Metabolomics and Metabolic Reprogramming in Kidney Cancer

The tumour microenvironment and metabolism in renal cell carcinoma targeted or immune therapy

Renal cell carcinoma (RCC) is one of the most common tumours of the urinary system, and is insidious and not susceptible to chemoradiotherapy. As the most common subtype of RCC (70-80% of cases), clear cell renal cell carcinoma (ccRCC) is characterized by the loss of von Hippel-Lindau and the accumulation of robust lipid and glycogen. For advanced RCC, molecular-targeted drugs, tyrosine kinase inhibitors (TKIs) and the immune checkpoint inhibitors (ICIs) have been increasingly recommended and investigated. Due to the existence of a highly dynamic, adaptive and heterogeneous tumour microenvironment (TME), and due to the glucose and lipid metabolism in RCC, this cancer may be accompanied by various types of resistance to TKIs and ICIs. With the increased production of lactate, nitric oxide, and other new by-products of metabolism, novel findings of the TME and key metabolic enzymes drived by HIF and other factors have been increasingly clarified in RCC carcinogenesis and therapy. However, there are few summaries of the TME and tumour metabolism for RCC progression and therapy. Here, we summarize and discuss the relationship of the important implicated characteristics of the TME as well as metabolic molecules and RCC carcinogenesis to provide prospects for future treatment strategies to overcome TME-related resistance in RCC.

A cluster of metabolism-related genes predict prognosis and progression of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) has long been considered as a metabolic disease characterized by metabolic reprogramming due to the abnormal accumulation of lipid droplets in the cytoplasm. However, the prognostic value of metabolism-related genes in ccRCC remains unclear. In our study, we investigated the associations between metabolism-related gene profile and prognosis of ccRCC patients in the Cancer Genome Atlas (TCGA) database. Importantly, we first constructed a metabolism-related prognostic model based on ten genes (ALDH6A1, FBP1, HAO2, TYMP, PSAT1, IL4I1, P4HA3, HK3, CPT1B, and CYP26A1) using Lasso cox regression analysis. The Kaplan–Meier analysis revealed that our model efficiently predicts prognosis in TCGA_KIRC Cohort and the clinical proteomic tumor analysis consortium (CPTAC_ccRCC) Cohort. Using time-dependent ROC analysis, we showed the model has optimal performance in predicting long-term survival. Besides, the multivariate Cox regression analysis demonstrated our model is an independent prognostic factor. The risk score calculated for each patient was significantly associated with various clinicopathological parameters. Notably, the gene set enrichment analysis indicated that fatty acid metabolism was enriched considerably in low-risk patients. In contrast, the high-risk patients were more associated with non-metabolic pathways. In summary, our study provides novel insight into metabolism-related genes’ roles in ccRCC.

A new survival model based on ferroptosis-related genes for prognostic prediction in clear cell renal cell carcinoma

In this study, we analyzed the clinical significance of ferroptosis-related genes (FRGs) in 32 cancer types in the GSCA database. We detected a 2-82% mutation rate among 36 FRGs. In clear cell renal cell carcinoma (ccRCC; n=539) tissues from the The Cancer Genome Atlas database, 30 of 36 FRGs were differentially expressed (up- or down-regulated) compared to normal kidney tissues (n=72). Consensus clustering analysis identified two clusters of FRGs based on similar co-expression in ccRCC tissues. We then used LASSO regression analysis to build a new survival model based on five risk-related FRGs (CARS, NCOA4, FANCD2, HMGCR, and SLC7A11). Receiver operating characteristic curve analysis confirmed good prognostic performance of the new survival model with an area under the curve of 0.73. High FANCD2, CARS, and SLC7A11 expression and low HMGCR and NCOA4 expression were associated with high-risk ccRCC patients. Multivariate analysis showed that risk score, age, stage, and grade were independent risk factors associated with prognosis in ccRCC. These findings demonstrate that this five risk-related FRG-based survival model accurately predicts prognosis in ccRCC patients, and suggest FRGs are potential prognostic biomarkers and therapeutic targets in several cancer types.

