NCF1/2/4 Are Prognostic Biomarkers Related to the Immune Infiltration of Kidney Renal Clear Cell Carcinoma

Neutrophil cytoplasmic factor 1/2/4 (NCF1/2/4) belongs to the NADPH oxidase complex, which is a cytoplasmic component, and its polymorphism is the main factor related to autoimmune diseases, which is probably caused by the regulation of peroxide. They also play a role in tumor growth and metastasis. This research is aimed at evaluating the biological function and prognostic role of NCF1, NCF2, and NCF4 genes in kidney renal clear cell carcinoma (KIRC) by using multiple online bioinformatics website, including Oncomine, GEPIA, UALCAN, Kaplan–Meier Plotter, TIMER, TISIDB, cBioPortal, LinkedOmics, GeneMANIA, and DAVID databases. The mRNA levels of NCFs were higher in KIRC tissues than in normal tissues. The overexpression of NCFs was significantly correlated with advanced pathological grades and individual cancer stages in KIRC. Meanwhile, the expressions of NCFs played an important role in the tumorigenesis and progression of KIRC. Prognostic value analysis suggested that high transcription levels of NCF1/4 were associated with poor overall survival in KIRC patients. In addition, results from the LinkedOmics database showed that the KEGG pathway related to NCFs mainly focused on immune activation and immune regulation function. NCF genetic alterations, including copy number amplification, missense mutation, and deep deletion, could be found through the cBioPortal database. Further, NCF expression was significantly correlated with infiltration levels of various immune cells as well as immune signatures. Protein-protein interaction network and enrichment analysis of NCF1/2/4 in KIRC showed that NCF coexpressed genes mainly associated with diverse immune marker sets showed significance. Overall, these results indicated that NCFs could be prognostic biomarkers as well as effective targets for diagnosis in KIRC.


Introduction
In recent years, the incidence of malignant kidney tumors has been increasing. In 2019, approximately 73,820 Americans were diagnosed with kidney cancer [1], and nearly 15,000 died of the disease [2,3]. It is the seventh most common cancer among men and the ninth most common cancer among women [4]. Kidney cancer represents several different types of cancer, which have different histology, clinical course, and response to treatment [5]. Clear cell carcinoma is the most common histological type of kidney cancer (75%) [6] and one of the most aggressive types [7]. Because the kidney is located deep in the body, its clinical symptoms usually appear in the late stage, so the 3-year survival rate in the kidney renal clear cell carcinoma (KIRC) in the population is less than 5% [8]. Until recently, we still lacked effective systemic therapies for KIRC, and surgery was the main treatment method [9]. In addition, the prognosis of KIRC is not good. One-third of patients will have local or distant metastases, and about one-quarter of patients undergoing radical surgery have recurred tumors at a distance [10]. Due to the high morbidity, high mortality, and difficulty of early diagnosis of KIRC, it is important to evaluate carcinogenic mechanisms and explore potential drug targets and molecular markers that have a prognostic value that affects the immune response of KIRC patients.
Neutrophil cytoplasmic factor 1 (NCF1), neutrophil cytoplasmic factor 2 (NCF2), and neutrophil cytoplasmic factor 4 (NCF4) are also referred to as p47phox, p67phox, and p40phox, respectively. They belong to the NADPH oxidase complex, which is a cytoplasmic component, and its polymorphism is the main factor related to autoimmune diseases, which is probably caused by the regulation of peroxide [11]. In the case of inflammatory stimulation, NADPH oxidase is activated; phosphorylation of NCF1 (p47phox) leads to the assembly of NCF2 (p67phox) and NCF4 (p40phox) into an active oxidase complex p22phox/gp91phox. In this process, it promotes the conversion of oxygen (O 2 ) into superoxide ions (O 2 -) and hydrogen peroxide (H 2 O 2 ), which are all reactive oxygen species (ROS) [12]. Studies have confirmed the correlation of these genes with chronic granulomatous disease [13], Crohn's disease [14], and autoimmune arthritis [15]. They also play a role in tumor growth and metastasis [16], such as Hodgkin's lymphoma [17]. However, their relationship with tumors in many other fields has not been explored, so this article is aimed at evaluating the biological function and prognostic role of NCF1, NCF2, and NCF4 genes in KIRC.

