Network-based discovery of molecular targeted agent treatments in hepatocellular carcinoma

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2020

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Fayetörbay, Rumeys

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Hepatocellular carcinoma (HCC) is one of the most-deadly cancers and the most common type of primary liver cancer. Multikinase inhibitor Sorafenib is one of FDA approved targeted agents in HCC treatment. PI3K/AKT/mTOR pathway is altered in about 51% of HCC; hence, understanding how Sorafenib and PI3K/AKT/mTOR pathway inhibitors act at signaling level is crucial for targeted therapies and to reveal the off-target effects. In this work, we use gene expression profiles (GEPs) of HCC cells (Huh7 and Mahlavu) which were treated with seven different agents and their combination. Our aim is to reveal the important targets and modulators in agent treatments by inferring the dysregulation of Interactome. In other words, we search for the mechanism of action of the agents in a network context beyond the list of genes. For this purpose, we use the DeMAND (Detecting Mechanism of Action based on Network Dysregulation) algorithm developed by Califano Lab. DeMAND compares GEPs and assesses the change in the individual interactions from weighted interactome obtained from STRING database. As a result, we reconstructed 18 agent-specific networks from each GEPs. Each gene and interaction within these networks have a value signifies how strongly these genes are affected from the chemical network perturbation. Then, we found enriched pathways in each network. We initially compared the networks of single agents and their combination; i.e. PI3Ki-α, Sorafenib and their combined treatment. Then, we compared all networks simultaneously. The simultaneous comparison of the reconstructed networks at gene and pathway levels shows that several pathways and proteins are commonly affected across agent treatments (e.g., Wnt, HIF-1, Notch pathways and MCM proteins, mTOR). On the other hand, some pathways are only affected in a specific agent treatment (e.g., SNARE interactions).

Subject Keywords

Data recovery (Computer science)., Hepatocarcinoma Network Reconstruction, Therapeutic Agents, DeMAND Network Modelling Algorithm, Omics Data Integration, Targeted Cancer Therapy.

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http://etd.lib.metu.edu.tr/upload/12625144/index.pdf
https://hdl.handle.net/11511/45302

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Graduate School of Informatics, Thesis

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Citation Formats

R. Fayetörbay, “Network-based discovery of molecular targeted agent treatments in hepatocellular carcinoma,” Thesis (M.S.) -- Graduate School of Informatics. Bioinformatics., Middle East Technical University, 2020.