Keywords

FormalPara Key Points

  • Different oncogenic mutations lead to various metabolic phenotypes in renal cell carcinomas (RCC).

  • Loss of the von Hippel-Lindau (VHL) tumor-suppressor gene results in metabolic alterations, including shifts toward aerobic glycolysis in RCC.

  • Fumarate hydratase mutations result in an increase in aerobic glycolysis in RCC.

  • The upregulation of glycolysis enzymes is correlated with high-grade RCC.

  • An increase in glutathione (GSH)/glutathione disulfide (GSSG) ratio protects RCC against oxidative stress in a grade-dependent manner.

  • Metabolic spatial heterogeneity can be induced by both gene-dependent and independent processes.

  • Metabolic intratumoral heterogeneity explains the failure of monotherapy and necessitates the need for personalized and/or combination therapies for RCC.

1 Introduction

According to data from the American Cancer Society, cancer is one of the deadliest health problems globally. Annually, renal cell carcinoma (RCC) causes more than 100,000 deaths worldwide [1,2,3,4], posing an urgent need to develop effective treatments to increase patient survival outcomes. New therapies are expected to address a major factor contributing to cancer’s resistance to standard therapies: oncogenic heterogeneity. Gene expression can vary tremendously among different types of cancers, different patients of the same tumor type, and even within individual tumors; various metabolic phenotypes can emerge, making single-therapy approaches insufficient. Novel strategies targeting the diverse metabolism of cancers aim to overcome this obstacle. Though some have yielded positive results, it remains a challenge to uncover all of the distinct metabolic profiles of RCC. In the quest to overcome this obstacle, the metabolic oriented research focusing on these cancers has offered freshly new perspectives, which are expected to contribute heavily to the development of new treatments.

2 Different Oncogenic Mutations Lead to Different Metabolic Phenotypes in RCC (Fig. 1)

Renal cell carcinoma (RCC), or hypernephroma, is the most common type of kidney cancer in adults, responsible for approximately 90–95% of all cases. RCC originates from the network of convoluted tubules of the nephron [5] and consists of diverse histological subtypes, each with unique sets of metabolic rearrangements that can be traced back to gene alterations [6, 7]. These genomic abnormalities provide cancer cells with the advantageous abilities to adapt to the limitations of their microenvironments and meet the demands of rapid and deleterious cell division.

Fig. 1
figure 1

Heterogeneous metabolic phenotypes in renal cell carcinoma as a result of different oncogenic mutations. AKT protein kinase B, AMPK AMP-activated protein kinase, ePC ether-type phosphatidylcholine, ePE ether type, FH fumarate hydratase, G6P glucose-6-phosphate, GLUT 2 glucose transporter 2, GSH glutathione, HIF-1α hypoxia-inducible factor 1-alpha, mTOR mammalian target of rapamycin, PEP phosphoenolpyruvic acid, ROS reactive oxygen species, SM sphingomyelin, TCA cycle tricarboxylic acid cycle

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2.1 Loss of the von Hippel-Lindau Tumor-Suppressor Gene Results in Metabolic Alterations Including Shifts Toward Aerobic Glycolysis in RCC

Loss of the von Hippel-Lindau (VHL) tumor-suppressor gene is the most prominent genetic alteration in RCC, commonly associated with over 80% of clear-cell renal cell carcinoma (ccRCC) tumors [8, 9]. The protein product of VHL facilitates the degradation of hypoxia-inducible factor (HIF) [10]. Thus, the loss of VHL leads to the accumulation of HIF-1α and the constitutive activation of hypoxia-inducible genes, even in oxygenated conditions. This includes the enhanced expressions of glucose transporter 2 (GLUT2), hexokinase 2 (HK2), and lactate dehydrogenase A (LDHA), which are keys to the metabolic shift towards aerobic glycolysis in tumors with this genotype [11, 12]. In fact, enhanced HIF-1α activity is thought to mediate the Warburg effect in RCC [13, 14]. Moreover, a study by Gill et al. found that HIF upregulation led to increases in glucose and amino acid uptake, lipogenesis, and augmentation of glycolysis through upregulation of MET protein expression and subsequent phosphatidylinositol 3-kinase (PI3K)/Akt signaling pathway activation [14,15,16].