Exploring serum metabolic markers for the discrimination of ccRCC from renal angiomyolipoma by metabolomics

Aim: The discrimination of renal cell carcinoma from renal angiomyolipoma (RAML) is crucial for the effective treatment of each. Materials & methods: Serum samples were analyzed by nuclear magnetic resonance spectroscopy-based metabolomics and a number of metabolites were further quantified by HPLC-UV. Results: Clear-cell renal carcinoma (ccRCC) was characterized by drastic disruptions in energy, amino acids, creatinine and uric acid metabolic pathways. A logistic model for the differential diagnosis of RAML from ccRCC was established using the combination of serum levels of uric acid, the ratio of uric acid to hypoxanthine and the ratio of hypoxanthine to creatinine as variables with area under the curve of the receiver operating characteristic curve value of 0.907. Conclusion: Alterations in serum purine metabolites may be used as potential metabolic markers for the differential diagnosis of ccRCC and RAML.

Volatilomics Reveals Potential Biomarkers for Identification of Renal Cell Carcinoma: An In Vitro Approach

The identification of noninvasive biomarkers able to detect renal cell carcinoma (RCC) at an early stage remains an unmet clinical need. The recognition that altered metabolism is a core hallmark of cancer boosted metabolomic studies focused in the search for cancer biomarkers. The present work aims to evaluate the performance of the volatile metabolites present in the extracellular medium to discriminate RCC cell lines with distinct histological subtypes (clear cell and papillary) and metastatic potential from non-tumorigenic renal cells. Hence, volatile organic compounds (VOCs) and volatile carbonyl compounds (VCCs) were extracted by headspace solid-phase microextraction (HS-SPME) and analyzed by gas chromatography-mass spectrometry (GC-MS). Multivariate and univariate analysis unveiled a panel of metabolites responsible for the separation between groups, mostly belonging to ketones, alcohols, alkanes and aldehydes classes. Some metabolites were found similarly altered for all RCC cell lines compared to non-tumorigenic cells, namely 2-ethylhexanol, tetradecane, formaldehyde, acetone (increased) and cyclohexanone and acetaldehyde (decreased). Furthermore, significantly altered levels of cyclohexanol, decanal, decane, dodecane and 4-methylbenzaldehyde were observed in all metastatic RCC cell lines when compared with the non-metastatic ones. Moreover, some alterations in the volatile composition were also observed between RCC histological subtypes. Overall, our results demonstrate the potential of volatile profiling for identification of noninvasive candidate biomarkers for early RCC diagnosis.

Targeting the TR4 nuclear receptor-mediated lncTASR/AXL signaling with tretinoin increases the sunitinib sensitivity to better suppress the RCC progression

Renal cell carcinoma (RCC) is one of the most lethal urological tumors. Using sunitinib to improve the survival has become the first-line therapy for metastatic RCC patients. However, the occurrence of sunitinib resistance in the clinical application has curtailed its efficacy. Here we found TR4 nuclear receptor might alter the sunitinib resistance to RCC via altering the TR4/lncTASR/AXL signaling. Mechanism dissection revealed that TR4 could modulate lncTASR (ENST00000600671.1) expression via transcriptional regulation, which might then increase AXL protein expression via enhancing the stability of AXL mRNA to increase the sunitinib resistance in RCC. Human clinical surveys also linked the expression of TR4, lncTASR, and AXL to the RCC survival, and results from multiple RCC cell lines revealed that targeting this newly identified TR4-mediated signaling with small molecules, including tretinoin, metformin, or TR4-shRNAs, all led to increase the sunitinib sensitivity to better suppress the RCC progression, and our preclinical study using the in vivo mouse model further proved tretinoin had a better synergistic effect to increase sunitinib sensitivity to suppress RCC progression. Future successful clinical trials may help in the development of a novel therapy to better suppress the RCC progression.

