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

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/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.


Background
In 2018, the new incidence of renal cell carcinoma (RCC) ranked sixth among all kinds of tumors, and the death rate ranked eighth [1]. It is estimated that 14 000 people died of RCC in 2012. The incidence of RCC varies geographically [2]. For example, the Czech Republic had the highest incidence in the world. The incidence in Nordic and Eastern Europe, North America, and Australia increased, but was relatively lower in Africa and Southeast Asia [3]. The reasons for the higher incidence in developed countries are not yet clear. Genomics, occupation, environmental exposures, and smoking are implicated [2]. RCC is divided into many different histological types. The clear cell type accounts for 70.90% of all RCC, followed by papilla (10-15%) and chromophobe RCCs (3-5%). Clear cell RCC is worse than papillary or chromophobe RCC, and is more likely to occur in late stage or metastasis [4,5]. In 90% of clear cell RCCs, tumors exhibit alteration the von Hippel-Lindau tumor suppressor (VHL) gene through genetic or epigenetic mechanisms [6,7]. The inactivation of VHL leads to a lower ubiquitination of hypoxia induced factor (HIF-a) and subsequently induces the expression of vascular endothelial growth factor (VEGF), both strictly linked to tumor angiogenesis [8]. VHL and VEGF has been validated as predictive and prognostic markers in RCC [9]. Further insights into the molecular biology of RCC could help find novel molecular biomarkers and potential targets for early diagnosis and precise treatment.
Elevated serum ferritin has been proved to play an important role in iron transport, angiogenesis, inflammation, immunity, signal transduction, and cancer in many human diseases [10]. Ferritin consists of 24 polypeptide subunits of heavy chain (FTH1) and light chain (FTL) [11,12]. In patients with RCC, serum ferritin concentration is significantly higher than in normal controls [13], and even associates with the presence of distant metastasis [14]. It is suggested that serum ferritin may be a useful tumor marker for renal cell carcinoma.
Ferritin consists of the heavy and light chains, encoded by FTH1 and FTL1 genes, respectively. FTH1 is differentially and abnormally expressed in tissues from multiple malignancies, including astrocytic brain tumors [15], prostate cancer [16], and breast cancer [17]. FTH1 has recently been considered a good prognostic protein for triple-negative breast cancer (TNBC) patients [17]. However, the expression of FTH1 is unclear in RCC.
The purpose of this study was to analyze the difference between FTH1 gene expression in RCC and normal renal tissues, and to explore the relationship between FTH1 gene expression and clinical characteristics and prognosis of RCC.

Material and Methods
The Cancer Genome Atlas (TCGA) database analysis TCGA is a huge repository of high-throughput data of DNA, RNA, and protein in a variety of human cancers, which is helpful in comprehensive analysis of the expression of these components in various cancer types [18]. The data of FTH1 mRNA expression in primary RCC and normal control samples, as well as clinicopathological characteristics of patients, were obtained from TCGA database (https://xena.ucsc.edu/). SPSS 22.0 software was used to analyze the differential expression of FTH1 in RCC and the relationship between FTH1 level and clinicopathological parameters and Cox multivariate survival. The survival curve was analyzed using GraphPad software.

Oncomine database analysis
Oncomine databases are online collections of microarrays from various sources, often associated with cancer, and contain many "multiple arrays" (collections of microarrays analyzed in a single study) [19]. The relative expression level of "FTH1" gene was searched in the "kidney cancer" dataset in the analysis type of "cancer vs. normal analysis".

Selection of studies and microarrays in GEO datasets
The mRNA expression of FTH1 in RCC was investigated in GEO database, with search terms as follow: 1) "renal cancer", 2) "kidney OR renal AND cancer OR carcinoma OR tumor OR neoplasm* OR malignant*". Microarray was used to examine the expression of FTH1 in RCC tissues and normal tissues, including meta-analysis. The criteria of inclusion were: 1) have more than 6 samples, and 2) sampled FTH1 from human tissues.

Real-time reverse transcription polymerase chain reaction
The transcriptional level of FTH1 was confirmed in normal renal epithelial cell 293 and renal cancer cell 786-0, which were stored in our lab. cDNA of primary renal cell carcinoma tissues and matched adjacent tissues were obtained from Shanghai Outdo Biotech Co. (Shanghai, China; Cat no: MecDNA-HKidE030CS01). The relative expression levels of FTH1 were detected using the Power SYBR Green PCR Master Mix (Foster City, CA, USA, Applied Biosystem) in a QuantStudio 5 Real-Time PCR System (Foster City, CA, USA, Applied Biosystem). After the reactions were completed, the comparative threshold cycle (Ct) method was used to calculate the relative gene expression. The sequences of primers used were as follows: FTH11-Forward, 5'-AAGCTGCAGAACCAACGAGG-3', FTH1-Reverse, 5'-AGTCACACAAATGGGGGTCATT-3'; GAPDH1-Forward, 5'-AAGCTCACTGGCATGGCCTT-3', GAPDH-Reverse, 5'-CTCTCTTCCTCTTGTGCTCTTG-3'.

