胰腺癌与高死亡率相关，是最具侵袭性的恶性肿瘤之一，但研究尚未完全评估其分子亚型、预后和对不同亚型免疫治疗的应答。本研究的目的是通过应用单细胞测序数据、块状RNA测序数据和从GEO和TCGA数据库检索的数据，探索胰腺癌患者的分子亚型和与预后相关的关键基因，并研究其临床表型、预后和对免疫治疗的应答。本研究采用单细胞测序数据和生物信息学方法进行研究。从GEO和TCGA数据库检索胰腺癌数据，利用六个cGAS-STING相关通路确定胰腺癌的分子亚型，并评估与胰腺癌相关的临床表型、突变、免疫特征和通路。胰腺癌分为三个分子亚型，生存分析显示Cluster3（C3）患者的预后最差，而Cluster1（C1）患者的预后最好。三个分子亚型的临床表型和基因突变在统计学上有显著差异。免疫治疗应答分析显示在三个亚型中大多数免疫检查点基因表达差异显著。Cluster1（C1）观察到较低的免疫逃逸风险，表明对免疫治疗药物更敏感，而此亚型的受试者更可能从免疫治疗中获益。胰腺癌相关通路在三个亚型中差异丰富。选择了SFRP1、GIPR、EMP1、COL17A和CXCL11这五个基因构建一个预后标志。通过单细胞测序数据根据临床表型、基因突变、免疫特征和不同富集通路的差异将胰腺癌分类为三个分子亚型。识别了五个与预后相关的基因，用于预测胰腺癌患者的生存率，并评估不同亚型中免疫治疗的疗效。 © 2023 Wang等人。

Pancreatic cancer is associated with high mortality and is one of the most aggressive of malignancies, but studies have not fully evaluated its molecular subtypes, prognosis and response to immunotherapy of different subtypes. The purpose of this study was to explore the molecular subtypes and the key genes associated with the prognosis of pancreas cancer patients and study the clinical phenotype, prognosis and response to immunotherapy using single-cell seq data and bulk RNA seq data, and data retrieved from GEO and TCGA databases.Single-cell seq data and bioinformatics methods were used in this study. Pancreatic cancer data were retrieved from GEO and TCGA databases, the molecular subtypes of pancreatic cancer were determined using the six cGAS-STING related pathways, and the clinical phenotype, mutation, immunological characteristics and pathways related to pancreatic cancer were evaluated.Pancreatic cancer was classified into 3 molecular subtypes, and survival analysis revealed that patients in Cluster3 (C3) had the worst prognosis, whereas Cluster1 (C1) had the best prognosis. The clinical phenotype and gene mutation were statistically different among the three molecular subtypes. Analysis of immunotherapy response revealed that most immune checkpoint genes were differentially expressed in the three subtypes. A lower risk of immune escape was observed in Cluster1 (C1), indicating higher sensitivity to immunotherapeutic drugs and subjects in this Cluster are more likely to benefit from immunotherapy. The pathways related to pancreatic cancer were differentially enriched among the three subtypes. Five genes, namely SFRP1, GIPR, EMP1, COL17A and CXCL11 were selected to construct a prognostic signature.Single-cell seq data were to classify pancreatic cancer into three molecular subtypes based on differences in clinical phenotype, mutation, immune characteristics and differentially enriched pathways. Five prognosis-related genes were identified for prediction of survival of pancreatic cancer patients and to evaluate the efficacy of immunotherapy in various subtypes.© 2023 Wang et al.