Field cancerization therapy with ingenol mebutate contributes to restoring skin-metabolism to normal-state in patients with actinic keratosis: a metabolomic analysis

Actinic keratosis (AK) is a skin premalignant lesion, which progresses into squamous cell carcinoma (SCC) if left untreated. Ingenol mebutate gel is approved for local treatment of non-hyperkeratotic, non-hypertrophic AK; it also has the potential to act as a field cancerization therapy to prevent the progression of AK to SCC. To gain better insights into the mechanisms of ingenol mebutate beyond the mere clinical assessment, we investigated, for the first time, the metabolome of skin tissues from patients with AK, before and after ingenol mebutate treatment, with high-resolution magic angle spinning nuclear magnetic resonance spectroscopy. The metabolomic profiles were compared with those of tissues from healthy volunteers. Overall, we identified a number of metabolites, the homeostasis of which became altered during the process of tumorigenesis from healthy skin to AK, and was restored, at least partially, by ingenol mebutate therapy. These metabolites may help to attain a better understanding of keratinocyte metabolism and to unmask the metabolic pathways related to cell proliferation. These results provide helpful information to identify biomarkers with prognostic and therapeutic significance in AK, and suggest that field cancerization therapy with ingenol mebutate may contribute to restore skin metabolism to a normal state in patients with AK.

HSP60 silencing promotes Warburg-like phenotypes and switches the mitochondrial function from ATP production to biosynthesis in ccRCC cells

HSP60 is a major mitochondrial chaperone for maintaining mitochondrial proteostasis. Our previous studies showed that HSP60 was significantly downregulated in clear cell renal cell carcinoma (ccRCC), the most common type of kidney cancer characterized by the classic Warburg effect. Here, we analyzed datasets in The Cancer Genome Atlas and revealed that higher HSP60 expression correlated with better overall survival in ccRCC patients. We also stably knocked down or overexpressed HSP60 in ccRCC cells to investigate the effects of HSP60 expression on the transition between oxidative phosphorylation and glycolysis. We confirmed that HSP60 knockdown increased cell proliferation, whereas its overexpression decreased cell growth. Proteomics and metabolomics revealed that HSP60 knockdown promoted Warburg-like phenotypes with enhanced glycolysis and decreased mitochondrial activity. Consistent with this finding, isotope tracing showed that the metabolic flow from glycolysis to TCA was reduced. However, HSP60 silencing enhanced mitochondrial functions in glutamine-directed biosynthesis with increased flow in two parts of the TCA cycle: Gln→αKG→OAA→Asp and Gln→αKG→ISO→acetyl-CoA, resulting in elevated de novo nucleotide synthesis and lipid synthesis. Proteomic analysis indicated that HSP60 silencing activated NRF2-mediated oxidative stress responses, while glutamate generated from glutamine increased glutathione synthesis for quenching excessive reactive oxygen species (ROS) produced upon elevated cell growth. We further found that HSP60 silencing activated the MEK/ERK/c-Myc axis to promote glutamine addiction, and confirmed that ccRCC cells were susceptible to oxidative stress and glutaminase inhibition. Collectively, our data show that HSP60 knockdown drives metabolic reprogramming in ccRCC to promote tumor progression and enhances mitochondrial-dependent biosynthesis.

Gamma-Glutamyltransferase 1 Promotes Clear Cell Renal Cell Carcinoma Initiation and Progression

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.

Metabolomic insights into pathophysiological mechanisms and biomarker discovery in clear cell renal cell carcinoma

INTRODUCTION

Clear cell renal cell carcinoma (ccRCC) is a metabolic disease, of which the incidence rate is increasing worldwide. Renal carcinoma is characterized by mutations in target genes involved in metabolic pathways. Metabolic reprogramming covers different processes such as aerobic glycolysis, fatty acid metabolism, and the utilization of tryptophan, glutamine, and arginine. In the era of the multi-omics approach (with integrated transcriptomics, proteomics, and metabolomics), discovering biomarkers for early diagnosis is gaining renewed importance. Areas covered: In this review, we discuss the pathophysiological mechanisms underlying ccRCC metabolic reprogramming. In addition, we describe the emerging metabolomics-based biomarkers differentially expressed in ccRCC and the rationale for the recently developed drugs specifically targeting the ccRCC metabolome. Expert opinion: A number of metabolic pathways will be explored in future years, and many of these pathways are potential therapeutic targets and may serve as diagnostic and prognostic biomarkers of ccRCC.

