All data used in the bioinformatics analysis were obtained from and analyzed using the following public databases: the UALCAN (http://ualcan.path.uab.edu/index.html), The Cancer Genome Atlas (TCGA; https://cancergenome.nih.gov/), STRING (https://string-db.org/) and the DAVID online analysis tool (https://davidbioinformatics.nih.gov). Gene Ontology (GO) and Kyoto Encyclopedia of Genome (KEGG) via the DAVID online analysis tool. Gene expression levels were compared and Kaplan-Meier survival analyses performed using the UALCAN online tool, which provides access to cancer transcriptome data from TCGA.

RPA1-related data were retrieved from TCGA, and differentially expressed genes were screened using the limma package in R (3.56.0; https://bioconductor.org/packages/limma/). The differentially expressed genes were subjected to protein-protein interaction (PPI) network analysis using the STRING database, which provides known and predicted protein interactions. The results were visualized using Cytoscape, and the molecular complex detection (MCODE) plug-in was used to identify clustered sub-networks within the PPI network In the GO and KEGG gene enrichment analysis conducted via DAVID, the significance threshold was set at P<0.05.

The HA1800 normal astrocyte cell line, two low-grade glioma (LGG) cell lines, namely U251 and SF295, and two GBM cell lines, namely A172 and TG905, were acquired. The normal astrocyte cell lines HA1800 and human glioma cell lines U251, SF295, A172 and TG905 were purchased from the Cell Bank of the Chinese Academy of Science. All cell lines were cultured in Dulbecco's modified Eagle's medium (DMEM) (HyClone; Cytiva) supplemented with 10% fetal bovine serum (HyClone; Cytiva), 100 g/ml streptomycin and 100 U/ml penicillin (Gibco; Thermo Fisher Scientific, Inc.) in a humidified atmosphere of 5% CO₂ at 37˚C. The cells were collected and homogenized, and the cellular proteins and RNA were extracted as described below.

Glioma tissue samples (WHO grades I-IV) were collected by neurosurgeons from 70 patients who underwent brain glioma resection and were diagnosed with glioma by postoperative histopathological examination at Linyi People's Hospital (Linyi, China) between June 2014 and December 2016 (Table I). In addition, 10 normal brain tissue samples were obtained from patients with craniocerebral trauma during frontal lobe decompression at Linyi People's Hospital (Linyi, China) between June 2014 and December 2016 (male:female, 6:4; 3 were <44 years old and 7 were ≥44 years old). Basic patient characteristics and clinical diagnosis information were obtained from all participants. The inclusion criteria comprised the availability of imaging data and complete details of the specific treatment process. Patients with a clear imaging diagnosis and postoperative pathological diagnosis were included in the experimental group. The study was approved by the Human Ethics Committee of Linyi People's Hospital (approval no. 30036), and all patients provided written informed consent.

Western blot analysis was performed to determine the RPA1 expression levels of the cell lines. Total protein was extracted from the cell homogenate in RIPA lysis buffer (Wanleibio) containing protease inhibitors, and the protein concentration was determined using the bicinchoninic acid method. Following electrophoresis (25 µg per lane; 10% SDS-PAGE), the proteins were transferred to a PVDF membrane. After blocking with 5% skimmed milk for 2 h at a room temperature (20-25˚C), the membrane was incubated with an RPA1 antibody (1:400; cat. no. DF6172; Wuhan Sanying Biotechnology) overnight at 4˚C. GAPDH mAb (1:2,000; cat. no. AF7021; Wuhan Sanying Biotechnology) was used as a control. The membrane was then washed by PBST (0.05% Tween-20) and incubated with horseradish peroxidase-labeled secondary antibody (1:2,500; cat. no. S0001; Cell Signaling Technology, Inc.) for 2 h at a room temperature. After washing the membrane three times, an ECL Supersensitive Detection kit (Shanghai Biyuntian Biotechnology Co., Ltd.) was used to visualize the protein bands. QuantityOne densitometric analysis software (version 4.6; Bio-Rad Laboratories, Inc.) was used to calculate the expression level of RPA1 using GAPDH as the loading control. Each western blot experiment was repeated at least three times to ensure the reproducibility of the results.

