Hepatitis C virus (HCV) is a major world health problem affecting millions of people worldwide. HCV causes fibrosis of the liver; untreated, it leads to complications such as hepatic cirrhosis, decompensation, and hepatocellular carcinoma (HCC). Current methodologies used to determine the progression of hepatic fibrosis rely heavily on liver biopsy, a dangerous and invasive procedure, with subjective analysis of the results of the biopsy. Liver biopsies are also difficult to perform in the developing world, where the strain of HCV infection is great. A new methodology, that is both convenient and inexpensive, is needed for monitoring the progression of liver fibrosis in HCV patients. Small noncoding RNAs known as microRNAs are up-regulated or down-regulated when damage occurs in the liver. miRNAs are stable and present in almost all body fluids, therefore the measurement of circulating miRNAs in serum of liver fibrosis as a noninvasive method to evaluate disease severity and progression is promising. Currently, miRNAs have been found to play essential roles in hepatic stellate cell (HSC) differentiation, proliferation, apoptosis and migration linking them to aberrant expression variations in the development of liver fibrosis. Several microRNAs have shown promise as noninvasive biomarkers of hepatic fibrosis, and some even in the treatment of HCV. To study regulation of genes at the miRNA level is a huge advantage as gene expression is regulated at an epigenetic level before even the formation of proteins. Hepatitis C-genotype 4 infected patients were selected to detect and study the progression of liver fibrosis. The study consisted of three patient groups: 42 cases of chronic hepatitis C (CHC) with early stage fibrosis, 45 cases of CHC with late stage fibrosis, and 40 healthy patients with no CHC or fibrosis as controls. Blood samples were taken from each patient and RNA was extracted using the miRNeasy extraction kit. Expression patterns of 5 miRNAs (miR-16, miR-146a, miR-214-5p, miR-221, miR-222) were measured in each group using TaqMan real-time reverse transcription-polymerase chain reaction. MiRNA analysis was performed to determine the most specific and sensitive miRNA to be used as a diagnostic biomarker. Serum levels of miRNA-16, miRNA-146a, miRNA-221, and miRNA-222 were all significantly upregulated in early and late stage fibrosis compared to the control (p<0.001). MiRNA-222 had the highest sensitivity and specificity values in both early and late stage fibrosis with values of (69.23 %, 83.83%) and (100%, 96.77%) respectively. MiRNA-221 had the second highest sensitivity and specificity values with the late stage fibrosis group having values of 100% and 88.24% respectively. MiRNA-222 and miRNA-221 suggest promising potential as biomarkers for HCV-induced liver fibrosis as they had the highest sensitivity and specificity values. MiRNA-221 showed significant positive correlations with both miRNA-16 and miRNA-146a in the early and late stage fibrosis groups, with the early stage having a stronger correlation (at the 0.01 level). These correlations have great substantial values for future uses in formulating liver fibrosis diagnostic assays.  


Biotechnology Program

Degree Name

MS in Biotechnology

Graduation Date


Submission Date

January 2018

First Advisor

Zada, Suher

Committee Member 1

El-Ahwany, Eman

Committee Member 2

Mostafa, Ahmed


88 p.

Document Type

Master's Thesis


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Institutional Review Board (IRB) Approval

Approval has been obtained for this item


My sincere appreciation and gratitude goes first and foremost, to my thesis advisor Dr. Suher Zada. Thank you for allowing me to be a part of your team, and for your continuous supervision, help, and support. I would also like to thank my thesis co-adviser, Dr. Eman El-Ahwany, for all her help throughout this long process. Thank you for helping throughout every step of the way, from collecting blood samples to analyzing the data to completing my thesis dissertation, and for all your support and effort. I would like to thank Dr. Hoda Abu-Taleb for helping me with the statistical analysis and patiently answering and explaining all of my questions. Special thanks to Mr. Amged Ouf for helping me throughout all my laboratory work and always being available whenever I needed him. A sincere and deep appreciation goes to my colleague and now friend, Lobna Abul-Dahab, for guiding and advising me throughout the entire process. Thank you for all the encouragement and emotional support you provided for me, and for always making time to help me whenever I needed it. This project would not have been possible without the alliance of Theodor Bilharz Research Institute (TBRI), which provided me with the patient samples necessary for this study. Thank you to AUC for providing the research grant which aided in funding this project. Finally, I would like to thank everyone who contributed and helped with this project including staff and lab members at AUC and TBRI.