Characterization of hepatocellular carcinoma (HCC) in non-alcoholic fatty liver disease (NAFLD) patients without cirrhosis

Mohamad, Bashar; Shah, Vaishal; Onyshchenko, Mykola; Elshamy, Maged; Aucejo, Federico; López, Rocío; Hanouneh, Ibrahim A.; Alhaddad, Razan; Alkhouri, Naim

doi:10.1007/s12072-015-9679-0

Cited by 137 publications

(115 citation statements)

References 34 publications

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“…The disease frequently progresses to non-alcoholic steatohepatitis (NASH) characterized by cell damage, inflammatory infiltration and apoptosis. Independent of etiology, the cellular and molecular mechanisms of steatosis are basically identical, and predispose the progression to advanced liver disease stages such as fibrosis, cirrhosis and/or hepatocellular carcinoma (HCC) (Dongiovanni et al, 2015; Mohamad et al, 2015). …”

Section: Introductionmentioning

confidence: 99%

Loss of c-Met signaling sensitizes hepatocytes to lipotoxicity and induces cholestatic liver damage by aggravating oxidative stress

et al. 2016

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Recent studies confirmed a critical importance of c-Met signaling for liver regeneration by modulating redox balance. Here we used liver-specific conditional knockout mice (MetKO) and a nutritional model of hepatic steatosis to address the role of c-Met in cholesterol-mediated liver toxicity. Liver injury was assessed by histopathology and plasma enzymes levels. Global transcriptomic changes were examined by gene expression microarray, and key molecules involved in liver damage and lipid homeostasis were evaluated by Western blotting. Loss of c-Met signaling amplified the extent of liver injury in MetKO mice fed with high-cholesterol diet for 30 days as evidenced by upregulation of liver enzymes and increased synthesis of total bile acids, aggravated inflammatory response and enhanced intrahepatic lipid deposition. Global transcriptomic changes confirmed the enrichment of networks involved in steatosis and cholestasis. In addition, signaling pathways related to glutathione and lipid metabolism, oxidative stress and mitochondria dysfunction were significantly affected by the loss of c-Met function. Mechanistically, exacerbation of oxidative stress in MetKO livers was corroborated by increased lipid and protein oxidation. Western blot analysis further revealed suppression of Erk, NF-kB and Nrf2 survival pathways and downstream target genes (e.g. cyclin D1, SOD1, gamma-GCS), as well as up-regulation of proapoptotic signaling (e.g. p53, caspase 3). Consistent with the observed steatotic and cholestatic phenotype, nuclear receptors RAR, RXR showed increased activation while expression levels of CAR, FXR and PPAR-alpha were decreased in MetKO. Collectively, our data provide evidence for the critical involvement of c-Met signaling in cholesterol and bile acids toxicity.

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Section: Introductionmentioning

confidence: 99%

Loss of c-Met signaling sensitizes hepatocytes to lipotoxicity and induces cholestatic liver damage by aggravating oxidative stress

et al. 2016

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“…An association between inflammation and cancer has long been suspected. Indeed, pathological changes in the metabolic and physiological status of the liver such as NAFLD, NASH, injury, and cirrhosis, result in the onset of liver cancer, including HCC . Here, we review and discuss recent advances in the elucidation of cellular and molecular alterations, signalling pathways associated with PCAF, and their effects on hepatocarcinogenesis and tumour growth.…”

Section: Pcaf In Liver Cancer and Tumour Growthmentioning

confidence: 99%

PCAF fine‐tunes hepatic metabolic syndrome, inflammatory disease, and cancer

Yao

Shao

Zheng

et al. 2018

J Cellular Molecular Medi

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The P300/CBP‐associating factor (PCAF), a histone acetyltransferase, is involved in metabolic and pathogenic diseases, particularly of the liver. The effects of PCAF on fine‐tuning liver diseases are extremely complex and vary according to different pathological conditions. This enzyme has dichotomous functions, depending on differently modified sites, which regulate the activities of various enzymes, metabolic functions, and gene expression. Here, we summarize the most recent findings on the functions and targets of PCAF in various metabolic and immunological processes in the liver and review these new discoveries and models of PCAF biology in three areas: hepatic metabolic syndrome, inflammatory disease, and cancer. Finally, we discuss the potential implications of these findings for therapeutic interventions in liver diseases.

