Small non-coding microRNAs (miRNAs) are key components of cancer development and are considered as potential biomarkers for cancer diagnosis and treatment monitoring. This study investigated miRNA expression profiles of human cancer cells in order to develop a screening method for lung cancer. A series of lung cancer related miRNAs (miR-21, miR-145, miR-155, miR-205, miR-210, miR-92, miR-17-5p, miR-143, miR-182, miR-372, let-7a) were selected as candidates for miRNA expression profiles of human lung cancer cell lines (A549, SK-mes-1). MicroRNA u6 was the endogenous control. Cancer cell lines for positive controls; breast MCF-7, prostate Du-145, and glioblastoma U118. The negative control was normal lung fibroblast cell line MRC-5. RT-PCR was performed on StepOnePlus (Applied Biosystem, USA). MiRNA expressions of malignant cells were compared with normal fibroblast cells as well as endogenous control (u6) using the thermal cycle at threshold. Assessment of miRNA expression profiles were then performed using agglomerative hierarchical cluster analysis software (SPSS13, USA). We demonstrated that miR-21, miR-182 and let7-5a were over-expressed, and miR-145 and miR-155 were under-expressed in all cancer cell lines. Combined with the cluster analysis we were able to clearly distinguish cell lines for normal fibroblasts, breast cancer, prostate cancer, glioblastoma, and lung cancer. There is potential utility of screening for lung cancer with miRNA expression profiles. Future work will focus on the sensitivity of such miRNA expression profiles in screening sputum for lung cancer, which can be performed in real time.
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