The Changing Global Epidemiology of Hepatocellular Carcinoma

Caines, Allyce; Selim, Ranya; Salgia, Reena

doi:10.1016/j.cld.2020.06.001

Cited by 51 publications

(41 citation statements)

References 62 publications

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“…Globally, approximately 350 million people are chronically infected with HBV, and 20-30% of chronically HBV-infected individuals may develop cirrhosis and HCC [3]. About 70% of HCC cases are related to HBV infection in developing countries [4]. Regulatory HBV X protein (HBx) is critical for HBV replication and cellular transformation [5,6].…”

Section: Introductionmentioning

confidence: 99%

Hepatitis B Virus X Protein (HBx) Suppresses Transcription Factor EB (TFEB) Resulting in Stabilization of Integrin Beta 1 (ITGB1) in Hepatocellular Carcinoma Cells

Yang

Pan

Zhao

et al. 2021

Cancers

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Hepatitis B virus (HBV) infection is a major etiological risk for the incidence of hepatocellular carcinoma (HCC), and HBV X protein (HBx) is essential for oncogenic transformation. It is not known that if HBx can sabotage the lysosomal system for transformation and tumorigenesis, or its mechanism if it does have an effect. Examining clinical data, we observed that the downregulation of lysosomal components and transcription factor EB (TFEB) was associated with a poor prognosis of HCC patients. In HCC cells, we found that expression of HBx suppressed TFEB, impaired biogenesis of autophagic-lysosome, and promoted cellular dissemination. HBx mediated downregulation of TFEB led to impairment of autophagic/lysosomal biogenesis and flux, and consequently, accumulation of integrin beta 1 (ITGB1) for motility of HCC cells. Conversely, TFEB, in a steady-state condition, through induction of lysosomal biogenesis restrained ITGB1 levels and limited mobility of HCC cells. Specifically, overexpression of TFEB upregulated and activated the cysteine proteases including cathepsin L (CTSL) to degrade ITGB1. Conversely, expression of cystatin A (CSTA) or cystatin B (CSTB), the cellular inhibitors of lysosomal cysteine proteinases, spared ITGB1 from degradation and promoted dissemination of HCC cells. Taken together, this study suggests a potential mechanism for HBV-mediated malignancy, showing that HBx mediated downregulation of TFEB leads to accumulation of ITGB1 for HCC cell migration.

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Section: Introductionmentioning

confidence: 99%

Hepatitis B Virus X Protein (HBx) Suppresses Transcription Factor EB (TFEB) Resulting in Stabilization of Integrin Beta 1 (ITGB1) in Hepatocellular Carcinoma Cells

Yang

Pan

Zhao

et al. 2021

Cancers

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“…HCC has high interpatient, intertumoral and intratumoral heterogeneity (3). Patients with localized HCC usually have poor survival (with a 5-year overall survival [OS] rate of 30%), and this rate is less than 5% for HCC patients with distant metastasis (4). Currently, due to the complicated etiologic factors and the high heterogeneity of HCC, it remains difficult to accurately predict the prognosis of HCC patients.…”

Section: Introductionmentioning

confidence: 99%

Identification of a Novel Four-Gene Signature Correlated With the Prognosis of Patients With Hepatocellular Carcinoma: A Comprehensive Analysis

Zhu

2021

Front. Oncol.

