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Статья в Китайский | WPRIM | ID: wpr-821739

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Objective@#To investigate the expression of IFIT2 (interferon-induced protein with tetratricopeptide repeats 2) in human lung cancer tissue and analyze the relationship between the IFIT2 expression and clinicopathological features and prognosis. @*Methods@#Tissue microarray and immunofluorescence staining were used to examine the IFIT2 expression in lung cancer tissue and their adjacent tissues. Wilcoxon rank test was used to compare the IFIT2 expression in lung cancer and corresponding adjacent tissues. The chi-square test was used to analyze the relationship between the IFIT2 expression in lung cancer tissues and clinicopathological features of the patients. Kaplan-Meier survival analysis was performed to analyze the correlation between IFIT2 expression and patients′ overall survival. Cox model was used to analyze the correlation between different clinical parameters and prognosis. @*Results@#There was significant difference for the IFIT2 expression between the lung cancer tissues and adjacent tissues (P<0.01). There was no significant correlation between IFIT2 expression and clinicopathological features of patients (P>0.05). In lung adenocarcinoma and squamous cell carcinoma, Kaplan-Merier survival analysis showed that the overall survival (OS) of patients in IFIT2 low expression group was significantly shorter than that in IFIT2 high expression group (HR=2.392, 95%CI: 1.103-5.186, P=0.027; HR=2.907, 95%CI: 1.118-7.559, P=0.029, respectively). Multi-factor Cox model analysis indicated that distant metastasis (HR=8.033, 95% CI: 3.664-17.614, P=0.000) was independent prognostic factors for lung adenocarcinoma, lymph node metastasis (HR=3.390, 95% CI: 1.029-11.175, P=0.045) and IFIT2 low expression (HR=3.762,95%CI: 1.236-11.451, P=0.020) were independent prognostic factors for lung squamous cell carcinoma. @*Conclusion@#The down-regulated expression of IFIT2 in lung cancer tissues suggests that it may play an important role in initiation and development of lung cancer. It could be used as a valuable risk factor to predict the prognosis of lung cancer patients.

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