HIF drives lipid deposition and cancer in ccRCC via repression of fatty acid metabolism

Du, William W.; Zhang, Luchang; Brett-Morris, Adina; Aguila, Brittany; Kerner, János; Hoppel, Charles L.; Puchowicz, Michelle; Serra, Dolors; Herrero, Laura; Rini, Brian I.; Campbell, Steven C.; Welford, Scott M.

doi:10.1038/s41467-017-01965-8

Cited by 317 publications

(307 citation statements)

References 43 publications

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“…41 HIF-2α controls the fate of fatty acids either in phospholipid synthesis or in storage to form lipid droplets. 42 We observed elevated levels of PGs and PIs and suppressed aminophospholipids such as PSs and PEs. PEs are synthesized in mitochondria and are produced from the decarboxylation of PS synthesized in endoplasmic reticulum (ER).…”

Section: Discussionmentioning

confidence: 65%

Identification of diagnostic metabolic signatures in clear cell renal cell carcinoma using mass spectrometry imaging

Vijayalakshmi

Shankar

Bain

et al. 2020

Intl Journal of Cancer

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Clear cell renal cell carcinoma (ccRCC) is the most common and lethal subtype of kidney cancer. Intraoperative frozen section (IFS) analysis is used to confirm the diagnosis during partial nephrectomy. However, surgical margin evaluation using IFS analysis is time consuming and unreliable, leading to relatively low utilization. In our study, we demonstrated the use of desorption electrospray ionization mass spectrometry imaging (DESI-MSI) as a molecular diagnostic and prognostic tool for ccRCC. DESI-MSI was conducted on fresh-frozen 23 normal tumor paired nephrectomy specimens of ccRCC. An independent validation cohort of 17 normal tumor pairs was analyzed. DESI-MSI provides two-dimensional molecular images of tissues with mass spectra representing small metabolites, fatty acids and lipids. These tissues were subjected to histopathologic evaluation. A set of metabolites that distinguish ccRCC from normal kidney were identified by performing least absolute shrinkage and selection operator (Lasso) and log-ratio Lasso analysis. Lasso analysis with leave-one-patient-out crossvalidation selected 57 peaks from over 27,000 metabolic features across 37,608 pixels obtained using DESI-MSI of ccRCC and normal tissues. Baseline Lasso of metabolites predicted the class of each tissue to be normal or cancerous tissue with an accuracy of 94 and 76%, respectively. Combining the baseline Lasso with the ratio of glucose to arachidonic acid could potentially reduce scan time and improve accuracy to identify normal (82%) and ccRCC (88%) tissue. DESI-MSI allows rapid detection of metabolites associated with normal and ccRCC with high accuracy. As this technology advances, it could be used for rapid intraoperative assessment of surgical margin status.K.V.L. and V.S. contributed equally to this work Ryan M. Bain's current address is: Dow Chemical Co., Midland, MI 48674 Additional Supporting Information may be found in the online version of this article.

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Section: Discussionmentioning

confidence: 65%

Identification of diagnostic metabolic signatures in clear cell renal cell carcinoma using mass spectrometry imaging

Vijayalakshmi

Shankar

Bain

et al. 2020

Intl Journal of Cancer

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“…Transcriptional repression of carnitine palmitoyltransferase ( CPT1A ), the rate limiting enzyme involved in fatty acid transport into the mitochondria for beta-oxidation, also occurs in ccRCC via a HIF-α dependent mechanism [80]. A recent report found that pVHL reconstitution in several ccRCC cell lines reduced lipid droplet (LD) accumulation in a CPT1A dependent manner (i.e., knockdown of CPT1A in pVHL-reconstituted cells partially increased lipid accumulation).…”

