OBJECTIVE: To identify new molecular diagnostic markers for non-small cell lung carcinoma (NSCLC) by analyzing microRNA (miRNA) expression profile differences in samples from NSCLC patients and adults with nonneoplastic diseases. STUDY DESIGN: miRNA expression was studied in archival formalin-fixed, paraffin-embedded tissues by microarray and confirmed by real-time PCR analysis of NSCLC and normal lung tissues. An algorithm for discriminating normal, squamous cell carcinoma (SQCC), and adenocarcinoma (ADC) tissue was derived from miRNA expression studies and applied towards characterization of poorly differentiated NSCLC samples. RESULTS: Microarray data from a genome-wide scan revealed 34 differentially expressed miRNAs, 5 of which enabled algorithmic discrimination of normal tissue from carcinoma (SQCC or ADC), as well as SQCC from ADC. Expression of miR-21 was significantly increased in both tumor types, whereas levels of miR-451 and miR-486-5p were reduced. SQCC was distinguished from normal tissue and ADC by high-level miR-205 expression and decreased miR-26b. Comparison of miRNA profiles to histological and immunohistochemical findings in 19 poorly differentiated specimens demonstrated the potential clinical utility of miRNA profiling to provide important insights into the classification of SQCC and ADC. CONCLUSION: This study presents a novel algorithm for specimen classification in cases of poorly differentiated NSCLC.
OBJECTIVE: To identify new molecular diagnostic markers for non-small cell lung carcinoma (NSCLC) by analyzing microRNA (miRNA) expression profile differences in samples from NSCLCpatients and adults with nonneoplastic diseases. STUDY DESIGN: miRNA expression was studied in archival formalin-fixed, paraffin-embedded tissues by microarray and confirmed by real-time PCR analysis of NSCLC and normal lung tissues. An algorithm for discriminating normal, squamous cell carcinoma (SQCC), and adenocarcinoma (ADC) tissue was derived from miRNA expression studies and applied towards characterization of poorly differentiated NSCLC samples. RESULTS: Microarray data from a genome-wide scan revealed 34 differentially expressed miRNAs, 5 of which enabled algorithmic discrimination of normal tissue from carcinoma (SQCC or ADC), as well as SQCC from ADC. Expression of miR-21 was significantly increased in both tumor types, whereas levels of miR-451 and miR-486-5p were reduced. SQCC was distinguished from normal tissue and ADC by high-level miR-205 expression and decreased miR-26b. Comparison of miRNA profiles to histological and immunohistochemical findings in 19 poorly differentiated specimens demonstrated the potential clinical utility of miRNA profiling to provide important insights into the classification of SQCC and ADC. CONCLUSION: This study presents a novel algorithm for specimen classification in cases of poorly differentiated NSCLC.
Authors: Maria Sromek; Maciej Glogowski; Magdalena Chechlinska; Mariusz Kulinczak; Lukasz Szafron; Klara Zakrzewska; Joanna Owczarek; Piotr Wisniewski; Robert Wlodarczyk; Lukasz Talarek; Maciej Turski; Jan Konrad Siwicki Journal: Cell Oncol (Dordr) Date: 2017-06-20 Impact factor: 6.730