HIF-1α and HIF-2α differently regulate tumour development and inflammation of clear cell renal cell carcinoma in mice

Hoefflin, Rouven; Harlander, Sabine; Schäfer, Silvia; Metzger, Patrick Bastos; Kuo, Fengshen; Schönenberger, Désirée; Adlesic, Mojca; Peighambari, Asin; Seidel, Philipp; Chen, Chia-yi; Consenza-Contreras, Miguel; Jud, Andreas; Lahrmann, Bernd; Grabe, Niels; Heide, Danijela; Uhl, Franziska Maria; Chan, Timothy A.; Duyster, Justus; Zeiser, Robert; Schell, Christoph; Heikenwälder, Mathias; Schilling, Oliver; Hakimi, A. Ari; Boerries, Melanie; Frew, Ian J.

doi:10.1038/s41467-020-17873-3

Cited by 181 publications

(182 citation statements)

References 106 publications

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“…It cannot be ruled out that Tgfa and Ndrg1 expression might be induced in some particular renal cell types in Vhl −/− kidneys and therefore could not be detected in this RNA analysis in the whole kidney tissue. Along this line, higher expression of CaIX , Phd3 , Slc7a5 , Glut1 , Pgm1 occurred but not Ndrg1 in a Vhl -deficient renal cell mouse model when compared with non-tumor renal region, which is in line with our data in Vhl -deficient kidneys [ 47 ]. This study detected an elevated expression of Tgfa .…”

Section: Discussionsupporting

confidence: 90%

Differential Contribution of N- and C-Terminal Regions of HIF1α and HIF2α to Their Target Gene Selectivity

Bouthelier

Meléndez-Rodríguez

Urrutia

et al. 2020

IJMS

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Cellular response to hypoxia is controlled by the hypoxia-inducible transcription factors HIF1α and HIF2α. Some genes are preferentially induced by HIF1α or HIF2α, as has been explored in some cell models and for particular sets of genes. Here we have extended this analysis to other HIF-dependent genes using in vitro WT8 renal carcinoma cells and in vivo conditional Vhl-deficient mice models. Moreover, we generated chimeric HIF1/2 transcription factors to study the contribution of the HIF1α and HIF2α DNA binding/heterodimerization and transactivation domains to HIF target specificity. We show that the induction of HIF1α-dependent genes in WT8 cells, such as CAIX (CAR9) and BNIP3, requires both halves of HIF, whereas the HIF2α transactivation domain is more relevant for the induction of HIF2 target genes like the amino acid carrier SLC7A5. The HIF selectivity for some genes in WT8 cells is conserved in Vhl-deficient lung and liver tissue, whereas other genes like Glut1 (Slc2a1) behave distinctly in these tissues. Therefore the relative contribution of the DNA binding/heterodimerization and transactivation domains for HIF target selectivity can be different when comparing HIF1α or HIF2α isoforms, and that HIF target gene specificity is conserved in human and mouse cells for some of the genes analyzed.

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Section: Discussionsupporting

confidence: 90%

Differential Contribution of N- and C-Terminal Regions of HIF1α and HIF2α to Their Target Gene Selectivity

Bouthelier

Meléndez-Rodríguez

Urrutia

et al. 2020

IJMS

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“…Therefore, targeting HIFs might influence RCC progression (Schodel et al, 2016). Interestingly, in contrast to initial thoughts, emerging evidence has now demonstrated a divergent role for HIF-α factors in RCC biology where HIF-1α reduces and HIF-2α promotes RCC growth (Kondo et al, 2002(Kondo et al, , 2003Shen et al, 2011;Gudas et al, 2014;Hoefflin et al, 2020). Several reports have evidenced that mTOR decreases expression of HIF-α factors and therefore might influence RCC growth (Faes et al, 2017b).…”

Section: Regulation Of Hypoxia-inducible Factors By Mechanistic Targementioning

confidence: 99%

Mechanistic Target of Rapamycin Inhibitors in Renal Cell Carcinoma: Potential, Limitations, and Perspectives

Faes

Demartines

Dormond

2021

Front. Cell Dev. Biol.

