The ‘Achilles Heel’ of Metabolism in Renal Cell Carcinoma: Glutaminase Inhibition as a Rational Treatment Strategy

Hoerner, Christian R.; Chen, Viola J.; Fan, Alice C.

doi:10.3233/kca-180043

Cited by 59 publications

(51 citation statements)

References 184 publications

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“…We also found argininosuccinate synthase 1 (ASS1) expression was downregulated, which can increase aspartate availability and is associated with poor prognosis in multiple cancers 34,35 . In RCC, an increase in aspartate levels can promote cell proliferation due to its role in nucleotide synthesis 36 . In KICH, genes related to the aspartate-malate shuttle were also upregulated suggesting that aspartate can act as an anaplerotic source for the TCA cycle.…”

Section: Discussionmentioning

confidence: 99%

Network-based metabolic characterization of renal cell carcinoma

Pandey

Lanke

Vinod

2020

Sci Rep

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An emerging hallmark of cancer is metabolic reprogramming, which presents opportunities for cancer diagnosis and treatment based on metabolism. We performed a comprehensive metabolic network analysis of major renal cell carcinoma (Rcc) subtypes including clear cell, papillary and chromophobe by integrating transcriptomic data with the human genome-scale metabolic model to understand the coordination of metabolic pathways in cancer cells. We identified metabolic alterations of each subtype with respect to tumor-adjacent normal samples and compared them to understand the differences between subtypes. We found that genes of amino acid metabolism and redox homeostasis are significantly altered in RCC subtypes. Chromophobe showed metabolic divergence compared to other subtypes with upregulation of genes involved in glutamine anaplerosis and aspartate biosynthesis. A difference in transcriptional regulation involving HIF1A is observed between subtypes. We identified E2F1 and FOXM1 as other major transcriptional activators of metabolic genes in RCC. Further, the co-expression pattern of metabolic genes in each patient showed the variations in metabolism within RCC subtypes. We also found that co-expression modules of each subtype have tumor stage-specific behavior, which may have clinical implications. Major biological processes namely reproduction, development, wound healing and tissue regeneration require cell proliferation. Cells proliferate in response to growth-promoting stimulus however, under adverse conditions they move into a reversible, non-proliferating state termed quiescence. Cells gauge the strength of proliferative and anti-proliferative signals through multiple molecular players to make cellular decisions. Cancer is a proliferative disease that arises when the regulatory control of quiescence-proliferation reversible transition is lost. An emerging hallmark of cancer is metabolic reprogramming, which helps to meet the energy demand for cell growth and division. Initial studies by Otto Warburg pointed to aerobic glycolysis, however recent advances have started to reveal other metabolic alterations and plasticity of cancer metabolism 1,2. Understanding the differences in metabolism between normal and cancer cells can shed light on the adaptations that promote disease progression and may also facilitate the identification of therapeutic metabolic targets. Mutations or epigenetic alterations in cancer can influence the expression of metabolic genes. Studies have explored transcriptome data of different cancers to understand the transcriptional dysregulation of metabolic genes. These studies are based on data generated by The Cancer Genome Atlas (TCGA) program. A pan-cancer analysis of different cancer types found a convergent metabolic landscape with upregulated nucleotide synthesis and downregulated mitochondrial metabolism as the main features 3. Rosario et al. 4 analyzed the gene expression of metabolic pathways in Kyoto Encyclopedia of Genes and Genomes (KEGG) and found that pentose and glucuronate inter...

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Section: Discussionmentioning

confidence: 99%

Network-based metabolic characterization of renal cell carcinoma

Pandey

Lanke

Vinod

2020

Sci Rep

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“…Additionally, some tumour cells in vitro are unable to survive in the absence of an exogenous supply of glutamine . Consequently, cells develop a metabolic strategy to provide a source of carbon other than glucose to derive the carbon that is necessary to fuel the tricarboxylic acid (TCA) cycle . Recently, it has been shown that glutamine can enhance cancer progression independently of its metabolic role, as it can act as a signalling agent to activate the transcription factor STAT3, which is required to mediate the proliferative effects of glutamine on cancer cells .…”

