Identification and validation of gene module associated with lung cancer through coexpression network analysis

Gene
Rong LiuHong-Hao Zhou

Abstract

Lung cancer, a tumor with heterogeneous biology, is influenced by a complex network of gene interactions. Therefore, elucidating the relationships between genes and lung cancer is critical to attain further knowledge on tumor biology. In this study, we performed weighted gene coexpression network analysis to investigate the roles of gene networks in lung cancer regulation. Gene coexpression relationships were explored in 58 samples with tumorous and matched non-tumorous lungs, and six gene modules were identified on the basis of gene coexpression patterns. The overall expression of one module was significantly higher in the normal group than in the lung cancer group. This finding was validated across six datasets (all p values <0.01). The particular module was highly enriched for genes belonging to the biological Gene Ontology category "response to wounding" (adjusted p value = 4.28 × 10(-10)). A lung cancer-specific hub network (LCHN) consisting of 15 genes was also derived from this module. A support vector machine based on classification model robustly separated lung cancer from adjacent normal tissues in the validation datasets (accuracy ranged from 91.7% to 98.5%) by using the LCHN gene signatures as predictors. Eight gene...Continue Reading

References

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Citations

Sep 15, 2016·Cancer Informatics·Wenying YanGuang Hu
Aug 5, 2017·Molecular BioSystems·Cynthia Martins Villar CoutoLuciano da Fontoura Costa
Dec 31, 2016·Oncotarget·Wangxiong HuShu Zheng
Sep 20, 2017·CPT: Pharmacometrics & Systems Pharmacology·Bing LiYongyan Wang
Feb 17, 2017·International Journal of Molecular Medicine·Jia-Qi PanWei Wang
Feb 1, 2019·Scientific Reports·Bruna Victorasso Jardim-PerassiDebora Aparecida Pires de Campos Zuccari

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