Genomic stratification based on microenvironment immune types and PD-L1 for tailoring therapeutic strategies in bladder cancer

Abstract

Background The tumour microenvironment (TME) not only plays a role during tumour progression and metastasis but also profoundly influences treatment efficacy. Environment-mediated drug resistance is a result of crosstalk between tumour cells and stroma. The presence of a “stromal exhaustion” response is suggested by the T cell exhaustion signature and PD-L1 expression. The prognostic role of PD-L1 in bladder cancer has been investigated in previous studies, but the results remain inconclusive. For a more comprehensive study, we discuss potential strategies to improve effectiveness in patients with various TME statuses and PD-L1 expression levels. Methods We estimated the prognostic role of PD-L1 using immunohistochemistry and identified four immune subtypes according to the type of stromal immune modulation and PD-L1 expression status. Results Patients in the PD-L1-low-exhausted group had the worst prognosis and showed the worst antigen-presenting cell (APC) immunosuppression status. The PD-L1-low-exhausted group showed the highest amount of infiltration by macrophage M2 cells, naïve B cells and resting mast cells. The TMB and the effectiveness of anti-PD-1 treatment were significantly increased in the PD-L1-high expression groups compared with the PD-L1-low expression groups. In the PD-L1-high groups, patients who underwent chemotherapy exhibited better overall survival rates than patients who did not undergo chemotherapy, whereas there was no significant difference in the PD-L1-low groups. We performed gene set enrichment analysis (GSEA) to explore the critical pathways that were active in the PD-L1-low-exhausted group, including the myogenesis, epithelial-mesenchymal transition and adipogenesis pathways. Copy number variations (CNVs) were related to the expression levels of differentially expressed genes upregulated in the PD-L1-low-exhausted group, including LCNL1, FBP1 and RASL11B. In addition, RASL11B played a role in predicting overall survival according to The Cancer Genome Atlas data, and this finding was validated in the PD-L1-low-exhausted group in the Gene Expression Omnibus database (GEO). Conclusion The immune environment of tumours plays an important role in the therapeutic response rate, and defining the immune groups plays a critical role in predicting disease outcome and strategy effectiveness.