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. 2023 Aug 22;35:101533. doi: 10.1016/j.bbrep.2023.101533

Expression and clinical significance of RBBP4 gene in lower-grade glioma: An integrative analysis

Ruofei Liang a,1, Yue Xiang b,1, Chao Hu a, Xiaoping Tang a,∗
PMCID: PMC10469049  PMID: 37664524

Abstract

This study investigated the expression pattern of retinoblastoma binding protein 4 (RBBP4) gene in glioma and explored its associations with clinicopathologic characteristics and prognosis of patients. Data retrieved from the GEPIA, CGGA, HPA and TIMER databases were processed to analyze RBBP4 expression in glioma and investigate its relationship with clinicopathologic characteristics, tumor immune infiltration and prognosis in glioma patients. Immunohistochemistry was applied to determine the expression of RBBP4 protein in glioma tissue. Additionally, the Coexpedia database was visited to identify co-expressed genes for RBBP4 gene, while the Cytoscape software was run to visualize the enriched GO entries and KEGG pathways of these co-expressed genes. The expression levels of RBBP4 in lower-grade glioma (LGG) and glioblastoma (GBM) tissues were markedly elevated when compared to normal tissues (both p < 0.05). The up-regulation of RBBP4 expression was associated with an increase in WHO grade (II-IV), wild-type IDH, and 1p/19q non-codeletion (all p < 0.05). Multi-variate Cox regression analysis showed that both increased abundance of infiltrating macrophages and up-regulated RBBP4 expression independently predicted poor survival outcomes in LGG patients (both p < 0.05). Furthermore, RBBP4 expression exhibited significant positive correlations with the abundance of infiltrating B cell, CD8+ T cell, CD4+ T cell, macrophage, neutrophil, and dendritic cell in LGG (all p < 0.05). Functional enrichment analyses indicated that the co-expressed genes associated with RBBP4 were highly involved in pathways such as the p53 signaling pathway, cell cycle, DNA replication, glutathione metabolism, as well as biological processes including cell cycle process, DNA replication, and DNA repair. High levels of RBBP4 are predictive for the poor survival outcome of LGG patients. RBBP4 gene, therefore, is expected to be a potential biomarker for prognosis of LGG and a target for immunotherapy.

Keywords: RBBP4 gene, Lower-grade glioma (LGG), Immune infiltration, Prognosis

Highlights

  • •

    The function and value of RBBP4 gene in prognosis of LGG have been less well studied by now.

  • •

    Our study first used bioinformatics to reveal the expression pattern and prognostic value of RBBP4 in LGG.

  • •

    Our study demonstrated that RBBP4 gene is promising as a target for clinical research and treatment of LGG.

1. Introduction

Glioma comprises the majority of adult primary malignant brain tumors. According to the WHO Classification of gliomas, gliomas are graded as I-IV and the malignancy increases with increasing WHO grade [1]. Glioblastoma (GBM) has the highest degree of malignancy, classified as WHO grade IV. Despite the advancement of treatment, patients with GBM still suffer from a low 5-year survival rate (below 6.9%) [2]. Lower-grade gliomas (LGG) (WHO grade II/III) are relatively less prevalent and associated with a better overall prognosis. However, they are also infiltrative and aggressive without clear boundaries. In this context, there is a high risk of recurrence or progression to higher grade gliomas [3], which prompts us to look for new therapeutic targets and prognostic biomarkers.

Retinoblastoma binding protein 4 (RBBP4), also known as retinoblastoma associated protein 48 (RbAp48), is essential in DNA damage repair and cell cycle regulation [4]. It is named for its binding with retinoblastoma protein (Rb). Research found that the RBBP4 gene exhibits aberrant expression in multiple tumors, which plays a role in tumorigenesis and progression [[5], [6], [7]]. Nevertheless, it remains elusive on the relationship between the RBBP4 gene and LGG. To this end, this study applied bioinformatics to analyze RBBP4 expression in gliomas. Meanwhile, associations of the RBBP4 gene with clinicopathological parameters, immune microenvironment and prognosis in glioma patients were explored. Moreover, the biological function of the RBBP4 gene was investigated via co-expression and enrichment analyses. This study attempts to help look for new therapeutic target for LGG.