The glioma tissue was embedded in paraffin with 4% paraformaldehyde for 24 h at room temperature (20-25˚C), sectioned (4 µm) and dried at 70˚C for 45 min. The paraffin sections were routinely dewaxed and hydrated, followed by antigen retrieval in citrate buffer (PH 6.0) for 15 min at 95-100˚C. The sections were then subjected to quenching with a peroxidase blocker (3% H₂O₂), washed with PBS, and blocked with 5% normal goat serum (Vector Laboratories, Inc.) for 1 h at 4˚C. The sections were then incubated with primary RPA1 antibody (1:400; cat. no. DF6172; Wuhan Sanying Biotechnology), anti-Ki67 (1:400; cat. no.27309-1-AP; Proteintech Group, Inc.) and anti-p53mut (1:300; cat. no. AF0879; Affinity Biosciences) overnight at 4˚C. After washing with PBS, the sections were incubated with a goat anti-mouse IgG (H+L) HRP secondary antibody (1:2,000; cat. no. S0002; Affinity Biosciences) for 1 h at room temperature (20-25˚C). Finally, the sections were counterstained with hematoxylin (5 min at normal temperature), digested with hydrochloric acid, washed, stained with ammonia bluing solution, dehydrated in an alcohol gradient, cleared and mounted. The IHC staining was interpreted independently by two pathologists using a light microscope. Positive expression of RPA1 was identified based on the appearance of brown granules in the cytoplasm and/or nucleus. The counting method was to count all tumor cells in the field of view one by one, and calculate the percentage of positive cells in the total cells, such as ’the RPA1-positive cell rate was ~30%’. An expression score was determined based on the percentage of positive cells and the staining intensity, which were scored as follows: 0 points, no positive cells in any visual fields; 2 points, ++ staining intensity and <10% positive cells; 3 points, + staining intensity and >50% positive cells; 4 points, ++ staining intensity and <50% positive cells); 5 points, ++ staining intensity and >50% positive cells; and 6 points, +++ staining intensity and 100% positive cells. A score of >4 was defined as high RPA1 expression and a score of ≤4 was defined as low RPA1 expression (14). In this immunohistochemistry of glioma cells, the high/low Ki-67 groups were classified based on the proportion of Ki-67 positive cells to total cells. Glioma samples with a positive cell proportion ≤5% were defined as the low Ki-67 groups, while those with a positive cell proportion >5% were classified as the high Ki-67 groups.

Total RNA was extracted from cells using an RNeasy Mini Kit (Takara Bio, Inc.), and the quality of the RNA was assessed using a NanoDrop ND-1000 instrument. cDNA was synthesized from 1 µg RNA using a High-Capacity cDNA Reverse Transcription Kit (Thermo Fisher Scientific, Inc.) was used according to the manufacturer's protocol. qPCR was then performed using the StepOnePlus system (Applied Biosystems; Thermo Fisher Scientific, Inc.) with SYBR Green Master Mix (Thermo Fisher Scientific, Inc.) and gene-specific primers (Fuzhou Phygene Biotechnology Co., Ltd.). The following PCR conditions were used: 95˚C for 10 min followed by 40 cycles of 95˚C for 15 sec and 60˚C for 1 min, and melting curve analysis. Relative gene expression was determined via the 2^-ΔΔCq method (15) using GAPDH as the reference gene. Triplicate reactions were performed, and a standard curve was used to verify 100% primer efficiency. The forward and reverse primer sequences were as follows: RPA1 forward, 5'-AAGTGGAGACCTACAACGAC-3' and reverse 5'-ACAACCACCTGAGCGTAT-3'; and GAPDH forward, 5'-GACCTCAACTACATGGTTTA-3' and reverse, 5'-AATGAGCCCCAGCCTTCTCC-3'. Primer synthesis was performed by Sangon Biotech Co., Ltd. The experiments were repeated three times under the same conditions.

SPSS 22.0 (IBM Corporation) statistical analysis software was used. Unpaired Student's t-test was used to compare RPA1 expression between two groups. One-way ANOVA followed by Tukey's post hoc tests was used for the comparison of multiple groups. χ² test was used to analyze the associations of RPA1 expression with clinicopathological parameters. The relationship between RPA1 expression and overall survival (OS) in patients with glioma was evaluated using Kaplan-Meier survival analysis, and survival differences were compared using the log-rank test. P<0.05 was considered to indicate a statistically significant difference.

