江汉大学学报（自然科学版）

目的通过生物信息学方法探讨肿瘤相关黏蛋白(mucins,MUC)基因MUC1、MUC4、MUC5B和MUC13联合表达及其对肿瘤发生的作用,为胰腺癌(pancreatic adenocarcinoma,PAAD)早期诊断和免疫治疗提供新靶点。方法 基于Timer2.0、TCGA+GTEx数据库进行泛癌分析筛选与PAAD相关高表达黏蛋白;利用Proteomic Data Commons数据库验证蛋白表达差异;通过生存分析及临床分期关联评估预后价值;采用GSEA进行wikipathways通路富集;构建Nomogram模型量化患病风险;分析mucins的肿瘤突变负荷(TMB);结合HPA数据库免疫组化验证蛋白表达。结果MUC1、MUC4、MUC5B、MUC13在PAAD组织中的mRNA和蛋白表达均显著高于癌旁组织(P<0.05);mucins低表达组总生存期(OS)显著延长(P<0.05),其表达量与临床分期相关:MUC1中StageⅣ最高,MUC4、MUC5B和MUC13中StageⅡ最高;GSEA富集显示MUC1、MUC4、MUC5B高表达组显著激活胰腺肿瘤相关信号通路,MUC13高表达组显著激活非特性免疫相关信号通路;Nomogram模型提示mucins联合评分90分时PAAD患病风险高达80%;mucins基因突变均与PAAD呈显著正相关。结论MUC1、MUC4、MUC5B和MUC13在PAAD中协同高表达,可能通过激活肿瘤通路、促进基因突变参与肿瘤进展与免疫逃逸,可作为PAAD早期诊断标志物和免疫联合治疗潜在靶点。

Objective To investigate,by bioinformatics methods,the co-expression of the tumor-associated mucin(MUC)genes MUC1,MUC4,MUC5B,and MUC13 and their roles in tumorigenesis,so as to provide new targets for the early diagnosis and immunotherapy of pancreatic adenocarcinoma(PAAD). Methods A pan-cancer analysis based on Timer2.0 and TCGA + GTEx databases was performed to screen mucins highly expressed in PAAD. Protein expression differences were validated using the Proteomic Data Commons(PDC) database. Prognostic value was assessed via survival analysis and clinical stage association analysis. Wikipathways enrichment analysis was conducted using Gene Set Enrichment Analysis(GSEA). A nomogram model was constructed to quantify disease risk. Tumor mutation burden(TMB)of the mucins was analyzed. Protein expression was further validated by immunohistochemistry using the Human Protein Atlas(HPA)database. Results mRNA and protein expression levels of MUC1,MUC4,MUC5B,and MUC13 were significantly higher in PAAD tissues compared to adjacent normal tissues(P < 0. 05). Overall survival(OS) was significantly prolonged in the low-mucinexpression group(P < 0. 05). Mucin expression correlated with clinical stage:MUC1 was highest in stage IV,while MUC4,MUC5B,and MUC13 were highest in stage II. GSEA revealed that the high-expression of MUC1,MUC4,and MUC5B significantly activated pancreatic tumor-associated signaling pathways, while the high-expression group of MUC13 significantly activated non-specific immune-related signaling pathways. The nomogram model indicated that when the combined mucin score reached 90 points,the risk of PAAD was as high as 80%. Mutations in the mucin genes were all significantly positively correlated with PAAD. Conclusion MUC1, MUC4, MUC5B, and MUC13 are synergistically overexpressed in PAAD and may participate in tumor progression and immune evasion by activating tumor-related pathways and promoting gene mutations.They may serve as biomarkers for the early diagnosis of PAAD and as potential targets for combined immunotherapy.