Systems biology approaches to decipher the underlying molecular mechanisms of glioblastoma multiforme

TY - JOUR

T1 - Systems biology approaches to decipher the underlying molecular mechanisms of glioblastoma multiforme

AU - Kaynar, Ali

AU - Altay, Ozlem

AU - Li, Xiangyu

AU - Zhang, Cheng

AU - Turkez, Hasan

AU - Uhlén, Mathias

AU - Shoaie, Saeed

AU - Mardinoglu, Adil

N1 - Funding Information: A.K. is being sponsored for his doctoral studies by the Turkish Government, Ministry of National Education. This work was financially supported by the ScandiBio Therapeutics and Knut and Alice Wallenberg Foundation, funding number 72110. Publisher Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

PY - 2021/12/1

Y1 - 2021/12/1

N2 - 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 method-ologies, 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.

AB - 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 method-ologies, 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.

KW - Genome-scale metabolic models

KW - Glioblastoma

KW - Multi-omics data

KW - Systems biology

UR - http://www.scopus.com/inward/record.url?scp=85120671378&partnerID=8YFLogxK

U2 - 10.3390/ijms222413213

DO - 10.3390/ijms222413213

M3 - Article

AN - SCOPUS:85120671378

SN - 1661-6596

VL - 22

JO - International Journal of Molecular Sciences

JF - International Journal of Molecular Sciences

IS - 24

M1 - 13213

ER -