Hong Xiafei, Zhang Xingwu, Jiang Rui, Qiao Sitan, Wang Wenze, Zhang Hao, Wang Jingqiao, Yin Bohui, Li Fuqiang, Ling Chao, Wang Xianze, Zhao Yupei, Wu Kui, Wu Wenming
Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China; State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China.
Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China; School of Medicine, Tsinghua University, Beijing, 100084, China.
Cancer Lett. 2024 Jul 22:217131. doi: 10.1016/j.canlet.2024.217131.
Pancreatic neuroendocrine tumors (PanNETs), the second most common type of primary pancreatic tumors, display notable heterogeneity in invasiveness. Current knowledge regarding genomic alterations, including DAXX/ATRX, MEN1 mutations, and copy number variations (CNVs), provides some insights into tumor invasiveness. However, the underlying reasons for the significant variation in invasiveness between insulinoma and other types of PanNETs remain unclear. To construct a comprehensive model for the stratification of prognosis, we employed analysis of both the well-established Rip1-Tag 2 (RT2) mouse model of PanNETs and human PanNETs with various functional types. Firstly, by applying single-cell and bulk RNA sequencing in PanNETs from different ages and strains of RT2 mice and human PanNETs, we introduced a 2-dimensional (2D) classification system. Based on the 2D classification system, human PanNETs were mainly classified as benign insulinomas or non-insulinomas subclusters. Non-insulinomas subtypes mainly included gastrinomas, glucagonomas, VIPomas, and NF-PanNETs, which all exhibited potential invasiveness. In addition, we discovered an enrichment of specific CNV patterns and mutations in corresponding human PanNET subclusters. Then we denoted somatic DAXX/ATRX as the 'second hit' and confounding factors for invasiveness. Finally, by combining the 2D system, DAXX/ATRX mutation status, and tumor diameter, a group of indolent PanNETs with minimal recurrence risk was identified. In conclusion, our current work constructed a comprehensive model to elucidate the heterogeneity of invasiveness in PanNETs and improve prognostic stratification.
胰腺神经内分泌肿瘤（PanNETs）是第二常见的原发性胰腺肿瘤类型，在侵袭性方面表现出显著的异质性。目前关于基因组改变的知识，包括DAXX/ATRX、MEN1突变和拷贝数变异（CNV），为肿瘤侵袭性提供了一些见解。然而，胰岛素瘤与其他类型的PanNETs之间侵袭性存在显著差异的根本原因仍不清楚。为了构建一个全面的预后分层模型，我们对成熟的PanNETs Rip1-Tag 2（RT2）小鼠模型和具有各种功能类型的人类PanNETs进行了分析。首先，通过对来自不同年龄和品系的RT2小鼠以及人类PanNETs的PanNETs应用单细胞和批量RNA测序，我们引入了一个二维（2D）分类系统。基于该二维分类系统，人类PanNETs主要分为良性胰岛素瘤或非胰岛素瘤亚群。非胰岛素瘤亚型主要包括胃泌素瘤、胰高血糖素瘤、血管活性肠肽瘤和无功能胰腺神经内分泌肿瘤（NF-PanNETs），它们均表现出潜在的侵袭性。此外，我们在相应的人类PanNET亚群中发现了特定CNV模式和突变的富集。然后我们将体细胞DAXX/ATRX标记为侵袭性的“二次打击”和混杂因素。最后，通过结合二维系统、DAXX/ATRX突变状态和肿瘤直径，确定了一组复发风险最小的惰性PanNETs。总之，我们目前的工作构建了一个全面的模型，以阐明PanNETs侵袭性的异质性并改善预后分层。
