Validation for histology-driven diagnosis in non-small cell lung cancer using hsa-miR-205 and hsa-miR-21 expression by two different normalization strategies

Targeted therapy of non-small cell lung cancer (NSCLC) demands a more accurate tumor classification that is crucial for patient selection in personalized treatment. MicroRNAs constitute a promising class of biomarkers and a helpful tool for the distinction between lung adenocarcinoma (AC) and squamous cell lung carcinoma (SCC). The aim of this study was to evaluate the impact of two different normalization strategies, using U6 snRNA and hsa-miR-103 as reference genes, on hsa-miR-205 and hsa-miR-21 expression levels, in terms of the classification of subtypes of NSCLC. By means of a quantitative real-time polymerase chain reaction (qRT-PCR) microRNA expression levels were evaluated in a classification set of 98 surgically resected NSCLC fresh-frozen samples, and validated findings in an independent set of 42 NSCLC samples. The microRNA expression levels were exploited to develop a diagnostic test using two data normalization strategies. The performance of microRNA profiling in different normalization methods was compared. We revealed the microRNA-based qRT-PCR tests to be appropriate measures for distinguishing between AC and SCC (the concordance of histologic diagnoses and molecular methods greater than 88%). Performance evaluation of microRNA tests, based on the two normalization strategies, showed that the procedure using hsa-miR-103 as reference target has a slight advantage (sensitivity 83.33 and 100% in classification and validation set, respectively) compared to U6 snRNA. Molecular tests based on microRNA expression allow a reliable classification of subtypes for NSCLC and can constitute a useful diagnostic strategy in patient selection for targeted therapy.