Abstract
Bladder cancer is a malignant tumor ranks among the most common urogenital malignancies. Treatment efficacy specifically in MIBC remains suboptimal due to profound tumor heterogeneity. Gene and protein biomarkers provide the opportunity for precise diagnosis and treatment. In this study, by using bioinformatic portals, we identified DCUN1D5 as an upregulated gene that may influence pan-cancer prognosis. Its expression showed significant differences across histological grades and tumor subtypes in BLCA. We found that co-expression genes of DCUN1D5 were enriched in translation initiation factor activity and methyltransferase activity, suggesting potential regulatory mechanisms of DCUN1D5. Furthermore, we validated the prognostic role of DCUN1D5 in BLCA through immunohistochemical analysis of 56 tissue microarray samples. The relationship between DCUN1D5 expression and clinicopathological parameters of BLCA was analyzed by Chi-square test, and result was consistent with bioinformatic analysis. In conclusion, we identified DCUN1D5 as a novel potential Biomarker for predicting the prognosis of BLCA.
Keywords: Bladder cancer, DCUN1D5, Immunohistochemistry, Prognosis, Co-expression network
Introduction
Bladder cancer (BLCA), a malignant tumor originating from the mucosal epithelium of the bladder, ranks among the most common urogenital malignancies. The bladder mucosa comprises urothelium, with urothelial carcinoma (UC) representing the predominant histological subtype (>90% of cases) [1]. Globally, it is the ninth most frequently diagnosed cancer [2]. According to 2022 data from China’s National Cancer Center, there were 92,900 newly diagnosed cases and 41,400 bladder cancer-related deaths nationwide that year [3]. Clinically, bladder cancers are stratified by muscle invasion status into muscle-invasive bladder cancer (MIBC) and non-muscle-invasive bladder cancer (NMIBC), with occurrence rates of 25% and 75%, respectively [4]. However, approximately 60% of NMIBC patients will suffer a recurrence within 1 year after transurethral resection of the bladder tumor material, and up to 17% will ultimately develop into MIBC. Upon progression to muscle-invasive bladder cancer (MIBC), patients exhibit significantly reduced 5-year survival rates, consistently reported below 50% [5]. Significant advances in BLCA therapeutics-including intravesical therapies, cisplatin-based combination regimens, and immune checkpoint inhibitors-have substantially improved patient prognoses [6]. However, treatment efficacy specifically in MIBC remains suboptimal due to profound tumor heterogeneity [7].
Cullin-RING ligase complex (CRL) are ubiquitin E3 enzymes activated by attachment of the ubiquitin-like protein NEDD8 to the cullin subunit [8]. In lower organisms, single DCN1 (defective in cullin neddylation 1) homologs exist that promote the neddylation of all cullins, whereas multiple DCN1 molecules are encoded by the genomes of higher organisms [9]. Human cells harbor 5 Dcn1-like proteins termed DCNL1-DCNL5 (also named DCUN1D1-5, defective in cullin neddylation 1 domain containing 1–5) [10]. DCNLs and cullins could form stable complexes which might represent ‘reserve’ CRLs that can be rapidly activated when needed [11]. DCUN1D5 (also named DCNL5 or SCCRO5), has been reported to mediate cellular responses to DNA damage stimuli, positive regulation of protein neddylation, and regulation of cell growth [12]. DCUN1D5 encoded a protein of 237 amino acids, which contained conserved C-terminal potentiating of neddylation (PONY) domain and the nuclear localization sequence (NLS) domain [13, 14]. Research on DCUN1D5 has expanded beyond laryngeal squamous cell carcinoma (LSCC) to breast cancer [15, 16], osteosarcoma [17], and lung adenocarcinoma [18]. Meanwhile, both alternative splicing and phosphorylation of DCUN1D5 are critical post-translational regulatory mechanisms in tumor progression [16, 19].
Here, using bioinformatic portals, we identified DCUN1D5 as an upregulated gene that may influence pan-cancer prognosis. Its expression showed significant differences across histological grades and tumor subtypes in BLCA. Furthermore, we validated the protein expression of DCUN1D5 in BLCA through immunohistochemical analysis of 56 tissue microarray samples.