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PurposeHepatocellular carcinoma (HCC) is a common solid-tumor malignancy with high heterogeneity, and accurate prognostic prediction in HCC remains difficult. This analysis was performed to find a novel prognostic multigene signature.MethodsThe TCGA-LIHC dataset was analyzed for differentially coexpressed genes through weighted gene coexpression network analysis (WGCNA) and differential gene expression analysis. A protein-protein interaction (PPI) network and univariate Cox regression analysis of overall survival (OS) were utilized to identify their prognostic value. Next, we used least absolute shrinkage and selection operator (LASSO) Cox regression to establish a prognostic module. Subsequently, the ICGC-LIRI-JP dataset was applied for further validation. Based on this module, HCC cases were stratified into high-risk and low-risk groups, and differentially expressed genes (DEGs) were identified. Functional enrichment analyses of these DEGs were conducted. Finally, single-sample gene set enrichment analysis (ssGSEA) was performed to explore the correlation between the prognostic signature and immune status.ResultsA total of 393 differentially coexpressed genes were obtained. Forty differentially coexpressed hub genes were identified using the CytoHubba plugin, and 38 of them were closely correlated with OS. Afterward, we established the four-gene prognostic signature with an acceptable accuracy (area under the curve [AUC] of 1-year survival: 0.739). The ICGC-LIRI-JP dataset also supported the acceptable accuracy (AUC of 1-year survival:0.752). Compared with low-risk cohort, HCC cases in the high-risk cohort had shorter OS, higher tumor grades, and higher T stages. The risk scores of this signature still act as independent predictors of OS (P<0.001). Functional enrichment analyses suggest that it was mainly organelle fission and nuclear division that were enriched. Finally, ssGSEA revealed that this signature is strongly associated with the immune status of HCC patients.ConclusionsThe proposed prognostic signature of four differentially coexpressed hub genes has satisfactory prognostic ability, providing important insight into the prediction of HCC prognosis.

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“…The burden of NAFLD is especially important since it can progress towards fibrosis, cirrhosis, and NAFLD-related HCC [ 4 ]. Moreover, this pathology is recognized not only as the most common etiology of chronic liver disease, but as a major cause of cirrhosis and HCC, and it is expected to become the leading recommendation for liver transplantation in this decade [ 9 , 10 ]. Mittal et al [ 11 ] reported that NAFLD individuals are fivefold more likely to develop HCC without underlying cirrhosis, compared to patients suffering from other chronic liver diseases.…”

Section: Introductionmentioning

confidence: 99%

Performance of Ultrasound Techniques and the Potential of Artificial Intelligence in the Evaluation of Hepatocellular Carcinoma and Non-Alcoholic Fatty Liver Disease

Lupșor-Platon

Şerban

Silion

et al. 2021

Cancers

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Global statistics show an increasing percentage of patients that develop non-alcoholic fatty liver disease (NAFLD) and NAFLD-related hepatocellular carcinoma (HCC), even in the absence of cirrhosis. In the present review, we analyzed the diagnostic performance of ultrasonography (US) in the non-invasive evaluation of NAFLD and NAFLD-related HCC, as well as possibilities of optimizing US diagnosis with the help of artificial intelligence (AI) assistance. To date, US is the first-line examination recommended in the screening of patients with clinical suspicion of NAFLD, as it is readily available and leads to a better disease-specific surveillance. However, the conventional US presents limitations that significantly hamper its applicability in quantifying NAFLD and accurately characterizing a given focal liver lesion (FLL). Ultrasound contrast agents (UCAs) are an essential add-on to the conventional B-mode US and to the Doppler US that further empower this method, allowing the evaluation of the enhancement properties and the vascular architecture of FLLs, in comparison to the background parenchyma. The current paper also explores the new universe of AI and the various implications of deep learning algorithms in the evaluation of NAFLD and NAFLD-related HCC through US methods, concluding that it could potentially be a game changer for patient care.

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The Changing Global Epidemiology of Hepatocellular Carcinoma

Cited by 51 publications

References 62 publications

Hepatitis B Virus X Protein (HBx) Suppresses Transcription Factor EB (TFEB) Resulting in Stabilization of Integrin Beta 1 (ITGB1) in Hepatocellular Carcinoma Cells

Hepatitis B Virus X Protein (HBx) Suppresses Transcription Factor EB (TFEB) Resulting in Stabilization of Integrin Beta 1 (ITGB1) in Hepatocellular Carcinoma Cells

Identification of a Novel Four-Gene Signature Correlated With the Prognosis of Patients With Hepatocellular Carcinoma: A Comprehensive Analysis

Performance of Ultrasound Techniques and the Potential of Artificial Intelligence in the Evaluation of Hepatocellular Carcinoma and Non-Alcoholic Fatty Liver Disease

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