Farklı tedavi ajanları uygunlanmış karaciğerkanserlerine ait RNA dizilerinden çembersel RNA'larıntespit edilmesi

Discovering therapeutic agents for hepatocellular carcinoma (HCC) pose challenges as HCC contains high heterogeneity in terms of molecular phenotypes. It is thus crucial to understand the role of circular RNAs in the treatment of HCC. Circular RNAs are small and non-coding endogenous RNAs that have single stranded and covalently bound structures. The clinical importance of circular RNAs is due to their high stability in the serum and tissue. Up to now, the detection of circular RNAs was done through specific experiments that were pre-enriched for circular isoforms. However, it is also possible to detect circular RNAs from regular RNA-Seq data using unmapped back-splice junction information. The aim of this thesis is to detect circular RNAs from the raw RNA-Seq data and to analyze their transcript level differential expression across conditions like treatment and non-treatment cell lines. The qualitative and quantitative circular RNA expression differences between the Mahlavu and HUH-7 HCC cell lines treated with sorafenib, PI3K-α, PI3K-β inhibitors and their combinations (i.e. sorafenib and PI3K-α inhibitor; and sorafenib and PI3K- β inhibitor) will be accomplished. This was be achieved by using 12 raw RNA-seq read sets. CirComPara was selected as detection and quantification method as it allows of working simultaneously with different detection methods such as CIRI, CircExplorer2, DCC, findcirc, circRNAfinder. In total 136 and 122 reliable circular RNAs were detected in HUH-7 and Mahlavu, respectively. When HUH-7 and Mahlavu cell line were not under any treatment, 12 common circular RNAs could be detected in both cell lines. Otherwise, no common circular RNAs were detected.