Section: Glutamine Metabolism and Addiction In Cancermentioning

confidence: 99%

“…8,10 Consequently, cells develop a metabolic strategy to provide a source of carbon other than glucose to derive the carbon that is necessary to fuel the tricarboxylic acid (TCA) cycle. 11 Recently, it has been shown that glutamine can enhance cancer progression independently of its metabolic role, as it can act as a signalling agent to activate the transcription factor STAT3, which is required to mediate the proliferative effects of glutamine on cancer cells. 12 Furthermore, glutamine can indirectly activate other signalling pathways, such as the mammalian target of rapamycin complex 1 (mTORC1) pathway; mTORC1 is a critical kinase that regulates cell growth and proliferation, as glutamine-derived a-KG is required for GTP loading of RagB and subsequent activation of mTORC1.…”

Section: Glutamine Metabolism and Addiction In Cancermentioning

confidence: 99%

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The role of glutaminase in cancer

et al. 2020

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Increased glutamine metabolism (glutaminolysis) is a hallmark of cancer and is recognised as a key metabolic change in cancer cells. Breast cancer is a heterogeneous disease with different morphological and molecular subtypes and responses to therapy, and breast cancer cells are known to rewire glutamine metabolism to support survival and proliferation. Glutaminase isoenzymes (GLS and GLS2) are key enzymes for glutamine metabolism. Interestingly, GLS and GLS2 have contrasting functions in tumorigenesis. In this review, we explore the role of glutaminase in cancer, primarily focusing on breast cancer, address the role played by oncogenes and tumour suppressor genes in regulating glutaminase, and discuss current therapeutic approaches to targeting glutaminase.

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“…In addition, GLS2 is a druggable metabolic node for breast cancer. In RCC, metabolic reprogramming is closely associated with disease progression and metastasis; as a result, glutaminase inhibitors are a novel strategy for RCC treatment [32]. Although GLS2 is predominantly found in liver tissue, its function as a tumor suppressor in RCC requires further discussion.…”

Section: Discussionmentioning

confidence: 99%

Loss of GLS2 function is essential for obtaining oncogenic functions and promotes the progression of clear cell renal cell carcinoma.

Sun¹,

Tian²,

Zhao³

et al. 2020

Preprint

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Background The incidence of RCC has drastically increased in recent years. The large intratumor heterogeneity of RCC, especially ccRCC, usually leads to treatment failure. In addition, single biomarkers have a limited ability to predict prognosis. Therefore, we performed this study to select variables and provided a simple but efficient way to predict prognosis. Method Three studies from the GEO database were involved in the selection of DEGs. A total of 840 RCC patients and 524 ccRCC patients from the TCGA database were involved in the prognostic analyses. Nomograms based on the Cox regression model were used to select variables to predict the prognosis, and GSEA was used to demonstrate the potential pathways altered by gene expression. Result Our study suggested that DEGs existed between metastatic and primary tumor tissues. Loss of GLS2 function was related to poor prognosis in RCC and ccRCC. These results revealed that GLS2 expression combined with basic characteristics, including age and TNM stage, could efficiently predict prognosis. GLS2 serves as a tumor suppressor in ccRCC, and loss of GLS2 function endows cells with oncogenic functions and is related to advanced disease. According to the GSEA results, loss of GLS2 function may alter the cell cycle by activating the E2F pathway. Conclusion GLS2 is a tumor suppressor in RCC. Loss of GLS2 function in ccRCC predicts a poor prognosis via the E2F pathway. Nomograms based on DEGs and clinical features provide doctors with a simple but efficient way to predict prognosis. Further studies are needed to verify the pathway in our study.

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The ‘Achilles Heel’ of Metabolism in Renal Cell Carcinoma: Glutaminase Inhibition as a Rational Treatment Strategy

Cited by 59 publications

References 184 publications

Network-based metabolic characterization of renal cell carcinoma

Network-based metabolic characterization of renal cell carcinoma

The role of glutaminase in cancer

Loss of GLS2 function is essential for obtaining oncogenic functions and promotes the progression of clear cell renal cell carcinoma.

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