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Updated: Jul 5, 2026

Optimization of a Multiplex RNA-based Expression Assay Using Breast Cancer Archival Material
Published on: August 1, 2018
Steroid receptor and growth factor receptor expression in human nonsmall cell lung cancers using cells procured by
Alan Kerr1, James F Eliason, James L Wittliff
1Hormone Receptor Laboratory, Department of Biochemistry and Molecular Biology, University of Louisville-HSC, Louisville, KY, USA.
Abstract:
Few biomarkers exist for management of nonsmall cell lung cancers (NSCLC), although estrogen receptor (ERalpha and ERbeta) and EGF receptor (EGFR) expression has been related to clinical outcome. To circumvent problems of cellular heterogeneity in whole tissue, relative gene expression of ERalpha, ERbeta, EGFR, and HER-2 (c-erb-B2) was examined in pure lung carcinoma (LC) cells and normal epithelia by LCM. Cell-specific RNA was isolated and purified for RT-qPCR and microarray. Comparison of NSCLC cells to normal epithelia indicated increased levels of mRNA expression of ERbeta, ERalpha, EGFR, and HER-2 by 31%, 38%, 54%, and 62%, respectively, in LCs. The majority of NSCLC exhibiting low ERalpha and high HER-2 expression were from smokers. Although there was no correlation between ERbeta or EGFR expression and smoking history, there appeared to be an inverse relationship between levels of ERbeta and EGFR mRNAs in normal and neoplastic lung. Additionally, microarray analyses of LCM cells revealed >2,000 genes significantly altered in LC compared with normal epithelia. Herein, differences in NSCLC gene expression and normal lung cells were noted between specimens from gender and smoking groups. Microarray data revealed ERa expression was associated with alterations in <20 genes while ERbeta expression revealed >500 associated genes, suggesting a more prominent role for ERbeta in lung. HER-2 mRNA levels appeared associated with >1,000 genes, while EGFR mRNA levels were associated with far fewer genes. Collectively, results suggest quantitative genomic analyses of pure cell populations allow more accurate interpretation of LC status, which is being correlated with clinical outcome.
