Multiplexed Imaging Mass Cytometry Analysis in Preclinical Models of Pancreatic Cancer

Author:

Erreni Marco12ORCID,Fumagalli Maria Rita1ORCID,Zanini Damiano1,Candiello Ermes3ORCID,Tiberi Giorgia3,Parente Raffaella1ORCID,D’Anna Raffaella1,Magrini Elena4,Marchesi Federica45ORCID,Cappello Paola3ORCID,Doni Andrea1

Affiliation:

1. Unit of Multiscale and Nanostructural Imaging, IRCCS Humanitas Research Hospital -, via Manzoni 56, 20089 Rozzano, Milan, Italy

2. Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, Pieve Emanuele, 20072 Milan, Italy

3. Department of Molecular Biotechnology and Health Sciences, University of Turin, Piazza Nizza 44b, 10126 Torino, Italy

4. IRCCS Humanitas Research Hospital -, via Manzoni 56, 20089 Rozzano, Milan, Italy

5. Department of Medical Biotechnology and Translational Medicine, University of Milan, 20133 Milan, Italy

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers. PDAC is characterized by a complex tumor microenvironment (TME), that plays a pivotal role in disease progression and resistance to therapy. Investigating the spatial distribution and interaction of TME cells with the tumor is the basis for understanding the mechanisms underlying disease progression and represents a current challenge in PDAC research. Imaging mass cytometry (IMC) is the major multiplex imaging technology for the spatial analysis of tumor heterogeneity. However, there is a dearth of reports of multiplexed IMC panels for different preclinical mouse models, including pancreatic cancer. We addressed this gap by utilizing two preclinical models of PDAC: the genetically engineered, bearing KRAS–TP53 mutations in pancreatic cells, and the orthotopic, and developed a 28–marker panel for single–cell IMC analysis to assess the abundance, distribution and phenotypes of cells involved in PDAC progression and their reciprocal functional interactions. Herein, we provide an unprecedented definition of the distribution of TME cells in PDAC and compare the diversity between transplanted and genetic disease models. The results obtained represent an important and customizable tool for unraveling the complexities of PDAC and deciphering the mechanisms behind therapy resistance.

Funder

AIRC

Italian Ministry of Foreign Affairs and International Cooperation

Fondazione Compagnia di San Paolo

Ministero degli affari esteri e della cooperazione internazionale

Publisher

MDPI AG

Subject

Inorganic Chemistry,Organic Chemistry,Physical and Theoretical Chemistry,Computer Science Applications,Spectroscopy,Molecular Biology,General Medicine,Catalysis

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