Pathway-based cancer transcriptome deciphers a high-resolution intrinsic heterogeneity within bladder cancer classification

Sep 23, 2026

The study investigates how cancer-intrinsic gene expression programs shape bladder cancer (BLCA) classification and patient prognosis, in the context of transcriptional heterogeneity driven by tumor microenvironment stromal components. Using BLCA single-cell transcriptome data from GSE135337 and pathway-based transcriptome classification, the work derives intrinsic heterogeneous cell subgroups and confirms intrinsic subtypes in TCGA. Four subtypes are linked to distinct molecular functions, immune activation patterns, and clinical outcomes.

LanguageEnglish

CategoryHealthcare

FormatPDF

Pages19

Reading Time48 min

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Abstract

Background

Materials and methods

Results

Conclusion

Keywords

Introduction

Wang et al. Journal of Translational Medicine (2025) 23:666 [https://doi.org/10.1186/s12967-025-06682-1](https://doi.org/10.1186/s12967-025-06682-1) Journal of Translational Medicine RESEARCH Open Access Pathway-based cancer transcriptome deciphers a high-resolution intrinsic heterogeneity within bladder cancer classification Zhan Wang 1†, Zhaokai Zhou2†, Shuai Yang 1†, Zhengrui Li3†, Run Shi4, Ruizhi Wang 1, Kui Liu5, Xiaojuan Tang6 and Qi Li7,8* Abstract Background The heterogeneity of bladder cancer (BLCA) is affected by its inherent transcriptional properties and tumor microenvironment (TME) . Stromal transcriptional components in theTME significantly influence the transcriptional classification of BLCA, and the intrinsic biological transcriptional characteristics of cancer cells may be obscured by the dominant, lineage-dependent transcriptional components of stromal origin. This study aimed to explore the degree and mechanisms by which cancer-intrinsic gene expression profiles contribute to the classification and prognosis of BLCA patients. Materials and methods In this study, BLCA single-cell transcriptome data from GSE135337 were used to identify pure tumor cells in BLCA and explore the different intrinsic heterogeneous cell subgroups of BLCA through pathwaybased cancer transcriptome classification. Additionally, BLCA intrinsic subtypes were uncovered in the TCGA BLCA dataset based on the characteristic genes of the subgroups. Lastly, various machine learning algorithms were applied to identify novel potential targets of BLCA, following which their pro-tumorigenic effects were experimentally verified. Results Four BLCA intrinsic subtypes with different molecular, functional and phenotypic characteristics were successfully identified. Specifically, MA and DP subtypes demonstrated malignant phenotypes, accompanied by unfavorable clinical prognoses, limited involvement in cell death pathways, marked cell proliferation, and diminished immune activation. Notably, MA subtype exhibited the most favorable response to immunotherapy, potentially attributable to its distinctive tumor immune microenvironment. DSM subtype represented an immune-rich subtype with the optimal prognosis, characterized by abundant immune cells, high levels of co-stimulatory, co-inhibitory, major histocompatibility complex molecules, and a potential for immunotherapy response. On the other hand, HM subtype was associated with a high level of autophagy and necrosis and an “immune-hot”TIME. Furthermore, BLCA †Zhan Wang, Zhaokai Zhou, Shuai Yang and Zhengrui Li contributed equally to this work and share senior authorship. *Correspondence: Qi Li [siloam1994@163.com](siloam1994@163.com) Full list of author information is available at the end of the article © The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit [http://creati](http://creati)[vecommons.org/l](vecommons.org/l)icenses/by-nc-nd/4.0/. Wang et al. Journal of Translational Medicine (2025) 23:666 Page 2 of 19 intrinsic subtypes effectively classified ind

FAQs

What is the main goal of the study on bladder cancer heterogeneity?

To determine how cancer-intrinsic gene expression profiles contribute to BLCA classification and prognosis, despite confounding effects from stromal transcriptional components in the tumor microenvironment.

How were BLCA intrinsic subtypes identified and validated?

Pure tumor cells were identified from BLCA single-cell transcriptome data in GSE135337 using pathway-based cancer transcriptome classification, and intrinsic subtypes were further uncovered in the TCGA BLCA dataset using characteristic genes of the subgroups.

What are the four intrinsic BLCA subtypes and how do they differ clinically?

Four intrinsic subtypes with distinct molecular, functional, and phenotypic characteristics were found. MA and DP show malignant phenotypes with unfavorable prognoses; DSM is immune-rich with the best prognosis; HM is associated with high autophagy/necrosis and an immune-hot tumor immune microenvironment.

Which genes were proposed as potential targets for the DP subtype?

Three potential target genes—DAD1, CYP1B1, and REXO2—were identified and reported as significantly associated with metabolic disorders as well as BLCA stage and grade.

Sep 23, 2026

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