This project includes the files and codes used in my doctoral thesis project named as "A systems network approach for differential responses of Cancer Cells toward PI3K isoform Inhibitors".
A global study model comprising two HCC cell lines; Huh7 and Mahlavu, treated with kinase inhibitors; Sorafenib and PI3K inhibitors respectively; PI3K-α (PIK-75), PI3K-β (TGX-221), and combinations of Sorafenib with PI3K; Sorafenib + PI3Ki-α and Sorafenib + PI3Ki- β and DMSO as negative control. Therefore, for RNA-seq experiment, cDNA libraries prepared from 2 cell lines per 5 treatments and 1 control for each in total 12 samples. FASTQ reads of them can be found https://www.ncbi.nlm.nih.gov/sra/PRJNA556552 when this study published.
Abstract: The underlying mechanism for the development of Hepatocellular Carcinoma (HCC) is highly complex due to the tissue heterogeneity. Although the traditional approaches mainly focus on single gene or locus, understanding the variations in the signaling pathways/networks 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 in 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.
Preprint discussing the results of this study is here.