Systematic Analysis of the Expression and Prognosis of Fcγ Receptors in Clear Cell Renal Cell Carcinoma

Background Clear cell renal cell carcinoma (ccRCC) remains a common malignancy in the urinary system. Although dramatic progress was made in multimodal therapies, the improvement of its prognosis continues to be unsatisfactory. The antibody-binding crystallizable fragment (Fc) γ receptors (FcγRs) are expressed on the surface of leukocytes, to mediate antibody-induced cell-mediated anti-tumor responses when tumor-reactive antibodies are present. FcγRs have been studied extensively in immune cells, but rarely in cancer cells. Methods ONCOMINE, UALCAN, GEPIA, TIMER, TISIDB, Kaplan–Meier Plotter, SurvivalMeth, and STRING databases were utilized in this study. Results Transcriptional levels of FcγRs were upregulated in patients with ccRCC. There was a noticeable correlation between the over expressions of FCGR1A/B/C, FCGR2A, and clinical cancer stages/tumor grade in ccRCC patients. Besides, higher transcription levels of FcγRs were found to be associated with poor overall survival (OS) in ccRCC patients. Further, high DNA methylation levels of FcγRs were also observed in ccRCC patients, and higher DNA methylation levels of FcγRs were associated with shorter OS. Moreover, we also found that the expression of FcγRs was significantly correlated with immune infiltrates, namely, immune cells (NK, macrophages, Treg, cells) and immunoinhibitor (IL-10, TGFB1, and CTLA-4). Conclusions Our study demonstrated that high DNA methylation levels of FcγRs lead to their low mRNA, protein levels, and poor prognosis in ccRCC patients, which may provide new insights into the choice of immunotherapy targets and prognostic biomarkers.


INTRODUCTION
Renal cell carcinoma (RCC) is one of the most common malignancies of the urinary system, which accounts for 3-5% of all new cases of cancer worldwide (1). Clear cell RCC (ccRCC) is the main type of RCC that accounts for 75-82% of the incidence (2). Although immunotherapy strategies of metastatic RCC have been partially improved in recent decades, namely, cytokines, monoclonal antibodies, immuno checkpoint inhibitors(ICI), and chimeric antigen receptor (CAR) modified immune cells therapy, the improvement in the clinical results of the patient still remained unsatisfactory duo to the multiple immune escape mechanisms of kidney cancer (3).
The family of Fc receptors for IgG (FcgRs) are membranebound glycoproteins, expressed by several types of circulating and tissue-resident leukocytes (4,5), which act as a bridge between specific antibodies and effector cell functions to make innate immunity and adaptive immunity closely related (6). To date, three different classes of FcgRs, known as FcgRI, FcgRII, and FcgRIII, have fully recognized in humans (7). FcgRI, which exists on the membrane surface of monocytes and macrophages, has a high affinity with IgG (8). Three genes encoding FcgRI have been identified, which are FCGR1A, FCGR1B, and FCGR1C, whereas only FCGR1A expresses the functional FcgRI, FCGR1B/C are duplicated pseudogenes of FCGR1A (9,10). Contrary to FcgRI, FcgRII, and FcgRIII exhibit low affinity for monomeric IgG, but they are capable of binding IgG-antigen complexes through high avidity, multimeric interactions (11). Three different FcgRII have been identified, FcgRIIa, FcgRIIb, and FcgRIIc are encoded by FCGR2A, FCGR2B, and FCGR2C respectively and mainly expressing on B lymphocytes, granulocytes, monocytes, macrophages, and dendritic cells (12,13). FcgRIIb is the sole inhibitory FcgR which can counterbalance the signaling activity of the activating FcgRs. Two classes of FcgRIII (FcgRIIIa and FcgRIIIb) are encoded by the FCGR3A and FCGR3B genes. FcgRIIIa is widely expressed by macrophages, NK cells, and monocyte subsets, while FcgRIIIb expression is restricted to neutrophils (14,15).
FcgRs are involved in anti-tumor immunity in the following ways. 1. FcgRs expressed by natural killer (NK) cells and macrophages engage with antibody (IgG), triggering antibodydependent cellular cytotoxicity (ADCC) of tumor cells (16,17); 2. Anti-tumor antibodies bind to phagocytic surface FcgRs to enhance the phagocytic function of phagocytosis (18). 3. Antitumor antibodies can bind to the corresponding tumor antigen to form an immune complex, where the IgG FC segment can bind to the FcgRs on the APC surface, thus enriching the antigen, facilitating the APC presentation of tumor antigens to T cells (19).
In the past few years, polymorphisms in some members of the FcgRs have been reported in studies which lead to a different response to monoclonal antibodies in cancer (20), whereas abnormal expression of FcgRs in cancer has not been reported yet. In this present study, bioinformatics was performed initially to address this problem by analyzing the expression, DNA methylation, and prognosis of FcgRs and their relations with individual cancer stages and tumor grade in ccRCC patients. Furthermore, we also analyzed the predicted functions and pathways of FcgRs and their 88 co-expression genes.

