Chengquan Shen1, Ting Xu2, Yefeng Sun1, Liping Wang3, Zhijuan Liang3, Haitao Niu1, Wei Jiao1, Yonghua Wang1. 1. Department of Urology, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China. 2. Department of Geratology, The 971st Hospital of PLA, Qingdao, Shandong, China. 3. Key Laboratory of Urology and Andrology, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
Abstract
BACKGROUND: In recent years, immune-associated genes (IAGs) have been documented as having critical roles in the occurrence and progression of muscle-invasive bladder cancer (MIBC). Novel immune-related biomarkers and a robust prognostic signature for MIBC patients are still limited. The study is aimed at developing an IAG-based signature to predict the prognosis of MIBC patients. METHODS: In the present study, we identified differentially expressed IAGs in MIBC by using transcriptomics data from The Cancer Genome Atlas (TCGA) database and proteomics data from our samples. We further constructed an IAG-based signature and evaluated its prognostic and predictive value by survival analysis and nomogram. Tumor Immune Estimation Resource (TIMER) was applied to explore the correlation between the IAG-based signature and immune cell infiltration in the microenvironment of MIBC. RESULTS: A total of 22 differentially expressed IAGs were identified, and 2 IAGs (NR2F6 and AHNAK) were used to establish a prognostic signature. Subsequently, survival analysis showed that high-risk scores were significantly correlated with poor overall survival (OS), progression-free survival (PFS), and disease-free survival (DFS) of MIBC patients. A prognostic nomogram was constructed by integrating clinical factors with the IAG-based signature risk score. In addition, the IAG-based signature risk score was positively associated with the infiltration of macrophages and dendritic cells in MIBC. CONCLUSIONS: We constructed and verified a novel IAG-based signature, which could predict the prognosis of MIBC and might reflect the status of the immune microenvironment of MIBC. Further studies in more independent clinical cohorts and further experimental exploration of the prognostic IAG-based signature are still needed.
BACKGROUND: In recent years, immune-associated genes (IAGs) have been documented as having critical roles in the occurrence and progression of muscle-invasive bladder cancer (MIBC). Novel immune-related biomarkers and a robust prognostic signature for MIBC patients are still limited. The study is aimed at developing an IAG-based signature to predict the prognosis of MIBC patients. METHODS: In the present study, we identified differentially expressed IAGs in MIBC by using transcriptomics data from The Cancer Genome Atlas (TCGA) database and proteomics data from our samples. We further constructed an IAG-based signature and evaluated its prognostic and predictive value by survival analysis and nomogram. Tumor Immune Estimation Resource (TIMER) was applied to explore the correlation between the IAG-based signature and immune cell infiltration in the microenvironment of MIBC. RESULTS: A total of 22 differentially expressed IAGs were identified, and 2 IAGs (NR2F6 and AHNAK) were used to establish a prognostic signature. Subsequently, survival analysis showed that high-risk scores were significantly correlated with poor overall survival (OS), progression-free survival (PFS), and disease-free survival (DFS) of MIBC patients. A prognostic nomogram was constructed by integrating clinical factors with the IAG-based signature risk score. In addition, the IAG-based signature risk score was positively associated with the infiltration of macrophages and dendritic cells in MIBC. CONCLUSIONS: We constructed and verified a novel IAG-based signature, which could predict the prognosis of MIBC and might reflect the status of the immune microenvironment of MIBC. Further studies in more independent clinical cohorts and further experimental exploration of the prognostic IAG-based signature are still needed.
Authors: Taiwen Li; Jingyu Fan; Binbin Wang; Nicole Traugh; Qianming Chen; Jun S Liu; Bo Li; X Shirley Liu Journal: Cancer Res Date: 2017-11-01 Impact factor: 12.701
Authors: I H Lee; M Sohn; H J Lim; S Yoon; H Oh; S Shin; J H Shin; S-H Oh; J Kim; D K Lee; D Y Noh; D S Bae; J K Seong; Y S Bae Journal: Oncogene Date: 2014-03-24 Impact factor: 9.867