Background: Lung cancer continues to be one of the top five causes of cancer-related mortality. This study aims to identify down- and upregulated miRNAs and mRNA which can be used as potential biomarkers and/or therapeutic targets for lung cancer.
Methods: Integrated analysis of differential expression profiles of miRNA and mRNA in lung cancer was performed by searching Gene Expression Omnibus datasets. Based on miRNA expression profiles, direct mRNA targets of miRNAs with experimental support were identified through miRTarBase. The levels of representative miRNAs and mRNAs were confirmed through qualitative real-time reverse transcriptase polymerase chain reaction (qRT-PCR).
Results: The miR-33a was decreased in non-small cell lung cancer (NSCLC) tissues compared with the para-carcinoma tissues, whereas its target mRNA of cullin-associated NEDD8-dissociated protein 1 (CAND1) was increased in NSCLC tissues. Further research has shown that miR-33a can inhibit lung cancer cell proliferation, cell cycle progression, and migration by targeting CAND1. Moreover, the CAND1 knockout lung cancer cells showed similar results as cells transfected with miR-33a mimic.
Conclusions: These results suggested that the data mining based on online databases was an effective method in finding novel target in cancer research, and the miR-33a and CAND1 played an important role in lung cancer proliferation and cell migration.
Keywords: CAND1; Data mining; Lung cancer; miR-33a.