Materials and Methods
2.1. Oncomine Database Analysis. The mRNA levels of NCFs in various cancers were identified in the Oncomine database. The Oncomine database (http://www.oncomine.org) is an online cancer microarray database and synthetic genewide data-mining platform [18]. We compared the transcriptional levels of NCFs in different cancer tissues with their corresponding adjacent normal controls from the Oncomine database, using Student's t-test to generate a p value. Cutoffs of p value and fold change were defined as 0.05 and 2, respectively.

Gene Expression Profiling Interactive Analysis. Gene
Expression Profiling Interactive Analysis (GEPIA) (http:// gepia.cancer-pku.cn/) integrates a tremendous amount of tumor and nontumor samples from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) database, providing differential expression analysis, correlation analysis, and patient survival analysis online [19]. In our study, GEPIA was used to analyze the expression of NCFs in kidney renal clear cell carcinoma with corresponding breast tissues. The cutoff of p value was 0.05 and log 2 FC was 1 (fold change was 2). We also obtained the top 100 similar expression protein-coding genes with certain NCFs in KIRC Tumor dataset by similar gene module for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis.

UALCAN Database
Analysis. UALCAN (http://ualcan .path.uab.edu) is a comprehensive web resource based on TCGA database level 3 RNA-seq and clinical data from 31 cancer types [20]. It can be used to estimate the relative transcriptional expression of query genes between tumor and normal samples as well as relative clinicopathologic parameters on patient survival. In this study, UALCAN was used to analyze the association between mRNA expressions of NCFs grouped by known prognostic factors (individual cancer stages, tumor grade, and KIRC subtype) in kidney renal clear cell carcinoma.

Kaplan-Meier Plotter
Database. The research on the NCF prognostic value was performed in the KM-plotter database, which could evaluate the survival of more than 50,000 genes in 21 cancer types [21]. The ccRCC dataset with 530 samples was selected to explore the expression profile of NCFs on ccRCC overall survival (OS). Furthermore, the hazard ratio (HR), log-rank p value, and survival plots were computed and output by the website automatically.

LinkedOmics Database Analysis.
LinkedOmics is a publicly available portal that included multiomics data from 32 TCGA cancer types [22]. The "Linkfinder" module was used to perform the volcano map showing the NCF association results and heat map showing the coexpressed genes of NCFs. The "LinkInterpreter" module was used to perform GO and KEGG analysis of NCFs based on gene set enrichment analysis (GSEA). The criterion about GSEA is as follows: the minimum number of genes (size) is 3 and a simulation is 500. The top 5 terms of GO and KEGG analysis were exhibited. Gene terms with p value < 0.05 and false discovery rate ðFDRÞ < 0:05 were considered significant.
2.6. cBioPortal Data Analysis. The cBioPortal for Cancer Genomics is a comprehensive web resource that can visualize and analyze multidimensional cancer genomic data [23]. Copy number variation (CNV), mutations, and the clinic outcomes of the gene types in KIRC were evaluated according to the online tools of cBioPortal. The p value set as 0.05 was considered significantly different.

