Schwann cell reprogramming and lung cancer progression: a meta-analysis of transcriptome data

Abstract

Schwann cells were identified in the tumor surrounding area prior to initiate the invasion process underlying connective tissue. These cells promote cancer invasion through direct contact, while paracrine signaling and matrix remodeling are not sufficient to proceed. Considering the intertwined structure of signaling, regulatory, and metabolic processes within a cell, we employed a genome-scale biomolecular network. Accordingly, a meta-analysis of Schwann cells associated transcriptomic datasets was performed, and the core information on differentially expressed genes (DEGs) was obtained by statistical analyses. Gene set over-representation analyses was performed on core DEGs to identify significantly functional and pathway enrichment analysis between Schwann cells and, lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). DEGs were further integrated with genome-scale human biomolecular networks. miRNAs were proposed by the reconstruction of a transcriptional and post-transcriptional regulatory network. Moreover, microarray-based transcriptome profiling was performed, and the prognostic power of selected dedifferentiated Schwann cell biomolecules was predicted. We observed that pathways associated with Schwann cells dedifferentiation was overexpressed in lung cancer samples. However, genes associated with Schwann cells migration inhibition system were downregulated. Besides, miRNA targeting those pathways were also deregulated. In this study, we report valuable data for further experimental and clinical analysis, because the proposed biomolecules have significant potential as systems biomarkers for screening or for therapeutic purposes in perineural invasion of lung cancer.