
==== Front
Transl Oncol
Transl Oncol
Translational Oncology
1936-5233
Neoplasia Press

S1936-5233(24)00216-X
10.1016/j.tranon.2024.102089
102089
Original Research
WDR77 in Pan-Cancer: Revealing expression patterns, genetic insights, and functional roles across diverse tumor types, with a spotlight on colorectal cancer
Wang Yan a1
Wu Qihui bc1
Liu Jiaxin d
Wang Xuan a
Xie Jialing a
Fu Xiaodan fuxiaodan@csu.edu.cn
ce⁎⁎
Li Yimin lym12999@rjh.com.cn
a⁎
a Department of Pathology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai 200025, PR China
b Department of Gynecology, Xiangya Hospital, Central South University, Changsha 410008, PR China
c National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Changsha 410008, PR China
d Department of Pathology, School of Basic Medical Sciences, Central South University, Changsha 410078, PR China
e Department of Pathology, Xiangya Hospital, Central South University, Changsha 410008, PR China
⁎ Corresponding authors: Department of Pathology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, No. 197, Ruijin Er Road, Huangpu District, Shanghai, PR China. lym12999@rjh.com.cn
⁎⁎ Corresponding authors: Department of Pathology, Xiangya Hospital, Central South University, No.87 Xiangya Road of Changsha, PR China. fuxiaodan@csu.edu.cn
1 These authors have contributed equally to this work.

24 8 2024
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© 2024 The Authors. Published by Elsevier Inc. CCBYLICENSE.
2024

https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Highlights

• Conducted a comprehensive pan-cancer analysis of WDR77, revealing diverse expression patterns and genetic alterations across multiple cancer types.

• Explored the relationship between WDR77 and the tumor immune microenvironment, uncovering potential immunosuppressive effects in certain cancers.

• Identified significant overexpression of WDR77 in colorectal cancer (CRC), linking it to enhanced cell proliferation and potential oncogenic roles.

Objective

Despite its involvement in regulating various cellular functions, the expression and role of WD repeat-containing protein 77 (WDR77) in cancer remain elusive. This study aims to explore the expression and potential roles of WDR77 across multiple cancers, with a particular focus on its relevance in colorectal cancer (CRC).

Methods

We obtained WDR77 RNA-seq data, mutations, CNVs, and DNA methylation data from the TCGA, GTEx, and GEO databases to investigate its expression patterns and prognostic value. Additionally, we examined the correlation between WDR77 expression and somatic mutations, copy number variations, DNA methylation, and mRNA modifications. We utilized GSVA, GSEA algorithms, and CRISPR KO data from the Dependency Map database to explore WDR77′s potential biological functions. The association between WDR77 and the tumor immune microenvironment was investigated using ESTIMATE and IOBR algorithms. Finally, we assessed WDR77 expression in CRC and its impact on cell proliferation through qRT-PCR, Western blotting, immunohistochemistry, CCK8, colony formation, and EdU assays.

Results

WDR77 was upregulated in various tumors and correlated with poor patient prognosis. Its high expression positively correlated with pathways related to cell proliferation and negatively correlated with immune-related pathways. In CRC, WDR77 expression was associated with specific clinical features, genomic alterations, and immune microenvironment characteristics. Experimental validation confirmed upregulated WDR77 expression in CRC tissues and cells, with WDR77 knockdown significantly inhibiting CRC cell proliferation.

Conclusion

WDR77 holds potential as an oncogene and biological marker in various cancers, particularly CRC.

Keywords

WDR77
Pan-cancer
Colorectal cancer
Tumor microenvironment
Proliferation
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pmcIntroduction

In recent years, cancer biology has garnered significant attention, highlighting the need for a thorough understanding of the molecular complexities driving tumor progression [1]. This focus arises from the recognition that cancer is a heterogeneous disease with diverse mechanisms [[2], [3], [4]]. Among the key contributors to this intricate landscape are chromatin regulatory factors, which orchestrate gene expression through mechanisms such as DNA methylation, histone modification, and chromatin remodeling [[5], [6], [7]]. WDR77, a key member of the WD repeat protein family, contributes to vital cellular functions like DNA damage repair, ubiquitin-mediated signaling, cell cycle regulation, epigenetic gene expression modulation, chromatin organization, and immune-related pathways [[8], [9], [10]]. This underscores its significance in cancer biology [11,12].

As a regulatory protein, WDR77 is poised to play a pivotal role in the dynamic interplay of molecular events governing cancer pathogenesis [13]. Studies have indicated that the overexpression of WDR77 is correlated with tumor growth promotion and adverse prognosis [14,15]. The exploration of WDR77′s significance holds the promise of unraveling novel insights into the molecular mechanisms that underlie cancer development. Despite the growing recognition of WDR77′s involvement in cancer [13], there remains a critical gap in our understanding of its expression patterns and functional consequences across diverse cancer types. Existing literature has primarily focused on individual cancers, such as breast, ovarian, and lung cancers [[14], [15], [16]], often lacking a holistic view of WDR77′s pan-cancer relevance. The current state of research highlights the need for comprehensive investigations into the pan-cancer implications of WDR77 to address these gaps in our understanding and provide a more nuanced perspective on its role in cancer biology.

