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. 2025 Apr 21;15:13666. doi: 10.1038/s41598-024-82867-w

Deciphering the prognostic significance of WDR77 in gliomas: a comprehensive analysis

Hanwen Lu 1,2, Bingchang Zhang 1,2, Wenhua Li 1,2, Zhanxiang Wang 1,2,✉
PMCID: PMC12012016  PMID: 40258838

Abstract

Biologically, the WDR77 gene is implicated in the occurrence and development of various clinical malignant tumors. However, its precise role in glioma remains unclear. Therefore, in this study we aimed to perform a comprehensive analysis of the biological functions of WDR77 in glioma. Transcriptome data was obtained from CGGA (mRNAseq-693, mRNAseq-325) and TCGA databases for analysis. A total of 699 glioma samples from the TCGA database were used as the training cohort, while 1018 samples from CGGA were used as the validation cohort. Our analysis revealed that WDR77 was significantly overexpressed in high-grade gliomas and mesenchymal subtype gliomas. Survival analysis indicated that elevated WDR77 gene expression was associated with poor prognostic outcomes for high-grade gliomas, particularly Glioblastoma (GBM). Gene co-expression analysis demonstrated a high correlation between WDR77 and glioma cell cycle, metabolism, and immune processes. Overall, we identified WDR77 as a new biomarker closely associated with the malignant phenotype and poor prognostic outcomes for glioma, playing an important role in regulating the cell cycle and immune processes.

Subject terms: Genetics, Risk factors

Introduction

Glioma, the primary malignant tumor of the central nervous system (CNS), is associated with a very poor prognosis in 80% of cases1–4. Especially in the most malignant GBM, five-year median survival time is about 12–17 months2–5.At present, the standard treatment options for gliomas include surgical resection, chemotherapy and radiotherapy. It is worth noting that immunotherapy is increasingly used in the treatment of malignant tumors. However, the overall response rate and improvement of survival time are not ideal6–9. Therefore, it is necessary to identify new and effective markers in order to provide a theoretical basis for further exploration.

Martin et al. reported that WDR77 plays a key role in prostate and lung cancer, which can drive epithelial cells to reenter cell cycle10,11. WDR77 levels were associated with cell proliferation and TGF, which were attributed to related weakening of signal transduction, and the weakened signal loses its sensitivity, thereby promoting abnormal lung tumor cell proliferation12. Qi et al. found that sirtuin7 can directly deacetylated WDR77, which interfered with WDR77-PRMT5 (protein arginine N-methyltransferase 5) interactions and inhibited the proliferation of human colon cancer HCT116 cells13. Furthermore, the expression levels of PRMT5 and WDR77, along with their methyltransferase activities, are closely linked to the initiation and progression of cancer10,13. Furthly, Han x et al. found that PRMT5 is associated with glioma prognosis14–16. In addition, compared to homozygous mice, the average testicular size for WDR77 (+ /-) heterozygous mice increased by about 29%12. These findings imply that the WDR77-PRMT5 complex in the nucleus and cytoplasm play different functions in fetal testicular development and testicular tumorigenesis17,18. Gu et al. showed that WDR77 is necessary for lung epithelial cell proliferation11. Interference with WDR77 expressions significantly inhibited in vitro lung adenocarcinoma cell proliferation, and suppressed the progression of mouse lung adenocarcinoma xenografts11,12.

In some spliceosomal SM proteins and histones, specific arginine is modified to dimethylargine19. Structurally, it is a kind of gene with 7 WD40 repeats β-Helical motif protein. Usually, WDR77 can directly bind PRMT5 and greatly enhance the histone methyltransferase ability of PRMT5 by promoting its affinity for the protein substrate20. The PRMT5-WDR77 complex is associated with higher levels of methyltransferase activities relative PRMT5 alone20. This may occur as WDR77 both enhances PRMT5’s allosteric effects on cofactor/protein binding and facilitates substrate presentation to PRMT520,21.

Biologically, WDR77 is a potential target for tumor diagnosis, immunity and cell cycle targeted therapy10,22–28. However, studies on the significance of WDR77 in central nervous system (CNS) tumors, particularly gliomas, remain limited. Current research has primarily focused on the structure and function of its complex with PRMT5. There is a lack of comprehensive studies investigating the role of WDR77 in glioma metabolism, cell cycle regulation, and immune responses, especially those based on large sample sizes. This scarcity of data hinders the potential of WDR77 as a clinical diagnostic marker and therapeutic target.

