Cerebrospinal fluid protein dynamic driver network: At the crossroads of brain tumorigenesis.

Published

Journal Article

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 developed 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 our controlled rat model study, matched ENU- and saline-exposed 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. Future characterization of the critical transition state (P60) during the brain tumor progression may reveal the underlying pathophysiology to device novel therapeutics preventing tumor formation. More detailed method and information are accessible through our website at http://translationalmedicine.stanford.edu.

Full Text

Cited Authors

  • Tan, Z; Liu, R; Zheng, L; Hao, S; Fu, C; Li, Z; Deng, X; Jang, T; Merchant, M; Whitin, JC; Guo, M; Cohen, HJ; Recht, L; Ling, XB

Published Date

  • July 2015

Published In

Volume / Issue

  • 83 /

Start / End Page

  • 36 - 43

PubMed ID

  • 25982164

Pubmed Central ID

  • 25982164

Electronic International Standard Serial Number (EISSN)

  • 1095-9130

International Standard Serial Number (ISSN)

  • 1046-2023

Digital Object Identifier (DOI)

  • 10.1016/j.ymeth.2015.05.004

Language

  • eng