Colorectal cancer (CRC) is a prevalent malignancy affecting the colon or rectum, ranking among the top three diagnosed cancers globally, with nearly 2 million confirmed cases in 2020 [17,18]. This malignancy ranks as the second leading cause of cancer-related mortality, resulting in approximately one million deaths annually and accounting for roughly one-tenth of global cancer cases and fatalities [19,20]. The high mortality rate in CRC is mainly attributed to failures in early diagnosis, cancer recurrence, and the lack of effective treatment options for metastatic cancer patients [[21], [22], [23]]. Hence, identifying new targets for the treatment and diagnosis of colorectal cancer is crucial [24]. Previous studies have shown that other members of the WDR domain protein family, such as WDR43 and WDR54, are upregulated in colorectal cancer. Knockdown of WDR43 and WDR54 significantly inhibits the growth and invasiveness of CRC cells and reduces tumor growth [23,25]. Through pan-cancer research on WDR77, we found elevated expression of WDR77 in various tumors, including colorectal cancer. However, the biological function of WDR77 in colorectal cancer remains largely unclear.

The principal aim of this study is to conduct a thorough investigation into the expression patterns, genetic alterations, and functional significance of WDR77 in the context of cancer biology. This multifaceted approach is essential for unraveling the intricate network of molecular events orchestrated by WDR77 and deciphering its impact on tumorigenesis and clinical outcomes. A key emphasis of our study is the experimental validation of WDR77′s functional relevance in CRC. By integrating in-depth bioinformatics analyses with robust experimental validation, our study aims to offer valuable insights into the intricate interplay between WDR77 and cancer, with a specific focus on its implications in colorectal cancer.

Materials and methods

Data collection and preprocessing

We acquired RNA-seq data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) via the University of California Santa Cruz (UCSC) Xena database (https://xenabrowser.net/datapages/). Comprehensive clinical and pathological data, survival information, mutation profiles, copy number variation (CNV), and DNA methylation data for various cancers were also sourced from the UCSC Xena. Aberrant mRNA expression of WDR77 in colorectal cancer (CRC) was assessed using six independent CRC cohorts (GSE110224, GSE32323, GSE21510, GSE33113, GSE39582, and GSE9348) retrieved from the Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/). The Dependency Map (DepMap) dataset (https://depmap.org/portal/) was employed to acquire CRISPR knockout (KO) data, gene expression profiles, CNV, DNA methylation patterns, and proteomic data specifically related to WDR77 across various cancer cell lines. Imaging data depicting the immunohistochemical and immunofluorescence staining of WDR77 (HPA027271) were sourced from The Human Protein Atlas (https://www.proteinatlas.org/). Gene lists related to methylation regulators (encompassing n1-methyladenosine (m1A), 5-methylcytosine (m5C), n6-methyladenosine (m6A)), genomic heterogeneity, and stemness indices were retrieved from SangerBox3.0 (http://sangerbox.com/).

Human tissue samples

We collected 20 fresh colorectal cancer tissues, along with paired non-cancer tissues, for quantitative real-time polymerase chain reaction (qRT-PCR) analyses. Additionally, 120 paraffin-embedded CRC tissues and 51 non-cancer tissues were assembled into tissue microarrays (TMAs) for immunohistochemistry (IHC) analysis. TMAs and resected fresh colorectal cancer tissue specimens were obtained from Xiangya Hospital. Importantly, none of the patients included in the study had undergone preoperative chemotherapy or radiotherapy. The research protocol received ethical approval from the Ethics Committee of Xiangya Hospital and Ruijin Hospital, Shanghai Jiaotong University School of Medicine. Written informed consent was obtained from all participants, and the study strictly adhered to the ethical guidelines outlined in the Declaration of Helsinki.

Tumor microenvironment and immune checkpoints analysis

We explored the correlation between immune score, immune cell infiltration, and WDR77 expression across various cancer types using six distinct algorithms: ESTIMATE, GSVA, MCP-counter, and IOBR [[26], [27], [28], [29]]. Additionally, Spearman's correlation analysis was implemented to probe associations between WDR77 expression levels and the abundance of immune checkpoint markers.

Functional and enrichment analysis

To unravel the correlation between WDR77 and cancer-related signatures, we utilized the "GSVA" package to compute cancer-related signature scores [27]. Gene set enrichment analysis (GSEA) was used to detect potential disparities in biological processes associated with varying levels of WDR77 expression. Differentially expressed genes (DEGs) between low and high WDR77 subgroups within each cancer type were identified. Patient rankings were determined based on WDR77 expression levels, with the top 30 % classified as the high WDR77 subgroup and the bottom 30 % as the low WDR77 subgroup. The "limma" R package facilitated the analysis of WDR77-related DEGs in each cancer type, with a stringent adjusted p-value threshold of <0.05. For GSEA, the R package “clusterProfiler” was employed [30]. The gene set "h.all.v7.5.1.symbols" from the MSigDB database (https://www.gsea-msigdb.org/gsea/msigdb/) was chosen as the reference gene set for the enrichment analysis.