Materials and methods
Analysis of DCUN1D5 expression in pan-cancer
The expression levels of the DCUN1D5 gene across various cancers were obtained from Tumor Immune Estimation Resource (TIMER, https://cistrome.shinyapps.io/timer/) [20]. The expression of DCUN1D5 at the protein levels in pan-cancer tissues was assessed using Immunohistochemistry (IHC) data from the Human Protein Atlas (https://www.proteinatlas.org/) [21]. Kaplan-Meier Plotter (https://kmplot.com/ analysis) were queried to elucidate the prognostic role of particular genes [22]. The relationships between DCUN1D5 expression and clinicopathological characteristics were retrieved at Xiantao academic database (https://www.xiantao.love; accessed on March 2025).
Co-expression network analysis of DCUN1D5
Co-expression genes of DCUN1D5 and their expression heatmap were identified at LinkedOmics (https://www.linkedomics.org/) [23]. Signaling pathway analysis was performed at Metascape (https://metascape.org/) [24]. Gene ontology biological processes and KEGG pathway were included (P-value < 0.05). Protein-protein interaction (PPI) analysis was operated via STRING (https://cn.string-db.org/) (version 12.0) [25] and cytoscape (https://cytoscape.org/) (version 3.9.1) [26].
Tissue microarray and inclusion criteria
The paraffin-embedded cancer tissue microarrays used in this study were purchased from SHANGHAI OUTDO BIOTECH CO., LTD. (NO. HBlaU079Su01). This microarray contains 16 cases of bladder cancer with paired adjacent non-cancerous tissues, and 47 stand-alone bladder cancer tissue samples, comprising 79 tissue specimens from a total of 63 patients. The inclusion criteria for cases were: (1) intact tumor tissue present on the microarray; (2) no core detachment in the tissue microarray; (3) complete sample ID information for bladder cancer tissues in the microarray platform. Through these criteria, we ultimately included 56 bladder cancer cases and 9 controls, comprising 65 tissue specimens available for subsequent analysis. All studies involving human tissues were conducted in strict accordance with the Declaration of Helsinki and were approved by Ethics Committee of SHANGHAI OUTDO BIOTECH CO. (SHYJS-CP-1910002).
Immunohistochemistry
Immunohistochemistry (IHC) staining was carried out as kit instructions. IHC kit (Cat# IHC003) and anti-rabbit secondary antibodies IgG H&L (Cat# 926–68071, 1:200 dilution) were purchased from BEIJING BIOSYNTHESIS BIOTECHNOLOGY CO., LTD. Rabbit Polyclonal antibody against DCUN1D5 was purchased from WUHAN Proteintech Group (Cat No. 14810-1-AP, 1:400 dilution). The paraffin-embedded slides were deparaffinized and rehydrated using xylene and a graded series of ethanol (100%, 95%, 70%), and then washed with PBS three times for 5 min each time. Antigen retrieval was conducted by heating the sections in boiling sodium citrate buffer for 20 min. After hydrogen peroxide and BSA blocking, the tissues were incubated with anti-DCUN1D5 at 37 °C for 90 min. Then tissues were incubated with HRP-conjugated secondary antibody. IHC signal was developed by DAB substrate, and counter-stained by haematoxylin for 2 min. IHC images were obtained by Olympus microscope (Olympus, Tokyo, Japan). DCUN1D5 expression was quantified as histochemical score (H-score) by two pathologists (Hongge Ju and Wei Zhang). Three high-power fields were randomly selected per tissue section. The scoring criteria were as follows: (1) The percentage of positively stained tumor cells was calculated in each field and averaged: 1 point for ≤ 25%, 2 points for 26%–50%, 3 points for 51%–75%, and 4 points for ≥ 75%. (2) Staining intensity was graded as follows: 0 point for no staining, 1 point for light yellow, 2 points for brownish yellow, and 3 points for dark brown. The final score was the sum of the two individual scores, and was graded as follows: 0–1 points negative (-), 2–3 points weakly positive (+), 4–5 points moderately positive (++), 6–7 points strongly positive (+++).
Statistical analysis
Statistical analysis was performed using SPSS software (version 29.0). For categorical data, the 
2 test was employed; Kaplan-Meier survival analysis was assessed using the Log-rank test; as data were non-normally distributed, Spearman’s rank correlation analysis was applied for correlation assessment.