2. Materials and methods

2.1. GEPIA database analysis

The GEPIA database can provide differential gene expression and patient survival analyses on the basis of the gene expression data from a vast number of tumors and normal samples from the TCGA and the GTEx projects [8]. In the Datasets Selection, LGG and GBM were selected as cancer names. After entering RBBP4 into the 'Gene' column, the GEPIA webpage automatically generated expression box plots. A p value cutoff of 0.01 was selected. Prognostic analysis was conducted using a Kaplan-Meier curve.

2.2. CGGA database analysis

The CGGA database is a repository composed of brain tumor datasets over 2000 samples from Chinese populations [9]. The mRNAseq_325 dataset was used to retrieve the RBBP4 gene expression data and its associations with clinicopathological parameters and glioma patient survival. In the Distribution section, the dataset mRNAseq_325 was selected. The 'Gene' column was inputted with RBBP4, which automatically generated a distribution pattern for each glioma subtype on the CGGA webpage. In the Survival section, the same procedure was followed for survival analysis. Subgroup analysis was performed using the following grouping strategy: WHO grade II, III, IV; wild-type and mutant isocitrate dehydrogenase (IDH); 1p/19q codeletion and non-codeletion; age ≥42 and age <42.

2.3. HPA database analysis

The HPA database provides a way to perform tumor/normal differential protein expression analysis using an integration of transcriptome and proteome data based on RNA sequencing and immunohistochemistry (IHC) techniques [10]. In this study, the gene RBBP4 was entered into the search box. The IHC data for normal brain and glioma tissues, using the anti-RBBP4 antibodies CAB006264 and HPA060724, were obtained.

2.4. IHC staining

A total of 36 cases pathologically diagnosed with glioma were collected for IHC analysis. All the sections were obtained between November 2019 and May 2020 in Affiliated Hospital of North Sichuan Medical College. The sections were initially deparaffinized and dehydrated. Antigen repair was obtained via microwave heating. The activity of endogenous peroxidase was blocked using H2O2. A diluted rabbit anti-human RBBP4 antibody (1:100) was added, and the sections were incubated overnight at 4 °C in a wet box [7]. Subsequently, HRP labeled goat anti-rabbit antibody was added for 30 min in an incubator at 37 °C. After washing with distilled water, the sections were exposed to DAB for color development and hematoxylin for nuclear counterstaining [5]. Slides were sealed with neutral resin after dehydration and transparency. Images were captured microscopically. The Informed Consent was signed by all participants or their family members, and the study received approval from the Ethics Committee of the Affiliated Hospital of North Sichuan Medical College.

2.5. TIMER database analysis

The TIMER database is a comprehensive resource for systematical analysis of immune infiltrates across diverse cancer types [11,12]. This study explored the association of immune infiltrates and RBBP4 gene expression using the TIMER database. We extracted data with the following conditions: (1) Module: Gene; (2) Gene symbol: RBBP4; (3) Cancer type: LGG and GBM; and (4) Immune infiltrates: B cell, CD8+T cell, CD4+T cell, macrophage, neutrophil, and dendritic cell. Multi-variate Cox regression model was established to investigate the value of the RBBP4 gene expression, tumor purity and immune infiltrates in prognosis. We obtained data with the following conditions: (1) Module: Survival; (2) Gene symbol: RBBP4; (3) Cancer type: LGG and GBM; (4) Clinical variables: Age, Gender, and Tumor Purity; and (5) Immune infiltrates: B cell, CD8+T cell, CD4+T cell, macrophage, neutrophil, and dendritic cell.

2.6. Potential mechanism of action of RBBP4

Coexpedia is an online tool with the deposition of co-expression data toward over 600 human and mouse datasets from the GEO database [13]. Here, the co-expressed genes of RBBP4 gene were retrieved from the Coexpedia database. The search was conducted by entering the gene name, RBBP4, into the designated search box provided by Coexpedia. These co-expressed genes were then processed for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Cytoscape software was applied for result visualizations.

2.7. Statistical analysis

Default statistical analytical methods were adopted corresponding to data derived from each database. Image-Pro Plus software was used to assess the average optical density of each IHC image [14]. SPSS 19.0 software was applied to perform t-test or one-way ANOVA, with p < 0.05 as significance threshold.

