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Activated amelogenin Y-linked (AMELY) regulation and angiogenesis in human hepatocellular carcinoma by biocomputation

Authors :
Lianxiu Qi
Minghu Jiang
Zhenfu Jiang
Lin Wang
Xiaohe Li
Huilei Zhou
Haizhen Diao
Juxiang Huang
Source :
Oncology Letters
Publication Year :
2013
Publisher :
D.A. Spandidos, 2013.

Abstract

In the present study, a comparison of the biological processes and gene ontology (GO) in human hepatocellular carcinoma (HCC) with high expression (fold change ≥2) of amelogenin Y-linked (AMELY)-activated upstream regulation networks with non-tumor hepatitis/cirrhotic tissues (HBV or HCV infection) with low expression of activated networks was performed. The principle biological processes involved in non-tumor hepatitis/cirrhotic tissues include positive regulation of mismatch repair, regulation of transcription from RNA polymerase II promoters, negative regulation of cell-cell adhesion, protein ubiquitinatin and protein catabolism. The main biological processes involved in the development of HCC include positive regulation of calcium ion transport into the cytosol, cell proliferation, DNA replication, fibroblast proliferation, immune response, microtubule polymerization and protein secretion. Specific transcription from RNA polymerase II promoters, regulation of angiogenesis, cell growth, protein metabolism, Wnt receptor signaling pathways, negative regulation of endothelial cell differentiation, microtubule depolymerization, peptidase activity and progression through the cell cycle are also involved. Positive regulation of transcription is involved in both processes. An activated AMELY-coupled upstream positive regulation of immune response-mediated protein secretion to Wnt signaling and calcium into cytosol-induced regulation of cell growth and angiogenesis in HCC is proposed. The AMELY upstream regulation molecular network model was constructed with BUB1B, CST6, ESM1, HOXA5, LEF1, MAPT, MYBL2, NOTCH3, PLA2G1B, PROK1, ROBO1, SCML2 and UBE2C in HCC from a Gene Expression Omnibus (GEO) dataset by gene regulation network inference methods and our programming methods.

Details

Language :
English
ISSN :
17921082 and 17921074
Volume :
5
Issue :
3
Database :
OpenAIRE
Journal :
Oncology Letters
Accession number :
edsair.doi.dedup.....a8fefc5b9e6a0df131f03108c4d54069