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Published on: April 6, 2016
Exploring microRNA-mediated alteration of EGFR signaling pathway in non-small cell lung cancer using an mRNA:miRNA
Fengfeng Wang1, Lawrence W C Chan1, Helen K W Law1
1Department of Health Technology and Informatics, Hong Kong Polytechnic University, Hong Kong, China.
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 (R(2)) 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.
Insights
This study introduces a novel regression model to analyze microRNA (miRNA) roles in non-small cell lung cancer (NSCLC) EGFR signaling. The model identifies specific miRNAs associated with key growth factors, aiding in understanding cancer development and treatment.
Area of Science:
- Oncology
- Molecular Biology
- Bioinformatics
Background:
- Non-small cell lung cancer (NSCLC) progression and treatment are influenced by the epidermal growth factor receptor (EGFR) signaling pathway and microRNAs (miRNAs).
- Existing microarray analysis methods may not fully capture the complex interplay between mRNA and miRNA expression.
- Understanding these interactions is crucial for developing targeted therapies.
Purpose of the Study:
- To develop and validate a novel mRNA:miRNA stepwise regression model for exploring miRNA functions within the EGFR signaling pathway in NSCLC.
- To identify specific miRNAs associated with key components of the EGFR pathway, such as epidermal growth factor (EGF) and protein tyrosine kinase 2 (PTK2).
- To assess the model's performance in distinguishing between oncomiRs and tumor suppressor miRs in NSCLC.
Main Methods:
- Development of an mRNA:miRNA stepwise regression model incorporating miRNA target prediction databases.
- Application of the model to microarray data from pre- and post-surgery NSCLC patient groups.
- Statistical validation using coefficient of determination (R²) and leave-one-out cross-validation (LOOCV).
Main Results:
- The regression model demonstrated good performance, with significant R² and LOOCV values.
- miR-145 was found to be positively associated with epidermal growth factor (EGF) in the pre-surgery NSCLC cohort.
- miR-199a-5p showed a positive association with EGF in the post-surgery NSCLC cohort, while miR-495 was positively associated with protein tyrosine kinase 2 (PTK2) in both groups.
Conclusions:
- The developed regression model effectively deciphers complex mRNA:miRNA interactions within the EGFR pathway in NSCLC.
- Specific miRNAs, including miR-145, miR-199a-5p, and miR-495, play significant roles in NSCLC pathogenesis.
- The model's ability to identify miRNA functions as oncomiRs or tumor suppressors offers potential for novel diagnostic and therapeutic strategies in NSCLC.
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