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Multi-omics analysis reveals critical metabolic regulators in bladder cancer

  • Urology - Original Paper
  • Published:
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Abstract

Background

The crosstalk between genomic alterations and metabolic dysregulation in bladder cancer is largely unknown. A deep understanding of the interactions between cancer drivers and cancer metabolic changes will provide novel opportunities for targeted therapeutic strategies.

Methods

Three primary bladder cancer specimens with paired normal tissues or blood samples were subjected to whole-exome sequencing, DNA methylation array and whole-transcriptome sequencing by next-generation sequencing technology. We applied the methods to multi-omics data combining the Cancer Genome Atlas (TCGA) bladder cancer samples, including somatic mutation, DNA copy number, DNA methylation and gene expression profile for validation.

Results

We identified 34 mutated cancer driver genes in bladder cancer. KDM6A was the most significantly mutated cancer driver gene. Metabolic pathways were enriched in both differentially methylated regions (DMRs) and differentially expressed genes. Twenty-nine DMRs in the TSS200 region were highly correlated with the upregulation of gene expression, and 24 DMRs in the genome were highly correlated with the downregulation of gene expression. A total of 201 genes had highly correlated DNA methylation and expression. Thirty-four genes, including the known metabolic genes CXXC5, PRR5, ABCB8 and BAHD1, were further validated in the TCGA cohort. Multi-omics alterations identified two new candidate driver genes, WIPI2 and GFM2, that warrant future studies.

Conclusions

This study provides a comprehensive and systematic analysis, focusing on identifying key regulatory factors that may lead to cancer metabolic heterogeneity. Further understanding and verification of the cancer genes driving metabolic reprogramming and their role in the progression of bladder cancer will help to identify new therapeutic targets.

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Availability of data and materials

The data and materials used in this study are available upon request from the corresponding author. Access to the data and materials will be granted after a review of the request to ensure that the request is consistent with the ethical guidelines of the study and that the privacy and confidentiality of the participants are protected.

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  1. Chengcheng Wei, Changqi Deng, and Rui Dong contributed equally to this work.

Authors and Affiliations

  1. Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China

    Chengcheng Wei, Changqi Deng, Yaxin Hou, Miao Wang, Liang Wang & Teng Hou

  2. Department of Urology, South China Hospital, Medical School, Shenzhen University, Shenzhen, 518116, People’s Republic of China

    Teng Hou & Zhaohui Chen

  3. Department of Urology, Hanyang Hospital of Wuhan City, Wuhan, 430050, China

    Rui Dong

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Acquisition of data, CW; conception and design of the research, ZC; analysis and interpretation of data, CD; statistical analysis, YH; obtaining funding, TH; drafting the manuscript, MW; revision of manuscript for important intellectual content, LW; revised the manuscript, RD.

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Wei, C., Deng, C., Dong, R. et al. Multi-omics analysis reveals critical metabolic regulators in bladder cancer. Int Urol Nephrol 56, 923–934 (2024). https://doi.org/10.1007/s11255-023-03841-5

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