Abstract

Clear cell renal cell carcinoma (ccRCC) is one of the pathological types of renal cell carcinoma with poor prognosis, which poses a serious threat to human life. Therefore, there is a need to develop appropriate tumor markers to predict the development, treatment, and prognosis of ccRCC. As a member of a new protein family involved in ammonia transport in the mammalian kidney, RHBG plays an important role in the kidney. Therefore, the relationship between RHBG and clinical characteristics, prognostic risk, overall survival and immune infiltration in patients with clear cell renal cell carcinoma was explored by bioinformatics. The Cancer Genome Atlas (TCGA) database was used to evaluate the correlation between RHBG and ccRCC. The results showed that the expression of RHBG in renal cancer tissues was lower than that in normal tissues (P<0.001); ROC curve showed that RHBG had a high diagnostic value (AUC=0.957). The low expression of RHBG is associated with the immune status of renal clear cell carcinoma. These data suggest that RHBG is a viable potential biomarker for ccRCC with great potential for future clinical application and translation.

1. Introduction

Renal cell carcinoma (RCC), a malignant tumor originating from renal tubular epithelial cells, accounts for about 90% of renal malignant tumors. (ccRCC) is the most common type of renal cell carcinoma. ^{1, 2, 3} The 5-year survival rate of patients with early clear cell renal cell carcinoma after surgical resection is more than 90%. However, patients with advanced clear cell renal cell carcinoma are prone to relapse after surgery. Even with chemotherapy and radiotherapy, most patients survive for about 3 years on average. ^{4, 5, 6, 7} In order to effectively control or eradicate tumor cells, there is an urgent need to develop new cancer treatments.

With the development of biomedical technology, targeted therapy and immunotherapy are the main forces for the treatment of advanced clear cell renal cell carcinoma. ^{8, 9, 10, 11} Compared with traditional tumor therapy, targeted therapy has the characteristics of identifying and analyzing the mechanism of action and key genes of RCC, which lays the foundation for the preparation and development of subsequent targeted drugs. ^{12, 13, 14, 15} Therefore, in order to provide a solid theoretical basis for the treatment of renal cell carcinoma, we study the genes of renal cell carcinoma in order to screen out the key genes for the diagnosis and treatment of renal cell carcinoma and achieve targeted therapy. ^{16, 17}.

RH blood group proteins have two non-erythroid homologs, RHCG(Rh family C glycoprotein) and RHBG(Rh family B glycoprotein), which share homology with specific ammonia transporters in primitive organisms and plants, are mainly expressed in the kidney, and represent members of a new family of proteins involved in ammonia transport in mammalian kidneys. ^{18, 19, 20, 21, 22} Among them, RHCG is expressed in the apical pole of all connecting tubule (CNT) cells as well as in intercalated cells of collecting duct (CD), whereas relatively few studies have been performed on RHBG. Recently, Regine et al. produced a polyclonal antibody against the RHB type glycoprotein to detect the localization of RHBG in the nephron. ²³ The presence of RHBG and RHCG at the major sites of renal ammonia secretion, CNT and CD, is consistent with their role in ammonia transport. Lee et al. found that RHBG participates in the transport of NH3/NH4+ and methylamine (hydrochloric acid) (MA/MA+) in oocytes in a manner distinct from NH3/NH4+. ²⁴ Based on this, we screened according to TCGA database that RHBG has potentially important value in the diagnosis and prognosis of patients with renal cell carcinoma.

In this study, we investigated the association of RHBG with renal clear cell carcinoma using clinical data in TCGA, including clinical characteristics, prognosis and survival data.

2. Materials and Methods

From the TCGA database (https://portal.gdc.cancer.gov) to download and organize TCGA - KIRC (renal clear cell carcinoma) project STAR process RNAseq data and extract the TPM (Transcripts Per Million) format of the data and clinical data. The clinicopathological data included age, height, weight, gender, and race. As this was a bioinformatics study, no ethics committee or institutional review board approval was required. This study was conducted in accordance with the published guidelines provided by TCGA.

TCGA data were used for clinicopathological analysis. The Kruskal-Wallis test was selected according to the data format characteristics, and the data were visualized using the ggplot2 package. Clinical prognostic information included overall survival (OS) and disease-specific survival (DSS). Kaplan-Meier (K-M) method was used for univariate and multivariate Cox regression analysis.

