4.7 Article

Quantitative Detection of Disseminated Melanoma Cells by Trp-1 Transcript Analysis Reveals Stochastic Distribution of Pulmonary Metastases

期刊

JOURNAL OF CLINICAL MEDICINE
卷 10, 期 22, 页码 -

出版社

MDPI
DOI: 10.3390/jcm10225459

关键词

Trp-1; metastasis; melanoma; animal models; lung; mice

资金

  1. Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) [259332240/RTG 2099]
  2. European Union under FP7 collaborative project TuMIC [HEALTH-F2-2008-201662]

向作者/读者索取更多资源

A better understanding of melanoma metastasis is crucial for developing novel therapies. The use of qRT-PCR for sensitive quantification of Trp-1 in murine lung metastasis allows detection even in low metastatic burdens, enabling quantification and analysis in various melanoma models.
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(Grm1)/Cyld(-/-) 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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