Analyzing time-series microarray data reveals key genes in spinal cord injury.

Although many scholars have utilized high-throughput microarrays to delineate gene expression patterns after spinal cord injury (SCI), no study has evaluated gene changes in raphe magnus (RM) and somatomotor cortex (SMTC), two areas in brain primarily affected by SCI. In present study, we aimed to analyze the differentially expressed genes (DEGs) of RM and SMTC between SCI model and sham injured control at 4, 24 h, 7, 14, 28 days, and 3 months using microarray dataset GSE2270 downloaded from gene expression omnibus and unpaired significance analysis of microarray method. Protein-protein interaction (PPI) network was constructed for DEGs at crucial time points and significant biological functions were enriched using DAVID. The results indicated that more DEGs were identified at 14 days in RM and at 4 h/3 months in SMTC after SCI. In the PPI network for DEGs at 14 days in RM, interleukin 6, glyceraldehyde-3-phosphate dehydrogenase (GAPDH), FBJ murine osteosarcoma viral oncogene homolog (FOS), tumor necrosis factor, and nuclear receptor subfamily 3, group C, member 1 (glucocorticoid receptor) were the top 5 hub genes; In the PPI network for DEGs at 3 months in SMTC, the top 5 hub genes were ubiquitin B, Ras-related C3 botulinum toxin substrate 1 (rho family, small GTP binding protein Rac1), FOS, Janus kinase 2 and vascular endothelial growth factor A. Hedgehog and Wnt signaling pathways were the top 2 significant pathways in RM. These hub DEGs and pathways may be underlying therapeutic targets for SCI.

Overexpression of MACC1 protein and its clinical implications in patients with glioma.

Metastasis associated in colon cancer 1 (MACC1) has been regarded as a novel potential therapeutic target for multiple cancers. However, the impact of MACC1 in glioma remains unclear. The aim of this study was to analyze the correlation of MACC1 expression with the clinicopathological features of glioma. MACC1 mRNA and protein expression levels in human glioma tissues were detected by quantitative real-time polymerase chain reaction and immunohistochemistry assays, respectively. MACC1 mRNA and protein expression were both significantly higher in glioma tissues than in corresponding noncancerous brain tissues (both P < 0.001). In addition, statistical analysis suggested that high MACC1 expression was significantly correlated with advanced pathological grade (P = 0.004) and that patients with high expression of MACC1 protein exhibited a poorer prognosis than those with low MACC1 expression. Furthermore, Cox multivariate analysis showed that MACC1 overexpression was an independent prognostic factor for predicting the overall survival of glioma patients. In conclusion, expression of MACC1 in glioma could be adopted as a candidate biomarker for the diagnosis of clinical stage and for assessing prognosis, indicating for the first time that MACC1 may play an important role in the tumor development and progression in glioma. MACC1 might be considered as a novel therapeutic target against this cancer.