Results
Expression profile and prognostic significance of DCUN1D5 across pan-cancer
To explore the expression levels of DCUN1D5 across various cancers, we performed an analysis utilizing Tumor Immune Estimation Resource (TIMER). DCUN1D5 is upregulated in most human cancers, including bladder cancer, breast invasive carcinoma, and stomach adenocarcinoma, but downregulated in thyroid cancer (Fig. 1). The protein expression levels of DCUN1D5 in ovarian cancer, liver cancer, lung cancer and urothelial caner tissues were assessed using the Human Protein Atlas (HPA), and had a medium expression (Fig. 1B–E).
Fig. 1.
Expression profile of DCUN1D5 across pan-cancer. A Boxplot of pan-cancer DCUN1D5 expression profiles generated by TIMER. Blue: normal adjacent tissues; red: BLCA tumor samples. B–E Immunohistochemical images of DCUN1D5 in ovarian cancer (patient id: 1911), liver cancer (patient id: 2325), lung cancer (patient id: 1249) and urothelial caner (patient id: 4676), as documented in the Human Protein Atlas. Scale bar: 50 μm and 200 μm
Overall survival analysis of DCUN1D5 in pan-cancer was performed using the Kaplan-Meier method. Analysis revealed that patients with low DCUN1D5 expression had significantly longer overall survival (OS) in bladder urothelial carcinoma (BLCA), liver hepatocellular carcinoma (LIHC), and kidney renal clear cell carcinoma (KIRC). Conversely, high DCUN1D5 expression correlated with improved OS in lung squamous cell carcinoma (LUSC), ovarian carcinoma (OV), and triple-negative breast cancer (TNBC) (Fig. 2).
Fig. 2.
Kaplan-Meier plotter analysis of DCUN1D5 expression across pan-cancer types. BLCA: bladder cancer; LIHC: liver hepatocellular carcinoma; LUSC: lung squamous cell carcinoma; KIRC: kidney renal clear cell carcinoma; OV: ovarian carcinoma; STAD: stomach adenocarcinoma; THCA: thyroid carcinoma; TNBC: triple-negative breast cancer
DCUN1D5 expression correlated with poor clinicopathological parameters in the TCGA-BLCA
To explore potential function of DCUN1D5 in BLCA, we compared the relationships between DCUN1D5 expression and clinicopathological characteristics, such as age, gender, T stage, tumor grade, recurrence, and lymph node metastasis, based on Xiantao academic database in conjunction with TCGA datasets. DCUN1D5 expression shown significant differences across histological grades and Tumor subtype, but demonstrated no association with patient gender, age, or clinical stage (Fig. 3).
Fig. 3.
DCUN1D5 expression in BLCA patient samples with different clinical pathological characteristic
Co-expression network analysis of DCUN1D5
We analyzed 20,047 DCUN1D5 co-expressed genes from LinkedOmics. Applying a false discovery rate (FDR) threshold of < 0.01 (P value < 0.05), we identified 8,203 significantly correlated genes, comprising 3,682 positively correlated and 4,521 negatively correlated genes. The top 50 positively and negatively correlated genes were displayed in a heatmap (Fig. 4B and D). Protein–protein interaction networks of top 50 positively and negatively correlated genes were constructed together. The top three nodes in terms of connectivity degree are CCT4, EIF3B, and PSMA7, which function in protein synthesis and degradation (Fig. 4C). We conducted the signaling pathway analysis of top 50 positively and negatively correlated genes. These genes were enriched in translation initiation factor activity (G0:0003743) and methyltransferase activity (G0:0008168:); moreover, the Parkinson disease signaling (hsa05012) was identified in KEGG analysis (Fig. 4E).
Fig. 4.
Co-expression gene analysis of DCUN1D5. A Volcano plot of 20,047 co-expression genes of DCUN1D5. B and D Heatmap of top 50 positively and negatively correlated genes with DCUN1D5 expression (red: high; blue: low). C Protein–protein interaction of top 50 positively and negatively correlated genes. The color of the nodes represents the Pearson correlation coefficient (red: positive; blue: negative). Border width of the nodes indicates the connectivity degree. E Signaling pathway analysis of top 50 positively and negatively correlated genes
DCUN1D5 expression was elevated in BLCA tissue microarray samples
To further investigate the significance of DCUN1D5 in BLCA, immunohistochemistry was performed to evaluate its protein expression levels in 56 BLCA tissue microarray samples (Fig. 5; Table 1). The intensity of DCUN1D5 expression was graded as follows: negative (-), weakly positive (+), moderately positive (++), strongly positive (+++). The results indicated the expression levels of DCUN1D5 in adjacent tissue were negative or weakly positive. While in BLCA tissues, DCUN1D5 was weakly positive, moderately positive or strongly positive. The weakly positive, moderately positive and strongly positive staining in BLCA tissues were 17/56 (30.4%), 22/56 (39.3%) and 9/56 (16.1%), respectively (Table 1). The results indicated the expression levels of DCUN1D5 was significantly higher in BLCA tissues than in adjacent tissues (
14.882, P
0.002).