Ethics Statement
The study has been admitted by the Institutional Review Board of the Medical Central Hospital of Qionglai. All written informed consent had already been obtained since all the data were retrieved from the online databases.

ONCOMINE Database
ONCOMINE is a publicly accessible online genome-wide expression analysis platform, covering 715 datasets and 86,733 samples of cancer (21). ONCOMINE was utilized to analyze expression differences of the FcgRs gene family in multiple tumor tissues and the corresponding adjacent normal tissues. The threshold was determined according to the following values: pvalue of 0.001, fold change of 1.5, and gene ranking the top 10%. In this study, the cell color is determined by the best gene rank percentile for the analysis within the cell, and the Student's t-test was applied to generate a p-value.

UALCAN
UALCAN is a comprehensive and interactive web resource for analyzing cancer OMICS data (TCGA, MET500, and CPTAC) (22). In our study, UALCAN was used to illustrate the distinct expression levels of tumor and normal tissues of ccRCC. Student's t-test was used to generate a p-value and the p-value cutoff was 0.05.

GEPIA
Gene Expression Profiling Interactive Analysis (GEPIA) is a newly developed interactive platform for elaborating the RNA sequencing expression data of 9,736 tumors and 8,587 normal samples from the TCGA and the Genotype-tissue Expression dataset, utilizing a standard processing pipeline (23). In this study, GEPIA was used to compare the association with cancer type staging of eight FcgRs members. The Student's t-test was used to generate a p-value and the p-value cutoff was 0.05.

TIMER2.0
TIMER is a comprehensive resource for systematical analysis of immune infiltrates across diverse cancer types. The 2.0 version of the webserver provides abundances of immune infiltrates estimated by multiple immune deconvolution methods, and allows users to generate high-quality figures dynamically to explore tumor immunological, clinical, and genomic features comprehensively (TIMER2.0 for analysis of tumor-infiltrating immune cells). In this study, we used TIMER2.0 to assess the correlation between FcgRs expression levels and immune cell infiltration and to assess the correlation between clinical outcomes and immune cell infiltration and FcgRs expression.

TISIDB
TISIDB is a web portal for tumor and immune system interaction, and a valuable resource for cancer immunology research and therapy, which integrates multiple heterogeneous data types (TISIDB: an integrated repository portal for tumorimmune system interactions). In this study, we used TISIDB to assess the correlation between FcgRs mRNA expression levels and immunoinhibitors expression levels or cancer grade of ccRCC.

Kaplan-Meier Plotter
The Kaplan-Meier plotter is an online database to assess the effect of gene expression on survival in 21 cancer types (24). We used this online tool to evaluate the prognostic value of FcgRs mRNA levels in ccRCC patients. The overall survival (OS) and recurrence-free survival (RFS) of patients were analyzed with a 50% (Median) cutoff for both low and high expression groups. The statically significant difference was considered when a pvalue is <0.05. Information on the number of patients, median values of mRNA expression, 95% confidence interval (CI), hazard ratio (HR), and P-value can be found on the Kaplan-Meier plotter web page.

