Xin-Yang He, Jun Zhao, Zhi-Qiang Chen, Rong Jin, Cheng-Ye Liu
Department of General Surgery, The First Affiliated Hospital of University of Science and Technology of China (Anhui Provincial Hospital), Hefei, Anhui, China (mainland)
Med Sci Monit 2018; 24: LBR2244-2251
Available online: 2018-04-14
To explore the expression level of retinoic acid induced 14 (RAI14) in gastric cancer (GC) patients and its potentially clinical prognostic value.
MATERIAL AND METHODS: Initially, The Cancer Genome Atlas (TCGA) and Oncomine databases were mined to examine the differential expression levels and clinical prognostic significance of RAI14 mRNA in GC patients. Subsequently, 68 cases of GC and paired adjacent normal tissues were collected retrospectively, and the expression level of RAI14 protein was detected by immunohistochemical staining. In addition, Kaplan-Meier univariate and Cox multivariate survival analyses were used to verify the correlation between RAI14 expression and clinicopathological parameters in GC patients and its clinical prognostic significance.
RESULTS: TCGA and GEO (from Oncomine database) data mining results found that RAI14 mRNA level was remarkably higher in GC than normal gastric tissues (All P<0.05). Besides, immunohistochemical results detected that RAI14 protein level in GC was dramatically higher (P=0.004) compared to that in the matched normal tissues. Moreover, TCGA database and Kaplan-Meier Plotter mining results showed that compared to those with RAI14 low mRNA expression levels, GC patients with RAI14 high mRNA expression levels had remarkably lower time of both overall survival and disease-free survival (All P<0.05). Additionally, based on the immunohistochemical results, Kaplan-Meier univariate and Cox multivariate survival analyses indicated that high expression of RAI14 was the only independent predictor of unfavorable prognosis in patients with gastric cancer (P=0.000).
CONCLUSIONS: RAI14 was highly expressed in GC, and the high expression of RAI14 could be an independent predictor of poor prognosis in GC patients.
Keywords: Prognosis, gastric cancer, bioinformatics, RAI14