Research Article: Nuclear Receptor Expression Defines a Set of Prognostic Biomarkers for Lung Cancer

Date Published: December 14, 2010

Publisher: Public Library of Science

Author(s): Yangsik Jeong, Yang Xie, Guanghua Xiao, Carmen Behrens, Luc Girard, Ignacio I. Wistuba, John D. Minna, David J. Mangelsdorf, William Pao

Abstract: David Mangelsdorf and colleagues show that nuclear receptor expression is strongly associated with clinical outcomes of lung cancer patients, and this expression profile is a potential prognostic signature for lung cancer patient survival time, particularly for individuals with early stage disease.

Partial Text: The prevalence of lung cancer as the primary cause of cancer death in the United States has led to renewed efforts to obtain biomarker signatures that provide either prognostic or predictive information to guide therapy for individual patients (i.e., “personalized medicine”) [1]–[3]. Multiple genome-wide expression studies have demonstrated the usefulness of this approach for lung cancer prognosis [4]–[6]. However, in general, each of these studies has identified different sets of genes, even when the various studies are used to cross-validate one another, and in the majority of these studies the individual genes identified have had little impact for understanding tumor pathogenesis or as therapeutic targets. Thus, identification of prognostic biomarkers that also provide hypotheses for mechanism-based studies of carcinogenesis and offer new therapeutic targets (sometimes referred to as “theragnostics”) would be of significant benefit.

In this study, we investigated the expression of NRs in lung cancer and found that specifically targeting this superfamily of ligand-dependent transcription factors provided a novel prognostic biomarker. Several recent studies using genome-wide microarray experiments have proposed various sets of genetic signatures for lung cancer prognosis [4]–[6],[29]–[31]. Interestingly, the gene signatures from these studies have shared little if any overlap with one another [4],[5],[29]. In addition, because of the open-ended nature of genome-wide analyses, the signatures have provided little insight into the pathogenesis or pathophysiology of lung cancer. Moreover, these studies have yet to identify new therapeutic targets. In contrast, NRs represent a well-studied class of proteins that (1) govern complex cellular programs such as differentiation, inflammation, and metabolism [9]–[13], (2) are known transcriptional drivers of oncogenesis, and (3) are themselves the targets of validated drugs for many diseases including cancer [32]–[35]. This superfamily also includes a number of orphan receptors, many of which are currently being evaluated as potential new therapeutic targets for a number of diseases [8]. Thus, our study suggests that specifically targeting NRs may provide an alternative and clinically relevant new strategy for profiling lung tumors.



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