PeerJ. 2026 Jan 15;14:e20617. doi: 10.7717/peerj.20617. eCollection 2026.
ABSTRACT
BACKGROUND: To investigate the molecular genetic features of multiple primary lung cancer (MPLC) to provide a basis and new methods for its identification, diagnosis, and treatment.
METHODS: Transcriptome sequencing (RNA-seq) was performed on 16 tissue samples from eight patients with synchronous multiple primary lung adenocarcinoma (sMP-LUAD) and eight tissue samples from eight patients with single primary lung adenocarcinoma (SP-LUAD). Differentially expressed genes selected by bioinformatic methods were validated in 24 sets of sMP-LUAD and SP-LUAD samples using quantitative reverse transcription polymerase chain reaction (qRT-PCR). Based on The Cancer Genome Atlas (TCGA) database, the differentially expressed genes responsible for the biological behavior of lung adenocarcinoma and their clinical significance were analyzed.
RESULTS: Overall, 194 differentially expressed genes were identified (P < 0.05), including 22 up-regulated and 172 down-regulated genes. Two up-regulated (DUOX1 and CACNA2D2) and three down-regulated (GPX8, COL1A2, and COL1A1) genes were selected for validation by qRT-PCR analysis. The qRT-PCR results showed that the expression of DUOX1 mRNA in the sMP-LUAD group was significantly higher (P < 0.05) than that in the SP-LUAD group; mRNA CACNA2D2, GPX8, COL1A2, and COL1A1 expression in the sMP-LUAD group was not statistically different from that in the SP-LUAD group (P > 0.05). Gene ontology (GO) enrichment analysis showed that DUOX1 mRNA was mainly enriched in the entries of positive regulation of wound healing and oxidation-reduction processes. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that DUOX1 can promote reactive oxygen species (ROS) production and be related to thyroid hormone production. Furthermore, based on the TCGA database, we analyzed the biological behavior and clinical significance of DUOX1 in lung adenocarcinoma using bioinformatics technology. DUOX1 mRNA expression was decreased in all stages and pathological subtypes of lung adenocarcinoma (P < 0.05). Immune infiltration analysis showed that DUOX1 with mast cells and eosinophils was positively correlated (P < 0.05), and Th2 cells were negatively correlated (P < 0.05). Logistic regression analysis showed that the expression of DUOX1 mRNA was significantly correlated with the patient’s age, lymph node metastasis, and pathologic stage (P < 0.05). Kaplan-Meier survival plots showed that low DUOX1 expression was not significantly correlated with OS, DSS, and PFI (P > 0.05). Univariate and multivariate COX regression analysis revealed that DUOX1 mRNA could not be used as an independent factor for predicting prognosis (P > 0.05). Therefore, we developed a predictive nomogram model combining clinicopathological variables and DUOX1 mRNA to predict the survival of patients with lung adenocarcinoma.
PMID:41556052 | PMC:PMC12812280 | DOI:10.7717/peerj.20617