Multivariate Regression Analysis of ccRCC Data in The Cancer Genome Atlas (TCGA) Database
We have downloaded RNA-sequencing, clinical, pathological, and follow-up data of 603 ccRCC patients from the TCGA-KIRC dataset. A total of 484 cases with complete data were screened out for multivariate regression analysis.

SurvivalMeth
SurvivalMeth is a web server to investigate the effect of DNA methylation-related functional elements on prognosis, and multiple kinds of commonly used functional elements associated with DNA methylation are considered (25). The frequently used data from the TCGA, the CCLE, and the GEO were prestored into SurvivalMeth, namely, 81 DNA methylation profiles in 13,371 samples across 36 cancers, covering more than 480,000 DNA methylation sites locating in 19,000 coding genes, 1,689,653 super enhancers, 1,304,902 CTCF binding regions, 77,634 repeat elements and multiple functional elements such as CpG island, shore, shelf, promoter, gene body, exon, etc.

STRING
STRING is a database of known and predicted protein-protein direct (physical) and indirect (functional) interactions (26). The protein-protein interactions (PPI) network of FcgRs coexpressed genes was visualized using the online tool of STRING with the species setting to Homo sapiens and a combined score of >0.7 was considered statistically significant. The nodes meant proteins; the edges meant the interaction of proteins and we hide disconnected nodes in the network.

DAVID
Functions of FcgRs and 88 co-expression genes significantly were analyzed by the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) in the Database for Annotation, Visualization, and Integrated Discovery (DAVID) (24). Gene ontology analyses focus on three domains: biological processes (BP), cellular components (CC), and molecular functions (MF), and such analyses are commonly used to predict the functional roles of FcgRs mutations and 80 genes significantly associated with FcgRs mutations, while the KEGG analysis can define the pathways related to the FcgRs mutations and 80 co-expressed genes associated with FcgRs mutations. Only terms with p-value of <0.05 were considered as significant.

Aberrant Expression of FcgRs in Patients With ccRCC
Differential mRNA expression levels of FcgRs were profiled in tumor and adjacent normal tissues of multiple cancer types using Oncomine platform. mRNA levels of FcgR family were remarkably upregulated in four cancer types, namely, brain and CNS, breast, head and neck colorectal and kidney, while mRNA levels of FcgRs were downregulated in leukemia and lung cancer ( Figure 1A). Table 1 shows that mRNA expression levels of FCGR1A/B, FCGR2A/B/C, and FCGR3B were remarkably upregulated in ccRCC in multiple datasets. As shown in Figure 1B, eight FcgRs are expressed abnormally in different tumor tissues. mRNA expression levels of FCGR1A/B/C, FCGR2A/B/C, and FCGR3A were remarkably upregulated in ccRCC tissues compared with normal tissues. The protein expression levels of FcgRs were analyzed using the CPTAC online tool of UALCAN platform. It was observed that only FCGR1A expresses the functional FcgRI, whereas FCGR1B/C represents duplicated pseudogenes of FCGR1A (6). Figure 1C showed that the protein expression levels of FCGR1A, FCGR2A/B, and FCGR3A were downregulated in ccRCC tissues compared with normal tissues.

Correlation Between Transcriptional Levels of FcgRs and Tumor Stages and Cancer Grade of ccRCC Patients
We used the GEPIA dataset to analyze the relationship between transcriptional levels of different FcgRs members with tumor stages of ccRCC patients. The results showed that the mRNA levels of FCGR1A/B/C and FCGR3A were correlated with the tumor stages of ccRCC patients, whereas the mRNA levels of FCGR2A/B/C and FCGR3B did not markedly differ among tumor stages (Figure 2A). The reason why the mRNA expression of FCGR2A/B/C and FCGR3B in ccRCC did not appear to be significantly different among tumor stages may be their unique roles in anti-tumor immunity. Likewise, cancer grades analysis by TISIDB indicated that mRNA expressions of FCGR1A/B, FCGR2A/B/C, and FCGR3A correlated with cancer grade of ccRCC ( Figure 2B). In short, the results above suggested that mRNA expressions of FcgRs (except for FCGR3B) were positively correlated with individual tumor stages or cancer grades of patients.

