Exploring microRNA-mediated alteration of EGFR signaling pathway in non-small cell lung cancer using an mRNA: MiRNA regression model supported by target prediction databases

Fengfeng Wang, Wing Chi Chan, Ka Wai Helen Law, William C.S. Cho, Petrus Tang, Jun Yu, Chi Ren Shyu, Sze Chuen Cesar Wong, Shea Ping Yip, Yat Ming Yung

Research output: Journal article publicationJournal articleAcademic researchpeer-review

21 Citations (Scopus)

Abstract

EGFR signaling pathway and microRNAs (miRNAs) are two important factors for development and treatment in non-small cell lung cancer (NSCLC). Microarray analysis enables the genome-wide expression profiling. However, the information from microarray data may not be fully deciphered through the existing approaches. In this study we present an mRNA:miRNA stepwise regression model supported by miRNA target prediction databases. This model is applied to explore the roles of miRNAs in the EGFR signaling pathway. The results show that miR-145 is positively associated with epidermal growth factor (EGF) in the pre-surgery NSCLC group and miR-199a-5p is positively associated with EGF in the post-surgery NSCLC group. Surprisingly, miR-495 is positively associated with protein tyrosine kinase 2 (PTK2) in both groups. The coefficient of determination (R2) and leave-one-out cross-validation (LOOCV) demonstrate good performance of our regression model, indicating that it can identify the miRNA roles as oncomirs and tumor suppressor mirs in NSCLC.
Original languageEnglish
Pages (from-to)504-511
Number of pages8
JournalGenomics
Volume104
Issue number6
DOIs
Publication statusPublished - 1 Jan 2014

Keywords

  • EGFR signaling pathway
  • Microarray analysis
  • MiRNA
  • Non-small cell lung cancer
  • Regression model

ASJC Scopus subject areas

  • Genetics

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