Materials and methods

Patients and samples

Transcriptomic profiles and corresponding clinical data were obtained from two independent glioma cohorts: The Cancer Genome Atlas (TCGA, https://portal.gdc.cancer.gov) and the Chinese Glioma Genome Atlas (CGGA, http://www.cgga.org.cn). Integration of CGGA data served to address potential biases inherent in single-database analyses. Prior to differential expression analysis, raw gene expression counts underwent log2-transformation followed by quantile normalization. Rigorous quality control excluded 15 TCGA samples and 323 CGGA samples lacking either transcriptomic data or complete molecular pathology annotations (including IDH mutation status, 1p/19q codeletion, and MGMT promoter methylation). The acquisition of tumor tissue samples was approved by the Ethics Committee of the First Affiliated Hospital of Xiamen University, with informed consent obtained from all patients. During the collection process, tissue samples were promptly placed on ice for preservation, and the source and collection time of each sample were meticulously recorded.

Western blotting

To detect protein expression in tumor tissues, we performed the following steps. Weighed the frozen tumor tissues and added RIPA lysis buffer gradually. Homogenized the tissues for 2 min and sonicated them using an ultrasonic breaker (4 cycles of 3 s on and 4 s off) to extract total protein. Centrifuged the homogenate at 12,000 × g for 15 min at 4 °C and collected the supernatant. Quantified the protein concentration using a BCA kit (Thermo, USA).

Loaded equal amounts of protein samples onto a 10% SDS-PAGE gel for electrophoresis and transferred them to a PVDF membrane (Millipore, USA). Blocked the membrane with 5% fat-free milk for 1 h at room temperature.Incubated the membrane overnight at 4 °C with primary antibodies for WDR77 (Proteintech, 10115-1-AP) and GAPDH (Proteintech, 60004-1-Ig). The next day, washed the membrane and incubated it with HRP-conjugated secondary antibodies (Sigma, USA) for 1 h at room temperature.Finally, visualized the protein bands using ECL detection reagent (NCM, China) and analyzed the chemiluminescent signal to determine the presence and quantity of the target proteins.

Analysis of differentially expressed genes

To identify differentially expressed genes (DEGs) associated with WDR77 expression in glioma samples from the CGGA and TCGA databases, we retrieved mRNA sequencing data for 699 TCGA samples and 1018 CGGA samples. The expression levels of WDR77 were calculated and normalized using the edgeR package in R statistical software. Subsequently, we used the limma package in R to identify DEGs between samples with high and low WDR77 expression levels. Genes with a log2 fold change greater than 1 or less than − 1 and a p-value less than 0.05, after multiple testing correction, were considered significant DEGs.To obtain commonly co-expressed genes with WDR77 in both datasets, we conducted a Venn diagram analysis of the identified DEGs in the CGGA and TCGA datasets. Only genes showing consistent upregulation or downregulation patterns in both datasets were retained as co-expressed genes.

Enrichment analysis of gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG)

To further understand the biological significance of the co-expressed DEGs, we performed GO annotation and KEGG pathway analysis using the database for Annotation, Visualization, and Integrated Discovery (DAVID) were used to annotate biological processes, cellular components, and molecular functions, while KEGG pathways were utilized for pathway analysis. An FDR of less than 0.05 was considered statistically significant. Finally, we visualized the enriched functional categories and assessed the degree of overlap between the GO terms and KEGG pathways using the Enrichment Map plugin in Cytoscape.

Univariate and multivariate regression analysis

To investigate the role of the WDR77 gene in glioma development, we conducted univariate and multivariate regression analyses to explore the relationship between WDR77 gene expression levels and prognosis. The univariate regression analysis involved two main steps: first, we normalized and analyzed the RNA-seq data using the edgeR package in R, converting WDR77 gene expression levels to log2-transformed. Subsequently, we used the survival package in R to construct a univariate Cox regression model, calculating hazard ratios and p-values. For the multivariate regression analysis, we began by identifying clinically relevant variables that showed significant correlation with WDR77 gene expression levels through correlation analysis. These variables were then used in multivariable regression modeling. Ultimately, we utilized the survival package in R to construct a multivariate Cox regression model, where we calculated adjusted hazard ratios and p-values.

