尾声
生物
胰腺
病理
高分辨率
医学
地质学
生物化学
遥感
地震学
作者
Ashley Kiemen,Alicia M. Braxton,Mia P. Grahn,Kyu Sang Han,Jaanvi Mahesh Babu,Rebecca Reichel,Ann Chenyu Jiang,Bridgette Kim,Jocelyn Y. Hsu,Falone Amoa,Sashank Reddy,Seung‐Mo Hong,Toby C. Cornish,Elizabeth D. Thompson,Peng Huang,Laura D. Wood,Ralph H. Hruban,Denis Wirtz,Pei-Hsun Wu
出处
期刊:Nature Methods
[Springer Nature]
日期:2022-10-24
卷期号:19 (11): 1490-1499
被引量:155
标识
DOI:10.1038/s41592-022-01650-9
摘要
A central challenge in biology is obtaining high-content, high-resolution information while analyzing tissue samples at volumes relevant to disease progression. We address this here with CODA, a method to reconstruct exceptionally large (up to multicentimeter cubed) tissues at subcellular resolution using serially sectioned hematoxylin and eosin-stained tissue sections. Here we demonstrate CODA's ability to reconstruct three-dimensional (3D) distinct microanatomical structures in pancreas, skin, lung and liver tissues. CODA allows creation of readily quantifiable tissue volumes amenable to biological research. As a testbed, we assess the microanatomy of the human pancreas during tumorigenesis within the branching pancreatic ductal system, labeling ten distinct structures to examine heterogeneity and structural transformation during neoplastic progression. We show that pancreatic precancerous lesions develop into distinct 3D morphological phenotypes and that pancreatic cancer tends to spread far from the bulk tumor along collagen fibers that are highly aligned to the 3D curves of ductal, lobular, vascular and neural structures. Thus, CODA establishes a means to transform broadly the structural study of human diseases through exploration of exhaustively labeled 3D microarchitecture.
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