Fig. 5.
Representative images of DCUN1D5 immunohistochemical staining in BLCA tissue microarrays. A DCUN1D5 was negatively expressed in adjacent tissue. B–D DCUN1D5 was weakly positive, moderately positive, strongly positive in BLCA tissues respectively. E–H are the part of indicated upper panel. Magnification ×40 upper panel, ×400 bottom panel. Scale bar: 50 μm
Table 1.
The expression of DCUN1D5 in BLCA and adjacent tissues
| Cases (%) | DCUN1D5 |
2
|
P | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Negative (–) | Weakly positive (+) | Moderately positive (++) | Strongly positive (+++) | ||||||
| BLCA | 56 (100%) | 8 (14.3%) | 17 (30.4%) | 22 (39.3%) | 9 (16.1%) | 14.882 | 0.002 | ||
| Adjacent | 9 (100%) | 6 (66.7%) | 3 (33.3%) | 0 (0.0%) | 0 (0.0%) | ||||
*P
0.05
Correlation between DCUN1D5 expression and clinicopathological parameters in 56 cases of BLCA tissue microarrays
The relationship between DCUN1D5 expression and clinicopathological parameters of BLCA was analyzed by Chi-square test. There was a significant correlation between DCUN1D5 expression and histologic grade (
2
23.571, P
0.001), depth of invasion (
2
14.922, P
0.021), T status (
2
28.490, P
0.019), tumor subtype (
2
8.095, P
0.044) (Table 2). DCUN1D5 expression was not associated with gender, age, lymph node, tumor number, tumor size, clinical stage (P
0.05). Results revealed that patients with a higher expression of DCUN1D5 exhibited greater potential to have an advanced histologic grade, depth of invasion, T stage and higher rates of lymph node metastasis.
Table 2.
The relationship between DCUN1D5 expression and clinicopathological characteristics
| Parameters | Total (n = 56) | DCUN1D5 |
2
|
P | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Negative (-) | Weakly positive (+) | Moderately positive (++) | Strongly positive (+++) | |||||||
| Gender | ||||||||||
| Male | 46 | 6 (13.0%) | 16 (34.8%) | 18 (39.1%) | 6 (13.0%) | 3.411 | 0.332 | |||
| Female | 10 | 2 (20.0%) | 1 (10.0%) | 4 (40.0%) | 3 (30.0%) | |||||
| Age (years) | ||||||||||
| ≥ 65 | 37 | 6 (16.2%) | 11 (29.7%) | 13 (35.1%) | 7 (18.9%) | 3.712 | 0.716 | |||
| < 65 | 18 | 2 (11.1%) | 5 (27.8%) | 9 (50.0%) | 2 (11.1%) | |||||
| Unknown | 1 | 0 (0%) | 1 (100%) | 0 (0%) | 0 (0%) | |||||
| Histologic grade | ||||||||||
| Poorly | 46 | 3 (6.5%) | 14 (30.4%) | 20 (43.5%) | 9 (19.6%) | 23.571 | 0.000* | |||
| Well | 7 | 5 (71.4%) | 1 (14.3%) | 1 (14.3%) | 0 (0%) | |||||
| Unknown | 3 | 0 (0%) | 2 (66.7%) | 1 (33.3%) | 0 (0%) | |||||
| Depth of invasion | ||||||||||
| MIBC | 36 | 2 (5.6%) | 8 (22.2%) | 18 (50.0%) | 8 (22.2%) | 14.922 | 0.021* | |||
| NMIBC | 16 | 4 (25.0%) | 7 (43.8%) | 4 (25.0%) | 1 (6.3%) | |||||
| Unknown | 4 | 2 (50.0%) | 2 (50.0%) | 0 (0%) | 0 (0%) | |||||
| Lymph node | ||||||||||
| YES | 7 | 2 (28.6%) | 2 (28.6%) | 2 (28.6%) | 1 (14.3%) | 9.079 | 0.169 | |||
| NO | 39 | 3 (7.7%) | 10 (25.6%) | 19 (48.7%) | 7 (17.9%) | |||||
| Unknown | 10 | 3 (30.0%) | 5 (50.0%) | 1 (10.0%) | 1 (10.0%) | |||||
| Tumor number | ||||||||||
| Multiple | 7 | 3 (42.9%) | 2 (28.6%) | 2 (28.6%) | 0 (0%) | 9.704 | 0.138 | |||
| Solitary | 43 | 3 (7.0%) | 13 (30.2%) | 19 (44.2%) | 8 (18.6%) | |||||
