Background: Alkylating cellular DNA, sulfur mustard (SM) is a chemical warfare agent that causes severe damage to the skin, eyes, and respiratory tract. Exposure can result in painful burns, chronic lung disease, immune system suppression, and an increased chance of developing cancer. The symptoms of itching, redness, and blistering are frequently followed by long-term genetic and psychological damage. By exploring the interaction between microRNA (miRNA), mRNA, and long non-coding RNA (lncRNA) in these patients, it is possible to identify gene expression patterns that could reduce cancer risk or improve treatment outcomes.
Methods: The purpose of this study is to examine transcriptome data from PBMC samples obtained from sulfur mustard exposed patients (Mild, Moderate, Severe) and healthy Control, separated into six groups (SC, SMo, SMi, MoMi, MoC, and MiC). miRNA, lncRNA, and mRNA interactions were explored using miRNA, lncRNA, and mRNA tools and databases, such as miRTarBase, miRDB, miRNET, miRcode, and DIANA. A tripartite mRNA-miRNA-lncRNA network was modeled with the aid of Cytoscape software, and functional analyses were performed to gain an understanding of molecular pathways using GO and KEGG functional analyses.
Results: By extracting miRNAs shared between lncRNAs and mRNAs, six groups were identified and Cytoscape software was used to visualize the lncRNA-miRNA-mRNA network. Betweenness, closeness, and degree filters identified key genes, with INO80D and lncRNAs MINCR, LINC00662, NEAT1, and DHRS4-AS1, along with miRNAs hsa-miR-1-3p, hsa-miR-124-3p, and hsa-let-7b-5p as the main players in all groups.
Conclusion: The interaction between key genes involved in chemical injuries and their association with genes implicated in lung cancer is highlighted in this study. By targeting these genes and their proteins, we can improve treatment strategies for sulfur mustard exposed patients and potentially reduce lung cancer risk.
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