Hub genes

Network spatio-temporal analysis predicts disease stage-related genes and pathways in renal cell carcinoma

X. H. Li, Yang, C. Z., Wang, J., Li, X. H., Yang, C. Z., and Wang, J., Network spatio-temporal analysis predicts disease stage-related genes and pathways in renal cell carcinoma, vol. 15, p. -, 2016.

The purpose of this study was to screen the key genes and pathways of renal cell carcinoma (RCC) and lay the foundation for its diagnosis and therapy. Microarray data of normal subjects and RCC patients at different stages of disease were used to screen differentially expressed genes (DEGs). Based on the DEGs in the four disease stages, four co-expression networks were constructed using the Empirical Bayes method and hub genes were obtained by centrality analysis. The enriched pathways of the DEGs and the mutual hub genes in the cluster of each disease stage were investigated.

Molecular-level effects of eribulin and paclitaxel on breast cancer based on differential co-expression network analysis

J. Qin, Chen, Y. H., Qin, J., and Chen, Y. H., Molecular-level effects of eribulin and paclitaxel on breast cancer based on differential co-expression network analysis, vol. 15, p. -, 2016.

We investigated the effects of eribulin and paclitaxel on breast cancer (BC) by exploring molecular biomarkers and pathways. Co-expression networks were constructed by differentially co-expressed genes and links, and centralities were analyzed to explore the hub genes. Pathway-enrichment analysis was performed. The hub genes were validated using the polymerase chain reaction and western blotting. A total of 132 and 153 differentially expressed genes were identified in BC cell lines treated with eribulin and paclitaxel, respectively.

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