3. Results

3.1. RBBP4 expression in glioma tissues

The analysis of GEPIA data showed a significant increase in RBBP4 gene expression in LGG and GBM tissues compared to normal brain tissues (Fig. 1A). Based on the CGGA data, RBBP4 expression up-regulated with the increasing WHO grade (p = 6.5e-14, Fig. 1B), consistent with our IHC results (Fig. 1C and D). Furthermore, the IHC data derived from the HPA database also revealed distinct increase in RBBP4 protein expression in glioma tissues than non-glioma brain tissues (Fig. 1E and F). Additionally, the CGGA data demonstrated that RBBP4 expression was associated with the IDH (p = 0.0023) and 1p/19q codeletion status (p = 1.3e-33), but independent of patient sex, age, and progression status (Fig. 2).

Fig. 1.

Fig. 1

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Expression of RBBP4 in glioma tissues. (A) Expression level of RBBP4 in gliomas and normal brain tissues based on GEPIA database. (B) Expression level of RBBP4 in different pathological grades of gliomas based on CGGA database. (C) Representative images of IHC staining for RBBP4 in different pathological grades of gliomas [Grade II (11), Grade III (10), Grade IV (15)], magnification: 20x. (D) Statistical result of the AOD for RBBP4 in different pathological grades of gliomas. AOD, average optical density, calculated by integrated optical density/area. (E, F) Representative IHC images of RBBP4 in normal brain and glioma tissues were from the HPA database (E, Antibody HPA060724; F, Antibody CAB006264). *P < 0.05.

Fig. 2.

Fig. 2

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Relationship between RBBP4 expression level and clinicpathological parameters of glioma patients based on CGGA database. (A) IDH mutation status. (B) 1p/19q co−deletion status. (C) Gender. (D) Age status. (E) Progression status.

3.2. High RBBP4 expression predicts poor prognosis of glioma

In the CGGA database, the expression of RBBP4 showed significant prognostic value in glioma and was predictive of poor survival outcomes when its expression was up-regulated (Fig. 3A and B). Similarly, according to GEPIA survival data, patients with LGG who had high expression of the RBBP4 gene had shorter overall survival (OS) and disease free survival (DFS) compared to patients with low expression of the RBBP4 gene (both p < 0.05) (Fig. 3C and D). However, no significant associations were observed in GBM patients (Fig. 3E and F).

Fig. 3.

Fig. 3

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Prognostic value of RBBP4 in glioma. (A) The relationship between RBBP4 expression level and survival in primary glioma analyzed by CGGA database. (B) The relationship between RBBP4 expression level and survival in recurrent glioma analyzed by CGGA database. (C)The relationship between RBBP4 expression level and overall survival (OS) in LGG analyzed by GEPIA database. (D)The relationship between RBBP4 expression level and disease free survival (DFS) in LGG analyzed by GEPIA database. (E)The relationship between RBBP4 expression level and OS in GBM analyzed by GEPIA database. (F)The relationship between RBBP4 expression level and DFS in GBM analyzed by GEPIA database.

3.3. RBBP4 gene expression correlates to immune infiltrates in glioma

To analyze the role of RBBP4 gene expression in the immune microenvironment of glioma, we utilized the TIMER database to explore its association with immune infiltrates. In LGG, RBBP4 gene expression showed distinct positive associations with the infiltration abundance of B cell (R = 0.533, p = 1.70e-36), CD8+ T cell (R = 0.352, p = 2.17e-15), CD4+ T cell (R = 0.36, p = 5.35e-16), macrophage (R = 0.406, p = 3.28e-20), neutrophil (R = 0.451, p = 3.58e-25) and dendritic cell (R = 0.451, p = 3.19e-25). However, it was independent of tumor purity (R = −0.004, p = 9.29e-01). On the other hand, in GBM, RBBP4 gene expression was positively associated with tumor purity (R = 0.312, p = 6.93e-11) and neutrophil (R = 0.21, p = 1.49e-05), but showed no relevance to the infiltration of B cell, CD8+ T cell, CD4+ T cell, macrophage and dendritic cell (Fig. 4A). Subsequently, Kaplan-Meier survival curves were generated. Our study found that LGG patients with higher RBBP4 gene expression and increased infiltration of these six immune cell subtypes had shorter survival time (all p < 0.05). In GBM patients, only a higher level of infiltrating dendritic cells correlated with a shorter survival time (p = 0.002) (Fig. 4B). Moreover, multi-variate Cox regression model displayed that higher RBBP4 gene expression and increase in infiltrating macrophages were independently prognostic for poor survival in LGG patients (both p < 0.05) (Table 1). However, no noteworthy correlation was noted between RBBP4 gene expression and survival in GBM patients (p > 0.05). Furthermore, an independent association between an elevated infiltration of dendritic cells and unfavorable survival in GBM patients was observed (p < 0.05) (Table 2).

