14 June 2020 : Database Analysis
Prediction of MiR-21-5p in Promoting the Development of Lung Adenocarcinoma via PDZD2 Regulation
Shengjin Cui1ACDEG*, Shuang Lou1BE, Weiquan Guo1C, Shihui Jian2B, Yunfeng Wu1D, Xintong Liu1F, Xi Lan1F, Xingwang Jia1AGDOI: 10.12659/MSM.923366
Med Sci Monit 2020; 26:e923366
Abstract
BACKGROUND: Lung adenocarcinoma currently accounts for the highest cancer-related mortality rate worldwide. MiR-21-5p has a vital role in various types of cancers. We have analyzed the miR-21-5p expression level, prognosis, and associated molecular pathways in lung adenocarcinoma with multiple bioinformatics databases.
MATERIAL AND METHODS: The Cancer Genome Atlas (TCGA) database was employed to fetch the miR-21-5p expression profile in multiple tumors. We used the UALCAN platform to assess the differential regulation of the miR-21-5p in healthy tissue and lung adenocarcinoma. Also, the survival prognosis of the miR-21-5p in each stage of lung adenocarcinoma was done by the Kaplan-Meier database. The STARBASE and UALCAN databases were employed to predict the miR-21-5p target genes, and the levels of target genes and their prognostic value were analyzed.
RESULTS: MiR-21-5p was overexpressed in the majority of human cancers. MiR-21-5p demonstrated escalated expression in the lung adenocarcinoma tissue in contrast to the normal tissue (P<0.05). Poor prognosis was witnessed in the miR-21-5p high expression group as compared to the low expression group (hazard ratio [HR]= 1.59, P<0.05). PDZD2 was predicted as a miR-21-5p potential target. We found a negative correlation between PDZD2 and miR-21-5p (r=–0.255, P<0.05). PDZD2 was downregulated in lung adenocarcinoma (P<0.05). Overexpression of PDZD2 was associated with a better prognosis of survival in lung adenocarcinoma patients (HR=0.45, P<0.05).
CONCLUSIONS: MiR-21-5p exhibits the potential to act as a biomarker for the survival prognosis of lung adenocarcinoma. It might be responsible for the onset and progression of lung adenocarcinoma through PDZD2 regulation.
Keywords: PDZ Domains, Adenocarcinoma of Lung, Cell Adhesion Molecules, Databases, Factual, Databases, Genetic, Proportional Hazards Models
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