Revealing the Potential Associations of Mutation-Related Genes with Lymph Node Metastasis in Gallbladder Cancer...

Background/Objectives: Gallbladder cancer (GBC) is an aggressive biliary tract malignancy with poor prognosis. Lymph node metastasis is a major determinant of adverse outcome in patients with GBC. Gene mutations play an essential role in tumorigenesis; however, it remains uncertain whether genetic mutations play a substantial role in lymph node metastasis in GBC. Methods: In this study, transcriptome and whole-exome sequencing (WES) were used to analyze gene mutations and expression in GBC tissues, focusing on lymph node metastasis. Bioinformatics tools identified differentially expressed genes (DEGs) and significantly mutated genes (SMGs), followed by pathway enrichment and survival analyses. Results: In total, 669 DEGs were identified between metastatic and non-metastatic GBC tissues. Through protein-protein interaction (PPI) network analysis of these DEGs, GPT and NR1I2 were identified as candidate genes associated with metabolic reprogramming in lymph node metastasis. Prognostic analysis revealed 22 DEGs associated with patient survival, and significant differences in overall survival, clinicopathological features (e.g., N-stage and positive lymph node count) were observed between cluster 1 and cluster 2. Mutation analysis identified 55 SMGs, primarily related to immune and inflammatory responses. By integrating DEGs and SMGs, PLCL2 was identified as a candidate gene potentially associated with both lymph node metastasis and prognosis. GSEA enrichment analysis suggested that PLCL2 was potentially linked to immunity, inflammation, and cellular processes, which may imply its possible involvement in GBC metastasis pending experimental validation. Conclusions: Based on integrative transcriptomic and exomic analyses, we identified PLCL2 as a candidate gene potentially associated with lymph node metastasis in GBC. These hypothesis-generating findings provide a preliminary basis for future mechanistic validation and biomarker exploration.