Abstract

We aim to use the microRNA (miRNA, micro-ribonucleic acid) data of lung cancer tissues to establish a miRNA biomarker database for lung cancer that can be used for marker screening and analysis of lung cancer prognosis. We obtained lung cancer-related data from The Cancer Genome Atlas (TCGA) and analyzed the miRNA expression profiles of lung cancer tissues and normal tissues using bioinformatics techniques to develop a new composite miRNA-based model for the prognostic assessment of lung cancer. The predictive power of this model was verified and evaluated based on grouping of data. We also performed RT-qPCR using lung cancer tissues from patients diagnosed with lung cancer. There was a significant difference between the miRNA expression profiles of lung cancer tissues and normal tissues adjacent to the cancerous lesions. The prognostic survival of patients with lung cancer was closely related to onset age and staging (p = 0.012) but was not related to gender (p = 0.39) and race (p = 0.51). Using three methods of survival model construction, we identified three miRNA composites, namely hsa-mir-21, hsa-mir-141, and has-mir-490, as markers for the prognosis of lung cancer. As confirmed by RT-qPCR, the expressions of hsa-miR-21-5p and hsa-miR-141-5p were upregulated, whereas hsa-miR-490-3p expression was downregulated in lung cancer lesion tissues. The three miRNA composites identified, namely hsa-mir-21, hsa-mir-141, and hsa-mir-490, have the potential to serve as novel prognostic biomarkers and therapeutic targets for lung cancer.

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