4.5 Article

The expression and prognostic significance of Drp1 in lung cancer A bioinformatics analysis and immunohistochemistry

Journal

MEDICINE
Volume 98, Issue 48, Pages -

Publisher

LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/MD.0000000000018228

Keywords

Drp1; lung cancer; prognosis

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Background: Dynamin-related protein 1 (Drp1) plays important roles in tumorigenesis, including lung cancer. However, the effect of Drp1 in lung cancer remains unclear. The present study was aimed to investigate the clinical significance and effect of Drp1 on prognosis of lung cancer. Methods: Oncomine and The Cancer Genome Atlas (TCGA) databases were selected to predict the differential expression levels of Drp1 in lung cancer. Then, 70 cases of lung cancer and normal tissues were collected and immunohistochemistry was used to detect the expression of Drp1. In addition, Kaplan-Meier Plotter database and TCGA database were used to verify the correlation between Drp1 expression and the clinical prognosis in lung cancer patients. Results: Drp1 was significantly overexpressed in lung cancer tissues based on Oncomine and TCGA databases (P<.05). Moreover, results from immunohistochemistry showed that Drp1 protein level in lung cancer was also significantly higher than that in the matched normal tissues (P<.05). Prognostic analysis from Kaplan-Meier Plotter database with the chosen probe IDs of 203105_s_at suggested that Drp1 was negatively correlated to overall survival (OS) of lung cancer patients (HR= 1.16, 95% CI: 1.02-1.31; P=.025), but not in the probe IDs of 226154_at (HR=0.86, 95% CI: 0.73-1.01; P=.069). However, prognosis from TCGA database showed inconsistent results in which high expression of Drp1 was correlated with worse survival probability of all, male, female in lung adenocarcinoma (P<.05), but not in LUSC (P>.05). Conclusion: Drp1 was highly expressed in lung cancer based on bioinformatics analysis and tissue microarray, but there was a lot of inconsistency in prognosis depending on different levels of Drp1 from the bioinformatics analysis.

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