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Comparative transcriptional analyses of preclinical models and patient samples reveal MYC and RELA driven expression patterns that define the molecular landscape of IBC

Inflammatory breast cancer (IBC) is an aggressive disease for which the spectrum of preclinical models was rather limited in the past. More recently, novel cell lines and xenografts have been developed. This study evaluates the transcriptome of an extended series of IBC preclinical models and perfor...

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Autores principales: Rypens, Charlotte, Bertucci, François, Finetti, Pascal, Robertson, Fredika, Fernandez, Sandra V., Ueno, Naoto, Woodward, Wendy A., Van Golen, Kenneth, Vermeulen, Peter, Dirix, Luc, Viens, Patrice, Birnbaum, Daniel, Devi, Gayathri R., Cristofanilli, Massimo, Van Laere, Steven
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8766434/
https://www.ncbi.nlm.nih.gov/pubmed/35042871
http://dx.doi.org/10.1038/s41523-021-00379-6
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author Rypens, Charlotte
Bertucci, François
Finetti, Pascal
Robertson, Fredika
Fernandez, Sandra V.
Ueno, Naoto
Woodward, Wendy A.
Van Golen, Kenneth
Vermeulen, Peter
Dirix, Luc
Viens, Patrice
Birnbaum, Daniel
Devi, Gayathri R.
Cristofanilli, Massimo
Van Laere, Steven
author_facet Rypens, Charlotte
Bertucci, François
Finetti, Pascal
Robertson, Fredika
Fernandez, Sandra V.
Ueno, Naoto
Woodward, Wendy A.
Van Golen, Kenneth
Vermeulen, Peter
Dirix, Luc
Viens, Patrice
Birnbaum, Daniel
Devi, Gayathri R.
Cristofanilli, Massimo
Van Laere, Steven
author_sort Rypens, Charlotte
collection PubMed
description Inflammatory breast cancer (IBC) is an aggressive disease for which the spectrum of preclinical models was rather limited in the past. More recently, novel cell lines and xenografts have been developed. This study evaluates the transcriptome of an extended series of IBC preclinical models and performed a comparative analysis with patient samples to determine the extent to which the current models recapitulate the molecular characteristics of IBC observed clinically. We demonstrate that the IBC preclinical models are exclusively estrogen receptor (ER)-negative and of the basal-like subtype, which reflects to some extent the predominance of these subtypes in patient samples. The IBC-specific 79-signature we previously reported was retrained and discriminated between IBC and non-IBC preclinical models, but with a relatively high rate of false positive predictions. Further analyses of gene expression profiles revealed important roles for cell proliferation, MYC transcriptional activity, and TNFɑ/NFκB in the biology of IBC. Patterns of MYC expression and transcriptional activity were further explored in patient samples, which revealed interactions with ESR1 expression that are contrasting in IBC and nIBC and notable given the comparatively poor outcomes of ER+ IBC. Our analyses also suggest important roles for NMYC, MXD3, MAX, and MLX in shaping MYC signaling in IBC. Overall, we demonstrate that the IBC preclinical models can be used to unravel cancer cell intrinsic molecular features, and thus constitute valuable research tools. Nevertheless, the current lack of ER-positive IBC models remains a major hurdle, particularly since interactions with the ER pathway appear to be relevant for IBC.
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spelling pubmed-87664342022-02-04 Comparative transcriptional analyses of preclinical models and patient samples reveal MYC and RELA driven expression patterns that define the molecular landscape of IBC Rypens, Charlotte Bertucci, François Finetti, Pascal Robertson, Fredika Fernandez, Sandra V. Ueno, Naoto Woodward, Wendy A. Van Golen, Kenneth Vermeulen, Peter Dirix, Luc Viens, Patrice Birnbaum, Daniel Devi, Gayathri R. Cristofanilli, Massimo Van Laere, Steven NPJ Breast Cancer Article Inflammatory breast cancer (IBC) is an aggressive disease for which the spectrum of preclinical models was rather limited in the past. More recently, novel cell lines and xenografts have been developed. This study evaluates the transcriptome of an extended series of IBC preclinical models and performed a comparative analysis with patient samples to determine the extent to which the current models recapitulate the molecular characteristics of IBC observed clinically. We demonstrate that the IBC preclinical models are exclusively estrogen receptor (ER)-negative and of the basal-like subtype, which reflects to some extent the predominance of these subtypes in patient samples. The IBC-specific 79-signature we previously reported was retrained and discriminated between IBC and non-IBC preclinical models, but with a relatively high rate of false positive predictions. Further analyses of gene expression profiles revealed important roles for cell proliferation, MYC transcriptional activity, and TNFɑ/NFκB in the biology of IBC. Patterns of MYC expression and transcriptional activity were further explored in patient samples, which revealed interactions with ESR1 expression that are contrasting in IBC and nIBC and notable given the comparatively poor outcomes of ER+ IBC. Our analyses also suggest important roles for NMYC, MXD3, MAX, and MLX in shaping MYC signaling in IBC. Overall, we demonstrate that the IBC preclinical models can be used to unravel cancer cell intrinsic molecular features, and thus constitute valuable research tools. Nevertheless, the current lack of ER-positive IBC models remains a major hurdle, particularly since interactions with the ER pathway appear to be relevant for IBC. Nature Publishing Group UK 2022-01-18 /pmc/articles/PMC8766434/ /pubmed/35042871 http://dx.doi.org/10.1038/s41523-021-00379-6 Text en © The Author(s) 2022 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
Rypens, Charlotte
Bertucci, François
Finetti, Pascal
Robertson, Fredika
Fernandez, Sandra V.
Ueno, Naoto
Woodward, Wendy A.
Van Golen, Kenneth
Vermeulen, Peter
Dirix, Luc
Viens, Patrice
Birnbaum, Daniel
Devi, Gayathri R.
Cristofanilli, Massimo
Van Laere, Steven
Comparative transcriptional analyses of preclinical models and patient samples reveal MYC and RELA driven expression patterns that define the molecular landscape of IBC
title Comparative transcriptional analyses of preclinical models and patient samples reveal MYC and RELA driven expression patterns that define the molecular landscape of IBC
title_full Comparative transcriptional analyses of preclinical models and patient samples reveal MYC and RELA driven expression patterns that define the molecular landscape of IBC
title_fullStr Comparative transcriptional analyses of preclinical models and patient samples reveal MYC and RELA driven expression patterns that define the molecular landscape of IBC
title_full_unstemmed Comparative transcriptional analyses of preclinical models and patient samples reveal MYC and RELA driven expression patterns that define the molecular landscape of IBC
title_short Comparative transcriptional analyses of preclinical models and patient samples reveal MYC and RELA driven expression patterns that define the molecular landscape of IBC
title_sort comparative transcriptional analyses of preclinical models and patient samples reveal myc and rela driven expression patterns that define the molecular landscape of ibc
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8766434/
https://www.ncbi.nlm.nih.gov/pubmed/35042871
http://dx.doi.org/10.1038/s41523-021-00379-6
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