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Several elements highlight the importance of the mechanistic target of rapamycin (mTOR) in the biology of renal cell carcinoma (RCC). mTOR signaling pathway is indeed frequently activated in RCC, inducing cancer cell proliferation and survival. In addition, mTOR promotes tumor angiogenesis and regulates the expression of hypoxia-inducible factors that play an important role in a subset of RCC. Despite mTOR protumorigenic effects, mTOR inhibitors have failed to provide long-lasting anticancer benefits in RCC patients, highlighting the need to readdress their role in the treatment of RCC. This review aims to present the rationale and limitations of targeting mTOR in RCC. Future roles of mTOR inhibitors in the treatment of RCC are also discussed, in particular in the context of immunotherapies.

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“…To enable the proliferation of tumor cells and to enable the formation of a membrane structure, it is necessary to produce a large number of fatty acids, a process that requires aerobic glycolysis, also known as the Warburg effect. This phenomenon is very common in malignant tumors [ 26 – 29 ]. Glycolysis is very important for tumors, and tumor cells exhibit high expression of key enzymes involved in the process of glycolysis to generate more energy.…”

Section: Discussionmentioning

confidence: 99%

Glycolysis‐Related Genes Serve as Potential Prognostic Biomarkers in Clear Cell Renal Cell Carcinoma

Zhang

Chen

Liu

et al. 2021

Oxidative Medicine and Cellular Longevity

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Metabolic rearrangement is a marker of cancer that has been widely studied in recent years. One of the major metabolic characteristics of tumor cells is the high levels of glycolysis, even under aerobic conditions, a phenomenon that is called the “Warburg effect.” We investigated the expression and copy number variation (CNV) frequency of all glycolysis-related genes in multiple cancer types and found many differentially expressed genes, particularly in clear cell renal cell carcinoma (ccRCC). Single nucleotide variants (SNVs) showed that the overall average mutation frequency for all genes was low. The purpose of this study was to establish a predictive model by studying glycolysis-related genes in ccRCC. We compared the expression of glycolysis-related genes in 539 ccRCC tissues and 72 normal renal tissues from The Cancer Genome Atlas dataset and identified 17 upregulated and 26 downregulated genes. Pathway analysis revealed that PSAT1 and SDHB could activate the cell cycle, RPIA could activate the DNA damage response, and HK3 could activate apoptosis and EMT signaling, while PDK2 could inhibit apoptosis. The results of the drug sensitivity analysis suggested that some of these differentially expressed genes were positively correlated with drug sensitivity. Thirteen genes were selected from the gene coexpression network and the LASSO regression analysis. The Kaplan-Meier overall survival curves showed that the expression of upregulated genes in ccRCC patients was associated with lower overall survival. We established a predictive model consisting of 13 genes (RPIA, G6PD, PSAT1, ENO2, HK3, IDH1, PDK4, PGM2, PGK1, FBP1, OGDH, SUCLA2, and SUCLG2). This predictive model correlated well with the development and progression of ccRCC. Thus, it is of great value in the diagnosis and prognostic evaluation of ccRCC and may aid the identification of potential prognostic biomarkers and drug targets.

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HIF-1α and HIF-2α differently regulate tumour development and inflammation of clear cell renal cell carcinoma in mice

Cited by 181 publications

References 106 publications

Differential Contribution of N- and C-Terminal Regions of HIF1α and HIF2α to Their Target Gene Selectivity

Differential Contribution of N- and C-Terminal Regions of HIF1α and HIF2α to Their Target Gene Selectivity

Mechanistic Target of Rapamycin Inhibitors in Renal Cell Carcinoma: Potential, Limitations, and Perspectives

Glycolysis‐Related Genes Serve as Potential Prognostic Biomarkers in Clear Cell Renal Cell Carcinoma

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