Neutrophil-related genes predict prognosis and response to immune checkpoint inhibitors in bladder cancer

Neutrophils play a key role in the occurrence and development of cancer. However, the relationship between neutrophils and cancer prognosis remains unclear due to their great plasticity and diversity. To explore the effects of neutrophils on the clinical outcome of bladder cancer, we acquired and analyzed gene expression data and clinical information of bladder cancer patients from IMvigor210 cohort and The Cancer Genome Atlas dataset (TCGA) database. We established a neutrophil-based prognostic model incorporating five neutrophil-related genes (EMR3, VNN1, FCGRT, HIST1H2BC, and MX1) and the predictive value of the model was validated in both an internal and an external validation cohort. Multivariate Cox regression analysis further proved that the model remained an independent prognostic factor for overall survival and a nomogram was constructed for clinical practice. Additionally, FCGRT was identified as the key neutrophil-related gene linked to an adverse prognosis of bladder cancer. Up-regulation of FCGRT indicated activated cancer metabolism, immunosuppressive tumor environment, and dysregulated functional status of immune cells. FCGRT overexpression was also correlated with decreased expression of PD-L1 and low levels of tumor mutation burden (TMB). FCGRT predicted a poor response to immunotherapy and had a close correlation with chemotherapy sensitivity. Taken together, a novel prognostic model was developed based on the expression level of neutrophil-related genes. FCGRT served as a promising candidate biomarker for anti-cancer drug response, which may contribute to individualized prognostic prediction and may contribute to clinical decision-making.

Automated summary

Neutrophils play a crucial role in the prognosis of bladder cancer. We developed a prognostic model based on neutrophil-related genes and identified FCGRT as a key gene associated with adverse prognosis. FCGRT may serve as a promising biomarker for anti-cancer drug response, contributing to personalized prognostic prediction and clinical decision-making.