Construction of a novel prognostic model for pancreatic adenocarcinoma to predict prognosis and guide immunotherapy

Pancreatic adenocarcinoma (PAAD) remains one of the most lethal malignant tumors, with poor prognosis and limited treatment options. This study aims to explore the role of butyrate metabolism-related genes (BMRGs) in PAAD to improve diagnostic and prognostic strategies. The study analyzed PAAD based on transcriptomic and clinical data obtained from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Through the construction of protein-protein interaction (PPI) networks and LASSO Cox regression, characteristic genes were selected to develop a risk model related to butyrate metabolism (BMRS). This model effectively divided patients into high BMRS and low BMRS groups. Kaplan-Meier (K-M) analysis showed a significant difference in overall survival rates between the two groups. ROC curves and nomograms including clinical features and BMRS demonstrated strong predictive capabilities. Functional enrichment analysis (including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG)) revealed key pathways, such as pancreatic secretion and immune-related processes. Additionally, the two BMRS groups showed different immune cell infiltration patterns, and several potential therapeutic drugs were determined through drug sensitivity prediction. Co-expression network analysis further revealed 20 genes related to biological processes such as keratinization and nucleosome assembly. In summary, this study highlights the clinical significance of BMRGs in PAAD and provides new insights into risk stratification and potential targets for personalized treatment.

胰腺腺癌（PAAD）仍是致死性最高的恶性肿瘤之一，患者预后不佳且治疗手段有限。本研究旨在探究丁酸代谢相关基因（BMRGs）在PAAD中的作用，以期优化胰腺腺癌的诊断与预后策略。本研究基于从基因表达综合数据库（GEO）及癌症基因组图谱（TCGA）获取的转录组与临床数据，对PAAD展开分析。本研究通过构建蛋白质相互作用（PPI）网络并结合LASSO Cox回归分析，筛选特征基因以构建丁酸代谢相关风险模型（BMRS）。该模型可有效将患者划分为高BMRS组与低BMRS组。Kaplan-Meier（K-M）分析结果显示，两组患者的总生存率存在显著差异。纳入临床特征与BMRS的ROC曲线及列线图均展现出优异的预测性能。功能富集分析（涵盖基因本体（GO）与京都基因与基因组百科全书（KEGG））揭示了胰腺分泌、免疫相关通路等关键通路。此外，两组BMRS患者的免疫细胞浸润模式存在差异，本研究通过药物敏感性预测筛选出数种潜在治疗药物。共表达网络分析进一步筛选出20个与角化、核小体组装等生物学过程相关的基因。综上，本研究阐明了BMRGs在PAAD中的临床意义，为胰腺腺癌的风险分层及个性化治疗潜在靶点提供了全新思路。