Hepatocellular Carcinoma: Updates in Pathogenesis, Detection and Treatment

Martínez‐Chantar, María Luz; Avila, Matı́as A.; Lu, Shelly C.

doi:10.3390/cancers12102729

Cited by 13 publications

(14 citation statements)

References 28 publications

(46 reference statements)

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“…Cancer is increasingly a global problem, and primary liver carcinoma is the second top leading cancer with high mortality worldwide. 28 , 29 As one of the main histological types of primary liver carcinoma, HCC accounts for approximately 90% of pathogenesis 30 and leading to a much lower 5-year survival. 31 Hence, it is significant to develop uncovering novel diagnostic and prognostic biomarkers of HCC, which would shed light on improving the HCC patient’s outcome.…”

Section: Discussionmentioning

confidence: 99%

Integrated Proteomics and Bioinformatics to Identify Potential Prognostic Biomarkers in Hepatocellular Carcinoma

Zhang¹,

Xiao²,

Sun³

et al. 2021

CMAR

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Background Liver hepatocellular carcinoma (HCC) is the third most common cause of death by cancer and has a high mortality world-widely. Approximately 75–85% of primary liver cancers are caused by HCC. Uncovering novel genes with prognostic significance would shed light on improving the HCC patient’s outcome. Objective In this research, we aim to identify novel prognostic biomarkers in hepatocellular carcinoma. Methods Integrated proteomics and bioinformatics analysis were performed to investigate the expression landscape of prognostic biomarkers in 24 paired HCC patients. Results As a result, eight key genes related to prognosis, including ACADS, HSD17B13, PON3, AMDHD1, CYP2C8, CYP4A11, SLC27A5, CYP2E1, were identified by comparing the weighted gene co-expression network analysis (WGCNA), proteomic differentially expressed genes (DEGs), proteomic turquoise module, The Cancer Genome Atlas (TCGA) cohort DEGs of HCC. Furthermore, we trained and validated eight pivotal genes integrating these independent clinical variables into a nomogram with superior accuracy in predicting progression events, and their lower expression was associated with a higher stage/risk score. The Gene Set Enrichment Analysis (GSEA) further revealed that these key genes showed enrichment in the HCC regulatory pathway. Conclusion All in all, we found that these eight genes might be the novel potential prognostic biomarkers for HCC and also provide promising insights into the pathogenesis of HCC at the molecular level.

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Section: Discussionmentioning

confidence: 99%

Integrated Proteomics and Bioinformatics to Identify Potential Prognostic Biomarkers in Hepatocellular Carcinoma

Zhang¹,

Xiao²,

Sun³

et al. 2021

CMAR

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“…The primary outcome was the cumulative risk of HCC development. HCC was diagnosed based on histological evidence or radiological findings determined by dynamic computed tomography and/or magnetic resonance imaging (nodule > 1 cm with arterial hyper-vascularity and portal/delayed-phase washout) [ 26 , 27 , 28 , 29 ]. In addition, we also investigated the cumulative risk of cirrhotic complication events (CCEs), including shift to Child–Pugh class B, presence of related symptoms (e.g., ascites, variceal hemorrhage, hepatorenal syndrome, or hepatic encephalopathy), cirrhosis-related death, or liver transplantation.…”

Section: Methodsmentioning

confidence: 99%

Hepatocellular Carcinoma Risk According to Regimens for Eradication of Hepatitis C Virus; Interferon or Direct Acting Antivirals

