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META-analysis of microarray data to assess gender biased differential gene expression in hepatic tissue
Hepatocellular carcinoma (HCC) is the second deadliest cancer globally, and with an estimated 782,000 new cases in 2012, it is the fifth most common cancer in men and ninth in women. HCC is of particular concern in Egypt because of the high prevalence of Hepatitis C Virus (HCV). Due to its poor prog...
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| Format: | Thesis |
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AUC Knowledge Fountain
2015
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| Summary: | Hepatocellular carcinoma (HCC) is the second deadliest cancer globally, and with an estimated 782,000 new cases in 2012, it is the fifth most common cancer in men and ninth in women. HCC is of particular concern in Egypt because of the high prevalence of Hepatitis C Virus (HCV). Due to its poor prognosis, HCC is the leading cause of cancer-related deaths in Egypt. A gender disparity is observed in liver cancer cases, with higher prevalence in men by three to five fold. This sex bias is even more pronounced in mouse models of HCC, which was found to be sex hormone-dependent. Some studies have attempted to elucidate the molecular mechanisms of this disparity; but with inconclusive and sometimes contradicting outcomes, they remain largely unresolved. Understanding the natural protective mechanisms in females would allow for the development of preventative and therapeutic strategies for patients at risk for HCC or already inflicted with the disease. In this study, we applied a meta-analysis approach on already available microarray data from human normal liver tissues to identify differentially expressed genes between males and females. Microarray datasets were downloaded from the Gene Expression Omnibus database, Robust Multiarray Average pre-processed and analyzed for differential expression. The combination of 2 distinct datasets and analysis using a p-value cut-off of 0.05 and fold change cut-off of 2 revealed male up-regulated genes including RPS4Y1, EIF1AY, CYorf15B, UTY, DDX3Y and USP9Y. Female up-regulated genes included XIST, PNPLA4 and PZP. Our results confirm gender-specific differential expression patterns found in other tissues and call for further investigation using a larger sample size and more sensitive approaches such as RNA-Sequencing and, targeted protein-level studies. |
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