WGCNA co-expression analysis

In order to gain deeper insights into the role of the WDR77 in tumorigenesis, we employed the Weighted Gene Co-expression Network Analysis (WGCNA) algorithm to analyze RNA-seq data from TCGA and CGGA databases. Initially, we preprocessed the expression matrix by eliminating outlier samples, normalizing and selecting highly expressed genes. Subsequently, we utilized the WGCNA algorithm to construct co-expression networks and modularized highly correlated genes into distinct modules. We then calculated the correlation between each module and clinical information and identified modules that were significantly associated with WDR77 expression levels. Finally, we conducted GO and KEGG enrichment analysis to elucidate the functions and pathways of the selected modules, thereby providing further insights into the underlying mechanisms governing the interplay between these modules and the WDR77 gene in tumorigenesis.

Flow cytometry analysis of cell cycle

To analyze the role of WDR77 in the regulation of the cell cycle in tumor cells, we utilized flow cytometry to detect the cell cycle of U87-MG and U251. After specific treatments, the cells were fixed with 70% ethanol and subsequently stained with a buffer containing 50 μg/mL propidium iodide (PI) and 100 μg/mL RNase A. Flow cytometry data collection and analysis were performed using Novoexpress software. The data obtained from the analysis were further processed for statistical analysis and visualization using Prism 8.0 software, allowing us to evaluate the proportion of cells in different cell cycle stages. The flow cytometer was used to measure the fluorescence intensity of the cells, and the percentage distribution of the cell cycle phases was quantified to ensure the accuracy and reproducibility of the results.

Analysis of the relationship between WDR77 gene expression and immune cell infiltration

To further understand the role of WDR77 in gliomas, we also explored its relationship with immune infiltration. We obtained RNA-seq expression data for the WDR77 gene from the TIMER2.0 database, focusing on lower-grade glioma (LGG) and glioblastoma multiforme (GBM). The analysis was conducted using the “Gene” module in TIMER2.0, which allows for the exploration of gene expression correlations with immune cell infiltration levels.We specifically examined the correlation between WDR77 expression and the infiltration of six distinct immune cell types: B cells, Treg cells, Macrophage cells, and dendritic cells. To assess these relationships, we calculated Spearman’s correlation coefficients and corresponding p-values for each immune cell type, which provided a measure of the strength and significance of the association between WDR77 expression and immune cell infiltration.

Statistical analysis

All statistical analyses and data visualizations were performed using R software (version 3.6.8) and various online database tools on Windows 10. Differences in overall survival were calculated using the Kaplan–Meier method. Cox regression analysis was conducted using the survival package in R, and graphical representations were generated with additional R packages. Genes significantly associated with WDR77 were identified through Spearman correlation analysis. Cell cycle genes were downloaded from the GSEA database (http://www.gsea-msigdb.org/gsea/index.jsp). Pearson’s correlation was used to determine significant differences. A p-value of  <0.05 was considered statistically significant.

Results

WDR77 is highly expressed in high-grade gliomas (HGG)

To delineate the oncogenic relevance of WDR77 in GBM, we performed integrated analysis across multiple public glioma datasets. Our results demonstrate a significant positive correlation between glioma grade and WDR77 expression levels, with marked differences observed among grades II, III, and IV. Notably, high-grade gliomas exhibited significantly higher WDR77 expression than LGG, with GBM samples showing the highest levels. However, no linear trend in WDR77 expression was detected in grade I samples across the Rembrandt and Gravendeel datasets  (Fig. 1A).

Fig. 1.

Fig. 1

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Expression analysis of WDR77 in glioma datasets and tissue Samples. (A) The expression of WDR77 in different glioma datasets. (B) Expression detection of WDR77 in glioma samples. (C) Grayscale statistical results of WDR77 expression in different grades of glioma tissue relative to GAPDH. (D) WDR77 expression in GBM cell lines U251 by IHC. p < 0.01 is considered statistically significant.

