Accurate classification of non-small cell lung carcinoma using a novel microRNA-based approach

Purpose: Advances in targeted lung cancer therapy now demand accurate classification of non-small cell lung cancer (NSCLC). MicroRNAs (miRNA) are recently discovered short, noncoding genes that play essential roles in tissue differentiation during normal development and tumorigenesis. For example, hsa-miR-205 is a miRNA that is highly expressed in lung squamous cell carcinomas (SqCC) but not in lung adenocarcinomas. The differential expression of miRNAs could be exploited to distinguish these tumor types. Experimental Design: One hundred and two resected NSCLCs were classified as SqCC or adenocarcinoma based on their histologic features and immunohistochemical profiles. Corresponding preoperative biopsies/aspirates that had been originally diagnosed as poorly differentiated NSCLCs were available for 21 cases. A quantitative reverse transcription-PCR diagnostic assay that measures the expression level of hsa-miR-205 was used to classify the carcinomas as SqCC or adenocarcinoma based solely on expression levels. The two sets of diagnoses were compared. Results: Using standard pathologic methods of classification (i.e., microscopy and immunohistochemistry), 52 resected lung carcinomas were classified as SqCCs and 50 as adenocarcinomas. There was 100% concordance between the diagnoses established by conventional and miRNA-based methods. MiRNA profiling also correctly classified 20 of the 21 preoperative biopsy specimens. Conclusions: MiRNA profiling is a highly reliable strategy for classifying NSCLCs. Indeed, classification is consistently accurate even in small biopsies/aspirates of poorly differentiated tumors. Confirmation of its reliability across the full range of tumor grades and specimen types represents an important step toward broad application.