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. 2015 Jun 15;75(12):2541-52.
doi: 10.1158/0008-5472.CAN-14-1703. Epub 2015 May 7.

Grade-Dependent Metabolic Reprogramming in Kidney Cancer Revealed by Combined Proteomics and Metabolomics Analysis

Hiromi I Wettersten  1 , A Ari Hakimi  2 , Dexter Morin  3 , Cristina Bianchi  4 , Megan E Johnstone  5 , Dallas R Donohoe  5 , Josephine F Trott  1 , Omran Abu Aboud  1 , Steven Stirdivant  6 , Bruce Neri  6 , Robert Wolfert  6 , Benjamin Stewart  7 , Roberto Perego  4 , James J Hsieh  8 , Robert H Weiss  9
Affiliations

Grade-Dependent Metabolic Reprogramming in Kidney Cancer Revealed by Combined Proteomics and Metabolomics Analysis

Hiromi I Wettersten et al. Cancer Res. .

Abstract

Kidney cancer [or renal cell carcinoma (RCC)] is known as "the internist's tumor" because it has protean systemic manifestations, suggesting that it utilizes complex, nonphysiologic metabolic pathways. Given the increasing incidence of this cancer and its lack of effective therapeutic targets, we undertook an extensive analysis of human RCC tissue employing combined grade-dependent proteomics and metabolomics analysis to determine how metabolic reprogramming occurring in this disease allows it to escape available therapeutic approaches. After validation experiments in RCC cell lines that were wild-type or mutant for the Von Hippel-Lindau tumor suppressor, in characterizing higher-grade tumors, we found that the Warburg effect is relatively more prominent at the expense of the tricarboxylic acid cycle and oxidative metabolism in general. Further, we found that the glutamine metabolism pathway acts to inhibit reactive oxygen species, as evidenced by an upregulated glutathione pathway, whereas the β-oxidation pathway is inhibited, leading to increased fatty acylcarnitines. In support of findings from previous urine metabolomics analyses, we also documented tryptophan catabolism associated with immune suppression, which was highly represented in RCC compared with other metabolic pathways. Together, our results offer a rationale to evaluate novel antimetabolic treatment strategies being developed in other disease settings as therapeutic strategies in RCC.