To validate these findings, we examined WDR77 protein expression in clinical glioma samples. The analysis revealed that WDR77 expression in GBM was significantly higher than in normal brain tissue and LGG groups (Fig. 1B,C). Furthermore, we queried the Human Protein Atlas (HPA) database (https://www.proteinatlas.org/) for WDR77 expression in the GBM cell line U251. The results indicated that WDR77 is predominantly expressed in the cytoplasm, with lower levels observed in the nucleus (Fig. 1D).

WDR77 levels are elevated in mesenchymal glioma subtypes

In order to scrutinize the expression patterns of WDR77 in different molecular subtypes, we assessed its expression levels across 1p19q, IDH status, oligodendroglioma, oligoastrocytoma, and GBM subtypes. In both TCGA and CGGA datasets, we observed elevated expression of WDR77 in the 1p19q non-codel subtype, relative to the other subtypes (Fig. 2A,D). Comparison between IDH mutants and wild types indicated greater abundance of WDR77 expression in wild types, with no significant difference between genders (Fig. 2B,E). Particularly noteworthy was the significantly lower expression of WDR77 in astrocytes and oligodendrocytes than in GBM, consistent with the results presented in Fig. 1 (Fig. 2G).

Figure2.

Figure2

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Correlation between WDR77 expression and glioma molecular subtypes. (A–D) WDR77 was significantly enriched in the 1p19q non-codel subtype from the TCGA and CGGA cohorts. (B–E) WDR77 was significantly enriched in the IDH wild type subtype from the TCGA and CGGA cohorts . (C–F) The expression of WDR77 was not statistically different between male and female glioma patients. (G) Among the oligoderdroglioma, oligoastrocytoma and GBM subtypes, WDR77 is the most expressed in GBM. (H–I) ROC curve analysis showing the predictive value of WDR77 in the TCGA and CGGA cohorts. *p < 0.05, **p < 0.01, ***p < 0.001.

Additionally, using the association between WDR77 expression and clinical features in both datasets, we built a diagnostic survival model (Fig. 2H,I). The diagnostic model, developed using data from the TCGA and CGGA databases, demonstrated excellent predictive performance, suggesting WDR77’s potential as a prognostic biomarker for glioma.

Compared to IDH mutant, wild-type gliomas exhibit a higher abundance of WDR77 expression, with no significant difference observed between male and female patients (Fig. 2C,F). Furthermore, the expression of WDR77 in astrocytes and oligodendrocytes was significantly lower than that in GBM, consistent with the findings presented in Fig. 2G. Based on the relationship between WDR77 levels and clinical features observed in both datasets, we constructed a diagnostic model for survival prediction (Fig. 2H,I). This model demonstrated strong predictive performance when validated against both TCGA and CGGA datasets, suggesting WDR77’s potential utility as a prognostic biomarker for glioma.

Elevated WDR77 associated with poor prognostic outcomes in glioma patients

Our previous findings identified WDR77 as a potential glioma biomarker, demonstrating its upregulation correlating with increasing tumor grade across diverse glioma samples. To further evaluate WDR77’s prognostic value, we performed Kaplan-Meier survival analysis on the glioma patient cohort, revealing that elevated WDR77 expression levels significantly correlate with poorer overall survival (Fig. 3A,B). Our observations were supported by similar analyses performed on two other datasets, which yielded consistent conclusions with those obtained from the TCGA and CGGA databases (Fig. 3C,D). These results collectively suggest that increased WDR77 expression in gliomas is indicative of poor prognostic outcomes, rendering it a potential prognostic marker for gliomas.

Fig. 3.

Fig. 3

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Survival curve of WDR77 in different databases. (A) Survival curve of WDR77 in Rembrandt database. (B) Survival curve of WDR77 in Gravendeel databset. (C) Survival curve of WDR77 in the TCGA database. (D) Survival curve of WDR77 in CGGA database. (E) Univariate Cox analyses evaluating the independent prognostic value of WDR77 in glioma patients from the CGGA database. (F) Multivariate Cox analyses evaluating the independent prognostic value of WDR77 in glioma patients from the CGGA database.