Considering the results of the multivariate analysis, nomograms were evaluated in order to personalize the prediction of life expectancy. The survival package was used for proportional hazards hypothesis testing and Cox regression analysis, and the rms package was used to construct and visualize the nomogram correlation model. Calibration and discrimination are the most commonly used methods to evaluate model performance. A calibration chart was constructed to evaluate the predictive accuracy of the nomogram based on the prognostic model.

Gene set enrichment analysis (GSEA) was used to establish a series of genes related to RHBG expression. Samples were divided into RHBG high and RHBG low expression groups as training sets to distinguish latent functions and elucidate significant survival differences. Gene set alignments were performed multiple times for each examination. Standardized enrichment scores and adjusted P values were used to rank pathways enriched for each phenotype.

Spearman correlation method was used to analyze the correlation between RHBG and immune cells, and Wilcoxon rank sum test was used to compare the infiltration of these cells between samples with high and low RHBG expression.

Wilcoxon signed rank test was used to analyze the expression level of RHBG gene in unpaired samples of renal cell carcinoma patients. Paired sample t test was used to analyze the expression of RHBG gene in renal cell carcinoma patients. Mann-Whitney U test (Wilcoxon rank sum test) and Wilcoxon signed rank test were used to analyze the difference of RHBG[ENSG00000132677.13] between multiple groups and paired samples. Cox regression was used to compare the prognosis between high and low RHBG groups and between subgroups. The pROC package was used for ROC analysis of the data, and the results were visualized by ggplot2. spearman analysis was used to analyze the correlation between RHBG and immune infiltration and presented in the form of a lollipop chart. GSEA analysis was performed with the clusterProfiler package. Significant markers: ns, P≥0.05; *, P<0.05; **, P<0.01; ***, P<0.001. A p-value<0.05 was considered statistically significant.

3. Results

Firstly, we retrieved 541 samples of ccRCC patients from TCGA database, including 269 samples with low RHBG expression and 272 samples with high RHBG expression. Table 1 lists the detailed clinical and genetic characteristics of ccRCC patients. There were significant differences in pathological M stage, pathological stage and hemoglobin between patients with low RHBG expression and patients with high RHBG expression. The low expression of RHBG was correlated with pathological M stage (P=0.030), pathological stage (P= 0.032) and hemoglobin (P=0.013).

In TCGA dataset, RHBG was highly expressed in renal clear cell carcinoma (Figure 1A). Paired sample analysis using Wilcoxon rank sum test also showed that RHBG was significantly upregulated in ccRCC (P<0.001) (Figure 1B). These results suggest that RHBG may play a role in the pathogenesis of clear cell renal cell carcinoma. qRT-PCR analysis of RHBG expression in human renal cortical/proximal tubular cell line HK-2, human renal adenocarcinoma cell line (ACHN) and human renal carcinoma cell line (A-498) showed that the expression of RHBG was significantly down-regulated in ACHN (P<0.01) and A-498 (P<0.01) cells (Figure 1C and 1D). In addition, pan-cancer RHBG expression was evaluated, and by Mann-Whitney U test (Wilcoxon rank sum test), RHBG expression was found to be higher in 15 tumors than in their corresponding normal tissues, including: BLCA (P<0.001) BRCA (P<0.001) COAD (P<0.001) HNSC (P<0.001) KICH (P<0.001) KIRC (P<0.001) KIRP (P<0.001) LUAD (P<0.001) LUSC (P<0.001) READ (P<0.001) UCEC (P<0.001) GBR (P<0.01) PRAD (P<0.01) CHOL (P<0.05) PCPG (P<0.05) (Figure 1E). By Wilcoxon signed rank test, RHBG expression was found to be higher in 11 tumors than in their corresponding normal tissues, including BRCA (P<0.001) COAD (P<0.001) HNSC (P<0.001) KICH (P<0.001) KIRC (P<0.001) KIRP (P<0.001) LUAD (P<0.001) LUSC (P<0.001) BLCA (P<0.01) READ (P<0.05) UCEC (P<0.05) (Figure 1F).