The Prognostic Value of FcgRs in Patients With ccRCC
To evaluate the prognostic value of the FCGR gene family in ccRCC progression, we analyze the correlation between FcgRs transcription levels and clinical outcomes including overall survival (OS) and disease-free survival (DFS) using the Kaplan-Meier Plotter database. ccRCC patients were divided into low and high-risk groups based on cutoff value. As shown in Figure 3A, high transcription levels of FcgRs were correlated with shorter OS in ccRCC. Nevertheless, high transcription levels of FCGR2B/C were correlated with longer DFS in ccRCC, and no significant correlation was observed between DFS and other FcgRs ( Figure 3B). We downloaded and screened the gene expression and clinical data of 485 ccRCC patients from the TCGA database (Supplementary Table 1) for multivariate Cox regression survival analysis. The results showed that the effects of FCGR1A, FCGR1B, and FCGR1C on prognosis were still significant after correcting for conventional prognostic factors ( Table 2; Supplementary Table 2).  Figure 4A), whereas, the DNA methylation levels of FCGR2A/B did not differ significantly between tumors and normal tissues. Moreover, lower FCGR1A/B/C and FCGR3A DNA methylation levels were associated with shorter OS, while lower FCGR2A DNA methylation level was associated with longer OS ( Figure 4B; Table 3).

PPI and Functional Enrichment Analysis of FcgRs and Their 88 Co-Expression Genes in ccRCC Patients
We then analyzed significant coexpression genes with FcgRs using the co-expression analysis module in the UAICAN database and listed in Supplementary Table 3. A total of 88 upregulated genes were significantly associated with FcgRs expression. Subsequently, the 88 genes were analyzed using GO and KEGG tools in DAVID, and constructed a PPI network by STRING. Figure 5A exposed that the activation of immune response-related genes, namely, C1QA, C1QB and, C1QC and adaptive immune response participant genes, such as LAIR1, LILRB4, CD4, and CD86 were closely connected with FcgRs alterations. The first 21 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of FcgRs and their 88 Co-expression genes are illustrated in Figure 5B. Among them, Phagosom, FcgR-mediated phagocytosis, Cytokine-cytokine receptor interaction, Toll-like receptor signaling pathway and Natural killer cell mediated cytotoxicity are significantly associated with anti-tumor immunity of ccRCC. In addition, GO (Gene Ontology) analysis including molecular functions (MF), cellular components (CC), and biological processes (BP) are shown in Figures 5C-E. Most results of GO analysis were associated with immune responses.

Correlation of FcgRs Expression Levels With Immune Infiltration in ccRCC
TIMER and TISIDB online analysis tools were used to evaluate the relationship between the expression levels of FcgRs and the level of immune infiltration in ccRCC. It was found that FcgRs are involved in immunosuppression regulation and immune cell infiltration, which might affect the clinical outcome of ccRCC patients. The analysis results showed that CD4 + T and NK were negatively correlated with FcgRs expression levels, whereas Treg and M2 macrophage cells were positively correlated with FcgRs expression levels ( Figure 6). The result of the TISIDB online analysis shows that immunoinhibitors, namely, IL-10 and CTLA-4 were positively correlated with all the FcgRs expression levels. TGFB1 was positively correlated with FCGR1A/B/C, FCGR2A/B, and FCGR3A (Figure 7).