Fig. 4.

Fig. 4

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Correlation between RBBP4 expression and immune infltration level in LGG and GBM. (A) Correlation analysis of RBBP4 expression and infltration levels of immune cells. (B). Survival curves of RBBP4 expression level and immune cells infiltration.

Table 1.

Multi-variate Cox regression model analysis of the correlation of RBBP4 expression and immune infiltrates with OS in LGG.

Coefficient HR 95% CI P- value Sig
Age 0.059 1.060 1.043–1.078 0.000 ***
Gender(male) 0.166 1.181 0.785–1.776 0.424
Purity −0.267 0.765 0.301–1.947 0.575
B_cell −0.348 0.706 0.001–641.700 0.920
CD8+Tcell 1.454 4.279 0.003–7124.630 0.701
CD4+Tcell −2.616 0.073 0.000–373.811 0.548
Macrophage 5.711 302.095 4.089–22318.831 0.009 **
Neutrophil −5.098 0.006 0.000–38.272 0.253
Dendritic 2.673 14.486 0.185–1132.340 0.229
RBBP4 0.631 1.880 1.146–3.082 0.012 *
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*P < 0.05; **P < 0.01; ***P < 0.001.

Table 2.

Multi-variate Cox regression model analysis of the correlation of RBBP4 expression and immune infiltrates with OS in GBM.

Coefficient HR 95% CI P- value Sig
Age 0.030 1.031 1.022–1.040 0.000 ***
Gender(male) 0.070 1.072 0.860–1.338 0.535
Purity 0.202 1.224 0.624–2.401 0.556
B_cell −0.422 0.655 0.350–1.228 0.187
CD8+Tcell 0.346 1.413 0.912–2.190 0.122
CD4+Tcell 0.098 1.102 0.508–2.393 0.805
Macrophage 0.462 1.588 0.748–3.371 0.229
Neutrophil 0.345 1.412 0.576–3.459 0.450
Dendritic 0.530 1.699 1.241–2.327 0.001 **
RBBP4 −0.072 0.931 0.812–1.067 0.305
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**P < 0.01; ***P < 0.001.

3.4. Potential mechanism of action of RBBP4

A total of 402 co-expressed genes of RBBP4 were retrieved from the Coexpedia database (Fig. 5) and processed for GO and KEGG enrichment analyses. The most enriched GO entries were categorized into three aspects. Cellular component (CC) included nucleolus, nuclear part, and nucleoplasm, etc. (p < 0.05) (Fig. 6A). Biological processes (BP) involved signal transduction by p53 class mediator, negative regulation of G0 to G1 transition, cell cycle process, DNA replication, and DNA repair, etc. (p < 0.05) (Fig. 6B). Molecular function (MF) included nuclear receptor binding, regulation of helicase activity, and regulation of helicase activity, etc. (p < 0.05) (Fig. 6C). Additionally, the most enriched KEGG pathways were associated with multiple tumor pathways, such as the p53 signaling pathway, cell cycle, DNA replication, and glutathione metabolism, etc. (p < 0.05) (Fig. 6D).

Fig. 5.

Fig. 5

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The co-expressed genes of RBBP4.

Fig. 6.

Fig. 6

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GO and KEGG enrichment analyses of the co-expressed genes of RBBP4.

(A) Cellular Components. (B) Biological processes. (C) Molecular function. (D) KEGG pathways.

4. Discussion

Gliomas, which account for the majority of primary malignant brain tumors in adults, exhibit rapid development, invasive growth and high malignancy. The 2016 WHO Classification of gliomas emphasized the importance of genotyping in predicting the prognosis of glioma patients [1]. IDH mutations are proved as an independent prognostic biomarker for good outcomes in glioma patients [15]. The deletion status of 1p/19q is considered to be an important factor in predicting the survival of patients with glioma. When there is a codeletion of 1p/19q, it suggests that the tumor is relatively stable and the prognosis is favorable for the patient [16,17]. Generally, LGG have a better prognosis compared to GBM. However, there is still a subset of LGG patients who are at risk of recurrence and progression to higher grade gliomas despite standard treatment, leading to poor survival outcomes [18,19]. Therefore, there is a pressing requirement for the identification of new therapeutic targets in order to enhance the effectiveness of treatment and prognosis for individuals diagnosed with LGG.

