Expression of gemcitabine and cisplatin-related genes according to histology and stage in non-small-cell lung cancer (NSCLC)

Background: A number of pharmacogenomic studies have been recently carried out to find out a possible relationship between gene expression and treatment outcome in NSCLC; however, to our knowledge, no data are available on the possible influence of tumor histology and tumor stage on gene expression profile. The aim of this study was the characterization of the expression pattern of genes involved in gemcitabine and cisplatin activity in primary or metastatic adenocarcinoma or squamous carcinoma NSCLC specimens. Methods: Excision repair cross-complementing 1 (ERCC1), human equilibrative nucleoside transporter-1 (hENT1), deoxycytidine kinase (dCK), 5’-nucleotidase (5’-NT), cytidine deaminase (CDA), and ribonucleotide reductase subunits M1 and M2 (RRM1 and RRM2) were analyzed by quantitative RT-PCR in 89 laser microdissected lung tissues (52 primary tumors, 23 metastatic lymph nodes and 14 normal lung tissues), from 69 patients. β-actin was used as housekeeping gene. Results: The quantitative expression analysis in patients’ samples demonstrated that these target genes were detectable in most surgical specimens. hENT1, CDA and dCK expression was significantly lower in normal than in tumor tissues (p<0.05). A difference in mean CDA expression was also found between tumor (1.015±0.015) and node metastasis (0.965±0.019). Furthermore, a significant (p<0.05) variability of mean gene expression was observed between adenocarcinoma and squamous cell carcinoma with respect to 5’-NT, RRM1 and RRM2. In particular, the mean gene expression values of both RRM1 and RRM2 were significantly higher in squamous cell carcinomas with respect to adenocarcinomas, while 5’-NT expression values were significantly higher in adenocarcinomas. Conclusions: We have identified the differences in expression of gemcitabine and cisplatin-related genes due to tumor stage and histology. The knowledge of these variations in gene profiles should be be taken into account for pharmacogenomic data interpretation and must be considered in predicting gemcitabine/cisplatin efficacy and in personalizing treatment for lung cancer patients.