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Article Open Access

pQTL Mendelian randomization analysis combined with single‑cell sequencing to identify biomarkers and drug targets for bladder cancer

  • Authors:
    • Wenzhi Gao
    • Yue Li
    • Zhixin Fu
    • Zihui Gao
    • Yaming Gu
    • Xiaopeng Jia
    • Yuqing Jiang
    • Yuexian Guo
  • View Affiliations / Copyright

    Affiliations: Department of Urology, Peking University First Hospital‑Miyun Hospital, Beijing 101500, P.R. China, Department of Urology, The Third Hospital of Hebei Medical University, Shijiazhuang, Hebei 050000, P.R. China
    Copyright: © Gao et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Article Number: 106
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    Published online on: October 6, 2025
       https://doi.org/10.3892/mco.2025.2901
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Abstract

Despite the development and application of numerous biomarkers and targeted therapeutic approaches for bladder cancer, substantial limitations and challenges persist in its early diagnosis and targeted treatment. As a result, there is an immediate necessity to discover novel biomarkers and develop new targeted drugs. In the present study the association between genes and bladder cancer was analyzed through Mendelian randomization (MR). Sensitivity analysis was conducted to evaluate the reliability of gene causality. Colocalization analysis was used to reduce confounding factors due to linkage disequilibrium and improve the accuracy of causal inference. Validation was performed using quantitative polymerase chain reaction (qPCR) in bladder cancer cell lines. A nomogram model was constructed, and drug sensitivity analysis and single‑cell expression typing were conducted to predict survival, select potential therapeutic targets, and detect specific cell types with abundant expression. The results identified seven genes whose predicted levels were associated with bladder cancer risk in the MR analysis. Elevated levels of four genes and decreased levels of three genes were associated with low risk of bladder cancer. All‑trans retinoic acid‑induced differentiation factor (ATRAID) and tripartite motif containing 25 (TRIM25) showed colocalization with SNP.PP.H4 values >0.95, indicating a high likelihood of association with bladder cancer risk. Reverse transcription qPCR validation revealed low expression of ATRAID and TRIM25 in bladder cancer. ATRAID is primarily expressed in fibroblasts and smooth muscle cells, while TRIM25 is highly expressed in endothelial cells. Using clinical data from patients, a model based on ATRAID and TRIM25 demonstrated excellent predictive performance. Furthermore, drug analysis revealed that the expression of ATRAID and TRIM25 is closely associated with the sensitivity to various chemotherapy drugs. In the present study, ATRAID and TRIM25 were identified as two biomarkers linked to the risk of bladder cancer. These findings not only provide new insights into the etiology of bladder cancer but also identify novel targets for the development of biomarkers and therapeutic medications against the disease.
View Figures

Figure 1

MR analysis screening. (A) Risk
associations of 114 causal relationships identified through MR
analysis. (B) Scatter plot of MR analysis for seven genes, with
different colors indicating different statistical methods. The
slopes of the lines represent the causal effects of each method.
MR, Mendelian randomization; SNP, single nucleotide polymorphism;
OR, odds ratio.

Figure 2

Key gene screening and reverse
transcription-quantitative PCR validation. (A-G) Forest plots of
leave-one-out analysis for SNPs corresponding to the seven genes.
(H and I) Associations between SNPs of ATRAID and TRIM25 with the
disease, where each point indicates a statistically significant
SNP-disease association. The x-axis represents the P-value of GWAS,
and the y-axis represents the P-value of the pQTL analysis. (J and
K) KEGG signaling pathways involving ATRAID and TRIM25, including
genes involved in pathway regulation. (L and M) mRNA expression
levels of ATRAID and TRIM25 in bladder cancer cell lines.
**P<0.01 and ***P<0.001. SNP, single
nucleotide polymorphism; ATRAID, all-trans retinoic acid-induced
differentiation factor; TRIM25, tripartite motif containing 25;
GWAS, genome-wide association studies; pQTL, protein quantitative
trait loci; KEGG, Kyoto, Encyclopedia of Genes and Genomes.

Figure 3

Association analysis with clinical
indicators. (A-H) Association analysis between ATRAID and clinical
indicators. (I-P) Association analysis between TRIM25 and clinical
indicators. ATRAID, all-trans retinoic acid-induced differentiation
factor; TRIM25, tripartite motif containing 25.

