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Tracking Tumor Cell Dissemination from Lung Metastases Using Photoconversion.
Madeline Friedman-DeLuca1, Prachiben P Patel1, Burcu Karadal-Ferrena1
1Department of Pathology, Albert Einstein College of Medicine/Montefiore Medical Center; Cancer Dormancy and Tumor Microenvironment Institute, Albert Einstein College of Medicine/Montefiore Medical Center.
Journal of Visualized Experiments : Jove
|July 24, 2023
Summary
Metastasis-to-metastasis seeding, where cancer spreads from existing lesions, is poorly understood. A new mouse model allows tracking of redisseminating tumor cells without genetic analysis.
Area of Science:
- Oncology
- Cancer Biology
- Surgical Oncology
Background:
- Metastasis, the spread of cancer, causes most cancer deaths.
- Metastasis-to-metastasis seeding, or redissemination from existing lesions, increases tumor burden and reduces survival.
- Current methods, primarily sequencing, limit the study of metastasis-to-metastasis seeding timing and drivers.
Purpose of the Study:
- To develop a novel methodology for studying metastasis-to-metastasis seeding.
- To enable tracking of tumor cell redissemination from lung metastases to tertiary sites.
- To provide a non-genomic approach for investigating metastasis-to-metastasis seeding.
Main Methods:
- A murine surgical protocol for selective photoconversion of lung metastases.
- In vivo marking and fate tracking of tumor cells redisseminating from the lungs.
- Utilizing a novel technique that bypasses the need for genomic analysis.
Main Results:
- Successful implementation of a surgical protocol for selective metastasis photoconversion in mice.
- Demonstrated ability to track redisseminating tumor cells from lung metastases to distant sites.
- Established a non-genomic method for studying metastasis-to-metastasis seeding.
Conclusions:
- The developed murine model offers a unique tool to study metastasis-to-metastasis seeding.
- This methodology overcomes limitations of existing techniques, facilitating research into tumor cell redissemination.
- Advances understanding of metastasis-to-metastasis seeding, crucial for improving treatment strategies in metastatic cancer.