To investigate whether WDR77 has an independent prognostic value in gliomas, univariate and multivariate Cox regression analyses were conducted using preprocessed data from the TCGA and CGGA datasets. After analyzing six clinicopathological factors (Age, Grade, Gender, IDH status, 1p/19q status, Chemotherapy and Radiotherapy status), it was found that WDR77 expression remained an independent prognostic factor for gliomas, with tumor grade, IDH mutation and 1p19q deletion as relevant independent factors (Fig. 3E,F).

WDR77 Expression Correlates with Cell Cycle Reprogramming in Glioma

To verify the significance of WDR77 in glioma cells, based on the Spearman correlation algorithm, we sorted the co-expressed genes of WDR77, and excluded the genes that did not meet the threshold (| R |> 0.6 and p < 0.05). A total of 998 related genes (750 positively related genes and 248 negatively related genes) and 907 related genes (902 positively related genes and 5 negatively related genes) were respectively screened from the TCGA and CGGA data sets. Then, GO functions of these genes were evaluated in R. Genes that were most closely associated with WDR77 were established to be enriched in glioma cell cycle regulation, mRNA metabolism, intracellular amino acid metabolism, G2/M phase signal transformation, NFκB signaling pathway and GTP binding activities. In terms of molecular functions, WDR77 related proteins were mainly enriched in protein binding, DNA dependent helicase activities and single stranded DNA dependent ATPase activities. In terms of cellular components, WDR77 was enriched in composition and function of the protease complex, peptidase complex and mitochondrial ribosomal subunits. These conclusions are consistent with results of enrichment in the TCGA and CGGA (Fig. 4A,B).

Fig. 4.

Fig. 4

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GO analysis of cell cycle-related biological processes and molecular functions in glioma. (A) GO analysis for the TCGA cohort. (B) GO analysis for the CGGA cohort. (C,D) GO analysis and Overlapping genes by TCGA and CGGA. The BP cluster boxes show the cell cycle-related biological processes and cellular components. The MF cluster boxes show the molecule functions. The CC cluster boxes show the Cell Component.

In addition, GO function analyses were performed on 136 related genes intersected by the two data sets, which revealed consistent results (Fig. 4C,D). These findings show that WDR77 is closely associated with cell cycle transformation and metabolism of glioma. To elucidate on the relationship between WDR77 levels in glioma and the cell cycle, we downloaded the related gene clusters that were specifically expressed in the cell cycle from the GSEA website. Then, through WGCNA coexpression analysis, cell cycle related genes that were significantly associated with WDR77 levels were screened from the TCGA and CGGA databases (| R |> 0.6, p ≤ 0.05). Finally, the top 125 genes in the TCGA databases were screened and displayed by a heat map. It was established that WDR77 was positively correlated with expressions of most cell cycle related genes (Fig. 5A). Overall, our results show that WDR77 levels are significantly correlated with expressions of cell cycle-associated genes in glioma.

Fig. 5.

Fig. 5

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Effect of WDR77 knockdown in glioma cells. (A) The relationship between WDR77 and cell cycle function-related genes in TCGA glioma samples. (B) Flow cytometry analysis of cell cycle distribution in U87-MG and U251 glioma cells. Cells were treated with different concentrations (5 µmol, 10 µmol, 15 µmol) of siRNA targeting WDR77. WT represents wild-type, untreated cells. The x-axis shows the DNA content, and the y-axis shows the cell count. The peaks correspond to the G1, S, and G2 phases of the cell cycle. (C) Bar graphs showing the percentage distribution of cells in the G1, S, and G2 phases for U87-MG and U251 cells treated with different concentrations of siRNA-WDR77 (5 µmol, 10 µmol, 20 µmol).

To investigate the functional role of WDR77 in glioma cells, we conducted WDR77 knockdown experiments and analyzed its impact on the cell cycle. Using different concentrations of siRNA (5 µmol, 10 µmol, 15 µmol) to knock down WDR77 expression in U87-MG and U251 cells, we analyzed cell cycle distribution by flow cytometry (Fig. 5B). The results showed a significant increase in the accumulation of cells in the G1 phase and a corresponding decrease in the S phase upon WDR77 knockdown, indicating G1/S phase arrest. Furthermore, the bar graphs of cell cycle distribution confirmed these results (Fig. 5C), showing that the proportion of cells in the G1 phase increased with higher concentrations of siRNA. These findings suggest that WDR77 knockdown induces G1/S phase cell cycle arrest in glioma cells, thereby inhibiting cell proliferation. Although knocking down WDR77 affects the progression of glioma cells at the G1/S phase, the results of the GO analysis of the co-expressed genes point to the G2/M phase. This indicates that the relationship between WDR77 and these co-expressed genes is relatively complex, and WDR77 may affect the expression or function of these co-expressed genes indirectly. Of course, there is another explanation, that is, WDR77 may be involved in a complex signaling pathway network, and its regulatory effects on different cell cycle stages are achieved through multiple levels.

