CSF protein dynamic driver network: At the crossroads of brain tumorigenesis

Published

Conference Paper

© 2014 IEEE. To get a better understanding of the ongoing in situ environmental changes preceding the brain tumorigenesis, we assessed cerebrospinal fluid (CSF) proteome profile changes in a glioma rat model in which brain tumor invariably develop after a single in utero exposure to the neurocarcinogen ethylnitrosourea (ENU). Computationally, the CSF proteome profile dynamics during the tumorigenesis can be modeled as non-smooth or even abrupt state changes. Such brain tumor environment transition analysis, correlating the CSF composition changes with the development of early cellular hyperplasia, can reveal the pathogenesis process at network level during a time before the image detection of the tumors. In this controlled rat model study, matched ENU and salineexposed rats' CSF proteomics changes were quantified at approximately 30, 60, 90, 120, 150 days of age (P30, P60, P90, P120, P150). We applied our transition-based network entropy (TNE) method to compute the CSF proteome changes in the ENU rat model and test the hypothesis of the critical transition state prior to impending hyperplasia. Our analysis identified a dynamic driver network (DDN) of CSF proteins related with the emerging tumorigenesis progressing from the non-hyperplasia state. The DDN associated leading network CSF proteins can allow the early detection of such dynamics before the catastrophic shift to the clear clinical landmarks in gliomas. An improved understanding of the critical transition state (P60) during the brain tumor progression can provide the scientific groundwork to device novel therapeutics preventing tumor formation.

Full Text

Duke Authors

Cited Authors

  • Fu, C; Tan, Z; Liu, R; Hao, S; Li, Z; Chen, P; Jang, T; Merchant, M; Whitin, JC; Wang, O; Guo, M; Cohen, HJ; Recht, L; Ling, XB

Published Date

  • January 1, 2014

Published In

  • Proceedings 2014 Ieee International Conference on Bioinformatics and Biomedicine, Ieee Bibm 2014

Start / End Page

  • 168 - 175

International Standard Book Number 13 (ISBN-13)

  • 9781479956692

Digital Object Identifier (DOI)

  • 10.1109/BIBM.2014.6999147

Citation Source

  • Scopus