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Dynamic prostate cancer transcriptome analysis delineates the trajectory to disease progression
Comprehensive genomic studies have delineated key driver mutations linked to disease progression for most cancers. However, corresponding transcriptional changes remain largely elusive because of the bias associated with cross-study analysis. Here, we overcome these hurdles and generate a comprehens...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8640014/ https://www.ncbi.nlm.nih.gov/pubmed/34857732 http://dx.doi.org/10.1038/s41467-021-26840-5 |
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author | Bolis, Marco Bossi, Daniela Vallerga, Arianna Ceserani, Valentina Cavalli, Manuela Impellizzieri, Daniela Di Rito, Laura Zoni, Eugenio Mosole, Simone Elia, Angela Rita Rinaldi, Andrea Pereira Mestre, Ricardo D’Antonio, Eugenia Ferrari, Matteo Stoffel, Flavio Jermini, Fernando Gillessen, Silke Bubendorf, Lukas Schraml, Peter Calcinotto, Arianna Corey, Eva Moch, Holger Spahn, Martin Thalmann, George Kruithof-de Julio, Marianna Rubin, Mark A. Theurillat, Jean-Philippe P. |
author_facet | Bolis, Marco Bossi, Daniela Vallerga, Arianna Ceserani, Valentina Cavalli, Manuela Impellizzieri, Daniela Di Rito, Laura Zoni, Eugenio Mosole, Simone Elia, Angela Rita Rinaldi, Andrea Pereira Mestre, Ricardo D’Antonio, Eugenia Ferrari, Matteo Stoffel, Flavio Jermini, Fernando Gillessen, Silke Bubendorf, Lukas Schraml, Peter Calcinotto, Arianna Corey, Eva Moch, Holger Spahn, Martin Thalmann, George Kruithof-de Julio, Marianna Rubin, Mark A. Theurillat, Jean-Philippe P. |
author_sort | Bolis, Marco |
collection | PubMed |
description | Comprehensive genomic studies have delineated key driver mutations linked to disease progression for most cancers. However, corresponding transcriptional changes remain largely elusive because of the bias associated with cross-study analysis. Here, we overcome these hurdles and generate a comprehensive prostate cancer transcriptome atlas that describes the roadmap to tumor progression in a qualitative and quantitative manner. Most cancers follow a uniform trajectory characterized by upregulation of polycomb-repressive-complex-2, G2-M checkpoints, and M2 macrophage polarization. Using patient-derived xenograft models, we functionally validate our observations and add single-cell resolution. Thereby, we show that tumor progression occurs through transcriptional adaption rather than a selection of pre-existing cancer cell clusters. Moreover, we determine at the single-cell level how inhibition of EZH2 - the top upregulated gene along the trajectory – reverts tumor progression and macrophage polarization. Finally, a user-friendly web-resource is provided enabling the investigation of dynamic transcriptional perturbations linked to disease progression. |
format | Online Article Text |
id | pubmed-8640014 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-86400142021-12-15 Dynamic prostate cancer transcriptome analysis delineates the trajectory to disease progression Bolis, Marco Bossi, Daniela Vallerga, Arianna Ceserani, Valentina Cavalli, Manuela Impellizzieri, Daniela Di Rito, Laura Zoni, Eugenio Mosole, Simone Elia, Angela Rita Rinaldi, Andrea Pereira Mestre, Ricardo D’Antonio, Eugenia Ferrari, Matteo Stoffel, Flavio Jermini, Fernando Gillessen, Silke Bubendorf, Lukas Schraml, Peter Calcinotto, Arianna Corey, Eva Moch, Holger Spahn, Martin Thalmann, George Kruithof-de Julio, Marianna Rubin, Mark A. Theurillat, Jean-Philippe P. Nat Commun Article Comprehensive genomic studies have delineated key driver mutations linked to disease progression for most cancers. However, corresponding transcriptional changes remain largely elusive because of the bias associated with cross-study analysis. Here, we overcome these hurdles and generate a comprehensive prostate cancer transcriptome atlas that describes the roadmap to tumor progression in a qualitative and quantitative manner. Most cancers follow a uniform trajectory characterized by upregulation of polycomb-repressive-complex-2, G2-M checkpoints, and M2 macrophage polarization. Using patient-derived xenograft models, we functionally validate our observations and add single-cell resolution. Thereby, we show that tumor progression occurs through transcriptional adaption rather than a selection of pre-existing cancer cell clusters. Moreover, we determine at the single-cell level how inhibition of EZH2 - the top upregulated gene along the trajectory – reverts tumor progression and macrophage polarization. Finally, a user-friendly web-resource is provided enabling the investigation of dynamic transcriptional perturbations linked to disease progression. Nature Publishing Group UK 2021-12-02 /pmc/articles/PMC8640014/ /pubmed/34857732 http://dx.doi.org/10.1038/s41467-021-26840-5 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Bolis, Marco Bossi, Daniela Vallerga, Arianna Ceserani, Valentina Cavalli, Manuela Impellizzieri, Daniela Di Rito, Laura Zoni, Eugenio Mosole, Simone Elia, Angela Rita Rinaldi, Andrea Pereira Mestre, Ricardo D’Antonio, Eugenia Ferrari, Matteo Stoffel, Flavio Jermini, Fernando Gillessen, Silke Bubendorf, Lukas Schraml, Peter Calcinotto, Arianna Corey, Eva Moch, Holger Spahn, Martin Thalmann, George Kruithof-de Julio, Marianna Rubin, Mark A. Theurillat, Jean-Philippe P. Dynamic prostate cancer transcriptome analysis delineates the trajectory to disease progression |
title | Dynamic prostate cancer transcriptome analysis delineates the trajectory to disease progression |
title_full | Dynamic prostate cancer transcriptome analysis delineates the trajectory to disease progression |
title_fullStr | Dynamic prostate cancer transcriptome analysis delineates the trajectory to disease progression |
title_full_unstemmed | Dynamic prostate cancer transcriptome analysis delineates the trajectory to disease progression |
title_short | Dynamic prostate cancer transcriptome analysis delineates the trajectory to disease progression |
title_sort | dynamic prostate cancer transcriptome analysis delineates the trajectory to disease progression |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8640014/ https://www.ncbi.nlm.nih.gov/pubmed/34857732 http://dx.doi.org/10.1038/s41467-021-26840-5 |
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