AUTHOR=Liang Shengjie , Fang Kai , Li Simin , Liu Dong , Yi Qingtong 

TITLE=Immune Microenvironment Terms Signature Robustly Predicts the Prognosis and Immunotherapy Response in Bladder Cancer Based on Large Population Cohorts

JOURNAL=Frontiers in Genetics

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.872441

DOI=10.3389/fgene.2022.872441

ISSN=1664-8021

ABSTRACT=Immune microenvironment is implicated in cancer progression. However, the role of immune microenvironment in bladder cancer has not been fully explored. Open-accessed datasets GSE120736, GSE128959, GSE13507, GSE31684, GSE32548, GSE48075, GSE83586 and the cancer genome atlas (TCGA) database were enrolled in our study. Single sample gene set enrichment analysis (ssGSEA) was used to quantify 53 immune terms in combined BLCA cohorts. Top ten important immune terms were identified through random forest algorithm for model establishment. Our model showed satisfactory efficacy in prognosis prediction. Further, we explored clinical and genomic features differences between high- and low-risk groups. The results indicated that the patients in high-risk might be associated with worse clinical features. GSEA analysis showed that EMT, mTORC1 signaling, mitotic spindle, glycolysis, E2F target and G2M checkpoint pathways were aberrantly activated in high-risk patients, partially explaining its worse prognosis. Patients in the low-risk group showed better immunotherapy response according to TIDE and TCIA analysis, indicating that our model could effectively predict the immunotherapy response rate. KCNH4, UGT1A1, TPO, SHANK1, PITX3, MYH1, MYH13, KRT3, DEC1 and OBP2A genes were identified as feature genes in the high- and low-risk patients. CMAP analysis was performed to identify potential compounds targeted riskscore.