| Unknown | 6 | 2 (33.3%) | 2 (33.3%) | 1 (16.7%) | 1 (16.7%) | |||||
| T status | ||||||||||
| Tis | 4 | 0 (0%) | 1 (25.0%) | 3 (75.0%) | 0 (0%) | 28.490 | 0.019* | |||
| T1 | 11 | 3 (27.3%) | 7 (63.6%) | 0 (0%) | 1 (9.1%) | |||||
| T2 | 14 | 2 (14.3%) | 3 (21.4%) | 6 (42.9%) | 3 (21.4%) | |||||
| T3 | 21 | 0 (0%) | 5 (23.8%) | 11 (52.4%) | 5 (23.8%) | |||||
| T4 | 1 | 0 (0%) | 0 (0%) | 1 (100%) | 0 (0%) | |||||
| Unknown | 5 | 3 (60.0%) | 1 (20.0%) | 1 (20.0%) | 0 (0%) | |||||
| Tumor size | ||||||||||
 3 cm |
7 | 2 (28.6%) | 22 (28.6%) | 12 (14.3%) | 2 (28.6%) | 10.652 | 0.300 | |||
 5 cm |
21 | 32 (14.3%) | 4 (19.0%) | 12 (57.1%) | 2 (9.5%) | |||||
 5 cm |
22 | 1 (4.5%) | 9 (40.9%) | 8 (36.4%) | 4 (18.2%) | |||||
| Unknown | 6 | 2 (33.3%) | 2 (33.3%) | 1 (16.7%) | 1 (16.7%) | |||||
| Stage | ||||||||||
 III |
21 | 2 (9.5%) | 7 (33.3%) | 8 (38.1%) | 4 (19.0%) | 12.268 | 0.056 | |||
 III |
26 | 2 (7.7%) | 6 (23.1%) | 13 (50.0%) | 5 (19.2%) | |||||
| Unknown | 9 | 4 (44.4%) | 4 (44.4%) | 1 (11.1%) | 0 (0%) | |||||
| Tumor subtype | ||||||||||
| Papillary | 18 | 6 (33.3%) | 5 (27.8%) | 5 (27.8%) | 2 (11.1%) | 8.095 | 0.044* | |||
| Non papillary | 38 | 2 (5.3%) | 12 (31.6%) | 17 (44.7%) | 7 (18.4%) | |||||
*P
0.05
Correlation between DCUN1D5 expression and survival of 56 BLCA patients
Kaplan-Meier survival analysis was performed to evaluate the prognostic values of DCUN1D5 using 56 BLCA tissue microarrays matching follow-up time. According to the expression level of DCUN1D5, the samples were divided into high expression group and low expression group. SPSS software was used to statistically analyze the expression of DCUN1D5 in bladder cancer and the matching follow-up time, and finally Kaplan-Meier survival curve was drawn. However, we did not observe a significant difference in the overall survival (
2
0.066, P
0.797) (Fig. 6).
Fig. 6.
DCUN1D5 expression and its prognostic value in BLCA tissue microarrays
Discussion
Bladder cancer is recognized as one of the most prevalent urogenital malignancies, characterized by a significant rate of recurrence and progression. The complexity of bladder cancer is exacerbated by its heterogeneous nature, which can result in varied clinical presentations and responses to treatment. Traditional diagnostic and prognostic methods have proven inadequate, particularly in muscle-invasive bladder cancer (MIBC), where treatment efficacy remains suboptimal. Developing highly accurate, cost-effective, non-invasive tests for bladder cancer diagnosis and surveillance is an area of need in clinical diagnosis, particularly for early and low-grade urothelial tumors [5]. Gene and protein biomarkers provide the opportunity for a tectonic shift in how bladder cancer is diagnosed and how recurrences are detected. The various tumor stages are associated with different genetic features, which can be used as markers for minimally invasive diagnostics and disease aggressiveness. The most informative molecular markers to date are genetic variants of TP53, ERCC1 and FGFR3 as markers of disease progression, chemotherapy sensitivity and small-molecule therapeutic selection, respectively [27]. We identified DCUN1D5 as novel potential biomarker for predicting the prognosis of BLCA.
