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Predictive modelling of response to neoadjuvant therapy in HER2+ breast cancer
HER2-positive (HER2+) breast cancer accounts for 20–25% of all breast cancers. Predictive biomarkers of neoadjuvant therapy response are needed to better identify patients with early stage disease who may benefit from tailored treatments in the adjuvant setting. As part of the TCHL phase-II clinical...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10533568/ https://www.ncbi.nlm.nih.gov/pubmed/37758711 http://dx.doi.org/10.1038/s41523-023-00572-9 |
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author | Cosgrove, Nicola Eustace, Alex J. O’Donovan, Peter Madden, Stephen F. Moran, Bruce Crown, John Moulton, Brian Morris, Patrick G. Grogan, Liam Breathnach, Oscar Power, Colm Allen, Michael Walshe, Janice M. Hill, Arnold D. Blümel, Anna O’Connor, Darren Das, Sudipto Milewska, Małgorzata Fay, Joanna Kay, Elaine Toomey, Sinead Hennessy, Bryan T. Furney, Simon J. |
author_facet | Cosgrove, Nicola Eustace, Alex J. O’Donovan, Peter Madden, Stephen F. Moran, Bruce Crown, John Moulton, Brian Morris, Patrick G. Grogan, Liam Breathnach, Oscar Power, Colm Allen, Michael Walshe, Janice M. Hill, Arnold D. Blümel, Anna O’Connor, Darren Das, Sudipto Milewska, Małgorzata Fay, Joanna Kay, Elaine Toomey, Sinead Hennessy, Bryan T. Furney, Simon J. |
author_sort | Cosgrove, Nicola |
collection | PubMed |
description | HER2-positive (HER2+) breast cancer accounts for 20–25% of all breast cancers. Predictive biomarkers of neoadjuvant therapy response are needed to better identify patients with early stage disease who may benefit from tailored treatments in the adjuvant setting. As part of the TCHL phase-II clinical trial (ICORG10–05/NCT01485926) whole exome DNA sequencing was carried out on normal-tumour pairs collected from 22 patients. Here we report predictive modelling of neoadjuvant therapy response using clinicopathological and genomic features of pre-treatment tumour biopsies identified age, estrogen receptor (ER) status and level of immune cell infiltration may together be important for predicting response. Clonal evolution analysis of longitudinally collected tumour samples show subclonal diversity and dynamics are evident with potential therapy resistant subclones detected. The sources of greater pre-treatment immunogenicity associated with a pathological complete response is largely unexplored in HER2+ tumours. However, here we point to the possibility of APOBEC associated mutagenesis, specifically in the ER-neg/HER2+ subtype as a potential mediator of this immunogenic phenotype. |
format | Online Article Text |
id | pubmed-10533568 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-105335682023-09-29 Predictive modelling of response to neoadjuvant therapy in HER2+ breast cancer Cosgrove, Nicola Eustace, Alex J. O’Donovan, Peter Madden, Stephen F. Moran, Bruce Crown, John Moulton, Brian Morris, Patrick G. Grogan, Liam Breathnach, Oscar Power, Colm Allen, Michael Walshe, Janice M. Hill, Arnold D. Blümel, Anna O’Connor, Darren Das, Sudipto Milewska, Małgorzata Fay, Joanna Kay, Elaine Toomey, Sinead Hennessy, Bryan T. Furney, Simon J. NPJ Breast Cancer Article HER2-positive (HER2+) breast cancer accounts for 20–25% of all breast cancers. Predictive biomarkers of neoadjuvant therapy response are needed to better identify patients with early stage disease who may benefit from tailored treatments in the adjuvant setting. As part of the TCHL phase-II clinical trial (ICORG10–05/NCT01485926) whole exome DNA sequencing was carried out on normal-tumour pairs collected from 22 patients. Here we report predictive modelling of neoadjuvant therapy response using clinicopathological and genomic features of pre-treatment tumour biopsies identified age, estrogen receptor (ER) status and level of immune cell infiltration may together be important for predicting response. Clonal evolution analysis of longitudinally collected tumour samples show subclonal diversity and dynamics are evident with potential therapy resistant subclones detected. The sources of greater pre-treatment immunogenicity associated with a pathological complete response is largely unexplored in HER2+ tumours. However, here we point to the possibility of APOBEC associated mutagenesis, specifically in the ER-neg/HER2+ subtype as a potential mediator of this immunogenic phenotype. Nature Publishing Group UK 2023-09-27 /pmc/articles/PMC10533568/ /pubmed/37758711 http://dx.doi.org/10.1038/s41523-023-00572-9 Text en © The Author(s) 2023 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 Cosgrove, Nicola Eustace, Alex J. O’Donovan, Peter Madden, Stephen F. Moran, Bruce Crown, John Moulton, Brian Morris, Patrick G. Grogan, Liam Breathnach, Oscar Power, Colm Allen, Michael Walshe, Janice M. Hill, Arnold D. Blümel, Anna O’Connor, Darren Das, Sudipto Milewska, Małgorzata Fay, Joanna Kay, Elaine Toomey, Sinead Hennessy, Bryan T. Furney, Simon J. Predictive modelling of response to neoadjuvant therapy in HER2+ breast cancer |
title | Predictive modelling of response to neoadjuvant therapy in HER2+ breast cancer |
title_full | Predictive modelling of response to neoadjuvant therapy in HER2+ breast cancer |
title_fullStr | Predictive modelling of response to neoadjuvant therapy in HER2+ breast cancer |
title_full_unstemmed | Predictive modelling of response to neoadjuvant therapy in HER2+ breast cancer |
title_short | Predictive modelling of response to neoadjuvant therapy in HER2+ breast cancer |
title_sort | predictive modelling of response to neoadjuvant therapy in her2+ breast cancer |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10533568/ https://www.ncbi.nlm.nih.gov/pubmed/37758711 http://dx.doi.org/10.1038/s41523-023-00572-9 |
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