Xiaoxia Liu1, Jinling Wang, Guiling Sun. 1. Department of Nephrology, Affiliated Hospital of Weifang Medical University, Weifang, Shandong, China.
Abstract
BACKGROUND/AIMS: To isolate key genes and pathways in renal cell carcinoma (RCC), which might reveal more evidences on the regulation network and contribute to pathogenic mechanisms of RCC. METHODS: Microarray data of GSE34676, GSE23926 and GSE48008 were downloaded from Gene Expression Omnibus. Differentially expressed genes (DEGs) and differentially expressed miRNAs were respectively screened using Limma package, followed by the selection of CNV associated genes and miRNAs. A multi-molecular regulation interaction network was constructed, and significant modules were subsequently isolated from the network by Molecular Complex Detection (Mcode) of Cytoscape. Finally, GO terms and KEGG pathways of these genes and miRNAs in significant modules were enriched using DAVID. RESULTS: Total 403 DEGs and 231 differentially expressed miRNAs were screened in RCC samples and normal group. Moreover, 1369 genes and 68 miRNAs were isolated by CNV analysis. Besides, a total of 59 miRNAs and 209 genes that related to 340 interaction pairs were analyzed and used to construct the network and 2 significant modules were identified. In the modules, CAV1 and CAV2 were shown to correlate with RCC. GNAI1, GPSM2 and GNAO1 were likely involved in the regulation of RCC through G protein signal transduction. Besides, G-protein coupled receptor protein signaling pathway, focal adhesion, MAPK signaling pathway and neuroactive ligand receptor interaction were enriched. CONCLUSION: Our study suggests that several crucial genes including CAV1,CAV2, GNAI1, GPSM2, and GNAO1 and pathways may play key roles in RCC progression.
BACKGROUND/AIMS: To isolate key genes and pathways in renal cell carcinoma (RCC), which might reveal more evidences on the regulation network and contribute to pathogenic mechanisms of RCC. METHODS: Microarray data of GSE34676, GSE23926 and GSE48008 were downloaded from Gene Expression Omnibus. Differentially expressed genes (DEGs) and differentially expressed miRNAs were respectively screened using Limma package, followed by the selection of CNV associated genes and miRNAs. A multi-molecular regulation interaction network was constructed, and significant modules were subsequently isolated from the network by Molecular Complex Detection (Mcode) of Cytoscape. Finally, GO terms and KEGG pathways of these genes and miRNAs in significant modules were enriched using DAVID. RESULTS: Total 403 DEGs and 231 differentially expressed miRNAs were screened in RCC samples and normal group. Moreover, 1369 genes and 68 miRNAs were isolated by CNV analysis. Besides, a total of 59 miRNAs and 209 genes that related to 340 interaction pairs were analyzed and used to construct the network and 2 significant modules were identified. In the modules, CAV1 and CAV2 were shown to correlate with RCC. GNAI1, GPSM2 and GNAO1 were likely involved in the regulation of RCC through G protein signal transduction. Besides, G-protein coupled receptor protein signaling pathway, focal adhesion, MAPK signaling pathway and neuroactive ligand receptor interaction were enriched. CONCLUSION: Our study suggests that several crucial genes including CAV1,CAV2, GNAI1, GPSM2, and GNAO1 and pathways may play key roles in RCC progression.
Authors: Annesa Flentje; Kord M Kober; Adam W Carrico; Torsten B Neilands; Elena Flowers; Nicholas C Heck; Bradley E Aouizerat Journal: Brain Behav Immun Date: 2018-03-13 Impact factor: 7.217