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Medical Science Monitor Basic Research


eISSN: 1643-3750

Value of Ferritin Heavy Chain (FTH1) Expression in Diagnosis and Prognosis of Renal Cell Carcinoma

Huimei Huang, Yuyun Qiu, Guilian Huang, Xiaohui Zhou, Xiaoying Zhou, Wenqi Luo

Department of Pathology, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, Guangxi, China (mainland)

Med Sci Monit 2019; 25:3700-3715

DOI: 10.12659/MSM.914162

Available online: 2019-05-19

Published: 2019-05-19


BACKGROUND: Serum ferritin is a useful tumor marker for renal cell carcinoma (RCC). However, the expression of ferritin heavy chain (FTH1), the main subunit of ferritin, is unclear in primary RCC tissues. In this study, we investigated FTH1 mRNA expression and its diagnostic and prognostic value in RCC.
MATERIAL AND METHODS: The mRNA expression of FTH1 was analyzed using including Oncomine, Gene Expression Omnibus, and Cancer Genome Atlas datasets, while the protein level of FTH1 was analyzed using the Human Protein Atlas database. The associations between FTH1 and clinicopathologic characteristics and survival time and Cox multivariate survival analysis were analyzed using SPSS 22.0 software. A meta-analysis was performed to assess consistency of FTH1 expression. GO, KEGG, and PPI analyses were used to predict biological functions.
RESULTS: According to TCGA data, overexpression of FTH1 was detected in 890 RCC tissues (15.2904±0.63157) compared to 129 normal kidney tissues (14.4502±0.51523, p<0.001). Among the clinicopathological characteristics evaluated, patients with increased pathologic T staging, lymph node metastasis, and distant metastasis were significantly associated with higher expression of FTH1. Elevated FTH1 mRNA levels were correlated with worse prognosis of RCC patients. Cox multivariate survival analysis indicated that age, stage, and M stage were predictors of poor prognosis in patients with RCC.
CONCLUSIONS: Our data suggest that FTH1 expression is an effective prognostic and diagnosis biomarker for RCC.

Keywords: Apoferritins, Carcinoma, Renal Cell, Computational Biology, Diagnosis, Prognosis