Cell culture and RNA interference

CRC cells (CACO2, HCT8, HT29, HCT116, LOVO, RKO, SW480, and SW620) and the NCM460 cell line were procured from the American Type Culture Collection. These cells were cultured in RPMI 1640 medium (Biological Industries, Israel) supplemented with 10 % fetal bovine serum (Gibco, USA) and 100 units/mL of penicillin-streptomycin (Invitrogen, USA) at 37 °Cwith 5 % CO2 in a humidified cell incubator. Small interfering RNAs (siRNAs) targeting WDR77 were synthesized by RiboBio (Guangzhou, China). Transfection of cells with siRNA was performed using Lipofectamine 3000 (Invitrogen, USA) following the manufacturer's instructions. Transfected cells were initially cultured in RPMI 1640 medium without FBS and subsequently switched to complete medium after 6–8 h. Experiments were conducted 48 h post-transfection. The siRNA sequences targeting WDR77 were as follows: si-1: TCAGCAAAGTGAAGTCTTT; si-2: GGGAGAGAGGTATTCTAGT.

RNA extraction and quantitative real-time PCR (qRT-PCR)

To assess the expression levels of WDR77 mRNA in CRC tissues and cells, a qRT-PCR experiment was conducted using conventional methods [31]. Total RNA extraction was performed with Trizol reagent (Vazyme, Nanjing, China) following the manufacturer's guidelines. Subsequently, 2 μg of total RNA was reverse transcribed into first-strand cDNA using the GoScript Reverse Transcription System (Promega, Madison, WI, USA). The resulting cDNA was subjected to qRT-PCR analysis using GoTaq qPCR Master Mix (Promega, Madison, WI, USA) on an ABI Prism 7000 thermal cycler (Applied Biosystems, Foster City, CA, USA). The relative expression levels of genes were calculated using the 2−ΔΔCT method, with GAPDH serving as the internal reference gene. The primer sequences used in PCR were as follows: WDR77 (forward primer: TGTTGCTGCCTCTCCTCACAAG; reverse primer: AGCCAGCGAGGTAGGAAGGTAG), GAPDH (forward primer: AACGGATTTGGTCGTATTGG; reverse primer: TTGATTTTGGAGGGATCTCG).

Western blotting

For the Western blotting assay, equal amounts of cell lysates were resolved by SDS/PAGE, transferred onto polyvinylidene fluoride membranes (Millipore, USA), and blocked with 5 % skim milk. After blocking, the membranes were incubated overnight at 4 °C with specific primary antibodies. Subsequently, the membranes were probed with appropriate HRP-conjugated anti-mouse or anti-rabbit secondary antibodies for 2 h at room temperature. Finally, immunoreactive bands were visualized using chemiluminescence kits following three washes with Tris-buffered saline containing 0.1 % Tween (TBST). Primary antibodies utilized in this study included anti-WDR77 (1:2000, ab154190, Abcam, UK) and anti-β-tubulin (1:2000, UM4003, Utibody, China).

Immunohistochemistry

The immunohistochemical analysis adhered to a previously established protocol [31]. Tissue microarrays (TMAs), with a thickness of 4 mm, underwent dewaxing and hydration using xylene and a gradient of ethanol concentrations. Antigen retrieval was achieved in sodium citrate, followed by microwave heating for 18 min. To block endogenous peroxidase activity, sections were treated with 3 % H2O2 for 10 min at room temperature. Non-specific staining was minimized by blocking with 5 % BSA. The anti-WDR77 antibody (1:1000, ab154190, Abcam, UK) working solution was applied dropwise onto the slides, followed by overnight incubation at 4 °C in a humidified chamber. This was succeeded by a 20-minute incubation with anti-mouse/rabbit labeled polymer. Subsequently, the exposed WDR77 protein was labeled using a 0.01 % DAB chromogenic solution, and nuclei were counterstained with hematoxylin. Staining outcomes were examined under a light microscope by two pathologists blinded to clinicopathological data.

Cell proliferation assays

Cell proliferation was assessed using the Cell Counting Kit-8 (CCK8) assay, Colony Formation assay, and EdU assay [31]. For the CCK8 assay, infected cells, 24 h post-transfection, were seeded into 96-well plates and cultured for 24–96 h. At designated time points (24, 48, 72, and 96 h), 10 μl of CCK8 solution (Dojindo, Dojindo Chemical Laboratories, Kumamoto, Japan) was added to each well and incubated for 2 h. Subsequently, the optical density (OD) at 450 nm was measured using a BioRad iMark microplate absorbance reader (BioRad Laboratories, Hercules, CA, USA). For the colony formation assay, 600 cells were seeded in 12-well plates and cultured for 10 days. The resulting colonies were fixed, stained with crystal violet, and quantified using ImageJ software. The EdU assay (RiboBio, Guangzhou, China) was performed according to the manufacturer's instructions. The experiments were repeated at least three times to ensure reliability and reproducibility of the results.