Based on this, we hypothesized that the low expression of RHBG in renal cell carcinoma may be associated with prognosis. Therefore, the study of Table 2 was performed. The results were consistent with our predictions. Low RHBG expression was associated with T stage (T3&T4 vs. T1&T2: OR = 1.525 (1.069-2.175), P =0.020) and Pathologic M stage (M1 vs. M0: OR = 1.719 (1.051-2.813), P=0.031), Pathologic stage (Stage III&Stage IV vs. Stage I&Stage II: OR = 1.652 (1.163-2.348), P=0.005) and Hemoglobin (Normal vs. Low&Elevated: OR = 0.598 (0.411-0.869), P=0.007).

The cBioPortal website was used to explore the genetic alterations of RHBG gene in different types of cancers in TCGA cohort. As shown in Figure 2, among CHOL(Cholangiocarcinoma) patients with “amplification” as the main change, the frequency of RHBG changes was the highest (11.11%). Alterations in the RHBG gene were found in only 0.2% of the "amplification" frequencies of all ccRCC cases.

The relationship between RHBG expression and OS of cancer patients was studied by basic evaluation of RHBG expression in different tumors. Kaplan-Meier survival analysis (P=0.011, HR=1.48) and multiple clinical subgroups (Figure 3A-O), including T3(P=0.005, HR=2.00), M0(P=0.006, HR=2.20), stageⅢ (P=0.004, HR=3.07), female (P=0.002, HR=3.22), male (P=0.005, HR=1.77), white (P=0.017, P=0.017; HR=1.47), age ≤60 years old (P=0.004, HR=2.14), age>60 years (P=0.017, HR=1.64), G3(P=0.006, HR=2.03), G4(P=0.016, HR=1.70), hypocalcemia (P=0.005, HR=2.11), normal serum calcium (P=0.003, P=0.005, HR=2.11), HR=2.58), left laterally (P=0.002, HR=2.07) and right laterally (P=0.019, HR=1.81). Univariate Cox analysis (logrank test) confirmed that the low expression of RHBG was related to the good prognosis of patients with renal cell carcinoma (hazard ratio (HR)=1.483, 95% CI, 1.094-2.010, P=0.011). Multivariate Cox analysis confirmed that low RHBG expression was associated with a good prognosis in patients with renal cell carcinoma [hazard ratio (HR)=1.408, 95% CI, 1.033-1.920, P=0.030] (Table 3).

According to ROC curve analysis, RHBG was not only closely related to the prognosis of renal cell carcinoma, but also had a high diagnostic value (AUC = 0.957) (Figure 4A). In addition, a nomogram was constructed to predict patient survival at 1, 3, and 5 years, taking into account RHBG expression and other predictive variables such as age and stage (Figure 4B). We constructed a bias correction line in the calibration plot to approximate the ideal curve (45-degree line), which indicates perfect agreement between prediction and observation (Figure 4C).

The gene expression profiles of RHBG high and low expression groups were compared by RNAseq gene expression analysis to clarify whether RHBG plays a role in the occurrence and development of ccRCC. We verified RHBG expression in normal and tumor samples using paired plots, and the results showed statistically significant differences. A total of 2793 up-regulated genes were detected in RHBG high expression group (P>1.5-fold) and 28 down-regulated genes (>-1.5 times). The expression of DEG is shown by the volcano plot (Figure 4D).

Spearman correlation coefficient was used to analyze RHBG-related gene expression in the data grouped according to RHBG gene expression, and the ggplot package was used to visualize the co-expression heat map of the analysis results with RHBG as the main variable (Figure 5). RHBG expression was positively correlated with DPM1, and negatively correlated with GCLC, NFYA, FUCA2 and other genes.

We analyzed the immune cell infiltration in patients with renal clear cell carcinoma from the TCGA database. The expression of RHBG correlated with B cells, aDC, CD8T cells, Cytotoxic, Eosinophils, Macrophages, Mast cells, Neutrophils, NK CD56dim cells, NK cells, p DC and T A negative correlation was observed in cells (Figure 6A-L). The results of the chord chart were consistent with the results of the immune infiltration scatter plot. The expression of RHBG was significantly negatively correlated with T cell infiltration, B cell infiltration, NK cell infiltration, CD8 cell infiltration, Neutrophils cell infiltration and Macrophages (Figure 6M). The results indicate that low expression of RHBG inhibits T cells, B cells, NK cells, CD8 cells, Neutrophils and Macrophages, suggesting that low expression of RHBG is related to the immune status of renal clear cell carcinoma. Spearman correlation analysis between RHBG expression and immune cell enrichment (ssGSEA generation) showed a positive correlation between RHBG expression and NK CD56 bright cell abundance (P =0.0249) (Figure 6N).

