Study of the co-expression gene modules of non-small cell lung cancer metastases

Abstract

Background: Metastasis regularly is a marker of the disease development of cancers. Some metastatic sites significantly showed a more serious clinical outcome in non-small cell lung cancer (NSCLC). Whether they are caused by tissue-specific (TS) or non-tissue-specific (NTS) mechanisms is still unclear. Methods: Weighted Correlation Network Analysis (WGCNA) was used to identify the gene modules among the metastases of NSCLC. The clinical significance of those gene modules was evaluated with the Cox hazard proportional model with another independent dataset. Functions of each gene module were analyzed with gene ontology. Typical genes were further studied. Results: There were two TS gene modules and two NTS gene modules identified. One TS gene module (green module) and one NTS gene module (purple module) significantly correlated with survival. This NTS gene module (purple module) was significantly enriched in the epithelial-to-mesenchymal transition (EMT) process. Higher expression of the typical genes ( CA14 , SOX10 , TWIST1, and ALX1 ) from EMT process was significantly associated with a worse survival. Conclusion: The lethality of NSCLC metastases was caused by TS gene modules and NTS gene modules, among which the EMT-related gene module was critical for a worse clinical outcome.

Interleukin‑1 receptor‑associated kinase 4 as a potential biomarker: Overexpression predicts poor prognosis in patients with glioma

“…GSEA is a widely used bioinformatics analysis tool for gene enrichment analysis of gene function annotation ( 16 , 17 ). Data from high-throughput sequencing contains the expression of a large number of genes, which can be used to investigate the relationships between genes ( 18 , 19 ). GSEA formulates a special algorithm based on the existing research status of genes and cell signalling pathways, which can be used to explore the cell signalling pathways that a single gene may participate in the regulation ( 16 , 17 ).…”