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Protocol for generating lung and liver metastasis in mice using models that bypass intravasation
Jöran Lücke1, Tao Zhang2, Dimitra E Zazara3
1Section of Molecular Immunology and Gastroenterology, I. Department of Medicine, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany; Hamburg Center for Translational Immunology (HCTI), University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany; Department of General, Visceral and Thoracic Surgery, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany.
This study introduces three forced metastasis models to efficiently study lung and liver cancer spread in mice. These models bypass early steps, enabling rapid evaluation of metastasis mechanisms and therapeutic targets.
Area of Science:
- Oncology
- Cancer Metastasis Research
- Animal Models in Cancer Research
Background:
- Metastasis research often requires efficient models to study cancer spread.
- Forced metastasis models bypass intravasation, allowing focused investigation of later metastatic stages.
- Evaluating therapeutic targets necessitates reliable and reproducible preclinical models.
Purpose of the Study:
- To present a protocol for three forced metastasis models.
- To enable rapid generation of lung and liver metastasis in mice.
- To facilitate the investigation of metastasis mechanisms and therapeutic targets.
Main Methods:
- Development of three forced metastasis models for lung and liver metastasis.
- Detailed protocol includes cancer cell preparation, anesthesia, and analgesia.
- Injection techniques include intrasplenic, intraportal, and intravenous routes.
- Daily monitoring for metastasis development.
Main Results:
- Metastasis generated within 3-4 weeks in approximately 99% of mice.
- Protocol allows for consistent and reproducible induction of metastasis.
- Models are suitable for studying mechanisms of metastasis and evaluating therapies.
Conclusions:
- The presented protocol offers a robust method for generating forced lung and liver metastasis in mice.
- These models are valuable tools for advancing our understanding of cancer metastasis.
- The models provide a platform for efficient preclinical testing of novel anti-metastatic therapies.
