3D spatial organization and network-guided comparison of mutation profiles in glioblastoma

Download

index.pdf

Date

2019

Author

Dinçer, Cansu

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

161
views

99
downloads

Glioblastoma multiforme (GBM) is the most aggressive and heterogeneous type of brain tumor. The heterogeneity of GBM is the main obstacle to develop effective treatment strategies. In this study, we aimed to decrease the heterogeneity among GBM patients from The Cancer Genome Atlas (TCGA), classify the patients and propose therapeutic hypothesis for patient groups by using patient mutation profiles. We therefore implemented a systems level approach to mutations using their biophysical characteristics and organization in patient-specific subnetworks. While 3D mutation patches decrease the heterogeneity among patients, network guided analysis classified patients into five groups. Since each patient group carries a set of signature 3D mutation patches, we collected GBM cell line mutation and drug sensitivity data to link GBM patient group to GBM cell lines and eventually drug responses through 3D patch mutations. Therefore, we can propose drug responses of specific patient group for specific drugs. As an example, by targeting CSF1R, Pazopanib can be effective for Group 3 yet Group 2 can be resistant to inhibition of ATM which is a mediator of PTEN phosphorylation. As a conclusion, from mutations to protein interaction networks and eventually to therapeutic data, this study is a new perspective for precision medicine.

Subject Keywords

Brain, Brain Tumors., Glioblastoma, 3D mutation patch, protein interactions, patient-specific network modeling, network-guided tumor grouping.

URI

http://etd.lib.metu.edu.tr/upload/12624078/index.pdf
https://hdl.handle.net/11511/44354

Collections

Graduate School of Informatics, Thesis

Suggestions

OpenMETU
Core

3D spatial organization and network-guided comparison of mutation profiles in Glioblastoma reveals similarities across patients Dincer, Cansu; Kaya, Tugba; Keskin, Ozlem; Gursoy, Attila; Tunçbağ, Nurcan (2019-09-01) Glioblastoma multiforme (GBM) is the most aggressive type of brain tumor. Molecular heterogeneity is a hallmark of GBM tumors that is a barrier in developing treatment strategies. In this study, we used the nonsynonymous mutations of GBM tumors deposited in The Cancer Genome Atlas (TCGA) and applied a systems level approach based on biophysical characteristics of mutations and their organization in patient-specific subnetworks to reduce inter-patient heterogeneity and to gain potential clinically relevant i...
Network Modeling Identifies Patient-specific Pathways in Glioblastoma. Tunçbağ, Nurcan; POKORNY, JL; JOHNSON, H; SIO, TT; DALIN, S; IYEKEGBE, DO; WHITE, FM; SARKARIA, JN; FRAENKEL, E (2016-06-29) Glioblastoma is the most aggressive type of malignant human brain tumor. Molecular profiling experiments have revealed that these tumors are extremely heterogeneous. This heterogeneity is one of the principal challenges for developing targeted therapies. We hypothesize that despite the diverse molecular profiles, it might still be possible to identify common signaling changes that could be targeted in some or all tumors. Using a network modeling approach, we reconstruct the altered signaling pathways from t...
Integrative network modelling of the dasatinib treatment in glioblastoma stem cells Senger, Gökçe; Tunçbağ, Nurcan; Department of Bioinformatics (2019) Glioblastoma (GBM), the most aggressive type of the glial tumours, is thought to be widely promoted by stem-like cells. Although certain cancer types have been radically treated with Receptor Tyrosine Kinases (RTKs) inhibitors, prior studies demonstrate that treatment Glioblastoma Stem Cells (GSCs) with RTK inhibitors led to dynamic interconversion from proliferative to slow-cycling, persistent state. In this work, we use the publicly available RNA-Seq and ChIP-Seq data in naive patient-derived GBM cell lin...
A comparative study on EpCAM antibody immobilization on gold surfaces and microfluidic channels for the detection of circulating tumor cells Cetin, Didem; Okan, Meltem; Bat, Erhan; Külah, Haluk (2020-04-01) Detection of circulating tumor cells (CTCs) from the bloodstream holds great importance to diagnose cancer at early stages. However, CTCs being extremely rare in blood makes them difficult to reach. In this paper, we introduced different surface modification techniques for the enrichment and detection of MCF-7 in microfluidic biosensor applications using gold surface and EpCAM antibody. Mainly, two different mechanisms were employed to immobilize the antibodies; covalent bonding and bioaffinity interaction....
Examination of the dielectrophoretic spectra of MCF7 breast cancer cells and leukocytes Çağlayan, Zeynep; Demircan Yalçın, Yağmur; Külah, Haluk (Wiley, 2020-03-01) The detection of circulating tumor cells (CTCs) in blood is crucial to assess metastatic progression and to guide therapy. Dielectrophoresis (DEP) is a powerful cell surface marker-free method that allows intrinsic dielectric properties of suspended cells to be exploited for CTC enrichment/isolation from blood. Design of a successful DEP-based CTC enrichment/isolation system requires that the DEP response of the targeted particles should accurately be known. This paper presents a DEP spectrum method to inve...

Citation Formats

C. Dinçer, “3D spatial organization and network-guided comparison of mutation profiles in glioblastoma,” Thesis (M.S.) -- Graduate School of Informatics. Bioinformatics., Middle East Technical University, 2019.