Anoikis-related gene signature as novel prognostic biomarker to predict immunotherapy with bladder urothelial carcinoma

Abstract Objectives Anoikis plays an active role in the metastasis and progression of many tumors is emerging as a new target for tumor therapy. We aimed to develop anoikis-related risk model assess prognosis patients with bladder urothelial carcinoma (BLCA) explore its potential application value immunotherapy. Methods Patient expression data clinical were obtained from GEO TCGA database. Lasso regression was used obtain efficacy evaluated Cox regression, calibration curves, nomogram diagram, receiver operating characteristics (ROC). Next, GSEA analysis performed estimate biological pathways ARGS. The microenvironment (TME) also assessed, including cancer-associated fibroblast (CAF), CIBERSORT, XCELL, immune exclusion, tumor-associated macrophage (TAM). Then, ggpubr ggplot2 packages utilized compare checkpoint discrepancies different groups. we discussed survival relevance ARGS combined checkpoints using survminer sensitivity immunotherapy through cancer immunome atlas (TCIA) IMvigor210 cohort. Results 15 anoikis genes identified construct prognostic can effectively divide BLCA cases into 2 groups outcomes reflect TME. It obvious that high-risk group could not benefit Conclusions be stratify hazards predict events give remarkable guidance personalized precise