TIMER Database Analysis.
The TIMER database is a comprehensive resource for systematical analysis of immune infiltrates across diverse cancer types [24]. Associations between NCF expression and TIIC infiltration levels were analyzed via TIMER, a website tool for analysis of genespecific correlation with TIICs. TIICs included B cells, CD4 + T cell, CD8 + T cell, macrophages, neutrophils, and dendritic cells.
2.9. Protein-Protein Interaction Network Construction. The STRING (http://string-db.org, version 11.0) database was used to predict the PPI network of DEGs and analyze the interactions between proteins [26]. GeneMANIA is an interactive and visual online protein-protein interaction (PPI) prediction tool, which provides the customizable function of the detection of genes with similar functions. GeneMA-NIA is a prediction website tool for analyzing genetic and protein interactions, coexpression, pathways, colocalization, and domain-protein similarity of target genes [27]. In this study, we analyzed the relationship between NCFs and their interactive genes by the GeneMANIA database and the STRING database.  's instructions, the total RNA was extracted  from cultured cells by using Trizol reagent (Invitrogen,  USA). Then, the cDNAs were synthesized following the protocol of PrimeScript™ RT Master Mix (Takara). Quantitative real-time PCR was conducted using SYBR Premix Ex Taq™ II (Takara) on Thermal Cycler CFX6 System (Bio-Rad). The relative transcriptional levels of target genes were calculated by using the 2−ΔΔCt method. The RT-qPCR primer sequences were as follows: NCF1 forward primer 5′-ACGA GAGTGGTTGGTGGTTC-3′ and reverse primer 5′-TGTA GGCTTTGATGGTGACG-3 ′ , NCF2 forward primer 5 ′ -GCGCTAGGCTGGGACCTTGAAGCC-3 ′ and reverse primer 5 ′ -GTCTTGAAGAAGGGCAGTGATAAC-3 ′ , and NCF4 forward primer 5 ′ -TGAACAGCTTCCGGAT GATG-3 ′ and reverse primer 5 ′ -TGAAGCCTCTCTTCTC CTCGAT-3 ′ . Western blot was performed by adding lysis buffer into cells and total protein was extracted. Equal amounts of protein samples were added to SDS/PAGE for conducting electrophoresis. Next, after being blocked for 1 hour with 5% defatted milk, the membranes with proteins were incubated in a primary antibody against NCF4 (Invitrogen), E-cadherin, α-catenin, vimentin, MMP9, and β-actin (Cell Signaling Technology), overnight at 4°C. Then, the membranes were incubated with the secondary antibodies and the proteins in the membranes were visualized by ECL after washing with TBST. β-Actin was used as a reference.
2.16. Statistical Analysis. Statistical analyses were performed using the SPSS 23.0 statistical software (IBM, USA), Graph-Pad Prism software (7.0). The quantitative data were shown as mean ± standard deviation (SD) and were compared through Student's t-test. The enumeration data enlisted as percentages were compared via the chi-square test. It would be considered as statistical significance when p < 0:05. In order to preliminarily evaluate the role in tumorigenesis, we analyzed the different expression levels for NCF1, NCF2, and NCF4 between tumor and adjacent normal tissues in all TCGA tumors (Figure 1(a)    3.2. The Levels of NCF1, NCF2, and NCF4 Expression in Subgroups of Patients with KIRC. To study various clinicopathological characteristics, we further analyzed TCGA-KIRC samples in the UALCAN database. We next explored the different expression levels of the 3 genes in KIRC, stratified according to the cancer stage and pathological grade. The results demonstrated that the expression of the 3 genes was higher in KIRC tissues than in normal tissues based on different pathological grades and individual cancer stages. Therefore, expression levels of NCF1, NCF2, and NCF4 may serve as potential diagnostic markers in patients with KIRC (Figures 2(a)-2(f)). In addition, we also analyzed the mRNA expression levels of the NCFs in different subgroups of primary KIRC patients and healthy people. NCF1, NCF2, and NCF4 are significantly higher in ccA and ccB subtypes than normal tissues, and the expression of NCF1 and NCF4 in ccB subtypes is significantly higher than that in ccA subtypes (Figures 2(g)-2(i)). Therefore, the results indicated that the expression of these genes plays an important role in the tumorigenesis and progression of HCC.