In this study, we focus on the DCUN1D5 gene and its potential role as a prognostic biomarker in bladder cancer. Our research employs bioinformatics analysis alongside immunohistochemistry to investigate the expression profile of DCUN1D5 in bladder cancer tissues and its correlation with clinicopathological parameters. Preliminary findings indicate that DCUN1D5 is significantly upregulated in bladder cancer tissue and correlates with poor prognostic indicators, including histological grade and tumor subtype. Research indicated that co-expression genes of DCUN1D5 were enriched in translation initiation factor activity and methyltransferase activity, suggesting potential regulatory mechanisms of DCUN1D5 (Fig. 4). This study aims to elucidate the regulatory mechanisms of DCUN1D5 in bladder cancer, thereby contributing to our understanding of tumor biology and potentially guiding therapeutic interventions.
The significance of our findings regarding the molecular mechanisms and signaling pathways associated with DCUN1D5 in bladder cancer cannot be overstated. The upregulation of DCUN1D5 in bladder cancer, particularly in relation to poor clinicopathological parameters, suggests its role in the regulation of critical biological processes such as translation initiation and methylation. This aligns with previous studies that have highlighted the involvement of DCUN1D5 in oncogenic pathways linked to malignancies, indicating that aberrant expression of this gene could be a driving force behind tumor progression and aggressiveness in bladder cancer [15]. Moreover, the co-expression analysis revealing the enrichment of genes related to translation initiation factor activity and methyltransferase activity provides insight into the regulatory networks that DCUN1D5 may interact with, potentially influencing protein synthesis and modification processes crucial for cancer cell proliferation [14]. Understanding these molecular interactions could pave the way for identifying novel therapeutic strategies that target the pathways modulated by DCUN1D5, thus contributing to personalized treatment approaches for bladder cancer patients.
In addition to the molecular mechanisms, our findings on the gene function of DCUN1D5 reveal its differential expression across various histological grades and tumor subtypes within bladder cancer. The strong correlation between high DCUN1D5 expression and advanced tumor features underscores its potential as a prognostic biomarker. This is particularly significant, as existing literature has demonstrated that molecular markers like DCUN1D5 can help differentiate between aggressive and less aggressive forms of cancer, thereby influencing clinical decision-making and treatment planning [18]. Furthermore, the implications of DCUN1D5 on cellular behaviors such as proliferation and invasion, as evidenced by our immunohistochemical analysis, suggest that this gene may play a pivotal role in the tumor microenvironment, affecting how cancer cells interact with their surroundings and respond to therapeutic interventions [17]. Future research focusing on the functional consequences of DCUN1D5 modulation in bladder cancer models will be essential to validate its utility as a therapeutic target.
The era of immune checkpoint blockade has led to tremendous success in cancer treatment in several cancer types. Researchers are striving to identify valid and reliable biomarkers for immune checkpoint blockade and immunotherapy through a combination of conventional and bioinformatic approaches [28, 29]. The potential immunological implications of DCUN1D5 expression in bladder cancer warrant further investigation, particularly as our study did not directly assess immune mechanisms. However, the expression of DCUN1D5 and its co-expressed genes may have consequential effects on immune cell infiltration and the overall immune landscape of the tumor microenvironment. Previous studies have highlighted the role of specific molecular markers in modulating immune responses within tumors, suggesting that DCUN1D5 could influence how bladder cancer cells evade immune detection or respond to immunotherapy [30]. Understanding the relationship between DCUN1D5 and immune checkpoint molecules could provide valuable insights into enhancing the efficacy of existing immunotherapies for bladder cancer, thereby advancing the field of cancer immunology and therapeutic strategies. As such, further studies exploring the interplay between DCUN1D5 expression, immune modulation, and treatment response are essential to elucidate its comprehensive role in bladder cancer biology [15].
