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Culture of Bladder Cancer Organoids as Precision Medicine Tools
Published on: December 28, 2021
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Pathway-based cancer transcriptome deciphers a high-resolution intrinsic heterogeneity within bladder cancer
Zhan Wang1, Zhaokai Zhou2, Shuai Yang1
1Department of Urology, The First Affiliated Hospital of Zhengzhou University, Henan, 450052, China.
Journal of Translational Medicine
|June 17, 2025
Summary
This study reveals four bladder cancer (BLCA) subtypes based on intrinsic gene expression, offering new prognostic and therapeutic insights. Targeting REXO2 may improve outcomes by addressing metabolic disorders in BLCA.
Area of Science:
- Oncology
- Genomics
- Cancer Biology
Background:
- Bladder cancer (BLCA) exhibits heterogeneity influenced by tumor microenvironment (TME) and intrinsic transcriptional properties.
- Stromal components can obscure cancer cell-specific gene expression, complicating BLCA classification.
- Understanding cancer-intrinsic gene expression is crucial for accurate BLCA classification and prognosis.
Purpose of the Study:
- To investigate the extent and mechanisms of cancer-intrinsic gene expression in BLCA classification and prognosis.
- To identify and characterize distinct intrinsic subtypes of BLCA.
- To discover novel therapeutic targets for BLCA.
Main Methods:
- Analysis of single-cell transcriptome data (GSE135337) to identify pure tumor cells and intrinsic BLCA subgroups.
- Pathway-based transcriptome classification and identification of BLCA intrinsic subtypes in the TCGA BLCA dataset.
- Application of machine learning algorithms to identify potential BLCA targets and experimental verification of their pro-tumorigenic effects.
Main Results:
- Four distinct BLCA intrinsic subtypes (MA, DP, DSM, HM) with unique molecular, functional, and phenotypic characteristics were identified.
- Subtypes showed varying prognoses, immune activation levels, and responses to immunotherapy (MA: best immunotherapy response; DSM: optimal prognosis, immune-rich).
- DP subtype, linked to the worst prognosis, revealed three potential therapeutic targets (DAD1, CYP1B1, REXO2) associated with metabolic disorders and disease stage.
Conclusions:
- The identified BLCA intrinsic subtypes provide a novel platform for understanding tumor heterogeneity and molecular mechanisms.
- These subtypes demonstrate significant predictive and prognostic value, distinct from existing classifications.
- Targeting REXO2 may offer a therapeutic strategy to improve BLCA patient prognosis by modulating mitochondria-related metabolic disorders.