DISCUSSION
In the past few decades, monoclonal antibodies (mAbs) that directly target tumor cells have become powerful tools in the fight against cancer, by triggering elimination of cancer cells through FcgRsmediated antibody-dependent cellular cytotoxicity (ADCC) or, phagocytosis (ADCP) and activating FcgRs on antigen-presenting cells (APC) to promote APC maturation (26). FcgRs were reported to be essential in anti-tumor immunity. FcgRI was demonstrated to play a central role in antibody therapy of experimental melanoma (32). DeLillo and Ravetch showed that the initial ADCC-mediated elimination of tumor cells is dependent on activating human FcgRIIIa using a murine model of EL4 lymphoma (33). The authors also demonstrated that the immune complex binding to FCgRIIa is an essential step in the activation of the T cell-dependent vaccinal effect. Indeed, patients carrying the allelic variants of FCGR2A, FCGR2C, and FCGR3A which exhibit increased affinity for human IgG demonstrated better responsiveness to anti-tumor antibody therapy in cases of B cell lymphomas, colorectal, renal, and breast cancers (20,(34)(35)(36)(37). Abnormal FcgRs expression was rarely reported in tumors. Only FCGR2B has been identified to be selectively expressed by metastasis melanoma that impairs the tumor susceptibility to FcgR-dependent innate effector responses, which might explain in part the low response of melanoma patients treated with antiidiotype (38). In the present study, we found that all FcgRs members have remarkably high expression in ccRCC, and patients with higher FcgRs expression levels exhibit a worse prognosis. Among them, FCGR1A/B/C and FCGR3A more highly express in ccRCC. Then we analyzed the DNA methylation levels of the FcgRs and found that almost all FCGR genes have high methylation levels in ccRCC, and patients with higher methylation levels have a worse prognosis. The above results indicate that the low DNA methylation levels of the FcgRs in ccRCC were likely to decrease their transcription levels, which in turn affects the prognosis of the patient.
RCC is an extremely heterogeneous cancer, in which a complex immune microenvironment provides favorable conditions for tumor immune escape (39). RCC consists of three major histopathologic groups-ccRCC), papillary (pRCC), and chromophobe RCC (chRCC). Pan-RCC clustering according to   RNA-sequencing data revealed a distinct histology-independent RCC subgroup characterized by strengthened mitochondrial and weakened angiogenesis-related gene signatures (40). RCC cells may induce cytokine expression, such as IL-10 and TGF-b, in the tumor microenvironment (TME), leading to an immunosuppressive tumor state and promoting immune escape (41)(42)(43). Tumorrelated immunosuppressive cells, namely, regulatory T cells and tumor-associated macrophages, also play an "accomplice" role in the immunosuppressive tumor state (42). In the present study immune infiltration analysis showed that the expression of FcgRs was negatively correlated with infiltration levels of NK and macrophage M2 cells which were the major immune cells that Emerging evidence indicates that angiogenesis and immunosuppression frequently occur simultaneously in tumor (44). Sasha et al. demonstrated that humanized or human IgG1 antibodies inhibited angiogenesis by binding to FcgRI of macrophages, resulting in reduced infiltration of macrophages in the tumor microenvironment (45). High expression of FCGR1 in ccRCC may compete with macrophages for binding to human IgG1 antibodies, thus inhibiting their antiangiogenic effects. The expression of FCgRs in ccRCC may simultaneously promote angiogenesis and immunosuppression.
To conclude, our research indicates that DNA methylation levels of FcgRs in ccRCC decreased and mRNA levels increased in ccRCC, which were both associated with poor clinical outcomes. FcgRs can be used as potential survival prognostic biomarkers and therapeutic target for ccRCC. The correlation between the expression of FcgRs and immune infiltration suggests that FcgRs may be involved in anti-tumor immunity in ccRCC. Our results indicated that FcgRs not only can be used as a risk factor for survival of patients with ccRCC but also reflect their immune status. Targeting the FcgRs might go a long way to find more appropriate prognostic factors for ccRCC as well as facilitate the development of novel immunotherapies.

DATA AVAILABILITY STATEMENT
The original contributions presented in the study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding author.

AUTHOR CONTRIBUTIONS
WN conceived the project and wrote the manuscript. SL, BL, JZ, and WL participated in data analysis. YY and TL participated in discussion and language editing. SY reviewed the manuscript. All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.