Clinicopathological Characteristics and Prognostic
Significance of NCF1, NCF2, and NCF4 Expression in KIRC. The transcriptome RNA-seq data from TCGA databases for 530 KIRC patients was collected. The clinicopathological characteristics of these kidney cancer patients are depicted in Table 1. Next, we sought to investigate the prognostic significance of NCF1, NCF2, and NCF4 expression in KIRC. The association between NCF1, NCF2, and NCF4 expression levels and the survival outcomes of KIRC patients was assessed using Kaplan-Meier survival curves. The results showed that patients were divided into two groups based on the expression values of NCF1, NCF2, and NCF4 in each   11 12     In addition, results from the LinkedOmics database showed that the KEGG pathway related to NCFs mainly focused on immune activation and immune regulation function (Figures 4(g)-4(i)).
High   3.5. Genomic Alterations of NCF1, NCF2, and NCF4 in KIRC. The frequency and types of genetic alterations in NCF1, NCF2, and NCF4 in patients with HCC were analyzed by using the cBioPortal database. A total of 274 KIRC cases from TCGA were explored. NCF1, NCF2, and NCF4 were altered in 4%, 7%, and 5% of KIRC cases, respectively ( Figure 5(a)). NCF1 mutation consisted of 4.01% mRNA high (11 cases). NCF2 mutation consisted of 0.36% mutation (1 case), 0.36% deep deletion (1 case), and 5.84% mRNA high (16 cases). NCF4 mutation consisted of 0.36% mutation (1 case), 0.36% deep deletion (1 case), and 4.01% mRNA high (11 cases) ( Figure 5(b)). NCF2 and NCF4 have existed mutations in the protein functional domain ( Figure 5(c)). However, the copy number alteration status of NCF1, NCF2, and NCF4 was not significantly associated with the overall survival (OS) and disease-specific survival (DSS) of KIRC ( Figures 5(d)-5(i)). In KIRC patients, the probability of mutations in NCF1, NCF2, and NCF4 is not high. We did not find that mutations may have beneficial or harmful effects on survival in this small sample of data. Therefore, genomic alterations of these genes could not be considered as poor prognosis factors in KIRC patients.

Correlation between NCF Expression and Immune
Infiltrating Level in KIRC. The survival of patients in several cancers is determined by the number and activity of tumorinfiltrating lymphocytes. Therefore, the TIMER database was used to investigate the relationship between the levels of immune infiltrating and the expressions of NCF1, NCF2, and NCF4 in KIRC patients. As shown in Figure 6 . Specifically, NCF2 expression was not correlated with immune subtypes (C1-C6: wound healing, IFN-gamma dominant, inflammatory, lymphocyte depleted, and TGF-β dominant) in KIRC. In addition, it was found that the mRNA levels of NCF1 and NCF4 were obviously decreased in immunologically quiet KIRC immune subtype.
Moreover, the relationships between somatic copy number alterations (SCNA) of the 3 genes and tumor infiltration levels among KIRC were investigated. Interestingly, the results showed that the CNA of NCF1 had significant correlations with the infiltration levels of CD4 + T cells and B cells; the CNA of NCF2 had significant correlations with CD8 + T cells, CD4 + T cells, B cells, neutrophils, dendritic cells, and macrophages; and the CNA of NCF4 had a significant correlation with CD8 + T cells, CD4 + T cells, neutrophils, and dendritic cells (Figures 7(a)-7(c)).

Enrichment Analyses of NCFs in KIRC.
We then performed enrichment analyses of NCFs. We collected NCF1, NCF2, and NCF4 and their coexpressed genes and plotted PPI plots with GeneMANIA (20) and STRING (10) (Figures 8(a) and 8(b)). The PPI network was constructed and revealed that NCFs were associated with osteoclast    To understand specifically the potential role of NCFs in the development of kidney renal clear cell carcinoma, we conducted GO and KEGG functional enrichment analysis of the top 100 correlated genes of distinct NCFs using DAVID which was extracted from the GEPIA (http://gepia .cancer-pku.cn/) database as presented in Table S1. We observed that all these three members were closely associated with immune-related biological functions, such as adaptive immune response, innate immune response, regulation of immune response, and integrin-mediated signaling pathway (Figure 8(c)). Therefore, we have reason to believe that NCF members may be related to the immune response in the tumor microenvironment (Figure 8(c)). In addition, we have also observed a higher correlation between NCFs and immunosuppressive immune infiltrating cells (Table 3).

