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miR-34a: Multiple Opposing Targets and One Destiny in Hepatocellular Carcinoma

Journal of Clinical and Translational Hepatology 2016年第4期4卷 300-305页

作者： Radwa Alaa Yacoub Injie Omar Fawzy Reem Amr Assal Karim Adel Hosny abdel-rahman nabawy zekri Gamal Esmat Hend Mohamed El Tayebi Ahmed Ihab abdelaziz Pharmaceutical Biology Department Faculty of Pharmacy and Biotechnology German University in Cairo Cairo Egypt pharmacology and Toxicology Department Faculty of Pharmacy and Biotechnology German University in Cairo Cairo Egypt Department of General Surgery Faculty of Medicine Cairo University Cairo Egypt Virology and Immunology Cancer Biology Department National Cancer Institute Cairo University Cairo Egypt Department of Endemic Medicine and Hepatology Cairo University Cairo Egypt pharmacology and Toxicology Department Faculty of Pharmacy and Biotechnology German University in Cairo Cairo Egypt School of Medicine New Giza University Cairo Egypt

Background and Aims:The role of miR-34a in hepatocellular carcinoma (HCC) is controversial and several unresolved issues remain,including its expression pattern and relevance to tumor etiology,tumor stage and prognosis,and finally,its impact on apoptosis.Methods:miR-34a expression was assessed in hepatitis C virus (HCV)-induced non-metastatic HCC tissues by RT-Q-PCR.Huh-7 cells were transfected with miR-34a mimics and the impact of miR-34a was examined on 84 pro-apoptotic/anti-apoptotic genes using PCR array;its net effect was tested on cell viability via MTTassay.Results:miR-34a expression was up-regulated in HCC tissues.Moreover,miR-34a induced a large set of pro-apoptotic/anti-apoptotic genes,with a net result of triggering apoptosis and repressing cell viability.Conclusions:HCC-related differential expression of miR-34a could be etiology-based or stage-specific,and low expression of miR-34a may predict poor prognosis.This study's findings also emphasize the role of miR-34a in apoptosis.

关键词： MicroRNA Hepatocellular carcinoma Apoptosis PCR array.

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Early detection of hepatocellular carcinoma co-occurring with hepatitis C virus infection: A mathematical model

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World Journal of Gastroenterology 2016年第16期22卷 4168-4182页

作者： abdel-rahman nabawy zekri Amira Salah El-Din Youssef Yasser Mabrouk Bakr Reham Mohamed Gabr Ola Sayed Ahmed Mostafa Hamed Elberry Ahmed Mahmoud Mayla Mohamed Abouelhoda Abeer A Bahnassy Molecular Virology and Immunology Unit Cancer Biology Department National Cancer Institute Cairo University Systems and Biomedical Engineering Department Faculty of Engineering Cairo University Center for Informatics Sciences Nile University Sheikh Zayed City Pathology Department National Cancer Institute Cairo University

AIM: To develop a mathematical model for the early detection of hepatocellular carcinoma(HCC) with a panel of serum proteins in combination with α-fetoprotein(AFP).METHODS: Serum levels of interleukin(IL)-8, soluble intercellular adhesion molecule-1(s ICAM-1), soluble tumor necrosis factor receptor Ⅱ(s TNF-RⅡ), proteasome, and β-catenin were measured in 479 subjects categorized into four groups:(1) HCC concurrent with hepatitis C virus(HCV) infection(n = 192);(2) HCV related liver cirrhosis(LC)(n = 96);(3) Chronic hepatitis C(CHC)(n = 96); and(4) Healthy controls(n = 95). The R package and different modules for binary and multi-class classifiers based on generalized linear models were used to model the data. Predictive power was used to evaluate the performance of the model. Receiver operating characteristic curve analysis over pairs of groups was used to identify the best cutoffs differentiating the different groups. RESULTS: We revealed mathematical models, based on a binary classifier, made up of a unique panel of serum proteins that improved the individual performance of AFP in discriminating HCC patients from patients with chronic liver disease either with or without cirrhosis. We discriminated the HCC group from the cirrhotic liver group using a mathematical model(-11.3 + 7.38 × Prot + 0.00108 × s ICAM + 0.2574 ×β-catenin + 0.01597 × AFP) with a cutoff of 0.6552, which achieved 98.8% specificity and 89.1% sensitivity. For the discrimination of the HCC group from the CHC group, we used a mathematical model [-10.40 + 1.416 × proteasome + 0.002024 × IL + 0.004096 × s ICAM-1 +(4.251 × 10-4) × s TNF + 0.02567 ×β-catenin + 0.02442 × AFP] with a cutoff 0.744 and achieved 96.8% specificity and 89.7% sensitivity. Additionally, we derived an algorithm, based on a binary classifier, for resolving the multi-class classification problem by using three successive mathematical model predictions of liver disease status. CONCLUSION: Our proposed mathematical model may be a useful method for the early detection of different

关键词： Mathematical model Hepatocellular carcinoma α-fetoprotein Soluble intercellular adhesion molecule-1

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