Bioinformatic analysis of prognostic value of ZW10 interacting protein in lung cancer
Received 19 August 2017
Accepted for publication 13 December 2017
Published 23 March 2018 Volume 2018:11 Pages 1683—1695
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Ingrid Espinoza
Wen Yuan,1,2,* Songping Xie,3,* Meng Wang,2 Shan Pan,2 Xiaoxing Huang,2 Meng Xiong,2 Rui-jing Xiao,2 Jie Xiong,2 Qiu-ping Zhang,2 Liang Shao1
1Department of Internal Medicine, Zhongnan Hospital of Wuhan University, 2Department of Immunology, Basic School, Wuhan University, 3Department of Thoracic Surgery, Renmin Hospital of Wuhan University, Wuhan, People’s Republic of China
*These authors contributed equally to this work
Background: ZWINT is a crucial component of the mitotic checkpoint. However, its possible role in lung cancer is unclear. In this study, we determined its correlation with lung cancer.
Methods: Real-time PCR and immunohistochemistry (IHC) were used to determine 40 collected clinical lung cancer samples. Chi-square test was used to examine possible correlations between ZWINT expression and clinicopathological factors. The prognostic significance of mRNA expression of ZWINT in lung cancer was evaluated using the Kaplan–Meier plotter. Univariate and multivariate Cox proportional hazards regression analysis were performed to determine whether ZWINT is an independent risk factor for overall survival (OS) and disease-free survival (DFS) of lung cancer patients. Additionally, STRING database was used to analyze protein-protein interactions.
Results: In this study, we screened 13 GSE datasets and detected that ZWINT is highly expressed in multiple carcinomas including lung, melanoma, prostate, nasopharyngeal, gastric, pancreatic, colon, esophageal, ovarian, renal, breast and liver cancer. Real-time PCR and IHC results of collected clinical lung cancer samples confirmed that ZWINT is highly expressed in tumor tissues compared with adjacent non-tumor tissues. Additionally, high expression of ZWINT might predict poor OS and DFS in lung cancer patients. Moreover, disease stage and expression level of ZWINT were correlated with recurrence-free survival and OS in lung cancer. Analysis of protein-protein interaction based on STRING database gained 8 top genes which could interact with ZWINT, including PMF1, MIS12, DSN1, ZW10, BUB1, BUB1B, CASC5, NDC80, NSL1 and NUF2.
Conclusion: ZWINT is aberrantly highly expressed in lung tumor tissues and might be involved in the pathogenesis of lung cancer.
Keywords: ZWINT, lung cancer, prognosis, overall survival, recurrence-free survival
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