Statistical analysis

All statistical analyses were conducted using R (version 4.2.2) and GraphPad Prism (version 9.0). Data were presented as means ± standard error (SD). For normally distributed variables, Student's t-test and one-way analysis of variance (ANOVA) were employed to compare differences between two and multiple groups, respectively. For non-normally distributed variables, the Wilcoxon test and Kruskal-Wallis test were used for comparisons. Spearman's correlation analysis was utilized for calculating correlation coefficients. Univariate Cox regression analysis explored the prognostic value of WDR77 in pan-cancer. A significance level of p-value < 0.05 was considered statistically significant.

Results

WDR77 expression patterns in pan-cancer tissues and its impact on tumor prognosis

Due to the limited availability of healthy tissue samples for certain cancer types in the TCGA database, we integrated healthy tissue samples from the GTEx database to conduct a comprehensive analysis. The heatmap illustrates the expression distribution of WDR77 in different tissues from both TCGA and GTEx databases (Fig. 1A). Box plots further demonstrate that WDR77 is highly expressed in various tumors, including READ, COAD, DLBC, OV, TGCT, ESCA, UCEC, GBM, THYM, UCS, LUSC, HNSC, STAD, SKCM, CESC, PRAD, BRCA, LUAD, CHOL, LGG, PAAD, and LIHC, while showing low expression in LAML, ACC, KICH, KIRC, THCA, and PCPG (Fig. 1B).Fig. 1 Pan-Cancer Expression Landscape of WDR77.

Fig 1:(A) Heatmap depicting the median expression of WDR77 across different organ systems in TCGA and GTEx databases. Yellow represents normal tissues, while blue represents tumors. (B) Expression levels of WDR77 in various human cancers from TCGA and GTEx databases. (C) Representative immunohistochemical staining images of WDR77 in different tumor tissues from the HPA database. (D) Immunofluorescence images from the HPA database showing the subcellular localization of WDR77 protein in A-431, U-251MG, and U2OS cells.

In non-paired samples from the TCGA database, WDR77 is upregulated in 14 tumor types and downregulated in 5 tumor types (Figure S1A). The same trend is observed in paired samples from the TCGA database, although less pronounced in UCEC, KIRP, CESC, and PCPG due to lower sample sizes (Figure S1B). Further analysis using the Human Protein Atlas (HPA) database reveals predominant expression of WDR77 protein in the cytoplasm and nucleus of tumor tissues (Fig. 1C), with a 100 % expression frequency in breast cancer, carcinoid, colorectal cancer, glioma, head and neck cancer, ovarian cancer, pancreatic cancer, prostate cancer, skin cancer, thyroid cancer, and urothelial cancer (Figure S1C). Immunofluorescence (IF) imaging confirms nuclear and cytoplasmic localization of WDR77 protein in A-431, U-251MG, HUVEC, and U2OS cell lines (Fig. 1D).

Additionally, our study delves into the relationship between WDR77 alterations and clinical survival outcomes, including overall survival (OS), disease-specific survival (DSS), disease-free interval (DFI), and progression-free interval (PFI). The results indicate a significant impact of WDR77 on the clinical survival prognosis across various tumors, particularly in LGG and ACC (Figure S2A). Furthermore, time-dependent area under the curve (AUC) analysis reveals stable performance of WDR77 in predicting the prognosis of LGG and ACC, except for DFI (Figure S2B, S2C).

WDR77 genetic alterations and epigenetic modifications in pan-cancer

We initiated our investigation by examining the genetic alterations of WDR77. As illustrated in Fig. 2A, WDR77 exhibits a relatively low mutation rate in pan-cancer, with mutation rates exceeding 1 % observed only in UCEC, SKCM, and LUAD. Further analysis of WDR77 mutation types and loci reveals that missense mutations, nonsense mutations, and splice site alterations are the predominant genetic changes (Fig. 2A). Notably, the majority of WDR77 gene mutations are situated within the COG2319 domain (Fig. 2B). CNV and DNA methylation dysregulation are common causes of gene expression abnormalities in the development of tumors [31]. Subsequently, we explored the correlation between WDR77 mRNA expression in tumor tissues and CNV as well as DNA methylation levels. In most cancer types, WDR77 expression positively correlates with CNV, particularly in LGG, CHOL, SKCM, and MESO (Fig. 2C). Simultaneously, we noted a negative correlation between the expression of WDR77 and its DNA methylation levels across 10 distinct tumors. (Fig. 2D). As a critical component of epigenetics, mRNA modifications (especially m1A, m5C, and m6A modifications) play a role in post-transcriptional gene regulation [32,33]. Correlation analysis between WDR77 and mRNA modification regulatory factors reveals a positive association between WDR77 gene expression and most m1A, m5C, and m6A methylation modification regulators in cancer tissues, particularly evident in THCA, THYM, and UVM (Fig. 2E).Fig. 2 Genetic Changes and Epigenetic Modifications of WDR77 in Pan-Cancer.

Fig 2:(A) The frequencies and types of WDR77 alterations across various cancer types. (B) Lollipop plot illustrating the distribution of variants for WDR77. (C, D) Correlation analysis of WDR77 expression with gene copy number variations (C) and DNA methylation (D) in pan-cancer. (E) Correlation analysis of WDR77 expression with mRNA-related modifications (m1A, m5C, m6A) gene expression in different TCGA cancer types.

