Expanding the Disease Network of Glioblastoma Multiforme via Topological Analysis

被引:3
作者
Badkas, Apurva [1 ]
De Landtsheer, Sebastien [1 ]
Sauter, Thomas [1 ]
机构
[1] Univ Luxembourg, Dept Life Sci & Med, 2 Ave Univ, L-4365 Esch Sur Alzette, Luxembourg
基金
英国科研创新办公室;
关键词
glioblastoma; network analysis; topology; betweenness centrality; CENTRALITY MEASURES; ROBUSTNESS; GENES; CANCER; ATLAS;
D O I
10.3390/ijms24043075
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Glioblastoma multiforme (GBM), a grade IV glioma, is a challenging disease for patients and clinicians, with an extremely poor prognosis. These tumours manifest a high molecular heterogeneity, with limited therapeutic options for patients. Since GBM is a rare disease, sufficient statistically strong evidence is often not available to explore the roles of lesser-known GBM proteins. We present a network-based approach using centrality measures to explore some key, topologically strategic proteins for the analysis of GBM. Since network-based analyses are sensitive to changes in network topology, we analysed nine different GBM networks, and show that small but well-curated networks consistently highlight a set of proteins, indicating their likely involvement in the disease. We propose 18 novel candidates which, based on differential expression, mutation analysis, and survival analysis, indicate that they may play a role in GBM progression. These should be investigated further for their functional roles in GBM, their clinical prognostic relevance, and their potential as therapeutic targets.
引用
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页数:14
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