Research Article

Expression profiles of variation integration genes in bladder urothelial carcinoma

Published: April 30, 2014
Genet. Mol. Res. 13 (2) : 3486-3494 DOI: https://doi.org/10.4238/2014.April.30.9
Cite this Article:
J.M. Wang, Y.Q. Wang, Z.L. Gao, J.T. Wu, B.K. Shi, C.C. Yu (2014). Expression profiles of variation integration genes in bladder urothelial carcinoma. Genet. Mol. Res. 13(2): 3486-3494. https://doi.org/10.4238/2014.April.30.9
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Abstract

Bladder cancer is a common cancer worldwide and its incidence continues to increase. There are approximately 261,000 cases of bladder cancer resulting in 115,000 deaths annually. This study aimed to integrate bladder cancer genome copy number variation information and bladder cancer gene transcription level expression data to construct a causal-target module network of the range of bladder cancer-related genomes. Here, we explored the control mechanism underlying bladder cancer phenotype expression regulation by the major bladder cancer genes. We selected 22 modules as the initial module network to expand the search to screen more networks. After bootstrapping 100 times, we obtained 16 key regulators. These 16 key candidate regulatory genes were further expanded to identify the expression changes of 11,676 genes in 275 modules, which may all have the same regulation. In conclusion, a series of modules associated with the terms ‘cancer’ or ‘bladder’ were considered to constitute a potential network.

Bladder cancer is a common cancer worldwide and its incidence continues to increase. There are approximately 261,000 cases of bladder cancer resulting in 115,000 deaths annually. This study aimed to integrate bladder cancer genome copy number variation information and bladder cancer gene transcription level expression data to construct a causal-target module network of the range of bladder cancer-related genomes. Here, we explored the control mechanism underlying bladder cancer phenotype expression regulation by the major bladder cancer genes. We selected 22 modules as the initial module network to expand the search to screen more networks. After bootstrapping 100 times, we obtained 16 key regulators. These 16 key candidate regulatory genes were further expanded to identify the expression changes of 11,676 genes in 275 modules, which may all have the same regulation. In conclusion, a series of modules associated with the terms ‘cancer’ or ‘bladder’ were considered to constitute a potential network.