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Figures

Figure 1
Figure 1. 1. Aerobic glycolysis is grade-dependently upregulated in RCC
Combined proteomics and metabolomics data of human RCC tissue was overlayed onto a stylized KEGG-based pathway diagram. Green, metabolite; orange, enzyme; black dot arrow, metabolism; red arrow, upregulated pathway; blue arrow, downregulated pathway; G6P, glucose-6-phosphate; PEP, F6P, fructose 6-phosphate; phosphoenolpyruvate; OAA, oxaloacetate; GPI, glucose-6-phosphate isomerase; ALDOB, aldolase B; TPI1, triosephosphate isomerase 1; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; PGK1, phosphoglycerate kinase 1; ENO, enolase; PKM, pyruvate kinase; PC, pyruvate carboxylase; AKR1A1, aldo-keto reductase family 1, member A1; LDH, lactate dehydrogenase.
Figure 2
Figure 2. 2. Inhibition of glycolysis attenuates RCC cell viability and lactate production
(A) 786-O (VHL-mut) and Caki-1 (VHL-wt) cells were treated with media at the indicated glucose concentration, or with the indicated concentration of 2-DG in 5 mM glucose media, for 72 hours and then subjected to MTT assays. *P < 0.05 compared to 5 mM glucose or 0 mM 2-DG. Error bars indicate standard deviation. Data are representative of three repeats. (B) 786-O (VHL-mut) and Caki-1 (VHL-wt) cells were treated with glucose depleted media (Glc-) or 2-DG (5 mM) for 24 hours then lactate in the media was measured as described in Materials and Methods. *P < 0.05 compared to control (glucose 5 mM). Error bars indicate standard deviation. Data are representative of three repeats.
Figure 3
Figure 3. 3. Acylcarnitines are increased and β-oxidation is downregulated in RCC
Combined proteomics and metabolomics data of human RCC tissue was overlayed onto a stylized KEGG-based pathway diagram. Green, metabolite; orange, enzyme; black dot arrow, metabolism; red, upregulated pathway; blue arrow, downregulated pathway. ACSL, acyl-CoA synthetase long-chain; PPAR, peroxisome proliferator-activated receptor; CPT, carnitine palmitoyltransferase; HADH, carnitine palmitoyltransferase alpha subunit; HADHA, hydroxyacyl-CoA dehydrogenase; EHHADH, enoyl-CoA, hydratase/3-hydroxyacyl CoA dehydrogenase; SCEH, short-chain enoyl-CoA hydratase; MCAD, medium-chain specific acyl-CoA dehydrogenase; VLCAD, very long-chain specific acyl-CoA dehydrogenase; ACAT, acetyl-CoA acetyltransferase.
Figure 4
Figure 4. 4. The glutamine pathway bolstered the glutathione system
Combined proteomics and metabolomics data of human RCC tissue was overlayed onto a stylized KEGG-based pathway diagram. Levels of metabolites and enzymes were graphed grade dependently. Green, metabolite; orange, enzyme; black dot arrow, metabolism; red arrow, upregulated pathway; blue arrow, downregulated pathway; ROS, reactive oxygen species; GSSG, oxidized glutathione; GSH, glutathione; GPX1, glutathione peroxidase 1; GSTT1, glutathione S-transferase theta 1; GSTO1, glutathione S-transferase omega 1; GSTM3, glutathione S-transferase mu 3; GSTP1, glutathione S-transferase pi 1; GSTA2, glutathione S-transferase alpha 2; GSTK1, glutathione S-transferase kappa 1; GGT5, gamma-glutamyltransferase 5; GABA, gamma-aminobutyric acid; α-KG, α-ketoglutarate; GLS, glutaminase; ACY1, aminoacylase 1; ASS1, argininosuccinate synthase 1.
Figure 5
Figure 5. 5. The TCA cycle is not fed by glycolysis, the FA pathway, or the glutamine pathway in RCC
(A) Combined proteomics and metabolomics data of human RCC tissue was overlayed onto a stylized KEGG-based pathway diagram. Green, metabolite; orange, enzyme; black dot arrow, metabolism; red arrow, upregulated pathway; blue arrow, downregulated pathway; ROS, reactive oxygen species; PC, pyruvate carboxylase; IDH, isocitrate dehydrogenase; GABA, gamma-aminobutyric acid; SDHA, succinate dehydrogenase complex subunit A; SDHB, succinate dehydrogenase complex subunit B., (B) Oxygen consumption rates (OCR) were measured with a Seahorse XF24 Analyzer in 786-O (RCC; top panels), Caki-1 (RCC; lower panels), and NHK (right panel) cells maintained in their growth media. Cells were treated 30 minutes prior to OCR measurement with glucose depleted media (Glc-; left panel), glutamine depleted media (Gln-; right panel), etomoxir (Eto) 50 μM, or 2-DG (middle panel) 5 mM unless stated otherwise. DMSO was used as the vehicle solution for etomoxir and 2-DG treatments. Data are the average OCR from six wells per group and error bars are the standard error of the mean. The data are representative of three repeats.
Figure 6
Figure 6. 6. Tryptophan metabolism favors a grade-dependent increase in immune suppressive metabolites
(A) Combined proteomics and metabolomics data of human RCC tissue was overlayed onto a stylized KEGG-based pathway diagram. Green, metabolite; orange, enzyme; black dot arrow, metabolism; red arrow, upregulated pathway; blue arrow, downregulated pathway; MAO, monoamine oxidase; DDC, dopa decarboxylase; ALDH, aldehyde dehydrogenase; IDO, indoleamine 2,3-dioxygenase; TDO, tryptophan 2,3-dioxygenase. (B) 786-O (VHL-mut) and Caki-1 (VHL-wt) cells were plated in 6-well plates the day before treating with either human IFN-g (50 ng/ml) and/or MTH-trp (100 μM) for four days and immunoblotted with the antibodies indicated. (C) 786-O (VHL-mut) and Caki-1 (VHL-wt) cells were plated in 6-well plates the day before treating with either human IFN-g (50 ng/ml) and/or MTH-trp (100 μM) for three days. The conditioned media was harvested and tryptophan (TRP) and kynurenine (KN) were measured by HPLC and normalized for cell number counted using the cell viability assay kit (EMD Millipore, Billerica, MA) on a MUSE (EMD Millipore, Billerica, MA). Data shown are means (n=3) and standard deviations. *P < 0.05.
Figure 7
Figure 7. 7. Summary of grade-dependent metabolic pathway alterations in RCC
With higher grade, glycolysis was directed towards lactate metabolism at the expense of TCA cycle intermediaries. Fatty acid β-oxidation was decreased, while the glutamine pathway served to attenuate oxidative stress thereby increasing cancer cell survival. Tryptophan was metabolized preferentially to immunosuppressive compounds. Red: increased; blue: decreased.
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