Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/14263
Title: In-silico analysis of EGFR-associated microRNA signature in cancer
Authors: Wang, F
Chan, L 
Law, HKW 
Wong, C 
Yip, SP 
Yung, BYM 
Cho, WCS
Keywords: EGFR
EGFR signaling pathway
MiRNA
Multiple linear regression
Issue Date: 2013
Source: Proceedings - 2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013, 2013, 6732612, p. 7-12 How to cite?
Abstract: Epidermal growth factor receptor (EGFR) is often overexpressed or mutated in human carcinomas. The EGFR signaling pathway plays a vital role in regulation of cell proliferation and apoptosis. At the moment the existing anticancer drugs for EGFR are limited or not effective. It is important to develop novel approaches to inhibiting the expression of EGFR and its signaling pathway. Recently, researchers have considered investigating EGFR down-regulation by microRNAs (miRNAs), single-stranded noncoding RNA molecules with about 22 nucleotides long. In this study, in-silico strategies were used to identify an eight-EGFR-associated-miRNA signature. We also studied the association of this miRNA signature and the directly interacting partners of EGFR. We investigated the functional role of this miRNA signature using the multiple linear regression analysis based on the expression profiles between mRNAs and their corresponding miRNAs, to verify if the regression coefficients would implicate the functional miRNA-mRNA relationships. The results showed that four potential miRNAs (miR-27a, miR-155, miR-27b and miR-7) positively or negatively associated with the expression of EGFR and its interacting partner PIK3CA were found in the cancer group, but not in the normal group. Our findings will contribute to the exploration of cancer mechanisms, as well as identification of cancer treatment targets and diagnostic markers.
Description: 2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013, Shanghai, 18-21 December 2013
URI: http://hdl.handle.net/10397/14263
ISBN: 9781479913091
DOI: 10.1109/BIBM.2013.6732612
Appears in Collections:Conference Paper

Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page view(s)

42
Last Week
2
Last month
Checked on Aug 20, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.