19 May 2019 : Laboratory Research
Value of Ferritin Heavy Chain (FTH1) Expression in Diagnosis and Prognosis of Renal Cell Carcinoma
Huimei Huang1BCEF, Yuyun Qiu1BD, Guilian Huang1BD, Xiaohui Zhou1CF, Xiaoying Zhou2AEG, Wenqi Luo1AEF*DOI: 10.12659/MSM.914162
Med Sci Monit 2019; 25:3700-3715
Abstract
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, Biomarkers, Tumor, Ferritins, Kidney Neoplasms, Oxidoreductases, RNA, Messenger
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01 November 2024 : Editorial
Editorial: Artificial Intelligence (AI), Digital Image Analysis, and the Future of Cancer Diagnosis and PrognosisDOI: 10.12659/MSM.947038
Med Sci Monit 2024; 30:e947038
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