Open AccessImmune‐related signature predicts the prognosis and immunotherapy benefit in bladder cancer
Author(s) -
Wang Yejinpeng,
Chen Liang,
Yu Mengxue,
Fang Yayun,
Qian Kaiyu,
Wang Gang,
Ju Lingao,
Xiao Yu,
Wang Xinghuan
Publication year - 2020
Publication title -
cancer medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.403
H-Index - 53
ISSN - 2045-7634
DOI - 10.1002/cam4.3400
Subject(s) - immunotherapy , immune system , cohort , oncology , medicine , lasso (programming language) , bladder cancer , immunology , cancer , cancer research , computer science , world wide web
Background There is no good prognostic model that could predict the prognosis of bladder cancer (BCa) and the benefit of immunotherapy. Methods Through the least absolute shrinkage and selection operator (LASSO) algorithm, we constructed a 13‐mRNA immune signature from the TCGA cohort (n = 406). We validated its prognostic value and predictive value for the benefit of immunotherapy with four independent validation cohort ( GSE13507 [n = 256], GSE31684 [n = 93], GSE32894 [n = 308], and IMvigor210 cohort [n = 298]). Results Our results indicating that high‐risk group with higher inhibitory immune cell infiltration (regulatory T cells [Tregs] and macrophage, etc), higher expression of immune checkpoints, and more T cell suppressive pathways (transforming growth factor β [TGF‐β], epithelial‐mesenchymal transition [EMT], etc) were activated. Besides, the immune signature showed a good predictive value for the benefit of immunotherapy in a cohort of urothelial carcinoma patients treated with PD‐L1. Conclusions The immune signature constructed is convenient to classify the immunotherapeutic susceptibility of patients with BCa, so as to achieve precision immunotherapy for BCa.