Similarity and difference of pathogenesis among lung cancer subtypes suggested by expression profile data

Lung cancer is difficult to diagnose, has a high mortality rate and a high recurrence rate. By grouping and analyzing the gene expression in lung cancer samples, we selected the differentially expressed genes (DEGs) in total lung cancers or each subgroup, and then searched for the similarities and differences among these. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were performed, in addition to predictable cell proliferation or immune-related pathways, ?hemostasis?, ?coagulation? and ?viral myocarditis? were also enriched in common DEGs, while specific functions or pathways were enriched in different subgroups. This may have implications for the treatment of total lung cancer or different subtypes. Through bioinformatics analysis, hub genes were obtained from total lung cancer and each subgroup respectively. Survival analysis of common hub genes led us to find that ZWINT, A2M, POLR2H and KIF11 are associated with unclassified lung cancer survival. For the construction of miRNA regulatory network, miR-16-5p was related to all of these four genes, and its expression is significantly different between lung cancers and normal samples. Combined with the hub genes of each subtype, it may have the ability of early screening and typing.

Automated summary

Different subtypes of lung cancer show differential gene expression, which can help in treatment. Certain hub genes are associated with survival in unclassified lung cancer, and combining them with miRNA regulatory network can aid in early screening and typing.