Identification and Quantification of Iron Metabolism Landscape on Therapy and Prognosis in Bladder Cancer - Song, Xiaodong; Xin, Sheng; Zhang, Yucong; Mao, Jiaquan; Duan, Chen; Cui, Kai; Chen, Liang; Li, Fan; Liu, Zheng; Wang, Tao; Liu, Jihong; Liu, Xiaming; et al. (Frontiers in Cell and Developmental Biology, 2022)
The morbidity of bladder cancer (BLCA) is high and gradually elevating in recent years. BLCA is also characterized by high recurrence and high invasiveness. Due to the drug resistance and lack of effective prognostic indicators, the prognosis of patients with BLCA is greatly affected. Iron metabolism is considered to be a pivot of tumor occurrence, progression and tumor microenvironment (TME) in tumors, but there is few research in BLCA. Herein, we used univariate COX regression analysis to screen 95 prognosis-related IMRGs according to transcription RNA sequencing and prognosis information of the Cancer Genome Atlas (TCGA) database. TCGA-BLCA cohort was clustered into four distinct iron metabolism patterns (C1, C2, C3 and C4) by non-negative matrix factorization (NMF) algorithm. Survival analysis showed that C1 and C3 patterns had a better prognosis. GSVA analysis revealed that C2 and C4 patterns were mostly enriched in carcinogenic and immune activation pathways. ESTIMATE and ssGSEA analysis also confirmed the level of immune cell infiltration in C2 and C4 patterns significantly elevated. Moreover, the immune checkpoint genes in C2 and C4 patterns were observably overexpressed. Studies on somatic mutations showed that the tumor mutation burden (TMB) of C1 and C4 patterns was the lowest. Chemotherapy response assessment revealed that C2 pattern was the most sensitive to chemotherapy, while C3 pattern was the most insensitive. Then we established the IMRG prognosis signature (IMRGscore) by the least absolute shrinkage and selection operator (LASSO), including 13 IMRGs (TCIRG1, CTSE, ATP6V0A1, CYP2C8, RNF19A, CYP4Z1, YPEL5, PLOD1, BMP6, CAST, SCD, IFNG and ASIC3). We confirmed IMRGscore could be utilized as an independent prognostic indicator. Therefore, validation and quantification of iron metabolism landscapes will help us comprehend the formation of BLCA immunosuppressive microenvironment, guide the selection of chemotherapeutic drugs and immunotherapy, and predict the prognosis of patients.