Abstract
Brain tumor research has been stapled for human health while brain network research is crucial for us to understand brain activity. Here the structural controllability theory is applied to study three human brain-specific gene regulatory networks, including forebrain gene regulatory network, hindbrain gene regulatory network and neuron associated cells cancer related gene regulatory network, whose nodes are neural genes and the edges represent the gene expression regulation among the genes. The nodes are classified into two classes: critical nodes and ordinary nodes, based on the change of the number of driver nodes upon its removal. Eight topological properties (out-degree DO, in-degree DI, degree D, betweenness B, closeness CA, in-closeness CI, out-closeness CO and clustering coefficient CC) are calculated in this paper and the results prove that the critical genes have higher score of topological properties than the ordinary genes. Then two bioinformatic analysis are used to explore the biologic significance of the critical genes. On the one hand, the enrichment scores in several kinds of gene databases are calculated and reveal that the critical nodes are richer in essential genes, cancer genes and the neuron related disease genes than the ordinary nodes, which indicates that the critical nodes may be the biomarker in brain-specific gene regulatory network. On the other hand, GO analysis and KEGG pathway analysis are applied on them and the results show that the critical genes mainly take part in 14 KEGG pathways that are transcriptional misregulation in cancer, pathways in cancer and so on, which indicates that the critical genes are related to the brain tumor. Finally, by deleting the edges or routines in the network, the robustness analysis of node classification is realized, and the robustness of node classification is proved. The comparison of neuron associated cells cancer related GRN (Gene Regulatory Network) and normal brain-specific GRNs (including forebrain and hindbrain GRN) shows that the neuron-related cell cancer-related gene regulatory network is more robust than other types.
Highlights
The world has opened its eyes to the threat posed by cancer (McGuire, 2016)
We find that the result of node classification is quite robust, and the neuron associated cells cancer related gene regulatory network is more robust than the health networks
2.1.1 Description of Brain-specific Gene Regulatory Network We construct three brain-specific gene regulatory networks, which consist of forebrain gene regulatory network, hindbrain gene regulatory network and neuron associated cells cancer related gene regulatory network
Summary
Brain tumor is a mass or growth of abnormal cells in the human brain It can begin in the human brain (primary brain tumors), or begin in other parts of body and spread to brain (secondary, or metastatic, brain tumors) (Cheng et al 2014). Brain tumor accounts for 85–90% of all primary central nervous system (CNS) tumors (Mehta et al, 2011). There are new cases and deaths from brain tumor and other nervous system tumors estimated around the world every year. 256,213 new cases of brain and other CNS tumors were diagnosed in the year 2012, with an estimated 189,382 deaths (Ferlay et al, 2012), and there are 296,851 new cases and 241,037 deaths in 2018 (Bray et al, 2018). It is urgent to study the pathogenic mechanism and treatment for brain tumors
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