Abstract：
This study attempted to build a prognostic riskscore model for pancreatic cancer (PC) patients based on vesicle-mediated transport protein-related genes (VMTGs). We initially conducted differential expression analysis and Cox regression analysis, followed by the construction of a riskscore model to classify PC patients into high-risk (HR) and low-risk (LR) groups. The GEO GSE62452 dataset further validated the model. Kaplan-Meier survival analysis was employed to analyze the survival rate of the HR group and LR group. Cox analysis confirmed the independent prognostic ability of the riskscore model. Additionally, we evaluated immune status in both HR and LR groups, utilizing data from the GDSC database to predict drug response among PC patients. We identified six PC-specific genes from 724 VMTGs. Survival analysis revealed that the survival rate of the HR group was lower than that of the LR group (P<0.05). Cox analysis confirmed that the prognostic riskscore model could independently predict the survival status of PC patients (P<0.001). Immunological analysis revealed that the ESTIMATE score, immune score, and stroma score of the HR group were considerably lower than those of the LR group, and the tumor purity score of the HR group was higher. The IC50 values of Gemcitabine, Irinotecan, Oxaliplatin, and Paclitaxel in the LR group were considerably lower than those in the HR group (P<0.001). In summary, the VMTG-based prognostic riskscore model could stratify PC risk and effectively predict the survival of PC patients.
摘要：
本研究试图建立基于囊泡介导的转运蛋白相关基因（VMTGs）的胰腺癌（PC）患者的预后风险评分模型。我们最初进行了差异表达分析和Cox回归分析，然后构建风险评分模型,将PC患者分为高危组(HR)和低危组(LR).GEOGSE62452数据集进一步验证了该模型。采用Kaplan-Meier生存分析对HR组和LR组的生存率进行分析。Cox分析证实了风险评分模型的独立预后能力。此外,我们评估了HR和LR组的免疫状态，利用GDSC数据库中的数据预测PC患者的药物反应。我们从724个VMTG中鉴定了6个PC特异性基因。生存分析显示HR组生存率低于LR组(P<0.05)。Cox分析证实，预后风险评分模型可以独立预测PC患者的生存状况（P<0.001）。免疫学分析显示，估计评分，免疫评分,HR组的间质评分明显低于LR组，HR组肿瘤纯度评分较高。吉西他滨的IC50值，伊立替康,奥沙利铂,LR组的紫杉醇水平明显低于HR组（P<0.001）。总之,基于VMTG的预后风险评分模型可以对PC风险进行分层，并有效预测PC患者的生存率。