Relationship between WDR77 levels and tumor immune infiltrating cells

To delineate the functional role of WDR77 in glioma, we systematically investigated its association with immune cell infiltration. The correlation between WDR77 expression levels and immune cell-specific marker genes was quantitatively assessed using the TIMER 2.0 platform29. Furthly, We evaluated the association between expressions of the common immune infiltrating cell specific markers (Treg cells, Macrophage cells, Dendritic cells, B cells and the WDR77 gene. We established that WDR77 levels were positively correlated with B cells (GBM R = 0.409, p < 0.01; LGG R = − 0.193, p < 0.01), Tregs (GBM R = 0.409, p < 0.01; LGG R = − 0.193, p < 0.01), Macrophage cells (GBM R = 0.409, p < 0.01; LGG R = 0.409, p < 0.01), DC cells (GBM R = 0.409, p < 0.01; LGG R = − 0.193, p < 0.01). The results suggest that glioma tissues with elevated WDR77 levels are highly infiltrated with invasive immune cells, especially immune cells with immunosuppressive characteristics (Fig. 6A). Through TISIDB database analysis, we found that WDR77 gene expression was significantly associated with increased immune cell infiltration levels in LGG tissues. This suggests that WDR77 regulates the response of LGG to immune therapy and provides theoretical basis for further investigation into whether targeting WDR77 could improve the immune therapeutic effect in LGGs (Fig. 6B,C).

Fig. 6.

Fig. 6

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Correlation between WDR77 Levels and Immune Cell Infiltration in Glioma. (A) The correlation between WDR77 levels and immune cell-specific marker genes using the online analysis tool TIMER 2.0. (B,C) We evaluated the association between the expression of common immune infiltrating cell-specific markers (Treg cells, Macrophage cells, Dendritic cells, and B cells) and the WDR77 gene. Our analysis established that WDR77 levels were positively correlated with B cells (GBM: R = 0.409, p < 0.01; LGG: R = − 0.193, p < 0.01), Treg cells (GBM: R = 0.409, p < 0.01; LGG: R = − 0.193, p < 0.01), Macrophage cells (GBM: R = 0.409, p < 0.01; LGG: R = 0.409, p < 0.01), Dendritic cells (GBM: R = 0.409, p < 0.01; LGG: R = − 0.193, p < 0.01). These results suggest that glioma tissues with elevated WDR77 levels are highly infiltrated with invasive immune cells, especially those with immunosuppressive characteristics.

Interaction networks of the WDR77 in the metabolic environment of Pan-cancer

The results of the gene GO analysis suggest that WDR77 may be associated with tumor metabolism. To further understand the relationship, we analyzed the network of interactions between WDR77 in different tumor metabolic environments. Interestingly, we found WDR77 protein in different tumors, such as COAD, KIRC, LUAD, THCA, LUSC, and UCEC. Participates in a different metabolic network relative to normal tissues. We believe that there are two main reasons for this result. First, differences in the interaction network of WDR77 may stem from variations in metabolic profiles, dysregulated cell cycle phases, immune infiltration levels, and cell proliferation signals across different tissues. Second, the tissue-specific and spatiotemporally specific expressions of genes likely contribute to this phenomenon.

In breast cancer, WDR77’s primary co-expressed proteins were LSM2, MAGOH, PSMA5, and PSMA2. In normal breast tissues, the proteins showing strongest correlation with WDR77 were PGK2, MAGOH, FH, PSMA5, and PSMB2. Similarly, WDR77 exhibited distinct metabolic networks in COAD, KIRC, LUAD, THCA, LUSC, UCEC and their corresponding normal tissues. Unfortunately, due to the limitations of the current study and the lack of some more direct evidence, we are unable to provide a valid, reliable network of WDR77 associations in gliomas. (Fig. 7A–V). Nonetheless, we are confident that the expression of the WDR77 gene is intricately linked to the metabolic microenvironment of glioma, a relationship that we intend to further investigate and clarify in our forthcoming studies.