In addition, pentose phosphate shunt dependence, increases in glutamine transport, and fatty acid production all have been documented as VHL-associated metabolic alterations in ccRCC [17]. The increased activity of the pentose phosphate pathway (PPP) plays a significant role in protecting cancer cells from oxidative stress as this pathway generates NADPH and enables the maintenance of glutathione levels [13]. The Consortia of The Cancer Genome Atlas Research Network revealed that upregulation of PPP genes (G6PH, PGLS, TALDO, and TKT), fatty acid synthesis genes (ACC and FASN), and PI3K pathway-enhancing genes (MIR21) correlated with worse survival. In contrast, upregulation of AMP-activated protein kinase (AM PK) complex genes, multiple Krebs cycle genes, and PI3K pathway inhibitors (phosphatase and tensin homolog deleted in chromosome 10 (PTEN), tuberous sclerosis 2 (TSC2)) correlated with better survival [17].

2.2 Fumarate Hydratase Mutations Result in an Increase in Aerobic Glycolysis in RCC

Studies by Tong et al. indicated that RCC cells carrying inactivated fumarate hydratase (FH), a tricarboxylic acid (TCA) cycle enzyme, demonstrated metabolic changes that were distinct from other genetically defined RCC, such as an increase in aerobic glycolysis and advanced tumorigenicity. Thus, fumarate hydratase-deficient kidney cancer has low oxygen consumption rates as well as low mitochondrial complex I activities [18, 19]. In addition to having a glycolytic shift, FH-deficient kidney tumors and cell lines from patients with hereditary leiomyomatosis and RCC also exhibited decreased levels of AMPK, a key metabolic regulator. Glycolytic upregulation allows the cells to adapt to growth demands by generating NADPH, acetyl-CoA, and precursors for ribose, protein, and fatty acid biosynthesis through reduced AMPK signaling. Furthermore, another study by Massari et al. demonstrated that intracellular augmentation of fumarate has an inhibitory effect on HIF prolyl hydroxylase (PHD) and consequently inhibited the activity of the VHL ubiquitination complex, which, in turn, led to the upregulation of HIF-target genes (VEGF and GLUT1) in a VHL-independent manner by stabilizing HIF1a [20]. On the other hand, intracellular reactive oxygen species (ROS) accumulation under glycolysis can also result in HIF1a stabilization [21].

Fig. 2
figure 2

Spatial and temporal intratumoral heterogeneity in renal cell carcinoma. Gal galactose, GSH glutathione, GSSG glutathione disulfide, Man mannose, MCFAs medium-chain fatty acids

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LDHA inhibition has shown promise against FH-deficient RCC cells in vitro and in vivo [22] and other cancers [23,24,25,26]. Metformin, an antidiabetic medication, was reported to activate AMPK and inhibit RCC growth in vitro and in vivo [27].

3 Metabolic Signatures of RCC

3.1 Metabolic Differences Between Normal Renal Cells and RCC

To compensate for the high demands of energy and biosynthetic macromolecules for proliferation, RCC cells change their metabolic phenotypes from that of normal renal cells to satisfy the demands. This leads to the different metabolic signatures of RCC cells as compared to normal renal cells. One of the metabolic signatures presenting in RCC cells found by Saito et al. is the decrease in the level of phosphatidylethanolamine (PE) in RCC cells as compared to normal cells [28]. PE is one of the most abundant glycerophospholipids in eukaryotes and plays a crucial role in autophagy, cell division, and protein folding and acts as a precursor for synthesizing phosphatidylcholine (PC), phosphatidylserine (PS) N-acylethanolamine (NAE) [29,30,31,32]. Furthermore, the study by Saito et al. shows that increased PE, which is induced by ethanolamine, inhibits RCC cell proliferation [28]. Low levels of PE inhibit cell apoptosis, which explains why the downregulation of PE benefits RCC cells. The study also found that increases in ether-type PE (ePE) and ether-type phosphatidylcholine (ePC) are associated with ccRCC metastasis [28].

