together, these experiments show that ccRCC cells are dependent upon GGT1 for their proliferation, migration, and drug resistance. We therefore propose that pharmacologic inhibition of the GGT1/GSH pathway could synergize with chemotherapeutics for the treatment of all stages of ccRCC tumors.

Figure 6.

Pharmacologic GSH pathway inhibition impairs ccRCC cell growth in vivo. A, Tumor volume measurements for 786O cell subcutaneous xenografts at indicated timepoints. When tumor volume reached 100 mm3, mice were treated with BSO (BSO–20 mmol/L in drinking water), cisplatin (CIS–3 mg/kg/week) or a combination of BSO (20 mmol/L in drinking water), and cisplatin (3 mg/kg/week). B, Tumor weights of 786O cell subcutaneous xenografts at day 41 postinjection. C, Average mouse body weight throughout the time course of the experiment. Statistical significance was defined as ***, P < 0.001; **, P < 0.01; *, P < 0.05; n.s., not significant.

Figure 6.

Pharmacologic GSH pathway inhibition impairs ccRCC cell growth in vivo. A, Tumor volume measurements for 786O cell subcutaneous xenografts at indicated timepoints. When tumor volume reached 100 mm3, mice were treated with BSO (BSO–20 mmol/L in drinking water), cisplatin (CIS–3 mg/kg/week) or a combination of BSO (20 mmol/L in drinking water), and cisplatin (3 mg/kg/week). B, Tumor weights of 786O cell subcutaneous xenografts at day 41 postinjection. C, Average mouse body weight throughout the time course of the experiment. Statistical significance was defined as ***, P < 0.001; **, P < 0.01; *, P < 0.05; n.s., not significant.

Close modal

Delineating tumor metabolism for specific cancers is important to establish their unique signatures of biosynthetic and energy demands. These studies can specifically aid the development of interventions targeted toward a particular malignancy. Moreover, understanding metabolic reprogramming can also provide functional imaging opportunities based on the altered pathways (34). Most forms of kidney cancer show changes in oxygen sensing, the tricarboxylic acid cycle, urea cycle, and metabolism of fatty acids, glucose and glutamine (3, 7, 8, 17). ccRCC can be a particularly aggressive form of cancer that arises from the proximal tubular epithelium (35) and is associated with high mortality rates in its metastatic form. In this study, we analyzed different metabolic changes and found a significant increase in the levels of reduced GSH, and its precursors like cysteine, glutamine, and dipeptides in tumor samples as compared with respective normal adjacent tissues. Moreover, both high GSH and high dipeptide levels were identified as aggressive metabolic signatures in ccRCC (3). These observations led us to hypothesize that the GSH pathway is essential for ccRCC progression. Interestingly, chromophobe renal cell carcinoma (chRCC), which accounts for 5% of all renal tumors, exhibits significantly lower GGT1 levels than normal kidney (28). Nevertheless, GGT1 inhibition also enhances chRCC cell sensitivity to oxidative stress, as well as in normal kidney cells (28). Differences between chRCC and ccRCC tumors, where ccRCCs instead express increased GGT1 levels relative to healthy tissue, are likely due to their genetic, transcriptional, and metabolic disparities. In contrast to ccRCCs, chRCCs have little or no changes in glycolysis and pentose phosphate intermediates relative to normal kidney (28). Therefore, chRCC dependence on GSH salvage pathways might be somewhat different mechanistically from that demonstrated for other human malignancies. In aggregate, increasing evidence indicates that targeting GGT1-dependent GSH conservation represents an appealing area of future investigation.

GGT1 is a transpeptidase whose activity increases the availability of amino acids, primarily cysteine, for intracellular GSH synthesis. GGT1 also plays a critical role in maintaining GSH homeostasis and defense against oxidative stress (23, 25). In liver and obstructive biliary diseases, circulating GGT1 activity has widely been used for diagnosis purposes, as well as an indicator of alcohol consumption (23). In ccRCC, circulating GGT1 has been associated with poor patient prognosis (26). Epidemiologic studies also suggest an association of increased GGT1 activity with a plethora of cardio-metabolic risk factors, including traditional cardiovascular risk factors, metabolic syndrome, systemic inflammation, oxidative stress, and associated mortality in patients (25). Furthermore, high GGT1 levels correlate with poor patient survival in those suffering from lung, prostate, and ovarian cancers (24, 26, 33).

