Quantitative Detection of Disseminated Melanoma Cells by Trp-1 Transcript Analysis Reveals Stochastic Distribution of Pulmonary Metastases
A better understanding of the process of melanoma metastasis is required to underpin the development of novel therapies that will improve patient outcomes. The use of appropriate animal models is indispensable for investigating the mechanisms of melanoma metastasis. However, reliable and practicable...
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| Autores principales: | , , , , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
MDPI AG
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/5efdfbfd7d5b4c978300e2058a145c84 |
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| Sumario: | A better understanding of the process of melanoma metastasis is required to underpin the development of novel therapies that will improve patient outcomes. The use of appropriate animal models is indispensable for investigating the mechanisms of melanoma metastasis. However, reliable and practicable quantification of metastases in experimental mice remains a challenge, particularly if the metastatic burden is low. Here, we describe a qRT-PCR-based protocol that employs the melanocytic marker Trp-1 for the sensitive quantification of melanoma metastases in the murine lung. Using this protocol, we were able to detect the presence of as few as 100 disseminated melanoma cells in lung tissue. This allowed us to quantify metastatic burden in a spontaneous syngeneic B16-F10 metastasis model, even in the absence of visible metastases, as well as in the autochthonous Tg(<i>Grm1</i>)/<i>Cyld<sup>−/−</sup></i> melanoma model. Importantly, we also observed an uneven distribution of disseminated melanoma cells amongst the five lobes of the murine lung, which varied considerably from animal to animal. Together, our findings demonstrate that the qRT-PCR-based detection of Trp-1 allows the quantification of low pulmonary metastatic burden in both transplantable and autochthonous murine melanoma models, and show that the analysis of lung metastasis in such models needs to take into account the stochastic distribution of metastatic lesions amongst the lung lobes. |
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