Yeni nesil dizileme tekniği kullanılarak karaciğer kanserinin sistem biyolojisi analizi

The underlying mechanism for the development of Hepatocellular Carcinoma (HCC) is highly complex due to tissue heterogeneity. Although the traditional approaches mainly focus on a single gene or locus, understanding the variations in the signaling pathways of cancerogenic cells during hepatocarcinogenesis may help to develop novel strategies for treatment and drug development to prevent cancer progression in the patients. This thesis study primarily focuses on unveiling the transcriptome sequencing of differentially expressed genes in HCC, which mainly concentrate on known disease signaling pathways. For this purpose, RNA-seq data of two HCC cell lines were targeted by three different kinase inhibitors and two of their combinations with Sorafenib. The functional pathways enriched with differentially expressed genes were identified by solving a graph problem called as Prize Collecting Steiner Tree (PCST) on human interactome generating inhibitor specific networks. As a result of this study, we found that combinatory treatment of Sorafenib with PIK-75 to HCC cell lines Huh7 and Mahlavu stimulates apoptosis, while TGX-221 with Sorafenib strikingly promotes cell growth antagonizing cellular death, especially for Mahlavu cell line. The states of transcriptomes for different kinase inhibitors were visualized using Cytoscape and molecular interactions were scanned deeply to understand synergistic or antagonistic effects of these kinase inhibitory treatments. Hence, this study provides comprehensive pathways analysis for differential kinase inhibitor reactions of HCC. Using these data, novel HCC drug targets were identified which may lead to more cost-effective and diverse treatment options available for the treatment of liver cancer.