Investigating cellular network heterogeneity and modularity in cancer: a network entropy and unbalanced motif approach

BMC Systems Biology
Feixiong ChengZhongming Zhao

Abstract

Cancer is increasingly recognized as a cellular system phenomenon that is attributed to the accumulation of genetic or epigenetic alterations leading to the perturbation of the molecular network architecture. Elucidation of network properties that can characterize tumor initiation and progression, or pinpoint the molecular targets related to the drug sensitivity or resistance, is therefore of critical importance for providing systems-level insights into tumorigenesis and clinical outcome in the molecularly targeted cancer therapy. In this study, we developed a network-based framework to quantitatively examine cellular network heterogeneity and modularity in cancer. Specifically, we constructed gene co-expressed protein interaction networks derived from large-scale RNA-Seq data across 8 cancer types generated in The Cancer Genome Atlas (TCGA) project. We performed gene network entropy and balanced versus unbalanced motif analysis to investigate cellular network heterogeneity and modularity in tumor versus normal tissues, different stages of progression, and drug resistant versus sensitive cancer cell lines. We found that tumorigenesis could be characterized by a significant increase of gene network entropy in all of the 8 cancer...Continue Reading

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Citations

Nov 25, 2016·Scientific Reports·Youngjune ParkSun Kim
Nov 11, 2019·Life Science Alliance·Reema BaskarSean C Bendall
May 2, 2017·Briefings in Bioinformatics·Jiansong FangFeixiong Cheng
May 28, 2019·Frontiers in Genetics·Beste TuranliKazim Yalcin Arga

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Methods Mentioned

BETA
RNA-Seq

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