Lee

Han

Shin

et al. 2020

Cancers

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By pegylated interferon (PegIFN)-free direct-acting antivirals (DAAs) against hepatitis C virus (HCV) infection, a sustained virological response (SVR) rate >95% can be attained with a satisfactory tolerability and shorter treatment duration. However, it remains controversial whether there is any difference in prognosis depending on regimens—PegIFN or DAAs. We compared the probabilities of hepatocellular carcinoma (HCC) development between patients achieving an SVR by PegIFN/ribavirin (PegIFN group, n = 603) and DAAs (DAAs group, n = 479). The DAAs group was significantly older and had a higher proportion of cirrhosis than the PegIFN group. Before adjustment, the DAAs group had a higher HCC incidence than the PegIFN group (p < 0.001). However, by multivariate analyses, the DAAs (vs. PegIFN) group was not associated with HCC risk (adjusted hazard ratio 0.968, 95% confidence interval 0.380–2.468; p = 0.946). Old age, male, higher body mass index, cirrhosis, and lower platelet count were associated with increased HCC risk (all p < 0.05). After propensity score matching (PSM), a similar HCC risk between the two groups was observed (p = 0.372). We also compared HCC incidences according to sofosbuvir (SOF)-based and SOF-free DAAs, showing a similar risk in both groups before adjustment (p = 0.478) and after PSM (p = 0.855). In conclusion, post-SVR HCC risks were comparable according to treatment regimens; PegIFN- vs. DAA-based regimens and SOF-based vs. SOF-free DAA regimens. Further studies with a longer follow-up period are required.

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“…Hepatocellular carcinoma (HCC) is the most frequent primary liver cancer, and incidence of about 10.1 cases per 100,000 persons, and HCC is ranked as the sixth most common neoplasm and the third leading cause of cancer death [ 1 ]. HCC occurs mainly in the context of cirrhosis, hepatitis B or C virus infection, or nonalcoholic steatohepatitis, and its incidence is expected to increase [ 2 ]. Perturbations in folate dependent methylation pathways have been associated with cancer occurrence [ 3 ] and many human pathological conditions [ 4 , 5 ].…”

Section: Introductionmentioning

confidence: 99%

Downregulation of Methionine Cycle Genes MAT1A and GNMT Enriches Protein-Associated Translation Process and Worsens Hepatocellular Carcinoma Prognosis

Chen

Tsai

Huang

et al. 2022

IJMS

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The major biological methyl donor, S-adenosylmethionine (adoMet) synthesis occurs mainly in the liver. Methionine adenosyltransferase 1A (MAT1A) and glycine N-methyltransferase (GNMT) are two key enzymes involved in the functional implications of that variation. We collected 42 RNA-seq data from paired hepatocellular carcinoma (HCC) and its adjacent normal liver tissue from the Cancer Genome Atlas (TCGA). There was no mutation found in MAT1A or GNMT RNA in the 42 HCC patients. The 11,799 genes were annotated in the RNA-Seq data, and their expression levels were used to investigate the phenotypes of low MAT1A and low GNMT by Gene Set Enrichment Analysis (GSEA). The REACTOME_TRANSLATION gene set was enriched and visualized in a heatmap along with corresponding differences in gene expression between low MAT1A versus high MAT1A and low GNMT versus high GNMT. We identified 43 genes of the REACTOME_TRANSLATION gene set that are powerful prognosis factors in HCC. The significantly predicted genes were referred into eukaryotic translation initiation (EIF3B, EIF3K), eukaryotic translation elongation (EEF1D), and ribosomal proteins (RPs). Cell models expressing various MAT1A and GNMT proved that simultaneous restoring the expression of MAT1A and GNMT decreased cell proliferation, invasion, as well as the REACTOME_TRANSLATION gene EEF1D, consistent with a better prognosis in human HCC. We demonstrated new findings that downregulation or defect in MAT1A and GNMT genes can enrich the protein-associated translation process that may account for poor HCC prognosis. This is the first study demonstrated that MAT1A and GNMT, the 2 key enzymes involved in methionine cycle, could attenuate the function of ribosome translation. We propose a potential novel mechanism by which the diminished GNMT and MAT1A expression may confer poor prognosis for HCC.

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Hepatocellular Carcinoma: Updates in Pathogenesis, Detection and Treatment

Abstract: Hepatocellular carcinoma (HCC) is the most frequent primary liver cancer and the second most common cause of cancer mortality worldwide [...]

Cited by 13 publications

References 28 publications

Integrated Proteomics and Bioinformatics to Identify Potential Prognostic Biomarkers in Hepatocellular Carcinoma

Integrated Proteomics and Bioinformatics to Identify Potential Prognostic Biomarkers in Hepatocellular Carcinoma

Hepatocellular Carcinoma Risk According to Regimens for Eradication of Hepatitis C Virus; Interferon or Direct Acting Antivirals

Downregulation of Methionine Cycle Genes MAT1A and GNMT Enriches Protein-Associated Translation Process and Worsens Hepatocellular Carcinoma Prognosis

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