Taking advantage of both TCGA and the CCLE datasets, we highlight the role of GGT1 and the GSH pathway in regulating proliferation, migration, and therapeutic sensitivity of ccRCC cells. More specifically, GGT1 mRNA is overexpressed in ccRCC tumors and cell lines compared with normal kidney tissue and other cancer cell lines. Indeed, GGT1 depletion induces a significant decrease in ccRCC cell growth and colony-forming properties. To further characterize these effects on ccRCC, we assessed apoptotic cell death via Annexin V-PI staining, yet did not observe any significant difference between control and GGT1 KD cells in vitro (data not shown) or in vivo (Fig. 4). However, we cannot exclude other forms of cell death, as inhibition of cystine uptake and GSH depletion have already been described to result in ccRCC cell death through ferroptotic processes (27, 36). Interestingly, Miess and colleagues recently suggested that ccRCC cells are highly dependent upon GSH synthesis to prevent lipid peroxidation and ferroptotic cell death (27). We found that all cells tested are sensitive to reduced GSH levels irrespective of their GGT1 levels. Therefore, besides GGT1, other factors regulate the production and utilization of GSH in ccRCC cells. Moreover, GGT1 inhibition only slightly impacts GSH/GSSG ratios, an indicator of oxidative stress in cells, especially for cells treated with shGGT1. We conclude that GGT1 likely exhibits additional functions, other than those involved in redox balance. GGT1 promotes the use of extracellular GSH and γ-glutamyl peptides as a source of cysteine, which can then be incorporated into proteins (37, 38). Cysteine and GSH metabolism crosstalk are also essential to control amino acid and mTORC1 signaling pathways in mouse embryonic fibroblasts and HepG2 cells (39, 40). Although more work is required to determine how cysteine and GSH metabolism are interconnected, we hypothesize that GGT1 provides a proliferative advantage to ccRCC cells through the regulation of cysteine metabolism, independent of GSH antioxidant functions.

In addition to the known effects on cell death induced by GSH depletion, we investigated the cell cycle as another potential explanation for decreased growth following GGT1 loss, and demonstrated that GGT1 inhibition results in increased numbers of Ki67-negative ccRCC cells. These in vitro observations correlate with our findings in vivo, where GGT1 deficiency significantly decreases the number of Ki67-positive cells, resulting in impaired tumor growth.

Metastatic ccRCC are aggressive tumors, and patient survival rates are extremely low. Hence, inhibiting the invasive capacities of this tumor type is particularly important. Here, we report that GGT1 inhibition significantly decreases ccRCC cell migration, suggesting that GGT1 could be of therapeutic interest for advanced stage patients. Most importantly, GGT1/GSH pathway inhibition enhances the efficacy of standard chemotherapeutic agents such as cisplatin. Inhibition of GSH production through BSO treatment has already been reported to improve the cytotoxicity of mTORC1 inhibitors (41). In addition, ovarian cancer cells overexpressing GGT1 are more resistant to chemotherapies, particularly cisplatin (42) and 5-fluorouracil (43). In line with these data, we show that GGT1 depletion or pharmacologic inhibition can improve the sensitivity of ccRCC cells to chemotherapeutics, and the development of a potent inhibitor of GGT1 represents a new therapeutic strategy. Overall, our findings support the potential of altering the levels of GSH, specifically by GGT1 inhibition, as a promising new treatment for ccRCC.

No potential conflicts of interest were disclosed.

Conception and design: A. Bansal, D.J. Sanchez, N. Skuli, M.C. Simon

Development of methodology: A. Bansal

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): A. Bansal, D.J. Sanchez, V. Nimgaonkar, D. Sanchez, N. Skuli

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): A. Bansal, V. Nimgaonkar, D. Sanchez, N. Skuli, M.C. Simon

Writing, review, and/or revision of the manuscript: A. Bansal, D.J. Sanchez, R. Riscal, N. Skuli, M.C. Simon

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): A. Bansal, M.C. Simon

Study supervision: M.C. Simon

We thank the Simon laboratory for helpful comments and suggestions. This work was supported by NIH grants F31CA206381 (to D.J Sanchez) and P01CA104838 (to M.C Simon).

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

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