Fig. 7.

Fig. 7

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(A–V) The WDR77 interaction network of co-expressed genes in different tumours. The coexpression network was drawn using R package, Only the top 20 genes with the highest correlations are shown. Red circle shows input gene, orange circle represents cell metabolism gene, and the sky circle represents other genes.

Discussion

This study represents the most comprehensive investigation to date of WDR77’s clinical significance in gliomas. Our findings demonstrate that WDR77 expression increases significantly with tumor grade and shows particularly high expression in established molecular subtypes of malignant gliomas, including IDH wild-type, 1p19q non-codeleted, and GBM. These results strongly suggest that elevated WDR77 levels correlate with malignant progression in gliomas. Notably, patients with high WDR77 expression face increased risks of tumor recurrence, disease progression, and treatment resistance.

Survival analysis demonstrated significantly higher risks of tumor recurrence, disease progression, and treatment resistance in the WDR77 high-expression group compared to the low-expression group. Importantly, our analysis of the Rembrandt and Gravendeel datasets indicated that expressions in grade I samples of LGG did not follow a linear trend with grades II, III, and IV. This may be due to the difficulty in recruiting stage I glioma patients, resulting in insufficient sample numbers that can impact results. Furthermore, the relatively low degree of tumor heterogeneity observed in grade I gliomas may lead to different expression patterns compared to the higher malignancy grades II, III, and IV.

WDR77 has been established as an independent prognostic factor in glioma patients and shows potential as a molecular diagnostic marker. Currently, no patents or clinical reports exist regarding WDR77’s application as a specific diagnostic marker for glioma. Future therapeutic strategies targeting WDR77 may prove valuable in multimodal glioma treatment approaches.

Functionally, WDR77 is involved in several key processes, including glioma cell cycle, inflammatory responses, neovascularization, nucleic acid metabolism, and amino acid metabolism. The histone methyltransferase complex consisting of WDR77 and PRMT5 has been reported to catalyze H4R3 dimethylation (H4R3me2) and mediate cancer cell proliferation and migration, although the underlying regulatory mechanisms remain unclear. Additionally, it has been demonstrated that WDR77 is overexpressed in prostate cells and functions independently as an androgen receptor cofactor18.

For example, silencing FAM64A in glioma cells disrupts cell proliferation and migration capabilities and increases cell accumulation in the G2/M phase30. Additionally, it has been found that GINS1 regulates the cell cycle through USP15-mediated deubiquitination of TOP2A, promoting glioma cell proliferation and migration31.

In Pan-cancer, gene expression patterns in normal and tumor tissues differ significantly. WDR77 is involved in multiple signaling networks within different tumor environments, particularly in metabolic environments. This impacts the occurrence and development of tumors. There are likely two reasons for this phenomenon. Firstly, variations in metabolism, cell cycle, and immune infiltration occur in differing degrees and ranges across different tumor tissues, which leads to diverse interaction networks of WDR77. Secondly, tissue-specific expressions and spatiotemporal specific expressions of genes contribute to this phenomenon. For example, in breast cancer, the co-expressed proteins of WDR77 were LSM2, MAGOH, PSMA5, and PSMA2, while in normal breast tissues, the proteins with the strongest correlations with WDR77 were PGK2, MAGOH, FH protein, PSMA2, and PSMA5. This indicates that compared to their normal tissue counterparts, WDR77 interacts with different molecules in various tumor tissues within the composition of metabolic networks.

Modifications, leading to distinct upstream and downstream protein interactions in normal versus tumor tissues. In certain tumors, mutations predominantly occur in enzymatic domains, causing functional alterations or inactivation of these enzymes and consequently impairing their normal biological functions. From a structural biology perspective, WDR77 overexpression in tumors may disrupt the normal stoichiometry of methyltransferase complex subunits, thereby affecting their proper assembly and function.

