Abstract
Previous studies have indicated that the airway epithelia of lung cancer-associated injury can extend to the nose and it was associated with abnormal gene expression. The aim of this study was to find the possible lung cancer-related genes from the nasal epithelium as bio-markers for lung cancer detection. WGCNA was performed to calculate the module-trait correlations of lung cancer based on the public microarray dataset, and their data were processed by statistics of RMA and t-test. Four specific modules associated with clinical features of lung cancer were constructed, including blue, brown, yellow, and light blue. Of which blue or brown module showed strong connection to genetic connectivity. From the brown module, it was found that HCK, NCF1, TLR8, EMR3, CSF2RB, and DYSF are the hub genes, and from the blue module, it was found that SPEF2, ANKFN1, HYDIN, DNAH5, C12orf55, and CCDC113 are the pivotal genes corresponding to the grade. These genes can be taken as the bio-markers to develop a noninvasive method of diagnosing early lung cancer.