Lymph node metastasis is the most important prognostic factor in patients with lung squamous cell carcinoma. The current findings show that lymph node metastatic tumor cells can arise by programming metastasis in primary tumor cells. Thereby, the genetic alterations responsible for the metastasis could be detected in the primary tumors. This bioinformatic study aimed to determine novel potential prognostic biomarkers shared between primary lung squamous cell tumors (without lymph node metastasis) and lymphatic metastasis, using the Cancer Genome Atlas database. Differentially expressed genes were screened by limma statistical package in R environment. Gene ontology and biological pathways analyses were performed using Enrichr for up-regulated and down-regulated genes. Also, we selected lymph node metastasis related genes among DEGs using correlation analysis between DEGs and suitable references genes for metastasis. Receiver operating characteristic curves was applied using pROC and R package ggplot2 to evaluate diagnostic value of differentially expressed genes. In addition, survival and drug resistance analyses were performed for differentially expressed genes. The miRNA-mRNA interaction networks were predicted by miRwalk and TargetScan databases and expression levels analysis of the miRNAs which were mainly targeting mRNAs was performed using UALCAN database. Protein–protein interaction network analysis and hub genes identification were performed using FunRich and Cytoscape plugin cytoHubba. In this study, a total of 397 genes were differentially expressed not only with a significant difference between N + vs. normal and N0 vs. normal but also with significant difference between N + vs. N0. Identified GO terms and biological pathways were consistent with DEGs role in the lung squamous cell carcinoma and lymph node metastasis. A significant correlation between 56 genes out of 397 differentially expressed genes with reference genes prompted them being considered for identifying lymph node metastasis of lung squamous cell carcinoma. In addition, SLC46A2, ZNF367, AC107214.1 and NCBP1 genes were identified as survival-related genes of patients with lung squamous cell carcinoma. Moreover, NEDD9, MRPL21, SNRPF, and SCLT1 genes were identified to be involved in lung squamous cell carcinoma drug sensitivity/resistance. We have identified several numbers of miRNAs and their related target genes which could emerge as potential diagnostic biomarkers. Finally, CDK1, PLK1, PCNA, ZWINT and NDC80 identified as hub genes for underlying molecular mechanisms of lung squamous cell carcinoma and lymphatic metastasis. Our study highlights new target genes according to their relation to lymph node metastasis, whose expressions in the primary lung squamous cell carcinoma are able to accurately assess the presence of lymphatic metastasis.
