Xiaofeng Wu1, Jing Zhu2, Wei Liu1, Meng Jin1, Mengqing Xiong1, Ke Hu1. 1. Department of Respiratory and Critical Care Medicine, Renmin Hospital of Wuhan University, Wuhan, Hubei Province, People's Republic of China. 2. Department of Respiratory and Critical Care Medicine, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, People's Republic of China.
Abstract
BACKGROUND: The hypoxia and immune status of the lung adenocarcinoma (LUAD) microenvironment appear to have combined impacts on prognosis. Therefore, deriving a prognostic signature by integrating hypoxia- and immune infiltrating cell-related genes (H&IICRGs) may add value over prognostic indices derived from genes driving either process alone. METHODS: Differentially expressed H&IICRGs (DE-H&IICRGs) were identified in The Cancer Genome Atlas transcriptomic data using limma, CIBERSORT, weighted gene co-expression network analysis, and intersection analysis. A stepwise Cox regression model was constructed to identify prognostic genes and to produce a gene signature based on DE-H&IICRGs. The potential biological functions associated with the gene signature were explored using functional enrichment analysis. The prognostic signature was externally validated in a separate cohort from the Gene Expression Omnibus database. RESULTS: Five prognostic genes associated with overall survival in LUAD were used in the DE-H&IICRG-based prognostic signature. Patients in the high-risk group had an inferior prognosis, which was validated in an independent external cohort, and had lower expression of most immune checkpoint genes. In multivariate analysis, only risk score and T stage were independent prognostic factors. Differentially expressed genes (DEGs) associated with the risk score were enriched for pathways related to cell cycle, hypoxia regulation, and immune response. TIDE analyses showed that low-risk LUAD patients might also respond better to immunotherapy. CONCLUSION: This study establishes and validates a prognostic profile for LUAD patients that combines hypoxia and immune infiltrating cell-related genes. This signature may have clinical application both for prognostication and guiding individualized immunotherapy.
BACKGROUND: The hypoxia and immune status of the lung adenocarcinoma (LUAD) microenvironment appear to have combined impacts on prognosis. Therefore, deriving a prognostic signature by integrating hypoxia- and immune infiltrating cell-related genes (H&IICRGs) may add value over prognostic indices derived from genes driving either process alone. METHODS: Differentially expressed H&IICRGs (DE-H&IICRGs) were identified in The Cancer Genome Atlas transcriptomic data using limma, CIBERSORT, weighted gene co-expression network analysis, and intersection analysis. A stepwise Cox regression model was constructed to identify prognostic genes and to produce a gene signature based on DE-H&IICRGs. The potential biological functions associated with the gene signature were explored using functional enrichment analysis. The prognostic signature was externally validated in a separate cohort from the Gene Expression Omnibus database. RESULTS: Five prognostic genes associated with overall survival in LUAD were used in the DE-H&IICRG-based prognostic signature. Patients in the high-risk group had an inferior prognosis, which was validated in an independent external cohort, and had lower expression of most immune checkpoint genes. In multivariate analysis, only risk score and T stage were independent prognostic factors. Differentially expressed genes (DEGs) associated with the risk score were enriched for pathways related to cell cycle, hypoxia regulation, and immune response. TIDE analyses showed that low-risk LUAD patients might also respond better to immunotherapy. CONCLUSION: This study establishes and validates a prognostic profile for LUAD patients that combines hypoxia and immune infiltrating cell-related genes. This signature may have clinical application both for prognostication and guiding individualized immunotherapy.
Authors: Sangbin Lim; Hao Liu; Luciana Madeira da Silva; Ritu Arora; Zixing Liu; Joshua B Phillips; David C Schmitt; Tung Vu; Steven McClellan; Yifeng Lin; Wensheng Lin; Gary A Piazza; Oystein Fodstad; Ming Tan Journal: Cancer Res Date: 2016-04-05 Impact factor: 12.701