Background: Current developments in the targeted therapies of non-small-cell lung carcinoma demand accurate classification to dodge the adverse drug response and to yield maximum therapeutic outcome. Accurate classification depends on the classical hematoxylin and eosin staining and immunohistochemistry techniques. In selected critical cases, inter-observer variability, lack of standardization, tumor heterogeneity, and degree of differentiation makes it difficult to classify NSCLC. During the last decade, microRNAs (miRNAs) have been proven to be a promising biomarker in the field of oncology from diagnosis to therapy. The present study developed a binary classification method based on the expression of three well-known miRNAs: miR-205, miR-196b, miR-375, since it is the most demanding criteria to the clinicians trying to provide better therapy to the patients. Methods: Quantitative real-time polymerase chain reaction was performed for 90 NSCLC samples. Receiver-Operator Characteristic Curve and Discriminant Function Analysis was done to classify the NSCLC. A discriminant formula was developed to calculate the Z-score of miR-375 (Z3 = −0.637 + (0.439 x NCt miR-375) + (−0.245 x NCt miR-21).
CITATION STYLE
Bhaumik, S., Ahmad, F., & Das, B. R. (2017). Molecular binary classification of NSCLC: miR-375 is a potential biomarker to differentiate SQCC from ADCC in Indian NSCLC patients. Applied Cancer Research, 37(1). https://doi.org/10.1186/s41241-017-0034-8
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