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“…HCC patients with or without cirrhosis may present with distinctive conditions, as reflected by their tumor sizes, recurrence rates, and patients' prognoses [6][7][8][9][10]. Prognostic evaluation has been recognized to fall short when only the tumor-related factors are considered because hepatocarcinogenesis is also considerably influenced by the status of the background liver, such as hepatic cirrhosis [11].…”

Section: Introductionmentioning

confidence: 99%

Identifying Differentially Expressed MicroRNAs Between Cirrhotic and Non-Cirrhotic Hepatocellular Carcinoma and Exploring Their Functions Using Bioinformatic Analysis

Mei¹,

You²,

Jin³

et al. 2018

Cell Physiol Biochem

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Background/Aims: Few studies have been designed to directly investigate the exact mechanisms underlying the different phenotypes between cirrhotic and non-cirrhotic hepatocellular carcinoma (HCC). This study aimed to illuminate the incidence and developmental mechanisms for both types of HCC through differentially expressed microRNAs (miRNAs) using bioinformatic analysis. Methods: The miRNA-seq data and clinical data of patients (from The Cancer Genome Atlas (TCGA) database) were utilized to determine differentially expressed miRNAs between cirrhotic and non-cirrhotic HCC. Afterwards, the function of the selected miRNAs was predicted with online tools. Furthermore, the miRNA expression and clinical significance were validated by external datasets and our experiment. Results: The present study included 135 non-cirrhotic and 80 cirrhotic patients to find differentially expressed miRNAs. Among them, four miRNAs (mir-1296, mir-23c, mir-149, and mir-95) were finally selected for further validation and analysis. Correlation analysis found that two miRNAs are greatly associated with the non-cirrhotic HCC patients’ clinical traits, such as the T, M, and N tumor stages. However, only mir-23c was associated with the cirrhotic HCC patients’ tumor T and N stages. Furthermore, survival analysis revealed that increased mir-149 in non-cirrhotic HCC, patients’ age and the existence of vessels in the tumor in cirrhotic HCC were independent risk factors for the patients’ postoperative overall survival. Functional and interaction analyses also supported the notion that these miRNAs function through some pathways that influence the behavior of the HCC. These results are strongly supported by analysis of extra datasets and our experiment. Conclusions: The cirrhotic and non-cirrhotic HCC types involve differentially expressed miRNAs, which are correlated with distinctive pathological traits. To some extent, non-cirrhotic HCC seems more dependent on miRNA network regulation, but additional studies are needed to confirm this conclusion.

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Characterization of hepatocellular carcinoma (HCC) in non-alcoholic fatty liver disease (NAFLD) patients without cirrhosis

Abstract: Patients with HCC in the absence of liver cirrhosis are more likely to present at an older age with larger tumor and have higher rates of tumor recurrence. Studies to assess the cost-effectiveness of HCC surveillance in this group should be conducted.

Cited by 137 publications

References 34 publications

Loss of c-Met signaling sensitizes hepatocytes to lipotoxicity and induces cholestatic liver damage by aggravating oxidative stress

Loss of c-Met signaling sensitizes hepatocytes to lipotoxicity and induces cholestatic liver damage by aggravating oxidative stress

PCAF fine‐tunes hepatic metabolic syndrome, inflammatory disease, and cancer

Identifying Differentially Expressed MicroRNAs Between Cirrhotic and Non-Cirrhotic Hepatocellular Carcinoma and Exploring Their Functions Using Bioinformatic Analysis

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