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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: Kyjacova, Lenka, Saup, Rafael, Rothley, Melanie, Schmaus, Anja, Wagner, Tabea, Boßerhoff, Anja, Garvalov, Boyan K., Thiele, Wilko, Sleeman, Jonathan P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8618565/
https://www.ncbi.nlm.nih.gov/pubmed/34830742
http://dx.doi.org/10.3390/jcm10225459
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author Kyjacova, Lenka
Saup, Rafael
Rothley, Melanie
Schmaus, Anja
Wagner, Tabea
Boßerhoff, Anja
Garvalov, Boyan K.
Thiele, Wilko
Sleeman, Jonathan P.
author_facet Kyjacova, Lenka
Saup, Rafael
Rothley, Melanie
Schmaus, Anja
Wagner, Tabea
Boßerhoff, Anja
Garvalov, Boyan K.
Thiele, Wilko
Sleeman, Jonathan P.
author_sort Kyjacova, Lenka
collection PubMed
description 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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spelling pubmed-86185652021-11-27 Quantitative Detection of Disseminated Melanoma Cells by Trp-1 Transcript Analysis Reveals Stochastic Distribution of Pulmonary Metastases Kyjacova, Lenka Saup, Rafael Rothley, Melanie Schmaus, Anja Wagner, Tabea Boßerhoff, Anja Garvalov, Boyan K. Thiele, Wilko Sleeman, Jonathan P. J Clin Med Article 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. MDPI 2021-11-22 /pmc/articles/PMC8618565/ /pubmed/34830742 http://dx.doi.org/10.3390/jcm10225459 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kyjacova, Lenka
Saup, Rafael
Rothley, Melanie
Schmaus, Anja
Wagner, Tabea
Boßerhoff, Anja
Garvalov, Boyan K.
Thiele, Wilko
Sleeman, Jonathan P.
Quantitative Detection of Disseminated Melanoma Cells by Trp-1 Transcript Analysis Reveals Stochastic Distribution of Pulmonary Metastases
title Quantitative Detection of Disseminated Melanoma Cells by Trp-1 Transcript Analysis Reveals Stochastic Distribution of Pulmonary Metastases
title_full Quantitative Detection of Disseminated Melanoma Cells by Trp-1 Transcript Analysis Reveals Stochastic Distribution of Pulmonary Metastases
title_fullStr Quantitative Detection of Disseminated Melanoma Cells by Trp-1 Transcript Analysis Reveals Stochastic Distribution of Pulmonary Metastases
title_full_unstemmed Quantitative Detection of Disseminated Melanoma Cells by Trp-1 Transcript Analysis Reveals Stochastic Distribution of Pulmonary Metastases
title_short Quantitative Detection of Disseminated Melanoma Cells by Trp-1 Transcript Analysis Reveals Stochastic Distribution of Pulmonary Metastases
title_sort quantitative detection of disseminated melanoma cells by trp-1 transcript analysis reveals stochastic distribution of pulmonary metastases
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8618565/
https://www.ncbi.nlm.nih.gov/pubmed/34830742
http://dx.doi.org/10.3390/jcm10225459
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