Abstract
Background
Cancer-associated fibroblasts (CAFs) are the most important cellular components in bladder urothelial carcinoma (BLCA) and are involved in the development and immunosuppression of BLCA. Therefore, we aimed to construct a CAF-associated signature for predicting the prognosis and immunotherapy response in patients with BLCA.
Methods
CAF infiltration and stromal score were quantified using two algorithms. Weighted gene co-expression network analysis (WGCNA) was performed to identify the CAF-associated modules and hub genes. Univariate Cox and Least Absolute Shrinkage and Selection Operator regression analyses were used for constructing CAF signatures and calculating CAF scores. The ability of the CAF signature to predict prognosis and response to immunotherapy was validated using the data from three cohorts.
Results
WGCNA identified two CAF-associated modules and constructed a CAF signature containing 27 genes. In all three cohorts, patients with high CAF scores had markedly worse prognoses than those with low CAF scores, and CAF scores were independent risk factors. In addition, patients with high CAF scores did not respond to immunotherapy, whereas those with lower CAF scores responded to immunotherapy.
Conclusion
CAF signature can be used to predict prognosis and immunotherapy response to guide individualized treatment planning in patients with BLCA.
Acknowledgments
We thank Bullet Edits Limited for the linguistic editing and proofreading of the manuscript.
Data availability statement
The datasets generated and analyzed in this study can be found in the Gene Expression Omnibus repository (accession number: GSE32894 and GSE13507), The Cancer Genome Atlas-bladder urothelial carcinoma (TCGA-BLCA), and IMvigor210 databases.
Disclosure statement
The authors declare that they have no competing interests.
Medical ethics statement
Ethical approval was waived by the Institutional Ethics Committee because data were obtained from public databases, and all patients were de-identified to maintain confidentiality.