Network‐based method for detecting dysregulated pathways in glioblastoma cancer

Abstract

The knowledge on the biological molecular mechanisms underlying cancer is important for the precise diagnosis and treatment of cancer patients. Detecting dysregulated pathways in cancer can provide insights into the mechanism of cancer and help to detect novel drug targets. Based on the wide existing mutual exclusivity among mutated genes and the interrelationship between gene mutations and expression changes, this study presents a network-based method to detect the dysregulated pathways from gene mutations and expression data of the glioblastoma cancer. First, the authors construct a gene network based on mutual exclusivity between each pair of genes and the interaction between gene mutations and expression changes. Then they detect all complete subgraphs using CFinder clustering algorithm in the constructed gene network. Next, the two gene sets whose overlapping scores are above a specific threshold are merged. Finally, they obtain two dysregulated pathways in which there are glioblastoma-related multiple genes which are closely related to the two subtypes of glioblastoma. The results show that one dysregulated pathway revolving around epidermal growth factor receptor is likely to be associated with the primary subtype of glioblastoma, and the other dysregulated pathway revolving around TP53 is likely to be associated with the secondary subtype of glioblastoma.

Identifying driver modules based on multi‐omics biological networks in prostate cancer

“…Previous studies have shown that the driver modules have two key characteristics, namely high coverage and high mutual exclusivity [ 14 ], which have been widely used in carcinogenic driver module identification [ 25 , 26 , 27 , 28 ]. The definitions of coverage and mutual exclusivity are described in this section.…”

Prediction of drug synergy score using ensemble based differential evolution

“…Rational design of multi-targeted drug combinations is an efficient way to handle the drug resistance issue for several complex disorders [1,2]. A combination of drug is generally decomposed into synergistic, antagonistic and additive based upon the deviation of the evaluated combination response from the probable effect computed using a reference technique of non-interaction [3][4][5].…”

Pan-Cancer Exploration of mRNA Mediated Dysregulated Pathways in the Cancer Genomics Cloud

“…Other network based methods for detecting dysregulated pathways includes multi-omics approaches where both gene mutations with high coverage and no gene overlap (single nucleotide variants, copy numbers) and gene expression data are analyzed with the Dendrix and Markov Chain Monte Carlo algorithms (Wu, Dong and Wei, 2017). Additional approaches include using subnetworks from pathway interaction networks to detect dysregulated pathways by treating the detection as a feature selection task (Liu, Liu, Hao, Chen and Zhao, 2012).…”