NCF4 Inhibition Blocks Kidney Cancer Cell Proliferation
In Vitro. We tested the expression of NCFs in human normal renal tubular epithelial cell line HK-2 and KIRC cell line 786-O and found that NCF1, NCF2, and NCF4 were significantly upregulated in the KIRC cell line (Figure 9(a)). To verify the effects of NCF4 on the biological function of KIRC cells in vitro, the siRNAs were synthesized for knocking down the expression of NCF4 in the 786-O cell line (Figures 9(b) and 9(c)). Overexpression of NCF4 led to activation of the NADPH oxidase 2 complex and ROS production (activation of NADPH oxidase subunit NCF4 induces ROS-mediated EMT signaling in kidney cancer cells). The generation, location, and local concentration of free radicals in tumor cells play an important role in the biological behavior of tumors [29]. In order to explore the relationship between them, we measured the level of ROS after knocking down NCF4 in the 786-O cell line. NCF4 knockdown decreases the level of ROS in kidney cancer cells (Figure 9(d)). A CCK-8 assay indicated that cell viability was inhibited by silencing NCF4 and enhanced by exogenous hydrogen peroxide in 786-O cells (Figure 9(e)). The data of the colony formation assay also showed that exogenous hydrogen peroxide increased the proliferation, whereas silencing NCF4 inhibited the proliferation in kidney cancer cells (Figure 9(f)).

NCF4 Inhibition Blocks the Migration and Epithelial-Mesenchymal Transition of Kidney Cancer Cells In Vitro.
Wound healing assays and transwell assays were conducted simultaneously after NCF4 knockdown to figure out the potential role of NCF4 in the migration and invasion capacity of bladder cancer cells. The results showed that knockdown of NCF4 significantly inhibited the ability of migration of KIRC cells (Figures 10(a) and 10(b)). Epithelial-mesenchymal transition (EMT) has been reported to play an important role in carcinoma metastasis, and due to EMT-mediated cell morphology changes, tumor cells are more likely to metastasize to distant places [30]. After confirming that NCF4 mediated KIRC cell migration, we investigated the EMT-relevant markers by western blotting. As the result showed, the expression of the epithelial marker E-cadherin was enhanced, and the mesenchymal markers vimentin and matrix metalloproteinase MMP9 that are closely correlated with metastasis were attenuated when NCF4 was knocked down (Figure 10(c)).

