Department of Pathology, Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Department of Comparative Medicine, Medical University of South Carolina, Charleston, SC, USA.
Nature. 2024 May;629(8012):679-687. doi: 10.1038/s41586-024-07359-3. Epub 2024 May 1.
Pancreatic intraepithelial neoplasias (PanINs) are the most common precursors of pancreatic cancer, but their small size and inaccessibility in humans make them challenging to study. Critically, the number, dimensions and connectivity of human PanINs remain largely unknown, precluding important insights into early cancer development. Here, we provide a microanatomical survey of human PanINs by analysing 46 large samples of grossly normal human pancreas with a machine-learning pipeline for quantitative 3D histological reconstruction at single-cell resolution. To elucidate genetic relationships between and within PanINs, we developed a workflow in which 3D modelling guides multi-region microdissection and targeted and whole-exome sequencing. From these samples, we calculated a mean burden of 13 PanINs per cm and extrapolated that the normal intact adult pancreas harbours hundreds of PanINs, almost all with oncogenic KRAS hotspot mutations. We found that most PanINs originate as independent clones with distinct somatic mutation profiles. Some spatially continuous PanINs were found to contain multiple KRAS mutations; computational and in situ analyses demonstrated that different KRAS mutations localize to distinct cell subpopulations within these neoplasms, indicating their polyclonal origins. The extensive multifocality and genetic heterogeneity of PanINs raises important questions about mechanisms that drive precancer initiation and confer differential progression risk in the human pancreas. This detailed 3D genomic mapping of molecular alterations in human PanINs provides an empirical foundation for early detection and rational interception of pancreatic cancer.
胰腺上皮内瘤变(PanINs)是胰腺癌最常见的前体,但由于其在人体中的体积小且难以接近,因此研究起来具有挑战性。至关重要的是,人类 PanINs 的数量、尺寸和连通性在很大程度上仍然未知,这使得我们无法深入了解早期癌症的发展。在这里,我们通过分析 46 个大体正常的人类胰腺样本,利用机器学习管道进行单细胞分辨率的定量 3D 组织学重建,对人类 PanINs 进行了微观解剖调查。为了阐明 PanINs 之间和内部的遗传关系,我们开发了一种工作流程,其中 3D 建模指导多区域显微解剖和靶向及全外显子组测序。从这些样本中,我们计算出每厘米有 13 个 PanINs,推断正常完整的成年胰腺中存在数百个 PanINs,几乎所有 PanINs 都具有致癌热点 KRAS 突变。我们发现,大多数 PanINs 作为具有不同体细胞突变特征的独立克隆起源。一些空间上连续的 PanINs 被发现含有多个 KRAS 突变;计算和原位分析表明,这些肿瘤内不同的 KRAS 突变定位于不同的细胞亚群,表明它们具有多克隆起源。PanINs 的广泛多灶性和遗传异质性提出了重要的问题,即驱动癌前起始和在人类胰腺中赋予不同进展风险的机制。这种对人类 PanINs 中分子改变的详细 3D 基因组图谱为胰腺癌的早期检测和合理干预提供了经验基础。