To clarify the relationships between RPA1 and glioma features, TCGA database and the UALCAN online tool were used to analyze the differences in RPA1 expression among 518 LGGs, 163 high-grade gliomas (HGGs) and 207 normal brain tissues. This revealed that the expression levels of RPA1 in both types of glioma were significantly higher than those in normal brain tissues. In addition, Kaplan-Meier OS analysis was performed for patients with glioma and high or low RPA1 expression (n=338/group). This analysis revealed that high RPA1 expression was associated with a significant shortening of the duration of OS in patients with glioma (Fig. 1).

The expression of RPA1 in HA1800 normal astrocyte cell line, U251 and SF295 glioma cell lines and A172 and TG905 GBM cell lines was analyzed. According to the WHO tumor grading criteria, gliomas are classified into grades I-IV, based on their cytological characteristics and molecular biological features, where a higher grade indicates greater malignancy. The U251 and SF295 glioma cell lines are considered LGGs while the A172 and TG905 glioma cell lines are considered HGGs. RT-qPCR analysis revealed that the mRNA levels of RPA1 in the glioma cell lines were significantly greater than those in the normal astrocyte cell line, and significantly higher in the A172 and TG905 GBM cell lines compared with those in the U251 and SF295 LGG cell lines (Fig. 2A). These findings indicate that the mRNA expression levels of RPA1 in glioma cells were greater than those in normal astrocyte cells and increased with the degree of glioma malignancy. The upregulation of RPA1 in HGGs suggests that RPA1 may play a role in the progression of glioma.

Similarly, western blot analysis revealed that the protein expression levels of RPA1 in the glioma and GBM cells were significantly greater than that in normal astrocyte cells. Furthermore, the expression levels of RPA1 in the A172 and TG905 GBM cell lines were greater than that in the U251 glioma cell line, and the expression level of RPA1 in the A172 glioblastoma cell line was greater than that in the SF295 glioma cell lines. These observations support the mRNA results in suggesting that the RPA1 expression level is positively associated with the WHO grade in glioma cells (Fig. 2B and C).

RPA1 IHC staining was performed on 70 glioma tissue samples from patients with glioma of WHO grades I-IV. The results revealed that the expression of RPA1 increased as the degree of glioma malignancy increased. In addition, the expression of RPA1 in HGG was significantly greater than that in LGG (Fig. 3). The 70 glioma samples were divided into high and low RPA1 groups, and the associations between the expression of RPA1 and various clinicopathological parameters were analyzed (Table I, Fig. 4). The results revealed that RPA1 expression was significantly associated with tumor WHO grade, Ki-67 and p53mut (P<0.05). However, no associations were found between RPA1 expression and patient sex distribution, age, tumor size, Karnofsky Performance Status (KPS; a commonly used tool for evaluating the overall health status and functional level of patients) score, or tumor location in 70 patients with glioma (Table I; Fig. 4).

The survival of the 70 patients with gliomas was analyzed. KaplanMeier analysis revealed that low RPA1 expression was associated with a significantly prolonged OS (Fig. 5). These findings are consistent with the results of the initial database analysis, further confirming that high RPA1 expression is associated with the degree of malignancy of glioma.

To further explore the role of RPA1 in glioma proliferation, bioinformatics analysis was performed to predict the signaling pathways mediated by RPA1. A PPI network involving RPA1 was constructed using the STRING database (Fig. 6). Following identification of the top 10 genes associated with RPA1 (Table II), gene set enrichment analysis was performed using the DAVID online analysis tool. The results indicate that RPA1 is mainly involved in GO pathways associated with DNA replication monitoring, including ‘DNA replication initiation’, ‘regulation of mitotic cell cycle’ and ‘nucleosome assembly’ through its target genes (Table III). KEGG pathway enrichment analysis was also performed to explore pathways associated with the differentially expressed genes. The main enriched pathways were ‘DNA replication’, ‘mismatch repair’, ‘Fanconi anemia pathway’, ‘homologous recombination’, ‘nucleotide excision repair’ and ‘cell cycle’ (Table IV). The results of the bioinformatics analysis provide a theoretical basis for further study of the functional role of RPA1 in gliomas.