Interestingly, other studies showed that there is an upregulation of the fetal isoform of pyruvate kinase, isoform M2 (PKM2), across all grades of RCC, suggesting that tumor cells utilize different enzymes from those found in normal tissue to enhance their growth [33, 34].

Moreover, another metabolic feature of RCC is the decrease of sphingomyelin (SM), an essential component of the plasma membrane that regulates the formation of lipid microdomains through interacting with cholesterol and glycerophospholipids [28, 35]. A high level of SM was reported to make the cells more vulnerable to apoptosis [36].

In addition to the metabolic signatures of RCC reported by Saito et al., the study by Catchpole et al. found that the upregulation of fatty acid levels was potentially linked to the metastatic stage of the malignancy [37]. The high fatty acid levels were the results of an increase in de novo fatty acid synthesis and/or a decrease in fatty acid oxidation, which often occurred during the invasive and metastatic stage of RCC [37, 38]. Another compound with high concentration, α-tocopherol, was found in RCC and ovarian cancer to protect tumor cells against oxidative stress [37, 39].

Another interesting metabolic signature in RCC cells is related to amino acid metabolism. Specifically, while arginosuccinate synthase 1 (ASS1) is known to play an important role in the urea cycle via ammonia detoxification through the conversion of citrulline to arginine [40], the study by Yoon et al. revealed an absence or decrease of ASS1 in ccRCC; therefore, arginine was identified as an auxotrophic marker for ccRCC [41]. With the use of proteomics, another study by Perroud et al. similarly demonstrated the downregulation of ASS1 across all the grades of ccRCC [34]. Metabolic profiling using metabolomics technologies [42] has revealed different key metabolic phenotypes of RCC and identified potential targets for new treatments for RCC patients.

3.2 Temporal Impact of RCC Metabolism (Fig. 2)

Using the Fuhrman grading system, Wettersten et al. demonstrated that different grades of RCC were associated with different biochemical processes that have distinctive and prominent metabolic reprogramming, which is supported by the observation of clinically distinguishable features within various tumor grades [43]. In addition, Kang et al. confirmed the metabolic reprogramming in ccRCC by demonstrating the stage-dependent alteration in the expression of solute carriers (SLCs) [44]. SLCs have an important role in transmembrane transportation of specific metabolic substrates, including inorganic ions, nucleotides, amino acids, fatty acids, and sugars [45].

Using a combination of proteomics and metabolomics analysis, Wettersten et al. correlated increasing amounts of metabolites in the aerobic glycolysis pathway, including glucose, glucose-6-phosphate, and fructose-6-phosphate, with higher tumor grade. Likewise, an indication that glucose metabolism is reprogrammed to the lactate fermentation pathway, especially in advanced disease, is supported by the grade-dependent upregulation of lactate [43]. Consistently, a study by Hakimi et al. reported a more than twofold downregulation of citrate concentration in high-stage tumors [46] that may contribute to a reduction in oxidative phosphorylation capacity. However, in a study conducted by Perroud et al., the correlation of the upregulation of phosphoglycerate kinase 1 (PGK1) and grade 1 and 2 tumors is debatable [34]. On the other hand, Hakimi et al. showed that high levels of galactose and mannose were associated with an advanced stage of tumor progression [46].

A study by Horiguchi et al. first revealed the correlation between fatty acid synthase expression and high grade and metastasis of RCC [47]. On the other hand, Wettersten et al. found a broad reduction in shorter chain free fatty acid (FFA) oxidation in high-grade tumors, whereas there was an increase in carnitine and acylcarnitine levels in all grades of RCC. In accordance with this finding, Hakimi et al. discovered in high-stage tumors a reduction in cis-aconitate and medium-chain fatty acids [43, 46]. Furthermore, Xiao et al. showed that genes related to fatty acid β-oxidation enzymes, EHHADH (3-hydroxyacyl CoA dehydrogenase and enoyl-CoA hydratase) and ACADM (medium-chain acyl-CoA dehydrogenase), were simultaneously downregulated at the mRNA and protein levels in opposite proportion to stages of ccRCC [48].