Previous studies have identified WDR77 as a subunit of Methylation modifier enzyme complex, which can be used as a steroid receptor co-activator20. It can enhance androgen and estrogen receptor-mediated transcriptional activities in a ligand dependent manner17. Contrary to previous findings of WDR77 in prostate, testicular and breast cancers, WDR77 showed strong cytoplasmic localizations on the normal ovarian surface and oviduct epithelium, while nuclear WDR77 was observed in invasive ovarian cancer32. In the presence of estrogen or androgen, overexpressions of nuclear localized WDR77 stimulates ovarian cancer cell proliferation as well as invasion32.

Gao et al. discovered that, in prostate cancer, WDR77 is initially expressed within the nucleus of benign epithelial cells but subsequently translocates to the cytoplasm of cancerous cells during the transformation from normal to malignant cell phenotype17,18. Furthermore, nuclear expression of WDR77 has been found to suppress the proliferation of prostate cancer cells18. In contrast to prostate cancer, strong cytoplasmic expression of WDR77 was observed in normal terminal ductal lobular units, while nuclear WDR77 was detected in ductal carcinoma in situ and invasive carcinoma18. Importantly, in the presence of estrogen, overexpression of nuclear WDR77 stimulated the proliferation and invasion of MCF7 breast cancer cells in an ER-dependent manner26. Bryant et al. have reported that targeted knockout of prostate-specific WDR77 can abrogate prostate cancer development induced by the deletion of tumor suppressor PTEN. The underlying mechanism involves WDR77 counteracting the inhibition of E2F3 activation and augmenting TGF β signal transduction, leading to suppressed cell proliferation in response to PTEN loss33. These findings underscore the pivotal role of WDR77 in prostate carcinogenesis.

While this study provides significant insights into WDR77’s biological functions in gliomas, some limitations should be acknowledged. First, as our analysis relied on public database samples, we had no control over their quality or collection methods. Second, although we validated our findings using extensive TCGA and CGGA datasets, additional clinical samples are needed to further corroborate these results. Additionally, our research is based on bioinformatics analysis, which requires further experimental validation to confirm our conclusions.Despite some limitations, this research has important implications for clinical practice. First, we found that WDR77 is significantly overexpressed in HGG and mesenchymal subtype gliomas, providing a basis for WDR77 as a potential therapeutic target for gliomas. Second, our survival analysis indicates that high WDR77 expression is associated with poor prognosis in HGG, especially in GBM. This suggests that WDR77 may serve as an important prognostic marker, with potential clinical applications in guiding the clinical management and treatment planning for glioma patients. Lastly, our gene co-expression analysis shows a high correlation between WDR77 and glioma cell cycle, metabolism, and immune processes, suggesting that WDR77 may be involved in the occurrence and development of gliomas by regulating cell cycle and immune processes. This provides new ideas and research directions for further exploring the pathogenesis of gliomas.

Ethics approval

All authors contributed to the article and approved the submitted version and the article was Approved by patients.

Informed consent

Informed consent was obtained from the patients or the patients families.

Supplementary Information

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Abbreviations

COAD

Colon adenocarcinoma

KIRC

Kidney renal clear cell carcinoma

LUAD

Lung adenocarcinoma

THCA

Thyroid carcinoma

LUSC

Lung squamous cell carcinoma

UCEC

Uterine corpus endometrial carcinoma

TCGA

The Cancer Genome Atlas Program

CGGA

Chinese Glioma Patient Database

DEGs

Differentially expressed genes

Author contributions

HL: conceptualization, formal analysis, and writing–original draft. ZW: funding acquisition. BZ : review and editing. WL：data processing. All authors contributed to the article and approved the submitted version.

Funding

This work was supported by the National Natural Science Foundation of China (Grant Number: 82072777), Xiamen Municipal Bureau of Science and Technology (Grant Number: 3502Z20209005). The Rare Earth Biomedical Project Fund of the Academician Workstation at the First Affiliated Hospital of Xiamen University (grant number:XDFY-AW-2406-001). Fujian Province Natural Science Foundation Project (grant number: 2024J08315).

Data availability

The original contributions presented in the study are included in the article/Supplementary Materials, further inquiries can be directed to the corresponding author/s.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-024-82867-w.

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Associated Data

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Supplementary Materials

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Data Availability Statement

The original contributions presented in the study are included in the article/Supplementary Materials, further inquiries can be directed to the corresponding author/s.

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