Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Beth Israel Deaconess Medical Center, Boston, MA, USA.
Mod Pathol. 2022 Jul;35(7):956-961. doi: 10.1038/s41379-021-00989-2. Epub 2021 Dec 30.
Pancreatic neoplasms are heterogenous and have traditionally been classified by assessing their lines of cellular differentiation using histopathologic methods, particularly morphologic and immunohistochemical evaluation. These methods frequently identify overlapping differentiation along ductal, acinar, and neuroendocrine lines, raising diagnostic challenges as well as questions regarding the relationship of these neoplasms. Neoplasms with acinar differentiation, in particular, frequently show more than one line of differentiation based on immunolabeling. Genome methylation signatures, in contrast, are better conserved within cellular lineages, and are increasingly used to support the classification of neoplasms. We characterized the epigenetic relationships between pancreatoblastomas, acinar cell carcinomas (including mixed variants), pancreatic neuroendocrine tumors, solid pseudopapillary neoplasms, and pancreatic ductal adenocarcinomas using a genome-wide array platform. Using unsupervised learning approaches, pancreatic neuroendocrine tumors, solid pseudopapillary neoplasms, ductal adenocarcinomas, and normal pancreatic tissue samples all localized to distinct clusters based on their methylation profiles, whereas all neoplasms with acinar differentiation occupied a broad overlapping region located between the predominantly acinar normal pancreatic tissue and ductal adenocarcinoma clusters. Our data provide evidence to suggest that acinar cell carcinomas and pancreatoblastomas are similar at the epigenetic level. These findings are consistent with genomic and clinical observations that mixed acinar neoplasms are closely related to pure acinar cell carcinomas rather than to neuroendocrine tumors or ductal adenocarcinomas.
胰腺肿瘤具有异质性,传统上通过使用组织病理学方法评估其细胞分化谱系进行分类,特别是通过形态学和免疫组织化学评估。这些方法经常在导管、腺泡和神经内分泌谱系中识别出重叠的分化,这不仅提出了诊断方面的挑战,还提出了这些肿瘤之间关系的问题。具有腺泡分化的肿瘤,特别是根据免疫标记,通常显示出不止一种分化谱系。相比之下,基因组甲基化特征在细胞谱系内更好地保持保守,并且越来越多地用于支持肿瘤的分类。我们使用全基因组芯片平台来描述胰腺母细胞瘤、腺泡细胞癌(包括混合变体)、胰腺神经内分泌肿瘤、实性假乳头状肿瘤和胰腺导管腺癌之间的表观遗传关系。使用无监督学习方法,胰腺神经内分泌肿瘤、实性假乳头状肿瘤、导管腺癌和正常胰腺组织样本根据其甲基化谱都定位于不同的簇中,而所有具有腺泡分化的肿瘤都占据了一个广泛重叠的区域,该区域位于主要的腺泡正常胰腺组织和导管腺癌簇之间。我们的数据提供了证据表明,腺泡细胞癌和胰腺母细胞瘤在表观遗传水平上相似。这些发现与基因组和临床观察结果一致,即混合腺泡肿瘤与纯腺泡细胞癌密切相关,而与神经内分泌肿瘤或导管腺癌无关。