Glutathione (GSH)/glutathione disulfide (GSSG) ratio is an important indicator of oxidative stress. Wettersten et al. revealed that this ratio is grade dependent and consistent with the downregulation of the catabolic enzymes responsible for utilizing glutamine and glutamate in the TCA and urea cycles, indicating a protective role of glutamine reprogramming against oxidative stress in high-grade tumors [43, 49]. Similarly, upregulation of the majority of metabolites involved in the glutathione synthesis such as cysteine, γ-glutamyl cysteine (GLU-CYS), and GSH was observed by Hakimi et al. in a stage-dependent manner [46]. Furthermore, they demonstrated that methionine augmentation at higher tumor stages could be related to the upregulation of glutathione metabolism. In fact, the glutathione regeneration pathway is carried out by homocysteine being converted to cysteine via cystathionine [50].

Interestingly, Hakimi et al. found a grade-dependent increase in the level of methylthioadenosine (MTA). MTA is a downstream product of the polyamine biosynthetic pathway, implying that alterations in the polyamine pathway are correlated to tumor progression [46]. MTA is also part of the methionine and adenine salvage pathway, where phosphorylation of MTA via methylthioadenosine phosphorylase (MTAP) leads to the regeneration of adenine and methionine [51]. Using metabolomic approaches, Xu et al. recently identified a stage-dependent decrease in the expression of MTAP that consequently resulted in the accumulation of MTA in RCC cells [52].

3.3 Intratumoral Heterogeneity of RCC (Fig. 2)

3.3.1 Gene Independence

While intratumoral genetic heterogeneity has been extensively investigated in ccRCC [53, 54], only a small number of recent studies has documented the regional variations in metabolic patterns [55,56,57]. Specifically, mutations of SET domain containing 2 (SETD2), PTEN, and lysine-specific histone demethylase (KDM5C) were found within the same tumor, suggesting that convergent phenotypic evolution and mutations of VHL were ubiquitously detected by multi-region sequencing in all analyzed regions [54]. Using global metabolomics analyses, Okegawa et al. investigated the heterogeneity of intratumoral metabolic profile and gene mutations in multiple regions of a single primary RCC tumor. Two major metabolically different tumor clusters, metabolic cluster 1 (MC1) and metabolic cluster 2 (MC2), were identified among 32 spatially separated sections of the tumor tissue. They observed an upregulation of the glycolysis-PPP, glutathione, and amino acids in the MC1 region as opposed to the downregulation of glycolysis-PPP metabolites and glutathione (reduced) in MC2 region. They also showed that the MC2 region had elevated levels of pyruvate, cystine, and 2-oxobutyric acid. This suggested that tumor cells are dependent on the presence of pyruvate in MC2 regions for growth stimulation, which may make pyruvate metabolism an ideal therapeutic target [55]. Importantly, they showed that the Warburg-like effect is present in all tumor sites without any correlation to the status of the VHL gene. Ultimately, the clear intratumoral metabolic heterogeneity identified within a single tumor may contribute to treatment resistance [56, 57]. In contrast, an almost uniform pattern of lipid profile was observed across the samples [55, 58]. Interestingly, the study also showed no correlation between the mutational status of genes and metabolic patterns, suggesting that other factors, such as noncanonical metabolic flux, tumor microenvironment, and epigenetics, may regulate the metabolic phenotype [55].

Accumulating evidence from various cancer studies suggests the important role of long noncoding RNAs (lncRNAs) in different cellular processes, including metabolism [59,60,61] through regulation of gene expression at the epigenetic level [62, 63]. Specifically, a study by Li et al. found intertumoral heterogeneity of lncRNAs in ccRCC that can contribute to the regulation of the HIF-1 signaling pathway [64].

