scholarly journals Targeting Lipid Metabolism in Liver Cancer

Biochemistry ◽  
2020 ◽  
Vol 59 (41) ◽  
pp. 3951-3964
Author(s):  
Malak Alannan ◽  
Hussein Fayyad-Kazan ◽  
Véronique Trézéguet ◽  
Aksam Merched
2020 ◽  
Vol 21 (6) ◽  
pp. 2061 ◽  
Author(s):  
Yaping Wang ◽  
Takero Nakajima ◽  
Frank J. Gonzalez ◽  
Naoki Tanaka

Peroxisome proliferator-activated receptor (PPAR) α, β/δ, and γ modulate lipid homeostasis. PPARα regulates lipid metabolism in the liver, the organ that largely controls whole-body nutrient/energy homeostasis, and its abnormalities may lead to hepatic steatosis, steatohepatitis, steatofibrosis, and liver cancer. PPARβ/δ promotes fatty acid β-oxidation largely in extrahepatic organs, and PPARγ stores triacylglycerol in adipocytes. Investigations using liver-specific PPAR-disrupted mice have revealed major but distinct contributions of the three PPARs in the liver. This review summarizes the findings of liver-specific PPAR-null mice and discusses the role of PPARs in the liver.


Hepatology ◽  
2021 ◽  
Author(s):  
Xiaoxiao Jiang ◽  
Hui Qian ◽  
Wen‐Xing Ding

2020 ◽  
Vol 470 ◽  
pp. 54-63 ◽  
Author(s):  
Man Zhao ◽  
Yanan Bu ◽  
Jinyan Feng ◽  
Huihui Zhang ◽  
Yujun Chen ◽  
...  

2017 ◽  
Vol 486 (3) ◽  
pp. 827-832 ◽  
Author(s):  
Guang Yang ◽  
Yuan Wang ◽  
Jinyan Feng ◽  
Yunxia Liu ◽  
Tianjiao Wang ◽  
...  

2019 ◽  
Vol 23 (6) ◽  
pp. 473-483 ◽  
Author(s):  
Evans D. Pope ◽  
Erinmarie O. Kimbrough ◽  
Lalitha Padmanabha Vemireddy ◽  
Phani Keerthi Surapaneni ◽  
John A. Copland ◽  
...  

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Wenjie Wang ◽  
Chen Zhang ◽  
Qihong Yu ◽  
Xichuan Zheng ◽  
Chuanzheng Yin ◽  
...  

Abstract Background Liver cancer is one of the most common malignancies worldwide. HCC (hepatocellular carcinoma) is the predominant pathological type of liver cancer, accounting for approximately 75–85 % of all liver cancers. Lipid metabolic reprogramming has emerged as an important feature of HCC. However, the influence of lipid metabolism-related gene expression in HCC patient prognosis remains unknown. In this study, we performed a comprehensive analysis of HCC gene expression data from TCGA (The Cancer Genome Atlas) to acquire further insight into the role of lipid metabolism-related genes in HCC patient prognosis. Methods We analyzed the mRNA expression profiles of 424 HCC patients from the TCGA database. GSEA(Gene Set Enrichment Analysis) was performed to identify lipid metabolism-related gene sets associated with HCC. We performed univariate Cox regression and LASSO(least absolute shrinkage and selection operator) regression analyses to identify genes with prognostic value and develop a prognostic model, which was tested in a validation cohort. We performed Kaplan-Meier survival and ROC (receiver operating characteristic) analyses to evaluate the performance of the model. Results We identified three lipid metabolism-related genes (ME1, MED10, MED22) with prognostic value in HCC and used them to calculate a risk score for each HCC patient. High-risk HCC patients exhibited a significantly lower survival rate than low-risk patients. Multivariate Cox regression analysis revealed that the 3-gene signature was an independent prognostic factor in HCC. Furthermore, the signature provided a highly accurate prediction of HCC patient prognosis. Conclusions We identified three lipid-metabolism-related genes that are upregulated in HCC tissues and established a 3-gene signature-based risk model that can accurately predict HCC patient prognosis. Our findings support the strong links between lipid metabolism and HCC and may facilitate the development of new metabolism-targeted treatment approaches for HCC.


2020 ◽  
Author(s):  
Gianmarco Mastrogiovanni ◽  
Clare Pacini ◽  
Sofia Kakava ◽  
Robert Arnes-Benito ◽  
Charles R Bradshaw ◽  
...  

The homologous E3 ubiquitin ligases RNF43/ZNRF3 negatively regulate WNT signalling activation. Recently, both genes have been found mutated in several types of cancers. Specifically, loss-of-function mutations result in adenoma formation in mouse small intestine. However, their role in liver cancer has not been explored yet. Here we describe that hepatocyte-specific deletion of both Rnf43/Znrf3 results in altered lipid metabolism and a non-alcoholic steatohepatitis (NASH) phenotype in mouse, in the absence of exogenous fat supplementation. The effect is cell-autonomous, as evidenced by the intracellular lipid accumulation detected in mutant liver organoids. Upon chronic liver damage, Rnf43/Znrf3 deletion results in impaired hepatocyte regeneration, subsequent to an imbalance between hepatocyte differentiation and proliferation, which leads to hepatocellular carcinoma. Remarkably, hepatocellular carcinoma patients with mutations in ZNRF3 also present altered lipid metabolism and poorer survival. Our findings imply that Wnt activation through the RNF43/ZNRF3 module predisposes to liver cancer by altering the liver lipid metabolic ground-state and impairing liver regeneration, which combined, facilitate the progression towards malignancy. Our results highlight the requirement for personalized therapeutic or dietary interventions for those RNF43/ZNRF3 mutated individuals at risk of developing steatosis, NASH and/or liver cancer.


Author(s):  
Guo-Dong Lu ◽  
Shing Chuan Hooi

Author(s):  
Sidney D. Kobernick ◽  
Edna A. Elfont ◽  
Neddra L. Brooks

This cytochemical study was designed to investigate early metabolic changes in the aortic wall that might lead to or accompany development of atherosclerotic plaques in rabbits. The hypothesis that the primary cellular alteration leading to plaque formation might be due to changes in either carbohydrate or lipid metabolism led to histochemical studies that showed elevation of G-6-Pase in atherosclerotic plaques of rabbit aorta. This observation initiated the present investigation to determine how early in plaque formation and in which cells this change could be observed.Male New Zealand white rabbits of approximately 2000 kg consumed normal diets or diets containing 0.25 or 1.0 gm of cholesterol per day for 10, 50 and 90 days. Aortas were injected jin situ with glutaraldehyde fixative and dissected out. The plaques were identified, isolated, minced and fixed for not more than 10 minutes. Incubation and postfixation proceeded as described by Leskes and co-workers.


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