Correlation analysis of WDR77 with genomic heterogeneity and stemness indices in diverse tumor types

To explore the relationship between WDR77 and genomic heterogeneity, we conducted a correlation analysis between WDR77 expression and various genomic metrics, including tumor mutational burden (TMB), mutant-allele tumor heterogeneity (MATH), microsatellite instability (MSI), Neoantigens (NEO), purity, ploidy, Homologous recombination deficiency (HRD), and loss of heterozygosity (LOH) (Fig. 3A). The analysis revealed that WDR77 expression positively correlated with TMB in LGG, LUAD, SKCM, ACC, and BRCA, while showing a negative correlation in THCA and COAD (Fig. 3A). Notably, the association between WDR77 expression and neoantigens was observed only in ACC and COAD (Fig. 3A), highlighting a specific correlation with new antigens, which originate from non-synonymous mutations and contribute to tumor specificity [34]. WDR77 exhibited a positive correlation with MATH in BRCA, COAD, ESCA, LUAD, MESO, STAD, and TGCT, while displaying a negative association in LGG (Fig. 3A). Additionally, WDR77 demonstrated a positive correlation with MSI in BRCA and KIRC, while exhibiting a negative correlation in COAD, HNSC, and THCA (Fig. 3A). Furthermore, we observed correlations between WDR77 and purity, ploidy, HRD, and LOH across various tumors (Fig. 3A).Fig. 3 WDR77 and Tumor Genomic Heterogeneity in Pan-Cancer.

Fig 3:(A) Correlation analysis of WDR77 expression with tumor genomic heterogeneity (TMB, MATH, MSI, NEO, purity, ploidy, HRD, LOH). (B) Correlation analysis of WDR77 expression with stemness index (DNAss, DMPss, RNAss, METHss, ENHss, and EXPss).

Given the pivotal role of stem cell-like characteristics in tumor development [35], we extended our analysis to explore the relationship between WDR77 expression and tumor stemness scores, encompassing both RNA and DNA stemness scores. Intriguingly, WDR77 expression demonstrated a significant correlation with tumor stemness scores in the majority of analyzed tumors (Fig. 3B).

Impact of WDR77 on tumor immune microenvironment and correlation with immune modulators

To further elucidate the influence of WDR77 on tumor development, we first examined its role in the tumor immune microenvironment. Across various tumors, WDR77 exhibited a negative correlation with immune score, stromal score, and ESTIMATE score, while showing a positive correlation with tumor purity (Fig. 4A). The observed associations suggest potential implications of WDR77 in shaping the immune contexture within the tumor microenvironment. Given the growing prominence of immunotherapy in cancer treatment [36], we extended our analysis to explore the correlation between WDR77 and immune checkpoints, immune cytokines, and immune cells. The results revealed a predominantly negative correlation between WDR77 expression and immune checkpoints, immune cytokines, and immune cells across most cancers, with notable patterns in COAD, LUAD, LUSC, and TGCT. Conversely, in KICH, LGG, and UVM, an opposite trend was observed (Fig. 4B). These findings underscore the potential modulatory role of WDR77 in the immune landscape of tumors and its relevance to immunotherapeutic strategies.Fig. 4 WDR77 and Tumor Immune Microenvironment.

Fig 4:(A) Correlation analysis of WDR77 with immune score, stromal score, and ESTIMATE score estimated by the ESTIMATE algorithm. Blue represents positive correlation, yellow represents negative correlation. (B) Correlation analysis of WDR77 with immune checkpoints (top), immune cytokine score (middle), and immune cells (bottom).

Functional pathways associated with WDR77 expression in pan-cancer

To elucidate the biological processes linked to WDR77 expression, we conducted a comprehensive analysis of pathway enrichment using GSVA and GSEA across various cancers. As illustrated in Fig. 5A, WDR77 exhibited positive correlations with several key pathways, including cell cycle, DNA damage response (DDR), DNA replication, homologous recombination, mismatch repair, and nucleotide excision repair in the majority of tumors. Conversely, it showed negative correlations with antigen presentation machinery (APM), CD8 T effector cells, immune checkpoint, and pan-fibroblast TGF-β response signature (Pan-F-TBRS) in certain tumor types.Fig. 5 Functional Analysis of WDR77 in Pan-Cancer using GSVA and GSEA.

Fig 5:(A) GSVA analysis of WDR77 in pan-cancer. (B) GSEA analysis of WDR77 in pan-cancer. The size of the circles represents the false discovery rate (FDR) value of enriched terms in each cancer, and the color represents the normalized enrichment score (NES).

Additionally, GSVA analysis of "hallmark" gene sets revealed WDR77′s involvement in diverse pathways such as DNA repair, E2F targets, G2M checkpoint, mitotic spindle, mTORC1 signaling, and MYC targets. GSEA results further highlighted the enrichment of several immune-related pathways in samples with high WDR77 expression in COAD, TGCT, and UCS. These pathways included allograft rejection, complement activation, IL-6 JAK STAT3 signaling, inflammatory response, interferon alpha response, interferon gamma response, and TNF-α signaling via NF-κB, suggesting a potential link between WDR77 and cancer immunity in these tumors (Fig. 5B).