Section: Metabolic Reprogramming In Ccrccmentioning

confidence: 99%

“…These metabolic changes were also correlated with gene expression levels of lipogenic genes. While it is clear that suppression of either HIF-1α or HIF-2α markedly reduces LD formation in ccRCC [96], [34], [80], the target genes and mechanisms responsible for the clear cell phenotype have not been completely defined. Additionally, the role of other lipogenic transcription factors such as sterol regulatory element-binding protein 1 or 2 (SREBP1/2), PPARγ, and carbohydrate-responsive element-binding protein (ChREBP) remain to be fully elucidated in ccRCC.…”

Section: Metabolic Reprogramming In Ccrccmentioning

confidence: 99%

Genetic and metabolic hallmarks of clear cell renal cell carcinoma

Sanchez

Simon

2018

Biochimica et Biophysica Acta (BBA) - Reviews on Cancer

116

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Clear cell renal cell carcinoma (ccRCC) is a malignancy characterized by deregulated hypoxia-inducible factor signaling, mutation of several key chromatin modifying enzymes, and numerous alterations in cellular metabolism. Pre-clinical studies have historically been limited to cell culture models, however, the identification of critical tumor suppressors and oncogenes from large-scale patient sequencing data has led to several new genetically engineered mouse models with phenotypes reminiscent of ccRCC. In this review, we summarize recent literature on these topics and discuss how they inform targeted therapeutic approaches for the treatment of ccRCC.

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“…Similar to other solid tumors, ccRCC is primarily driven by loss of key tumor suppressor such as von Hippel-Lindau (VHL) and activation of oncogenes (23)(24)(25). Closely associated with these genetic alterations, lipid metabolic processes are dramatically altered in the ccRCC tumor microenvironment (3,4,(26)(27)(28)(29)(30)(31)(32)(33). In fact, the "clear cell" subtype gets its name from cholesterol ester-rich lipid droplets that accumulate in tumor cells (32,33).…”

Section: Discussionmentioning

confidence: 99%

MBOAT7-Driven Phosphatidylinositol Remodeling Promotes the Progression of Clear Cell Renal Carcinoma

Neumann

Zhang

Silver

et al. 2019

Preprint

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The most common kidney cancer, clear cell Renal Cell Carcinoma (ccRCC) is closely associated with obesity. In fact, the "clear cell" variant of RCC is given this name due to large lipid droplets within the tumor cells. Although it is well appreciated that renal lipid metabolism is altered in ccRCC, the mechanisms driving this are not well understood. Leveraging a shotgun lipidomics approach we have identified a lipid signature for ccRCC that includes an increase in arachidonic acid-enriched phosphatidylinositols (AA-PI). In parallel, we found that ccRCC tumors have increased expression of the acyltransferase enzyme membrane bound O-acyltransferase domain containing 7 (MBOAT7) that contributes to AA-PI synthesis. In ccRCC patients, MBOAT7 expression increases with tumor grade, and increased MBOAT7 expression correlates with poor survival. Genetic deletion of MBOAT7 in ccRCC cells decreases proliferation and induces cell cycle arrest, and MBOAT7 -/cells fail to form tumors in vivo. RNAseq of MBOAT7 -/cells identified alterations in cell migration and extracellular matrix organization, which were functionally validated in migration assays. Our work highlights the accumulation of AA-PI in ccRCC and demonstrate a novel way to decrease the AA-PI pool in ccRCC by limiting MBOAT7. Our data reveal that metastatic ccRCC is associated with altered AA-PI metabolism, and identify MBOAT7 as a novel target in advanced ccRCC.

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HIF drives lipid deposition and cancer in ccRCC via repression of fatty acid metabolism

Cited by 317 publications

References 43 publications

Identification of diagnostic metabolic signatures in clear cell renal cell carcinoma using mass spectrometry imaging

Identification of diagnostic metabolic signatures in clear cell renal cell carcinoma using mass spectrometry imaging

Genetic and metabolic hallmarks of clear cell renal cell carcinoma

MBOAT7-Driven Phosphatidylinositol Remodeling Promotes the Progression of Clear Cell Renal Carcinoma

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