4. Discussion

Renal clear cell carcinoma is the most common pathological type of renal cell carcinoma, accounting for 70% of all renal cell carcinomas, and it is also one of the pathological types of renal cell carcinoma with the worst prognosis. ^{25, 26} Targeted therapy is often used for advanced ccRCC patients with distant metastasis or recurrence after surgery. Although targeted therapy drugs can effectively improve the overall survival of patients, it is difficult to avoid the emergence of tumor drug resistance. Therefore, clarifying the oncogenes and mechanism of action of cancer is conducive to excavating new therapeutic targets, thereby reversing tumor resistance and improving patient survival time.

RHBG, an Rh family B glycoprotein with homology to specific ammonia transporters in primitive organisms and plants, represents a member of a new family of proteins involved in ammonia transport in the mammalian kidney. I David Weiner et al. found that RhBG and RhCG play important cell-specific roles in ammonium transport and signaling in these regions of the kidney. ²⁷ Lee et al. used two-electrode voltage clamp and ion-selective microelectrodes to measure NH4+-induced and methylammonium MA+ current and intracellular pH (pH (i)) changes, respectively, and found that RHBG is ph-sensitive to NH4+ and MA/MA+ transport. ²⁸ By expressing human RHAG, RHBG and RHCG in Xenopus oocytes, Raif Musa-Aziz and his team discovered the mechanism by which RHBG and RHCG promote CD acid secretion by enhancing NH₃ and CO₂ transmembrane transport. ²⁹ Connie M Westhoff and his team found that the polarized localization of RhBG and RhCG in the renal tubules and the different substrate affinities may allow these proteins to participate in transepium ammonia secretion and thus play an important role in acid-base regulation throughout the animal. ³⁰ Yves Colin and his team found findings suggesting a close relationship between the sorting and anchoring of RHBG and the basolateral domain of epithelial cells. ³¹ I David Weiner et al. found that both RHBG and RHCG are highly expressed in specific cells of the male reproductive tract and that they can promote multiple components of male fertility. ³² Ashley M Toye and his team found that RHCG is the major putative ammonia transporter expressed in the human kidney under normal conditions, whereas RHBG is not expressed at high levels. ³³ Existing studies have shown that RHBG is associated with ammonia transport in the kidney. However, studies on RHBG in cancer are very scarce. We first investigated the diagnostic and prognostic functions of RHBG in ccRCC using bioinformatics methods.

At the bioinformatics level, we performed paired and unpaired analyses of ccRCC in RHBG and found that the expression level of RHBG in ccRCC was significantly lower than that in normal tissues. We then analyzed the expression level of RHBG in all cancers and found that it was low expressed in the vast majority of cancers. We found that RHBG is significant in terms of M stage, pathological stage, and hemoglobin in ccRCC patients, and it plays a very important role in the prognosis of ccRCC. In addition, the results of ROC curve and column line table indicated that RHBG had a high diagnostic value in ccRCC. Scatter plots, lollipop plots and chord plots of immune infiltration indicated that RHBG was closely related to immune cell infiltration.

5. Results

In conclusion, bioinformatics studies have shown that RHBG is lowly expressed in ccRCC and is associated with tumor M stage, pathological stage and hemoglobin aspects. In addition, the ROC curve suggested that RHBG had a high diagnostic value in ccRCC and may be used as a diagnostic marker for ccRCC. The immune infiltration scatter plot, lollipop plot and chord plot also suggested the potential correlation between RHBG and immune cell infiltration, which provided the basis and suggestion for further study of the mechanism of action.

Author Contributions

Methodology: Ying Song

Supervision: Haiming Yu

Writing – original draft: Ying Song

Writing – review & editing: Haiming Yu

References