The Human Protein Atlas (HPA)
HPA is a pathology tool that provides a large number of protein expression profiles of human proteins. Clinical tumor tissue samples come from a clinical biobank, including a large number of retrospectively collected patient cohorts and longterm follow-up for research. Here, we used this tool to compare the expression of RCC tissues and normal tissues at the protein level.

cBioPortal for ClueGo
The co-expression genes of FTH1 in KIRC (|Pearson's r|³0.4 and |Spearman's r|³0.4) were identified by cBioPortal network tools. Then, genes were loaded into ClueGo in CytoCop3.3.1 to analyze GO and KEGG pathways. Only a path with a p value of 0.05 was included. In addition, co-expressed genes (|Pearson's r|³0.5 and |Spearman's r|³0.5) were selected and STING was used for PPI network analysis.

Statistical analysis
All statistical analyses were performed using SPSS 22.0 software. The correlation between FTH1 gene expression and clinical pathological parameters of RCC patients was evaluated by independent-samples t test. The differences in TNM stages were tested using analysis of variance (ANOVA). Cox multivariate survival analysis was performed to predict unfavorable prognosis. The diagnostic value of FTH1 in RCC was evaluated by receiver operating characteristic (ROC) curve. Kaplan-Meier curves and logarithmic rank test were used to analyze the survival of RCC patients. STATA 12 software was used for metaanalysis. p£0.05 was considered statistically significant.

Association between FTH1 expression and clinicopathological parameters, diagnosis and prognosis of RCC patients
According to TCGA data, over-expression 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; Figure 1A). This was further confirmed in cell lines and tissues by realtime RT-PCR. In contrast with normal renal epithelial cell line 293, the mRNA level of FTH1 was elevated in renal cell carcinoma cell line 786-0 ( Figure 1B). We also observed a relatively higher expression of FTH1 in 10 out of 14 primary RCCs than in matched adjacent samples ( Figure 1C). There was a significant difference between the expression of FTH1 and age, T stage, M stage, and lymph node metastasis (  (Table 2). In addition, Cox multivariate survival analysis was performed, including 6 significant statistical parameters, and demonstrated that age, stage, and M stage were predictors of adverse prognosis in patients with RCC ( Table 3).
The P value of ROC curve was <0.001, revealing that the expression of FTH1 is associated with diagnosis of RCC (AUC=0.849, 95% CI: 0.818-0.880, p<0.001; Figure 1D). The Kaplan-Meier curve showed that of RCC patients with high FTH1 expression had worse outcomes (p=0.0014; Figure 1E). In these 3 types of RCC, FTH1 expression was significantly higher than in the 129 normal controls (Figure 2A-2C). To further confirm this finding, we used Oncomine database to analyze the FTH1 expression in 3 types of RCC. Figure 2D-2F shows that FTH1 is overexpressed in KIRC, KICH, and KIRP, but the difference is significant only in KIRC and KIRP.  (23) KICH (6) Reporter    The expression of FTH1 was also remarkably different in different T stages in KIRC patients. These patients with lymph node or distant metastasis had higher FTH1 expression (Table 4), but no significant difference was found between the expression of FTH1 and any clinical characteristics in KICH patients (Table 5). KIRP patients age <60 years showed lower FTH1 expression compared with those age ³60 years. The expression of FTH1 was also remarkably different in different T stages. Patients with lymph node or distant metastasis also had higher FTH1 expression (Table 6).  RCC tissue subgroup was highly heterogeneous (I 2 =87.0%, p<0.001).

Lower CI limit Upper CI limit Estimated
Meta-analysis estimates, given maned study is ommited  469 normal tissues in GEO database were included for metaanalysis, in which we combined the effective data (GEO and TCGA) and used the random-effects model to obtain the pooled Standard Mean Difference (SMD) as 0.64 (95% CI: 0.53-0.75, p<0.001; Figure 3), and the p value of the heterogeneity test was less than 0.001 (I 2 =87.0%). Sensitivity analysis showed that no single study led to significant bias in overall merger results ( Figure 4). In addition, no significant publication bias was found in the study (Begg's test: p=0.054; Figure 5). Relevant information was extracted from each study, such as ID number, first author, public year, country, sample type, platform, number of cancer cases, mean (M) and standard deviation (SD) of FTH1 expression in the cancer group, and normal tissue N, M, and SD of FTH1 expression in the normal group (Table 7).