WDR77 correlation with tumor cell activity in cell line analyses

To further validate the correlation between WDR77 expression, CNV, and DNA methylation in cell lines, we conducted additional analyses using the CCLE database through the DEPMAP platform. Consistent with the TCGA data analysis, WDR77 expression displayed a positive correlation with CNV, with no significant correlation detected with DNA methylation (Fig. 6A). Analysis of proteinomic data from the DEPMAP database unveiled a correlation between WDR77 mRNA and WDR77 protein levels, implying that evaluating WDR77 mRNA offers insights into WDR77 protein levels (Fig. 6B). The expression of WDR77 was detected in cancer cell lines grouped by cancer type (Fig. 6B). Intriguingly, the observed expression of WDR77 in diverse cancer cell lines, coupled with the pronounced impact on cell viability following WDR77 knockout, accentuates its relevance in influencing tumor cell activity (Fig. 6B). This observation highlights the functional relevance of WDR77 in regulating the vitality of cancer cells, providing valuable insights into its potential role as a therapeutic target.Fig. 6 Correlation Analysis of WDR77 in Cancer Cell Lines.

Fig 6:(A) Scatter plots showing the correlation between WDR77 mRNA, copy number, DNA methylation, and proteomics in various cell lines. (B) Expression of WDR77 in different tumor cell lines (top) and cell viability after WDR77 KO (bottom) in the DEPMAP dataset.

Elevated expression and clinical correlations of WDR77 in colorectal cancer

Given the high expression of WDR77 in colorectal cancer (CRC) (Fig. 1B), we validated its expression in multiple GEO datasets, consistently showing elevated WDR77 levels in CRC tissues (Fig. 7A). Due to the lack of other GEO chips with both WDR77 copy number and mRNA data, we only explored the correlation between WDR77 and mRNA modification regulatory factors in GEO datasets. The results also showed that WDR77 was correlated with some mRNA modification regulatory factors (Figure S3A). In TCGA-CRC data, high WDR77 expression correlated with younger patients, MSI-H, CIN subtype, and CMS2 subtype, characterized by WNT and MYC pathway activation and chromosomal instability (Fig. 7B). In GSE39582, high WDR77 expression was similarly associated with pMMR and CMS2 subtypes (Fig. 7C).Fig. 7 High Expression of WDR77 in Colorectal Cancer Tissues.

Fig 7:(A) Box plots showing the expression of WDR77 in colorectal cancer from various GEO databases. (B) Relationship between WDR77 and clinical data in TCGA-CRC. (C) Distribution of WDR77 in different subtypes in the GSE39582. (D) The distribution of the top 20 mutated genes in colorectal cancer among patients with different expression levels of WDR77. (E) Distribution of WDR77 in APC (left) and TP53 (right) mutant and wild-type in TCGA-CRC.

Further analyses of the TCGA-CRC data indicated a negative correlation between WDR77 and TMB/NEO in CRC (Fig. 3A). Investigating the distribution of the top 20 mutated genes in CRC between high and low WDR77 expression groups revealed higher mutation rates in APC and TP53 in the high WDR77 expression group, with lower rates in genes like TTN, SYNE1, and FAT4 (Fig. 7D). Elevated WDR77 expression was noted in both APC and TP53 mutant groups in TCGA-CRC and GSE39582 datasets (Fig. 7E). While WDR77 showed no significant correlation with overall CRC prognosis (Figure S2A), its role in the prognosis of patients with different subtypes of CRC remains unclear. It was associated with prognosis in specific subgroups, such as M0 and stage I-II CRC patients (Figures S4A-S4G).

Relationship between WDR77 and the immune microenvironment validated in another CRC cohort

Subsequently, we further validated the relationship between WDR77 and the immune microenvironment in GSE39582. Based on the ESTIMATE algorithm, the results similarly revealed a negative correlation between WDR77 and ESTIMATE score, immune score, and stromal score, while showing a positive correlation with tumor purity (Fig. 8A). Additionally, employing the GSVA algorithm to assess immune cell infiltration in GSE39582, we observed a predominant negative correlation between WDR77 and most immune cell types (Fig. 8B). Remarkably, both in TCGA-CRC and GSE39582 datasets, patients with low WDR77 expression exhibited higher levels of CYT, GEP, and IFN-γ (Fig. 8C). Furthermore, in GSE39582, WDR77 demonstrated a negative correlation with immune checkpoint-related proteins (Fig. 8D). GSVA and GSEA revealed that high WDR77 expression in GSE39582 was positively associated with growth-related pathways such as cell replication, DNA repair, MYC, and AKT signaling, while low WDR77 expression was positively associated with immune-related pathways and EMT pathways (Figure S5A, S5B).Fig. 8 WDR77 and the Colorectal Cancer Tumor Microenvironment.

Fig 8:(A) Correlation analysis of WDR77 expression with immune score, stromal score, and ESTIMATE score in the GSE39582. (B) Correlation analysis of WDR77 with immune cells using GSVA algorithms in the GSE39582. (C) Distribution of CYT, GEP, and IFN-γ in patients with different WDR77 expression levels in TCGA-CRC and GSE39582. (D) Correlation analysis of WDR77 with immune checkpoints in the GSE39582.

