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Three-dimensional genomic mapping of human pancreatic tissue reveals striking multifocality and genetic heterogeneity in precancerous lesions.
Braxton, Alicia M; Kiemen, Ashley L; Grahn, Mia P; Forjaz, André; Babu, Jaanvi Mahesh; Zheng, Lily; Jiang, Liping; Cheng, Haixia; Song, Qianqian; Reichel, Rebecca; Graham, Sarah; Damanakis, Alexander I; Fischer, Catherine G; Mou, Stephanie; Metz, Cameron; Granger, Julie; Liu, Xiao-Ding; Bachmann, Niklas; Almagro-Pérez, Cristina; Jiang, Ann Chenyu; Yoo, Jeonghyun; Kim, Bridgette; Du, Scott; Foster, Eli; Hsu, Jocelyn Y; Rivera, Paula Andreu; Chu, Linda C; Liu, Fengze; Niknafs, Noushin; Fishman, Elliot K; Yuille, Alan; Roberts, Nicholas J; Thompson, Elizabeth D; Scharpf, Robert B; Cornish, Toby C; Jiao, Yuchen; Karchin, Rachel; Hruban, Ralph H; Wu, Pei-Hsun; Wirtz, Denis; Wood, Laura D.
Afiliação
  • Braxton AM; Department of Pathology, Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Kiemen AL; Department of Pathology, Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Grahn MP; Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD.
  • Forjaz A; Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Babu JM; Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD.
  • Zheng L; Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD.
  • Jiang L; Department of Pathology, Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Cheng H; McKusick-Nathans Institute for Genetic Medicine, Johns Hopkins University, Baltimore, MD.
  • Song Q; Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD.
  • Reichel R; State Key Lab of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences, and Peking Union Medical College, Beijing, China.
  • Graham S; State Key Lab of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences, and Peking Union Medical College, Beijing, China.
  • Damanakis AI; State Key Lab of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences, and Peking Union Medical College, Beijing, China.
  • Fischer CG; Department of Pathology, Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Mou S; Department of Pathology, Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Metz C; Department of Pathology, Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Granger J; Department of Pathology, Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Liu XD; Department of Pathology, Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Bachmann N; Department of Pathology, Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Almagro-Pérez C; Department of Pathology, Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Jiang AC; Department of Pathology, Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Yoo J; Department of Pathology, Molecular Pathology Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
  • Kim B; Department of Pathology, Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Du S; Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD.
  • Foster E; Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD.
  • Hsu JY; Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD.
  • Rivera PA; Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD.
  • Chu LC; Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD.
  • Liu F; Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD.
  • Niknafs N; Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD.
  • Fishman EK; Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD.
  • Yuille A; Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Roberts NJ; Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Thompson ED; Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Scharpf RB; Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Cornish TC; Department of Computer Science, Johns Hopkins University, Baltimore, MD.
  • Jiao Y; Department of Pathology, Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Karchin R; Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Hruban RH; Department of Pathology, Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Wu PH; Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Wirtz D; Department of Pathology, University of Colorado School of Medicine, Aurora, CO.
  • Wood LD; Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD.
bioRxiv ; 2023 Jan 28.
Article em En | MEDLINE | ID: mdl-36747709
ABSTRACT
Pancreatic intraepithelial neoplasia (PanIN) is a precursor to pancreatic cancer and represents a critical opportunity for cancer interception. However, the number, size, shape, and connectivity of PanINs in human pancreatic tissue samples are largely unknown. In this study, we quantitatively assessed human PanINs using CODA, a novel machine-learning pipeline for 3D image analysis that generates quantifiable models of large pieces of human pancreas with single-cell resolution. Using a cohort of 38 large slabs of grossly normal human pancreas from surgical resection specimens, we identified striking multifocality of PanINs, with a mean burden of 13 spatially separate PanINs per cm3 of sampled tissue. Extrapolating this burden to the entire pancreas suggested a median of approximately 1000 PanINs in an entire pancreas. In order to better understand the clonal relationships within and between PanINs, we developed a pipeline for CODA-guided multi-region genomic analysis of PanINs, including targeted and whole exome sequencing. Multi-region assessment of 37 PanINs from eight additional human pancreatic tissue slabs revealed that almost all PanINs contained hotspot mutations in the oncogene KRAS, but no gene other than KRAS was altered in more than 20% of the analyzed PanINs. PanINs contained a mean of 13 somatic mutations per region when analyzed by whole exome sequencing. The majority of analyzed PanINs originated from independent clonal events, with distinct somatic mutation profiles between PanINs in the same tissue slab. A subset of the analyzed PanINs contained multiple KRAS mutations, suggesting a polyclonal origin even in PanINs that are contiguous by rigorous 3D assessment. This study leverages a novel 3D genomic mapping approach to describe, for the first time, the spatial and genetic multifocality of human PanINs, providing important insights into the initiation and progression of pancreatic neoplasia.

Texto completo: 1 Bases de dados: MEDLINE Idioma: En Revista: BioRxiv Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Moldávia

Texto completo: 1 Bases de dados: MEDLINE Idioma: En Revista: BioRxiv Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Moldávia