Title :
CSF protein dynamic driver network: At the crossroads of brain tumorigenesis
Author :
Changlin Fu ; Zhou Tan ; Rui Liu ; Shiying Hao ; Zhen Li ; Pei Chen ; Taichang Jang ; Merchant, Milton ; Whitin, John C. ; Wang, Oliver ; Minyi Guo ; Cohen, Harvey J. ; Recht, Lawrence ; Ling, Xuefeng B.
Author_Institution :
Shanghai Jiao Tong Univ., Shanghai, China
Abstract :
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.
Keywords :
biomedical engineering; brain; proteins; proteomics; tumours; CSF proteins; CSF proteome profile dynamics; brain tumorigenesis; cellular hyperplasia; cerebrospinal fluid; critical transition state; glioma rat model; neurocarcinogen ethylnitrosourea; nonhyperplasia state; pathogenesis process; protein dynamic driver network; transition-based network entropy method; tumor image detection; Bifurcation; Brain modeling; Eigenvalues and eigenfunctions; Entropy; Markov processes; Proteomics; Tumors; critical transition; dynamical driver biomarker (DDN); network entropy; transition state; tumorigenesis progressing;
Conference_Titel :
Bioinformatics and Biomedicine (BIBM), 2014 IEEE International Conference on
Conference_Location :
Belfast
DOI :
10.1109/BIBM.2014.6999147