MicroRNA Gene Dosage Alterations and Drug Response in Lung Cancer

Katey S S Enfield,Wan L Lam,Carlos E Alvarez,Stephen Lam,Larissa A Pikor,Greg L Stewart,Raj Chari

doi:10.1155/2011/474632

Katey S S Enfield, Wan L Lam + Show 5 more

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https://doi.org/10.1155/2011/474632

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Abstract

Chemotherapy resistance is a key contributor to the dismal prognoses for lung cancer patients. While the majority of studies have focused on sequence mutations and expression changes in protein-coding genes, recent reports have suggested that microRNA (miRNA) expression changes also play an influential role in chemotherapy response. However, the role of genetic alterations at miRNA loci in the context of chemotherapy response has yet to be investigated. In this study, we demonstrate the application of an integrative, multidimensional approach in order to identify miRNAs that are associated with chemotherapeutic resistance and sensitivity utilizing publicly available drug response, miRNA loci copy number, miRNA expression, and mRNA expression data from independent resources. By instigating a logical stepwise strategy, we have identified specific miRNAs that are associated with resistance to several chemotherapeutic agents and provide a proof of principle demonstration of how these various databases may be exploited to derive relevant pharmacogenomic results.

Highlights

Lung cancer is the most common cause of cancer-related deaths worldwide, with a five-year survival rate of less than 15% [1]
We have performed an integrative analysis of genomewide miRNA copy number, miRNA expression, mRNA expression, and drug sensitivity data from 18 different chemotherapeutics on a panel of lung cancer cell lines to identify miRNAs that are significantly different at the copy number and expression levels between the most sensitive and resistant cell lines for a given drug
We have demonstrated our method of integrative analysis of multiple dimensions of data including genome-wide miRNA copy number, miRNA expression, mRNA expression, and drug sensitivity data, all available in the public domain, can be a powerful tool to identify miRNAs and genes involved in drug sensitivity

Summary

Introduction

Lung cancer is the most common cause of cancer-related deaths worldwide, with a five-year survival rate of less than 15% [1]. The high incidence of late-stage diagnosis and a lack of efficient therapeutic strategies remain key contributors to the dismal survival statistics. To improve lung cancer patient outcome, improvement in early detection and a better understanding of the underlying tumor biology that governs response to therapy are necessary. Response to systemic therapy has been shown to be strongly associated with a variety of clinical and molecular features. The chemotherapeutics Avastin and Permetrexed have shown differential response or adverse effects in different histological subtypes of lung cancer [2, 3]. Tyrosine kinase inhibitors (TKIs) targeting the epidermal growth factor receptor (EGFR) have shown preferential efficacy in Asian females who typically harbor sequence mutations in EGFR as well as those individuals who harbored EGFR amplifications, EGFR mutations, and the absence of KRAS mutations [4,5,6]

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