Investigating the biomarker potential and molecular targets of TIGD1 in lung cancer using bioinformatics

Lung cancer, a predominant contributor to cancer mortality, is characterized by diverse etiological factors, including tobacco smoking and genetic susceptibilities. Despite advancements, particularly in nonsmall-cell lung cancer (NSCLC), therapeutic options for lung squamous cell carcinoma (LUSC) are limited. Transposable elements (TEs) and their regulatory proteins, such as tigger transposable element derived (TIGD) family proteins, have been implicated in cancer development. TIGD1, upregulated in various cancers, including LUSC, lacks a defined function. The aim of our study was to elucidate the biological functions, associated pathways, and interacting proteins of TIGD1.

The GSE229260 microarray dataset was investigated using the GEO2R tool to identify the differentially expressed genes (DEGs) in TIGD1 silenced in A549 lung cancer cells in contrast to controls. Enrichment analyses and protein-protein interaction (PPI) network construction were performed to uncover key pathways using KEGG and STRING analyses. Hub genes were determined through the intersection of DEGs with lung cancer-related genes via Cytoscape software and the cytoHubba plug-in, and their functions were analyzed. Immune and stromal scores of hub genes were also evaluated using the ESTIMATE algorithm.

Analyzing microarray data from TIGD1-silenced A549 NSCLC cells, a total of 13 upregulated DEGs and 1 downregulated DEGs were identified. The TIGD1-associated DEGs revealed significant involvement in crucial molecular pathways, including the PI3K/AKT, FOXO, and p53 signaling pathways. The hub genes AKT1, BRAF, SRC, GAPDH, CCND1, CDKN2A, CTNNB1, KRAS, MYC, and TP53 emerged as central regulators of cell proliferation, apoptosis, and protein metabolism. The hub genes exhibited negative correlations with immune and stromal components in the tumor microenvironment, suggesting their potential as biomarkers for lung cancer therapy.

This study elucidates the potential functions of TIGD1 in lung cancer and identifies promising biomarker candidates associated with TIGD1 gene expression, presenting potential therapeutic targets for lung cancer therapies.