Using hyperpolarized carbon-13 (13C) magnetic resonance imaging (HP-MRI) technique, Tran et al. noted the intertumoral heterogeneity of pyruvate delivery, pyruvate-to-lactate metabolic conversion, and ratio of lactate to pyruvate across the RCC but did not investigate whether this heterogeneity is gene dependent or not [65].

Using Dixon-based MRI technique, Zhang et al. demonstrated the correlation between fat fraction and intratumoral heterogeneity of metabolites; however, the heterogeneity was more prominent between different tumor types [66].

3.3.2 Gene Dependence

Using [18F] fluorodeoxyglucose (FDG) and positron-emission tomography (PET)/MR imaging, Brooks et al. also demonstrated that the presence of glycolytic enzyme FBP1, higher levels of glucose transporter GLUT1, and lower expression of FBP1 and HIF-1α transcription factor led to regional variation in metabolic heterogeneity. This study revealed an association between [18F]FDG avidity and distinct patterns of metabolic genes and protein expression. The [18F] FDG-avid region had a lower expression of FBP1 and HIF1a and higher expression of glucose transporter GLUT1, which could be related to a higher metabolic activity supported by boosting glucose uptake [22].

Polybromo-1 (PBRM1) gene is one of the major subunits of PBAF (polybromo-associated BRG1 or BRM-associated factors). Loss of its expression is considered as another common mutation in tumor-suppressor gene in ccRCC, besides VHL [67, 68]. Interestingly, Chowdhury et al. demonstrated that re-expression of PBAF in a PBAF-deficient ccRCC could lead to the reversion of several important metabolic signatures in RCC, including glucose and cholesterol metabolism [69]. Using tissue microarray (TMA)-based immunohistochemistry from each tumor, a study by Jiang et al. revealed different expressions of PBRM1, AT-rich interaction domain 1A (ARID1A), SETD2, brahma-related gene 1 (BRG1), and brahma gene (BRM) among 160 ccRCCs, indicating high intratumoral heterogeneity of PBRM1 expression and its associated proteins of the same tumor [70].

4 RCC Therapy

The current standard frontline therapies for metastatic RCC are largely VEGFR inhibitors, such as sunitinib and sorafenib. However, about 20–30% of patients do not respond to these therapies, and among those, nearly all the patients become resistant to these drugs [71].

Activation of the mammalian target of rapamycin (mTOR), a member of PI3K-related kinases, through VEGF signaling pathways, can lead to protein synthesis and energy production in RCC [72]. Although a variety of agents have been investigated to target the mTOR pathway, only recently three mTOR inhibitors have been approved as second-line therapy in patients with RCC: temsirolimus (Torisel®–CCI-779, 4), everolimus or rad001 (Afinitor®, 4a), and sirolimus (Rapamycin®, 4b) [73, 74]. Interestingly, a study by Li et al. revealed that mTOR inhibitor (everolimus) treatment could overcome the Warburg effect via mTOR pathway blocking and HIF1α expression inhibition [75]. Recent work by Gameiro et al. found that loss of VHL rendered RCC cells sensitive to glutamine deprivation [76]. In line with this finding, they found that systematic treatment with glutaminase inhibitors suppressed ccRCC growth both in vitro and in vivo. Other metabolic targeting therapies for RCC include mitochondrial inhibition by auraptene [77] and GLUT1 inhibition by STF-3 [78].

5 Conclusion

Metabolic spatial and temporal heterogeneity represents one of the main mechanisms behind the high therapy resistance of RCC. Recent findings suggest that initial monotherapy failure can be associated with subclonal variation in metabolic heterogeneity. Targeting several metabolic pathways is the key strategy for effective therapy [79, 80]. It is also important to mention that metabolic phenotypic heterogeneity is regulated through both gene-dependent and gene-independent manners. Taken together, RCC treatment has a variety of challenges posed by intratumoral metabolic heterogeneity, highlighting the need for the further development of novel approaches to identify clonally dominant metabolic targets for the future development of effective therapies for RCC.