Impact of WDR77 on colorectal cancer cell proliferation validated in CRC

To further validate the bioinformatics findings of this study, we conducted qRT-PCR and Western Blot experiments to confirm WDR77 expression in multiple colorectal cancer cell lines and fresh tissues (Figs. 9A-9D). The results demonstrated elevated WDR77 expression in colorectal cancer compared to normal colon epithelial cells and fresh tissues (Figs. 9A-9D). Immunohistochemical analysis of WDR77 expression in paraffin-embedded tissues revealed cytoplasmic and nuclear localization in tumor cells, with a notable increase in expression in tumor tissues (Fig. 9E). Subsequent transfection of WDR77 siRNAs into HCT116 cells resulted in efficient knockdown, as validated by qRT-PCR and Western Blot experiments (Figs. 9F, 9G). Functional assays assessing CRC cell proliferation, including CCK-8, colony formation, and EdU assays, demonstrated a significant decrease in cell proliferation capacity following WDR77 knockdown (Figs. 9H-9J). These findings underscore the significant role of WDR77 in modulating colorectal cancer cell proliferation.Fig. 9 WDR77 Knockdown Inhibits CRC Cell Proliferation.

Fig 9:(A-D) qRT-PCR (A, C) and Western Blot (B, D) experiments to detect the expression of WDR77 in colorectal cancer cell lines (A, B) and fresh colorectal cancer tissues (C, D). (E) IHC detection of WDR77 expression in normal and tumor tissues of colorectal cancer. (F, G) qRT-PCR (F) and Western Blot (G) experiments to detect the expression of WDR77. (H-J) CCK8 (H), colony formation experiment (I), and EDU experiment (J) to detect cell proliferation capacity.

Discussion

This study comprehensively analyzed the expression patterns, prognostic value, genomic, and epigenomic alterations of WDR77 across multiple cancers, shedding light on its diverse biological functions and relationship with the tumor immune microenvironment. The varied expression patterns of WDR77 across different cancer types underscore its multifaceted involvement in cancer biology [[14], [15], [16]]. We found elevated expression of WDR77 in several tumors, such as READ, COAD, DLBC, suggesting a potential role in tumorigenesis. Conversely, lower expression in tumors like LAML, ACC, KICH highlights the complexity and diversity of the cancer regulatory network.

The diverse expression patterns of WDR77 across various cancer types highlight the need for a detailed exploration of its potential functional roles. Previous research has linked WDR77 to various cellular processes, such as transcriptional regulation and RNA processing [11]. In the context of cancer, these functions may contribute to altered gene expression profiles, affecting critical pathways linked to cell proliferation, survival, and metastasis. For instance, in lung cancer patients, studies have demonstrated the reactivation of the p44/WDR77-dependent cell proliferation process during lung development [37]. Mechanistically, WDR77 may promote the cell cycle process by affecting the p21-Rb-E2F pathway. Inhibiting or directly knocking down WDR77 can induce G1 cell cycle arrest in lung epithelial cells and non-small cell lung cancer (NSCLC), leading to cell differentiation, maturation, and growth restriction of cancer cells [16,37]. Further investigations into the specific molecular mechanisms through which WDR77 operates in different cancers will provide valuable insights into its diverse functional roles and potential as a therapeutic target.

The genetic landscape of WDR77 reveals a low mutation rate in pan-cancer, with only a few mutations observed in UCEC, SKCM, and LUAD. In addition to genetic alterations, the correlation analysis between WDR77 expression and CNV as well as DNA methylation provides additional layers of insight. Positive associations between WDR77 expression and CNV in several cancer types, particularly in LGG, CHOL, SKCM, and MESO, suggest a potential role of gene dosage in regulating WDR77 levels. Conversely, the negative correlation between WDR77 expression and DNA methylation in specific cancers implies a regulatory role of epigenetic modifications in modulating WDR77 expression levels. Understanding the interplay between genetic alterations and epigenetic modifications in shaping WDR77 expression is crucial for unraveling its functional significance in cancer. Potential mechanisms may involve altered transcriptional regulation, aberrant signaling pathways, or disruptions in DNA repair mechanisms.

The clinical significance of WDR77 in cancer emerges as a pivotal aspect of its multifaceted role. Its positive correlation with TMB in certain cancers, like ACC, BRCA, LGG, LUAD, and SKCM, suggests its potential as a prognostic and immunotherapeutic indicator, given TMB's link to neoantigen production and immunotherapy response [38]. Conversely, the negative correlation with immune scores, stromal scores, and ESTIMATE scores across cancers implies a less favorable tumor microenvironment with elevated WDR77 expression, potentially due to increased non-tumor cell infiltration. The association of WDR77 with immune checkpoint markers and cytokines in various cancers further hints at an immunosuppressive role for WDR77. However, in KICH, LGG, and UVM, a positive correlation suggests a more intricate relationship, possibly involving distinct immune evasion mechanisms. Given the growing importance of immunotherapy [39], understanding the impact of WDR77 on the tumor microenvironment and immune response becomes crucial. The dual role of WDR77 in modulating immune infiltration across different cancers underscores the need for personalized approaches in immunotherapeutic interventions. Moreover, the association of WDR77 with stem cell-like characteristics across various cancers adds another layer to its clinical relevance [40]. The correlation with RNA and DNA stemness scores in most tumors underscores its potential role in driving tumorigenic processes, which could impact disease progression and therapeutic response. These findings open avenues for future investigations leveraging WDR77-related information for precise clinical predictions and therapeutic strategies.