The limitations of this study warrant careful consideration. Firstly, while our findings are promising, the absence of wet lab experiments to validate the bioinformatics and immunohistochemical results limits the robustness of our conclusions. Additionally, the relatively small sample size of the tissue microarray may introduce variability and compromise the statistical power of our analyses. The reliance on multiple datasets also raises concerns regarding potential batch effects, which could skew the interpretation of DCUN1D5 expression profiles. Furthermore, the lack of comprehensive clinical validation limits our ability to generalize the prognostic implications of DCUN1D5 across diverse populations. These limitations underscore the necessity for further research to substantiate our findings and elucidate the mechanistic role of DCUN1D5 in bladder cancer.
Conclusion
In conclusion, this study establishes DCUN1D5 as a novel potential biomarker for bladder cancer prognosis, demonstrating its significant upregulation in tumor tissues and correlation with advanced clinicopathological parameters. The insights gained from this research may pave the way for developing DCUN1D5-targeted therapeutic strategies and enhancing personalized treatment approaches for bladder cancer. However, future investigations are essential to validate these findings in larger, more diverse cohorts, as well as to explore the functional implications of DCUN1D5 in tumor biology and its interactions within the tumor microenvironment.
Acknowledgements
This research was supported by the Central Guidance for Local Science and Technology Development Funds Project (2024ZY0043), the Inner Mongolia Science and Technology Plan (2023YFSH0055), the Zhejiang Province Medical and Health Science and Technology Plan (2023RC199) and the Zhejiang Province Traditional Chinese Medicine Health Technology Program Project (2024ZF101), the Research Program of Science and Technology at Universities of Inner Mongolia (NJZY22052), the Science and Technology Program of the Joint Fund of Scientific Research for the Public Hospitals of Inner Mongolia Academy of Medical Sciences (2024GLLH0531), the Wenzhou Public Welfare Science and Technology Foundation (Y2023209), the Research and Development Funds of Baotou Medical College (BYJJ-ZRQM 202417, BYJJ-ZRQM 202426, BYJJ-ZRQM 202428, BYJJ-GCJH 202510), the Baotou Medical College Young Fellow Development Program (BYJJ-QNGG 2022042) and the Baotou Medical College Innovation Team Development Program (bycxtd-15).
Author contributions
XMH: Conceptualization, Formal Analysis, Methodology, Software, Writing – original draft. LQL: Formal Analysis, Methodology, Software, Writing – original draft. YZJ: Formal Analysis, Methodology, Software, Writing – original draft. LJA: Formal Analysis, Methodology, Software. XYW: Formal Analysis, Methodology, Software. CX: Formal Analysis. RG: Formal Analysis, Methodology, Software. RHW: Formal Analysis, Methodology. YLD: Formal Analysis, Methodology, Software. SYF: Methodology, Software. RXL: Software. JMZ: Methodology, Software. JXL: Methodology, Software. ZQZ: Methodology, Software. YJW: Conceptualization. LY: Conceptualization, Methodology, Validation, Writing – review & editing. HGJ: Conceptualization, Methodology, Formal Analysis, Validation, Writing – review & editing. QM: Conceptualization, Methodology, Formal Analysis, Validation, Writing – review & editing. KWZ: Conceptualization, Methodology, Formal Analysis, Validation, Writing – review & editing. All authors commented on the manuscript. All authors contributed to the article and approved the submitted version.
Data availability
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
Declarations
Ethics approval and consent to participate
All studies involving human tissues were conducted in strict accordance with the Declaration of Helsinki and were approved by Ethics Committee of Shanghai Outdo Biotech Company (SHYJS-CP-1910002). The tissue samples and Corresponding official document for exemption of informed consent were obtained from Shanghai Outdo Biotech Company. The product information URL is as follows: https://www.superchip.com.cn/biology/tissue.html.
Consent for publication
The authors confirm their consent to publish the manuscript.
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.
Xiaomin Han, Lanqi Li, Yuzhe Jia, Lijuan Ai and Xingyu Wang have contributed equally to this work and share first authorship.
Contributor Information
Li Yang, Email: 436094297@qq.com.
Hongge Ju, Email: juhongge1088@163.com.
Qiang Ma, Email: maqiang@btmc.edu.cn.
Kewen Zheng, Email: zkw2121@163.com.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.