Identification of GRB2 and GAB1 Coexpression as an Unfavorable Prognostic Factor for Hepatocellular Carcinoma by a Combination of Expression Profile and Network Analysis

Abstract

AimTo screen novel markers for hepatocellular carcinoma (HCC) by a combination of expression profile, interaction network analysis and clinical validation.MethodsHCC significant molecules which are differentially expressed or had genetic variations in HCC tissues were obtained from five existing HCC related databases (OncoDB.HCC, HCC.net, dbHCCvar, EHCO and Liverome). Then, the protein-protein interaction (PPI) network of these molecules was constructed. Three topological features of the network ('Degree', 'Betweenness', and 'Closeness') and the k-core algorithm were used to screen candidate HCC markers which play crucial roles in tumorigenesis of HCC. Furthermore, the clinical significance of two candidate HCC markers growth factor receptor-bound 2 (GRB2) and GRB2-associated-binding protein 1 (GAB1) was validated.ResultsIn total, 6179 HCC significant genes and 977 HCC significant proteins were collected from existing HCC related databases. After network analysis, 331 candidate HCC markers were identified. Especially, GAB1 has the highest k-coreness suggesting its central localization in HCC related network, and the interaction between GRB2 and GAB1 has the largest edge-betweenness implying it may be biologically important to the function of HCC related network. As the results of clinical validation, the expression levels of both GRB2 and GAB1 proteins were significantly higher in HCC tissues than those in their adjacent nonneoplastic tissues. More importantly, the combined GRB2 and GAB1 protein expression was significantly associated with aggressive tumor progression and poor prognosis in patients with HCC.ConclusionThis study provided an integrative analysis by combining expression profile and interaction network analysis to identify a list of biologically significant HCC related markers and pathways. Further experimental validation indicated that the aberrant expression of GRB2 and GAB1 proteins may be strongly related to tumor progression and prognosis in patients with HCC. The overexpression of GRB2 in combination with upregulation of GAB1 may be an unfavorable prognostic factor for HCC.

Thymoquinone exerts anti-tumor activities on human hepatocellular carcinoma cells: role of angiogenesis-related genes VCAN, Grb2 and EZH2

“…This hypothesis is supported by the fact that EZH2 was shown to has a key role in the regulation of tumor angiogenesis and the decrease in its expression levels inhibited metastasis suggesting EZH2 as a potential therapeutic target to reverse the migration and invasion of cancer cells [40][41][42][43][44]. Like VCAN and EZH2 genes, several studies have shown that Grb2 has an important role in proliferation and angiogenesis of several tumors including HCC through its contribution in the signaling pathway of various angiogenic factors [17,22,45,46]. The overexpression of miR-564 was shown to inhibit the proliferation, migration and invasion of HCC cell lines through a direct effect on Grb2 gene [46].…”

“…A cytoplasmic expression of VCAN protein was shown to be upregulated in HCC compared to matched normal tissues [19] and this overexpression was suggested as candidate biomarker for early stages of HCC [20]. In the same context, high expression of EZH2 [21] and Grb2 genes [22] were detected in HCC and also suggested as a promising diagnostic biomarkers of HCC.…”

To Elucidate the Inhibition of Excessive Autophagy of <i>Rhodiola crenulata</i> on Exhaustive Exercise-Induced Skeletal Muscle Injury by Combined Network Pharmacology and Molecular Docking

“…Gene Ontology (GO) and Signaling Pathway Analysis GO analysis and signaling pathway analysis for the targets were analyzed through the Database for Annotation, Visualization, and Integrated Discovery (DAVID). 25) The results were assigned into 3 categories: biological processes, molecular function, and Kyoto encyclopedia of genes and genomes (KEGG) signaling pathway analysis. p ≤ 0.05 was regarded as significance.…”

Discovery of potential drugs for COVID-19 based on the connectivity map

“…Centiscape [15], the app of Cytoscape, was used to calculate the degree measure of each node. Referring to the previous study of others [16,17], we determined the nodes whose degree were more than twice the mean degree value as hub genes. In order to explore more specific regulatory relationship in the above PPI network, the cluster analysis was performed by MCODE [18].…”