Pathway enrichment analysis reveals a positive correlation of WDR77 with key pathways, including the cell cycle, DNA damage response, and DNA replication, implying a potential role in promoting cell proliferation and genomic instability. This aligns with findings in various cancers where elevated WDR77 expression is observed, suggesting its involvement in crucial cellular processes linked to cancer progression [[41], [42], [43]]. Conversely, the negative correlation with antigen presentation machinery, immune checkpoint pathways, and fibroblast TGF-β response implies a potential immunosuppressive role for WDR77 [44]. The enrichment of immune-related pathways in samples with high WDR77 expression in specific cancers like COAD, TGCT, and UCS further underscores its involvement in cancer immunity. This reinforces the notion that WDR77 might contribute to shaping the immune landscape within the tumor microenvironment, potentially influencing the anti-tumor immune response and contributing to the overall immune evasion strategies adopted by cancer cells.

Bioinformatics analysis allowed us to perform an in-depth examination of WDR77 expression patterns, genetic alterations, and functional implications across a diverse range of cancers. Experimental validation is imperative to confirm and contextualize these findings. Our decision to concentrate on CRC in this study is motivated by multiple considerations. Firstly, the high incidence and associated mortality of CRC underscore the critical necessity for a thorough understanding of the molecular mechanisms driving its development and progression [45,46]. Furthermore, CRC displays significant heterogeneity, both genetically and clinically, emphasizing the importance of investigating its diverse molecular landscape of CRC to identify potential biomarkers and therapeutic targets tailored to specific subtypes of the disease [[47], [48], [49]]. The application of qRT-PCR, Western blotting, immunohistochemistry, and functional assays not only validated our bioinformatics results but also provided mechanistic insights into the role of WDR77 in CRC. Notably, while WDR77 shows some correlation with immune cells and immune pathways, its high expression is mainly observed in the CMS2 subtype of CRC, which typically has low immunogenicity and a generally better prognosis. By focusing on CRC, our study aims to contribute valuable insights into the broader understanding of WDR77′s involvement in cancer while providing context-specific information that may have direct clinical implications for colorectal cancer patients.

While our study provides valuable insights into the role of WDR77 in pan-cancer, several limitations should be acknowledged. The reliance on existing datasets, although comprehensive, may introduce potential biases inherent in retrospective analyses. Additionally, the variability in sample sizes across different cancer types may affect the generalizability of our findings. Future studies could benefit from larger, well-balanced cohorts to enhance the robustness of our conclusions. Furthermore, the clinical implications of WDR77 warrant closer scrutiny. Prospective clinical studies are essential to validate WDR77 as a prognostic biomarker and explore its potential as a therapeutic target. Investigating the association between WDR77 expression and response to specific treatments, especially immunotherapies, could open new avenues for personalized cancer therapies. Although WDR77 is upregulated in CRC and correlation analyses show that its abnormal expression is related to CNV and RNA modifications, the specific regulatory mechanisms still require functional experiments for validation. While in vitro experiments confirmed that WDR77 knockdown inhibits CRC cell proliferation, in vivo validation and further investigation into its specific mechanisms are needed.

In conclusion, our study provides a comprehensive analysis of WDR77 across diverse cancer types, shedding light on its expression patterns, genetic alterations, and functional roles, with successful validation in CRC. Our findings contribute valuable insights that can inform future research directions and therapeutic strategies. As we delve deeper into the complexities of WDR77′s involvement in cancer, the increasing potential for its translation into clinically relevant applications emerges, paving the way for targeted interventions and personalized treatment approaches.

Statement of ethics

This study received approval from the Ethics Committee of Xiangya Hospital, Central South University and Ruijin Hospital, Shanghai Jiaotong University School of Medicine, and adhered to the principles outlined in the Declaration of Helsinki.

CRediT authorship contribution statement

Yan Wang: Writing – original draft, Investigation. Qihui Wu: Writing – original draft, Investigation. Jiaxin Liu: Writing – review & editing. Xuan Wang: Writing – review & editing. Jialing Xie: Writing – review & editing. Xiaodan Fu: Conceptualization, Investigation, Validation. Yimin Li: Writing – review & editing, Software, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization, Validation.

Declaration of competing interest

The authors declare no potential conflicts of interest.

Appendix Supplementary materials

Image, application 1

Data availability

The datasets supporting the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments and Funding

We would like to thank GEO, GTEx, TCGA database, as well as all those who have shared their data on the platforms. This work received support from the Ruijin Hospital Youth Fund nurturing program (No. KY20240052 ) and 10.13039/501100001809 National Natural Science Foundation of China (No. 82403198 ).

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.tranon.2024.102089.
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