FTH1 protein expression in RCC tissues from HPA
Using the HPA database, we compared 3 normal samples and 3 RCC samples, which showed an elevation of FTH1 protein in RCC ( Figure 6).
The GO, KEGG network, and PPI network with coexpressed genes of FTH1 Among these co-expressed genes, 278 genes were selected for GO and pathway analyses (Figures 7-9). These genes are abundantly expressed in positive regulation of the Wnt signal transduction pathway, response to oxygen level, binding of ribosome subunits, and RNA polymerase. In addition, KEGG pathway analysis showed that the expression of FTH1 co-expression gene in hepatocellular carcinoma, proteasome, and ribosome was significantly higher than in the control group ( Figure 10). The most important GO items (BP, CC, and MF) are listed in Table 8 and the PPI network is shown in Figure 11.

Discussion
To date, no diagnostic modality for early detection of RCC has been established, other than incidental radiologic discovery. Some promising studies have identified several potential biomarkers in sera and urine. For example, tumor necrosis factor receptor-related factor-1, heat shock protein 27, carbonic anhydrase IX, and ferritin in RCC patients were significantly higher      Currently available biomarkers seem to be most useful as diagnostic tools, prognostic indicators, and follow-up in patients with renal cancer [29]. Steven et al. reported that the positive expression of receptor activator of NF-kB had both worse cancer-specific survival and recurrence-free survival in RCC patients [30]. Increased expression of long noncoding RNA GIHCG is positively correlated with advanced TNM stages, Fuhrman grades, and poor prognosis [31]. In a meta-analysis of 2013 patients, including 22 studies, positive expression of P53 was associated with poor prognosis and advanced clinicopathological features in RCC patients [32]. The nuclear translocation of CXCR4 plays an important role in RCC metastasis and is associated with poor prognosis [33]. Here, we found that RCC patients with higher FTH1 expression in primary RCC were associated with a shorter survival time. Besides, RCC patients with lymph node and distant metastasis had higher FTH1 expression metastasis, which indirectly suggests a poorer prognosis. These finding suggest that the high expression of FTH1  could be used as a predictor to indicate the poor prognosis of RCC patients.
Dysregulation of iron homeostasis has been linked to numerous diseases, such as cancer and neurodegenerative diseases [34,35]. Cellular iron regulation includes iron uptake, storage, and export. Iron-regulated proteins, such as transferrin receptors in glioblastoma and ferritin in serum, were upregulated, thereby increasing iron uptake [36,37]. Ferritin plays an important role in the storage and release of iron in cells.
Ferritin complexes capture intracellular ferrous ions (Fe 2 ) and convert them into iron ions (Fe 3 ) by the activity of ferrous oxidase [38]. It consists of 24 subunits of heavy and light ferritin chains (FTH1 and FTL1). In this study, we found that there was no significant correlation between the expression of FTL1 and RCC (data not shown), suggesting that FTH1 might play an important role in the tumorigenesis of RCC. In addition, approaches targeting cellular iron and iron signaling to inhibit tumor growth have been developed and applied in cancer therapy. The application of iron chelators can suppress tumor growth and induce apoptosis, which suggests iron chelators as potential anti-cancer drugs [39,40]. FTH1 controls HIF-induced hypoxia by activating asparagine hydroxylase and affects the expression of HIF-1 target gene [38]. Based on our results of GO analyses, the top enriched functional term of FTH1 genes were regulation of Wnt signaling pathway and response to cellular hypoxia. Overexpressing FTH1 in acute myeloid leukemia (AML) stem cells significantly induced the expression of genes involved in immune and inflammatory response, including NF-kB pathway, oxidative stress, and iron pathways [41]. These findings suggest that FTH1 could be a novel therapeutic target.
The limitations of this study should be considered. The expression of FTH1 in RCC and its correlation with clinical features were analyzed and validated only in TCGA and GEO datasets. Further research is needed to improve our understanding of the functional role of FTH1 in RCC.

Conclusions
In this study, we found that expression of FTH1 is elevated in RCC, which could serve as a potential diagnosis and prognosis biomarker. Our data suggest that higher mRNA levels of FTH1 might contribute to the progression of RCC, and thus could be used as a target for RCC therapy.