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

Fayetörbay, Rumeys
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).


Analyses and modeling of ovarian cancer microarray data
Karakelle, Barış S; Purutçuoğlu Gazi, Vilda; Department of Biomedical Engineering (2019)
Ovarian cancer is one of the common cancer types among other oncological diseases. The major causes of this cancer can be listed as age, obesity, hormone therapy, material inheritance and contraceptive pills. Due to its generality and importance, many researches have been conducted from distinct labs about this illness and its plausible causes have been intensively investigated either inmicroarray studies, where just part of the related genes are detected, or in thepairwise correlation analyses between the ...
Cancer modeling via biologically validated genes
Karakelle, Barış Su; Purutçuoğlu Gazi, Vilda; Ürün, Yüksel (2017-05-10)
The cancer disease is the second most common disease type seen after the frequency of the cardiovascular diseases. The frequency of this genetic disease changes with respect to the gender. Accordingly, the gynecological cancer, which covers ovarian, endometrial or cervical cancer, is the second most common cancer type in women after the breast cancer. Similar to other cancer types, the gynecological cancer is the system disease, meaning that the malfunctions and mutations in the gene regulatory ...
Structural mapping and network analysis of patient-specific mutations in glioblastoma
Kaya, Tuğba; Tunçbağ, Nurcan; Doğan, Tunca; Department of Bioinformatics (2018)
Cancer is one of the most common cause of death worldwide. It occurs as a result of a collection of somatic deviations from normal state. Therefore, many efforts have been invested to profile mutations in different types of tumors; such as, the Cancer Genome Atlas (TCGA) which deposits multiple omic data for more than 11,000 tumor samples. In this thesis, we present a pipeline which retrieves patient-specific mutation data in Glioblastoma from TCGA, maps these mutations on the protein structures in Protein ...
Tailoring magnetic PLGA nanoparticles suitable for doxorubicin delivery
Tansik, Gulistan; YAKAR, ARZU; Gündüz, Ufuk (2013-12-07)
One of the main problems of current cancer chemotherapy is the lack of selectivity of anti-cancer drugs to tumor cells, which leads to systemic toxicity and adverse side effects. In order to overcome these limitations, researches on controlled drug delivery systems have gained much attention. Nanoscale-based drug delivery systems provide tumor targeting. Among many types of nanocarriers, superparamagnetic nanoparticles with their biocompatible polymer coatings can be targeted to an intented site by an exter...
Modeling of Breast and Gynecological Cancers Data and Investigating New Biological Findings
Ağyüz, Umut; Purutçuoğlu Gazi, Vilda (null; 2018-06-27)
The breast and gynecological cancers are two most common fatal cancers’ types in women in the world [1]. In oncological literature, these two cancers types are typically worked together since they are the risk factors of each other if the patient has one of these diseases [2]. In general, the cancers, like the heart diseases, are the systems’ ilnesses in the sense that any malfunctions in the associated transaction pathways cause problems in the activation flow, resulting in tumors. Therefore, the mathemati...
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.