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Evidence-Based Severity Assessment of Animal Models for Pancreatic Cancer

Authors :
Tim Schreiber
Ingo Koopmann
Jakob Brandstetter
Steven R. Talbot
Lea Goldstein
Lisa Hoffmann
Anna Schildt
Markus Joksch
Bernd Krause
Robert Jaster
Rupert Palme
Dietmar Zechner
Brigitte Vollmar
Simone Kumstel
Source :
Biomedicines, Vol 12, Iss 7, p 1494 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

Animal models are crucial to preclinical oncological research and drug development. Animal experiments must be performed in accordance with the 3R principles of replacement and reduction, if possible, and refinement where these procedures remain crucial. In addition, European Union legislations demand a continuous refinement approach, as well as pro- and retrospective severity assessment. In this study, an objective databased severity assessment was performed in murine models for pancreatic cancer induced by orthotopic, subcutaneous, or intravenous injection of Panc02 cells. Parameters such as body weight change, distress score, perianal temperature, mouse grimace scale, burrowing, nesting behavior, and the concentration of corticosterone in plasma and its metabolites in feces were monitored during tumor progression. The most important parameters were combined into a score and mapped against a reference data set by the Relative Severity Assessment procedure (RELSA) to obtain the maximum achieved severity for each animal (RELSAmax). This scoring revealed a significantly higher RELSAmax for the orthotopic model than for the subcutaneous and intravenous models. However, compared to animal models such as pancreatitis and bile duct ligation, the pancreatic cancer models are shown to be less severe. Data-based animal welfare assessment proved to be a valuable tool for comparing the severity of differently induced cancer models.

Details

Language :
English
ISSN :
22279059
Volume :
12
Issue :
7
Database :
Directory of Open Access Journals
Journal :
Biomedicines
Publication Type :
Academic Journal
Accession number :
edsdoj.4c9b8db04af94f29a2bbb907d2af0e71
Document Type :
article
Full Text :
https://doi.org/10.3390/biomedicines12071494