Figure 4

Mutational landscape of key genes,
differences in TMB/MSI, and construction of the Nomogram model. (A
and B) SNP-related data of bladder cancer, showing the top 30 genes
with high mutation frequencies in 2 patient groups. (C-F)
Differences in MSI and TMB between ATRAID and TRIM25. (G) Column
chart of the key gene model. (H) Prediction analysis of OS for 3
and 5 years. (I and J) ROC curve and decision curve analysis. TMB,
tumor mutation burden; MSI, microsatellite instability; SNP, single
nucleotide polymorphism; ATRAID, all-trans retinoic acid-induced
differentiation factor; TRIM25, tripartite motif containing 25; OS,
overall survival; ROC, receiver operating characteristic; LExp; low
expression; HExp, high expression; AUC, area under the curve.

Figure 5

Drug sensitivity analysis.
Sensitivity analysis of (A) ATRAID and (B) TRIM25 to chemotherapy
drugs. ATRAID, all-trans retinoic acid-induced differentiation
factor; TRIM25, tripartite motif containing 25; LExp; low
expression; HExp, high expression; IC50, half maximal inhibitory
concentration.

Figure 6

Expression of key genes at the
single-cell level. (A) Clustering of cells into 17 clusters based
on principal component analysis using the t-SNE algorithm. (B) Cell
annotation of the 17 clusters, annotated into five cell types,
namely Epithelial_cells, Fibroblasts, Smooth_muscle_cells,
Endothelial_cells. (C and D) Expression profiles of key genes in
cells. t-SNE, t-distributed Stochastic Neighbor Embedding; ATRAID,
all-trans retinoic acid-induced differentiation factor; TRIM25,
tripartite motif containing 25.
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Copy and paste a formatted citation
Spandidos Publications style
Gao W, Li Y, Fu Z, Gao Z, Gu Y, Jia X, Jiang Y and Guo Y: pQTL Mendelian randomization analysis combined with single‑cell sequencing to identify biomarkers and drug targets for bladder cancer. Mol Clin Oncol 23: 106, 2025.
APA
Gao, W., Li, Y., Fu, Z., Gao, Z., Gu, Y., Jia, X. ... Guo, Y. (2025). pQTL Mendelian randomization analysis combined with single‑cell sequencing to identify biomarkers and drug targets for bladder cancer. Molecular and Clinical Oncology, 23, 106. https://doi.org/10.3892/mco.2025.2901
MLA
Gao, W., Li, Y., Fu, Z., Gao, Z., Gu, Y., Jia, X., Jiang, Y., Guo, Y."pQTL Mendelian randomization analysis combined with single‑cell sequencing to identify biomarkers and drug targets for bladder cancer". Molecular and Clinical Oncology 23.6 (2025): 106.
Chicago
Gao, W., Li, Y., Fu, Z., Gao, Z., Gu, Y., Jia, X., Jiang, Y., Guo, Y."pQTL Mendelian randomization analysis combined with single‑cell sequencing to identify biomarkers and drug targets for bladder cancer". Molecular and Clinical Oncology 23, no. 6 (2025): 106. https://doi.org/10.3892/mco.2025.2901
Copy and paste a formatted citation
x
Spandidos Publications style
Gao W, Li Y, Fu Z, Gao Z, Gu Y, Jia X, Jiang Y and Guo Y: pQTL Mendelian randomization analysis combined with single‑cell sequencing to identify biomarkers and drug targets for bladder cancer. Mol Clin Oncol 23: 106, 2025.
APA
Gao, W., Li, Y., Fu, Z., Gao, Z., Gu, Y., Jia, X. ... Guo, Y. (2025). pQTL Mendelian randomization analysis combined with single‑cell sequencing to identify biomarkers and drug targets for bladder cancer. Molecular and Clinical Oncology, 23, 106. https://doi.org/10.3892/mco.2025.2901
MLA
Gao, W., Li, Y., Fu, Z., Gao, Z., Gu, Y., Jia, X., Jiang, Y., Guo, Y."pQTL Mendelian randomization analysis combined with single‑cell sequencing to identify biomarkers and drug targets for bladder cancer". Molecular and Clinical Oncology 23.6 (2025): 106.
Chicago
Gao, W., Li, Y., Fu, Z., Gao, Z., Gu, Y., Jia, X., Jiang, Y., Guo, Y."pQTL Mendelian randomization analysis combined with single‑cell sequencing to identify biomarkers and drug targets for bladder cancer". Molecular and Clinical Oncology 23, no. 6 (2025): 106. https://doi.org/10.3892/mco.2025.2901
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