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Discussion
Clear cell RCC (KIRC) is a kind of silent cancer. The symptoms are not obvious in the early stage of the disease and it is difficult to be detected [31]. Therefore, the prognosis of this disease is often very bad [31]. RCC is showing an upward trend all over the world, especially in developed countries that maintain a high incidence [32]. At present, the research on early screening and molecular diagnosis of RCC is continuously deepening, and the diagnosis and treatment of RCC have been improved to a certain extent [33]. RCC is considered to be an immunogenic tumor, but it is known to mediate immune function to a large extent by causing immunosuppressive cells (such as regulatory T cells and suppressor cells of myeloid origin) to infiltrate the tumor microenvironment, considered as a "cold tumor" [34]. With the further in-depth research of TME, the receptors on the surface of immune cells and stromal cells in the tumor microenvironment have been recognized and studied more, which brings more opportunities and approaches for tumor treatment but also clarifies tumor progression. Therefore, more abnormally expressed genes with potential clinical relevance need to be considered for their possible effects, which will bring benefits to patients with more detailed diagnostic evaluation and treatment. In addition, the data of the past few decades clearly show that immunosuppressive changes in tumors are important tumor driving factors and immune escape mechanisms, which occur earlier. Tumor immunosuppression is usually found in cancer. Tumors mainly pass through two types of cells, regulatory T cells or Tregs and myeloid cells, called myeloid-derived suppressor cells (MDSC), which are immunosuppressive agents, which means that they secrete chemicals (such as cytokines) to inhibit infiltrating T cells [35].
In our study, NCF1, NCF2, and NCF4 showed a high expression in renal clear cell carcinoma. And we further proved that especially NCF1 and NCF4 were significantly correlated with high tumor grade and clinic stage. In addition, overexpression of NCF1, NCF2, and NCF4 was associated with shorter overall survival. So far, more and more evidence show that NCF1, NCF2, and NCF4 play an important role in tumorigenesis and development.
NOX2 is often referred to as NADPH oxidase, composed of the assembly of CYBB/gp91phox with the membraneanchored CYBA/p22phox and the cytosolic subunits NCF4/p40phox, NCF1/p47phox, and NCF2/p67phoxon the plasma membrane to generate extracellular ROS [16]. ROS affects the occurrence, development, and metastasis of cancer through a variety of mechanisms [16]. In recent years, a large number of studies have shown that altered ROS production may promote tumors, while other findings have also proved that ROS production can increase the sensitivity of cancer cells to various death-inducing pathways [36]. NCFs are the subunits of NOX2. Variations and deletions in any one subunit may induce changes in ROS production, which will affect tumors.
The study by van der Weyden et al. showed that NOX2 significantly affects the process of metastasis, because mice that are genetically deprived of any major NOX2 subunits (any subunit is necessary for NOX2 function) always after intravenous injection of tumor cells show a lower rate of lung metastasis [37]. Kelkka et al. found that NCF1 (m1J) mutant mice developed significantly smaller tumors in two melanoma models and tumor incidence was reduced in Lewis lung cancer tumors. The lack of ROS-mediated protection against tumor growth was associated with increasing immunityassociated cytokines [38]. NCF2 is significantly upregulated in RCC, as a potential factor predicting RCC [39].   Immune infiltrating cells in the tumor environment have received more and more attention, and many of their functions have been found to be targets for tumor treatment. As early as 1985, Miller et al. began to study the effect of active immunotherapy for renal cell carcinoma [40]. Gillon et al. explored the role of the immune response reflected in the migration inhibition factor (MIF) test in the defense mechanism of RCC patients and explored the role of macrophages in kidney cancer [41].
The results of expression with NCFs and TIMER database results indicate that these three genes are strongly related to SPI1, HCK, VAV1, CD53, ITGB2, and so on. According to the results of KEGG pathway enrichment, they are mainly involved in inflammation and immune response or tumorigenesis [42][43][44][45][46]

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However, the comprehensive analysis of the NCF family is carried out using different databases and algorithms, and there are still some limitations. First of all, the prognostic NCF family themselves and their related gene characteristics have not been widely adopted and verified. Considering that there are some potential obstacles to the promotion of sequencing technology in clinical tumor detection, the era when molecular prognostic biomarkers are widely used in clinical practice will take more time. Secondly, the role of the NCF family in tumors is only based on our bioinformatics analysis, and the internal mechanism of its impact on tumors deserves more exploration. Thirdly, as a retrospective study, the main limitation of this study lies in its retrospective nature. Therefore, it is necessary to conduct a multicenter prospective study in the future.

Conclusion
In summary, we found that the overexpression of NCFs in KIRC is associated with clinical manifestations and predicts a poor prognosis. The high expression of NCFs is closely related to the level of infiltrating immune cells, and it may promote the differentiation of macrophages into TAM. Targeting NCFs, NOX2, and ROS-related pathways may become a new antitumor treatment strategy by regulating immune infiltration. These results bring new insights into NCF-mediated KIRC immune regulation.

Data Availability
The datasets analyzed in the current study are publicly available in cBioPortal and TCGA and accessed via the Genomic Data Commons Data Portal (https://gdc.cancer.gov). The

Consent
All the datasets were retrieved from the publishing literature, so it was confirmed that all written informed consent was obtained.

Conflicts of Interest
There is no conflict of interest between the authors of this article.