In this study, results of two sets of GBS-related genes were identified. As shown in Table 2 and Table 3, 20 GBS-related genes were identified from the analysis of up-regulated significant expressed genes from the gene expression profile data, while 23 GBS-related genes were identified from the data of down-regulated ones.
From Table 2 and Table 3, it can be seen that there were 13 overlap genes, which were TP53, UBC, CTNNB1, EGFR, EP300, MDM2, AKT1, SF3A2, STAT3, GRB2, GSK3B, SRC, YBX1. These genes were identified both from up-regulated analysis and down-regulated analysis, indicating they could play more important roles in GBS.
TP53 is a critical tumor suppressor gene that regulates cell cycle progression, apoptosis, cellular senescence and many other properties critical for control of normal cellular growth and death . MDM2 has p53-independent transcription factor-like effects in nuclear factor-kappa beta (NFκB) activation. Therefore, MDM2 promotes tissue inflammation and MDM2 inhibition has potent anti-inflammatory effects in tissue injury. Increased levels of STAT3 proteins were observed in CD4+ T cells from GBS patients . Previous data reveal that Grb2 facilitates the association of FasL with adaptin beta, and promotes sorting of FasL to the cell surface in Schwann cells. As FasL is a potent regulator of cell death, dynamic regulation of its cell surface localization is critical for controlling local tissue remodeling and inflammation .
Ppi Relationship Between The Gbs-related Genes
We mapped all the GBS-related genes to the PPI network constructed from the STRING database. The PPI relationships between the GBS-related genes were shown in Figure 2. The coding genes of the proteins were denoted as nodes. The 20 GBS-related genes identified from up-regulated analysis were represented as red circles, while the 23 genes from down-regulated ones were represented as blue circles. Note that there were 13 overlap genes, which were represented as green circles.
Go Enrichment Analysis
The functional annotation tool DAVID  was implemented for GO enrichment analysis on the GBS-related genes. The results were provided in Supporting Information S2. We also plot the GO enrichment results in Figure 3 from the data in Supporting Information S2. The overlap GO terms in both up-regulated and down-regulated analysis were listed as follows:
GO:0010604~positive regulation of macromolecule metabolic process
GO:0007242~intracellular signaling cascade
GO:0007166~cell surface receptor linked signal transduction
GO:0043232~intracellular non-membrane-bounded organelle
Kegg Pathway Enrichment Analysis
The functional annotation tool DAVID  was implemented for KEGG enrichment analysis on the GBS-related genes. The enrichment p-value was corrected to control family-wide false discovery rate under a certain rate (e.g. <=0.05) with the Benjamin multiple testing correction method. The results were provided in Supporting Information S3. We also plot the KEGG pathway enrichment results in Figure 4 from the data in Supporting Information S3. The overlap KEGG pathway terms in both up-regulated and down-regulated analysis were listed as follows:
hsa05215: Prostate cancer
hsa05200: Pathways in cancer
hsa05213: Endometrial cancer
hsa05210: Colorectal cancer
hsa04012: ErbB signaling pathway
hsa04510: Focal adhesion
hsa04722: Neurotrophin signaling pathway
hsa04310: Wnt signaling pathway