Integrated multi-omics characterization reveals a distinctive metabolic signature and the role of NDUFA4L2 in promoting angiogenesis, chemoresistance, and mitochondrial dysfunction in clear cell renal cell carcinoma

An altered metabolism is involved in the development of clear cell - renal cell carcinoma (ccRCC), and in this tumor many altered genes play a fundamental role in controlling cell metabolic activities. We delineated a large-scale metabolomic profile of human ccRCC, and integrated it with transcriptomic data to connect the variations in cancer metabolism with gene expression changes. Moreover, to better analyze the specific contribution of metabolic gene alterations potentially associated with tumorigenesis and tumor progression, we evaluated the transcription profile of primary renal tumor cells. Untargeted metabolomic analysis revealed a signature of an increased glucose uptake and utilization in ccRCC. In addition, metabolites related to pentose phosphate pathway were also altered in the tumor samples in association with changes in Krebs cycle intermediates and related metabolites. We identified NADH dehydrogenase (ubiquinone) 1 alpha subcomplex 4-like 2 (NDUFA4L2) as the most highly expressed gene in renal cancer cells and evaluated its role in sustaining angiogenesis, chemoresistance, and mitochondrial dysfunction. Finally, we showed that silencing of NDUFA4L2 affects cell viability, increases mitochondrial mass, and induces ROS generation in hypoxia.

Hyperpolarized 13C magnetic resonance imaging, using metabolic imaging to improve the detection and management of prostate, bladder, and kidney urologic malignancies

Approximately 25% of the 2 million new cancer diagnoses in the United States in 2018 were comprised of malignancies of the urogenital system. Of these cancers, 75% occurred in the kidney/renal pelvis, prostate, and urinary bladder. Early diagnosis is beneficial to long-term survival. Currently, urologists rely heavily on computed tomography (CT), magnetic resonance imaging (MRI), ultrasound (US), and positron emission tomography (PET) to both diagnose and offer prognoses, but these techniques are limited in their resolution and are more effective when cancers have reached macroscopic size in later stages. Recent developments in cancer metabolomics have revealed that cancerous cells preferentially upregulate specific metabolic pathways as a means of conserving their resources and maximizing their growth potential. This has opened a new avenue for early diagnosis with much higher resolution, reliability, and accuracy through ¹³C hyperpolarized MRI. Preferential cancer pathways can be elucidated through this technique using ¹³C-labeled molecules utilized for energy generation and tumor growth. As these pathways are identified, targeted therapies are being designed to inhibit these pathways to allow for treatment that is cytotoxic to malignant cells but preserves native cells. In this paper, we review the current understanding of urologic cancer metabolomics, specifically in the kidney, prostate, and bladder. We will review the basic physics of MRI and demonstrate how hyperpolarized ¹³C MRI offers an innovative solution to early diagnosis as well as creates novel avenues for more targeted therapy.

CAV2 promotes the growth of renal cell carcinoma through the EGFR/PI3K/Akt pathway

Background

Caveolin-2 (CAV2) is reported to have an important role in cancer. The following study investigated the expression and function of CAV2 in kidney cancer in vitro and in vivo.

Materials and methods

Real-time PCR, immunohistochemistry and Western blotting analysis were used to determine CAV2, epidermal growth factor receptor (EGFR), phosphatidylinositol 3-kinase (PI3K) and protein kinase B (Akt) in kidney cancer cell line OS-RC-2 and clinical specimens. The role of CAV2 in maintaining kidney cancer malignant phenotype was examined by wound healing assay, Matrigel invasion assays and mouse orthotopic xenograft model.

Results

Higher expression of CAV2 was found in renal cell carcinoma tissue compared to normal tissue. Furthermore, increased expression of CAV2 was associated with cancer progression. Also, silencing of CAV2 inhibited the proliferation, migration and invasion, as well as the expression of EGFR, PI3K and p-Akt in OS-RC-2 cells in vitro, and OS-RC-2 xenograft growth in vivo.

Conclusion

Our results revealed that CAV2 promotes the growth of renal cell carcinoma through EGFR/PI3K/Akt pathway.