Department of General Surgery, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, 100023, People's Republic of China.
Key Laboratory of Research in Pancreatic Tumor, Chinese Academy of Medical Sciences, Beijing, 100023, People's Republic of China.
J Transl Med. 2024 Apr 29;22(1):393. doi: 10.1186/s12967-024-05158-y.
Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy with high probability of recurrence and distant metastasis. Liver metastasis is the predominant metastatic mode developed in most pancreatic cancer cases, which seriously affects the overall survival rate of patients. Abnormally activated endoplasmic reticulum stress and lipid metabolism reprogramming are closely related to tumor growth and metastasis. This study aims to construct a prognostic model based on endoplasmic reticulum stress and lipid metabolism for pancreatic cancer, and further explore its correlation with tumor immunity and the possibility of immunotherapy.
Transcriptomic and clinical data are acquired from TCGA, ICGC, and GEO databases. Potential prognostic genes were screened by consistent clustering and WGCNA methods, and the whole cohort was randomly divided into training and testing groups. The prognostic model was constructed by machine learning method in the training cohort and verified in the test, TCGA and ICGC cohorts. The clinical application of this model and its relationship with tumor immunity were analyzed, and the relationship between endoplasmic reticulum stress and intercellular communication was further explored.
A total of 92 characteristic genes related to endoplasmic reticulum stress, lipid metabolism and liver metastasis were identified in pancreatic cancer. We established and validated a prognostic model for pancreatic cancer with 7 signatures, including ADH1C, APOE, RAP1GAP, NPC1L1, P4HB, SOD2, and TNFSF10. This model is considered to be an independent prognosticator and is a more accurate predictor of overall survival than age, gender, and stage. TIDE score was increased in high-risk group, while the infiltration levels of CD8 T cells and M1 macrophages were decreased. The number and intensity of intercellular communication were increased in the high ER stress group.
We constructed and validated a novel prognostic model for pancreatic cancer, which can also be used as an instrumental variable to predict the prognosis and immune microenvironment. In addition, this study revealed the effect of ER stress on cell-cell communication in the tumor microenvironment.
胰腺导管腺癌（PDAC）是一种致命的恶性肿瘤，复发和远处转移的可能性很高。肝转移是大多数胰腺癌病例中主要的转移方式，严重影响患者的总体生存率。内质网应激和脂质代谢重编程的异常激活与肿瘤生长和转移密切相关。本研究旨在构建基于内质网应激和脂质代谢的胰腺癌预后模型，并进一步探讨其与肿瘤免疫的相关性和免疫治疗的可能性。
从 TCGA、ICGC 和 GEO 数据库中获取转录组学和临床数据。通过一致聚类和 WGCNA 方法筛选潜在的预后基因，将全队列随机分为训练组和测试组。在训练队列中使用机器学习方法构建预后模型，并在测试、TCGA 和 ICGC 队列中进行验证。分析该模型的临床应用及其与肿瘤免疫的关系，并进一步探讨内质网应激与细胞间通讯的关系。
在胰腺癌中确定了 92 个与内质网应激、脂质代谢和肝转移相关的特征基因。我们建立并验证了一个包含 7 个特征基因的胰腺癌预后模型，包括 ADH1C、APOE、RAP1GAP、NPC1L1、P4HB、SOD2 和 TNFSF10。该模型被认为是一个独立的预后指标，比年龄、性别和分期更能准确预测总生存期。在高危组中 TIDE 评分增加，而 CD8 T 细胞和 M1 巨噬细胞的浸润水平降低。内质网应激水平高的组细胞间通讯的数量和强度增加。
我们构建并验证了一个新的胰腺癌预后模型，该模型还可以作为工具变量来预测预后和免疫微环境。此外，本研究揭示了内质网应激对肿瘤微环境中细胞间通讯的影响。
