# Single-cell transcriptomics identifies fibroblast associated immune heterogeneity and prognostic signatures in bladder cancer

## TL;DR

This study uses single-cell RNA sequencing to uncover fibroblast-related immune patterns and prognostic markers in bladder cancer, helping to improve treatment strategies.

## Contribution

The study introduces fibroblast-associated prognostic gene signatures and a risk stratification model for bladder cancer.

## Key findings

- Analysis identified 500 fibroblast-associated marker genes and key transcription factors like MAF, TWIST1, and TCF21.
- A prognostic model stratified patients into high- and low-risk groups based on fibroblast-related gene signatures.
- The study highlights the role of fibroblasts in the immune microenvironment for bladder cancer prognosis.

## Abstract

The immune microenvironment and prognosis of bladder cancer (BLCA) remain ongoing challenges in its treatment. This study aimed to establish predictive prognostic indicators and investigate the immune microenvironment to enhance clinical treatment strategies. A single-cell transcriptional atlas was constructed using single-cell RNA-seq data from patients with bladder cancer, focusing on fibroblast-related gene expression, intercellular communication, metabolic pathways inferred by single-cell flux estimation analysis, and transcription factor networks. Fibroblast-associated prognostic gene signatures were validated using data from The Cancer Genome Atlas, and a prognostic model was developed to stratify patients with bladder cancer into high- and low-risk groups. Analysis of three para-carcinoma single-cell samples revealed the presence of 3,603 fibroblasts and 500 fibroblast-associated marker genes. Notably, key fibroblast-specific transcription factors, including MAF, TWIST1, and TCF21, were identified through SCENIC analysis. The incorporation of comprehensive RNA sequencing data enabled the discovery of prognostic markers associated with fibroblasts. Using this classification model, patient survival could be stratified into high- and low-risk categories based on the model. The results of our study highlight the prognostic genetic signatures associated with the fibroblast component of the immune microenvironment in BLCA, offering preliminary insights into prognostic assessment and potential therapeutic implications.

The online version contains supplementary material available at 10.1038/s41598-026-38219-x.