Shared network pattern of lung squamous carcinoma and adenocarcinoma illuminates therapeutic targets for non-small cell lung cancer - Li, Piaopiao; Kuang, Xuemei; Zhang, Tingting; Ma, Lei (Frontiers in Surgery, 2022)
Background: Non-small cell lung cancer is considered to be one of the malignant tumors with high mortality. However, the prognosis of its advanced patients is still poor. This study aims to analyze the database data using the cross-subtype double network method to identify key genes related between and within non-small cell lung cancer subtypes. Methods: The weighted gene co-expression network analysis (WGCNA) method was used to build modules which were evaluated the preservation degree between subtypes. Genes with high module correlation are screened by pearman method, and then gene ontology (GO) enrichment was performed, the hub genes and key modules are identified, and verify hub genes. The expression differences of central genes in cancer and paracancerous tissues were verified by using gene expression omnibus (GEO) data sets. Results: We obtained the hub gene COL5A2 between the non-small cell lung cancer subtypes, the characteristic module genes AKR1C1, AKR1C2, AKR1C3, CCL19, CCL21, and CCR7 within the subtypes. The expression of COL5A2 in Lung squamous cell carcinoma and lung adenocarcinoma tissues was higher than that in normal tissues (P < 0.001). Lung squamous cell carcinoma hub genes were mainly enriched in regulation of extent of cell growth pathways. Meanwhile, lung adenocarcinoma hub genes were primarily enriched in pathways related to T lymphocytes. Conclusions: In summary, hub genes that may be prognostic markers between and within subtypes using the cross-subtype co-expression method. This study can provide potential biomarkers for the non-small cell lung cancer early diagnosis and offer a reference basis for