RBBP4 proteins, belonging to a subfamily of WD-repeat proteins, are important participants in the initiation and progression of malignancies. In a study conducted by Li et al. [6], it was found that RBBP4 is increasingly expressed in colon cancer. Additionally, suppressing the expression of this gene was found to inhibit the proliferation of cancer cells [6]. Similarly, Zhong et al. [20] reported up-regulated expression of RBBP4 in cervical cancer tissues, and after silencing its expression, there was a considerable reduction in the migration and invasion capabilities of cancer cells. Guo et al. [5] also discovered increased RBBP4 expression in breast cancer tissues. Moreover, they found that high levels of RBBP4 expression were independently predictive of poor prognosis in patients [5]. These findings suggest that the RBBP4 holds potential application for tumor gene therapy. Nevertheless, its function and value in prognosis of LGG have been less well studied by now. In this study, we first utilized bioinformatics to investigate the expression pattern, tumor immune infiltration, and prognostic significance of RBBP4 in LGG. The findings may provide a new target for LGG immunotherapy and thereby to improve the patient clinical outcomes.

The analysis of GEPIA and HPA data showed a significant increase in RBBP4 expression in glioma tissues at both the RNA and protein levels. Additionally, data retrieved from the CGGA database indicated a relationship between the expression of RBBP4 and the WHO grade of glioma, which was further supported by our IHC experiment. The CGGA data also revealed a strong association between RBBP4 expression and the IDH and 1p/19q codeletion statuses. Specifically, patients with wild-type IDH and non-codeletion of 1p/19q showed higher levels of RBBP4 expression. Survival analysis revealed that elevated levels of RBBP4 expression were predictive of shorter survival times in LGG patients.

To discuss the role of RBBP4 expression in immune microenvironment, TIMER data were obtained and processed for multi-variate Cox regression. The findings showed that increases in RBBP4 expression and infiltration of macrophages were independent risk factors for adverse prognosis of LGG patients. It was noting that RBBP4 expression was remarkably positively linked to multiple immune infiltrates in LGG, including B cell, CD8+ T cell, CD4+ T cell, macrophage, neutrophil and dendritic cell. These results imply that RBBP4 gene expression regulates the immune status in LGG via affecting the immune microenvironment, which provides new insights into the tumorigenesis and treatment from the aspect of immunity.

Furthermore, we mined co-expressed genes for RBBP4 gene from the Coexpedia database to study its biological function and employed the Cytoscape software to visualize the most enriched GO entries and KEGG pathways for the co-expressed genes. The most enriched GO entries were involved in cell cycle, DNA replication and repair, etc. There was evidence showing that regulation of cell cycle and DNA repair is important in the initiation and progression of gliomas [[21], [22], [23], [24]]. Therefore, RBBP4 gene might affect the development of gliomas via modulating the cell cycle and DNA damage repair. Another compelling evidence was provided by Kitange et al. [25], who found that RBBP4 regulated the expression of DNA repair genes and silencing of RBBP4 increased the sensitivity of GBM cells to temozolomide. In addition, KEGG analysis revealed that RBBP4 may exert its function in gliomas through multiple pathways such as p53 signaling pathway, cell cycle, DNA replication and glutathione metabolism. p53 is present as wild-type or mutant, with the former being tumor-suppressive while the latter being oncogenic. Both the wild-type and mutant p53 are vital in cell cycle regulation and apoptosis. In addition, p53 also has implications in glioma response to chemotherapy and radiotherapy [[26], [27], [28]]. Collectively, the findings indicate that RBBP4 gene may cooperate with its co-expressed genes to affect the onset and progression of gliomas. In all, this study provides certain reference for further research into the biological functions and mechanisms of RBBP4 gene in gliomas, in spite of the lack of validation via in vivo and vitro experiments.

5. Conclusions

To conclude, the study revealed increased RBBP4 expression in gliomas and that LGG patients highly expressing RBBP4 tended to experience a poorer survival outcome. Additionally, RBBP4 was involved in LGG development probably through participation in tumor immune microenvironment. Moreover, RBBP4 also showed implications in various biological processes and signal transduction in tumor. RBBP4 gene, therefore, is promising as a target for clinical research and treatment of LGG. However, further experiments are required to unravel the specific mechanism.

Funding

This work was supported by the project of Affiliated Hospital of North Sichuan Medical College (2021JC003).

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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