期刊
CANCER MANAGEMENT AND RESEARCH
卷 10, 期 -, 页码 2683-2693出版社
DOVE MEDICAL PRESS LTD
DOI: 10.2147/CMAR.S163918
关键词
weighted gene co-expression network analysis; WGCNA; lung adenocarcinoma; LAC; co-expressing; prognostic signature
类别
资金
- National Natural Science Foundation of China [81472702, 81501977, 81672294]
- Natural Science Foundation of Jiangsu Province [SBK016030028]
- Innovation Capability Development Project of Jiangsu Province [BM2015004]
Background: A substantial increase in the number of non-smoking lung adenocarcinoma (LAC) patients has been drawing extensive attention in the past decade. However, effective biomarkers, which could guide the precise treatment, are still limited for identifying high-risk patients. Here, we provide a network-based signature to predict the survival of non-smoking LAC. Materials and methods: Gene expression profiles were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus. Significant gene co-expression networks and hub genes were identified by Weighted Gene Co-expression Network Analysis. Potential mechanisms and pathways of co-expression networks were analyzed by Gene Ontology. The predictive signature was constructed by penalized Cox regression analysis and tested in two independent datasets. Results: Two distinct co-expression modules were significantly correlated with the non-smoking status across 4 Gene Expression Omnibus datasets. Gene Ontology revealed that nuclear division and cell cycle pathways were main mechanisms of the blue module and that genes in the turquoise module were involved in lymphocyte activation and cell adhesion pathways. Seventeen genes were selected from hub genes at an optimal lambda value and built the prognostic signature. The prognostic signature distinguished the survival of non-smoking LAC (training: hazard ratio [HR]=3.696, 95% CI: 2.025-6.748, P<0.001; testing: HR=2.9, 95% CI: 1.322-6.789, P=0.006; HR=2.78, 95% CI: 1.658-6.654, P=0.022) and had moderate predictive abilities in the training and validation datasets. Conclusion: The prognostic signature is a promising predictor of non-smoking LAC patients, which might benefit clinical practice and precision therapeutic management.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据