Systems Biology Approaches to Decipher the Underlying Molecular Mechanisms of Glioblastoma Multiforme

被引:9
作者
Kaynar, Ali [1 ]
Altay, Ozlem [2 ]
Li, Xiangyu [2 ]
Zhang, Cheng [2 ]
Turkez, Hasan [3 ]
Uhlen, Mathias [2 ]
Shoaie, Saeed [1 ,2 ]
Mardinoglu, Adil [1 ,2 ]
机构
[1] Kings Coll London, Ctr Host Microbiome Interact, Fac Dent Oral & Craniofacial Sci, London SE1 9RT, England
[2] Royal Inst Technol KTH, Sci Life Lab, SE-10691 Stockholm, Sweden
[3] Ataturk Univ, Med Biol Dept, Fac Med, TR-25240 Erzurum, Turkey
关键词
glioblastoma; genome-scale metabolic models; multi-omics data; systems biology; GENOMIC CHARACTERIZATION; GLOBAL RECONSTRUCTION; GENE-EXPRESSION; NETWORK; REVEALS; PROTEIN; STEM; PROGRESSION; ASSOCIATION; METABOLISM;
D O I
10.3390/ijms222413213
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) is one of the most malignant central nervous system tumors, showing a poor prognosis and low survival rate. Therefore, deciphering the underlying molecular mechanisms involved in the progression of the GBM and identifying the key driver genes responsible for the disease progression is crucial for discovering potential diagnostic markers and therapeutic targets. In this context, access to various biological data, development of new methodologies, and generation of biological networks for the integration of multi-omics data are necessary for gaining insights into the appearance and progression of GBM. Systems biology approaches have become indispensable in analyzing heterogeneous high-throughput omics data, extracting essential information, and generating new hypotheses from biomedical data. This review provides current knowledge regarding GBM and discusses the multi-omics data and recent systems analysis in GBM to identify key biological functions and genes. This knowledge can be used to develop efficient diagnostic and treatment strategies and can also be used to achieve personalized medicine for GBM.
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页数:18
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