Predictive modelling of response to neoadjuvant therapy in HER2+ breast cancer
Abstract 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...
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-09-01
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| Series: | npj Breast Cancer |
| Online Access: | https://doi.org/10.1038/s41523-023-00572-9 |
| _version_ | 1827709231230353408 |
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| author | Nicola Cosgrove Alex J. Eustace Peter O’Donovan Stephen F. Madden Bruce Moran John Crown Brian Moulton Patrick G. Morris Liam Grogan Oscar Breathnach Colm Power Michael Allen Janice M. Walshe Arnold D. Hill Anna Blümel Darren O’Connor Sudipto Das Małgorzata Milewska Joanna Fay Elaine Kay Sinead Toomey Bryan T. Hennessy Simon J. Furney |
| author_facet | Nicola Cosgrove Alex J. Eustace Peter O’Donovan Stephen F. Madden Bruce Moran John Crown Brian Moulton Patrick G. Morris Liam Grogan Oscar Breathnach Colm Power Michael Allen Janice M. Walshe Arnold D. Hill Anna Blümel Darren O’Connor Sudipto Das Małgorzata Milewska Joanna Fay Elaine Kay Sinead Toomey Bryan T. Hennessy Simon J. Furney |
| author_sort | Nicola Cosgrove |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-03-10T17:18:03Z |
| format | Article |
| id | doaj.art-2aa94f4a6ce8446ea48464a6049912d0 |
| institution | Directory Open Access Journal |
| issn | 2374-4677 |
| language | English |
| last_indexed | 2024-03-10T17:18:03Z |
| publishDate | 2023-09-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Breast Cancer |
| spelling | doaj.art-2aa94f4a6ce8446ea48464a6049912d02023-11-20T10:25:30ZengNature Portfolionpj Breast Cancer2374-46772023-09-019111610.1038/s41523-023-00572-9Predictive modelling of response to neoadjuvant therapy in HER2+ breast cancerNicola Cosgrove0Alex J. Eustace1Peter O’Donovan2Stephen F. Madden3Bruce Moran4John Crown5Brian Moulton6Patrick G. Morris7Liam Grogan8Oscar Breathnach9Colm Power10Michael Allen11Janice M. Walshe12Arnold D. Hill13Anna Blümel14Darren O’Connor15Sudipto Das16Małgorzata Milewska17Joanna Fay18Elaine Kay19Sinead Toomey20Bryan T. Hennessy21Simon J. Furney22Genomic Oncology Research Group, Department of Physiology and Medical Physics, RCSI University of Medicine and Health SciencesSchool of Biotechnology, National Institute for Cellular Biotechnology, Dublin City UniversityGenomic Oncology Research Group, Department of Physiology and Medical Physics, RCSI University of Medicine and Health SciencesData Science Centre, RCSI University of Medicine and Health SciencesConway Institute, University College DublinDepartment of Medical Oncology, St Vincent’s University HospitalClinical Oncology Development EuropeDepartment of Medical Oncology, Beaumont HospitalDepartment of Medical Oncology, Beaumont HospitalDepartment of Medical Oncology, Beaumont HospitalDepartment of Surgery, RCSI University of Medicine and Health SciencesDepartment of Surgery, RCSI University of Medicine and Health SciencesDepartment of Medical Oncology, St Vincent’s University HospitalDepartment of Surgery, RCSI University of Medicine and Health SciencesSchool of Pharmacy and Biomolecular Sciences, RCSI University of Medicine and Health SciencesSchool of Pharmacy and Biomolecular Sciences, RCSI University of Medicine and Health SciencesSchool of Pharmacy and Biomolecular Sciences, RCSI University of Medicine and Health SciencesMedical Oncology Group, Department of Molecular Medicine, Royal College of Surgeons in IrelandRCSI Biobank Service, RCSI University of Medicine and Health Sciences, Beaumont HospitalDepartment of Pathology, RCSI University of Medicine and Health Sciences, Beaumont HospitalMedical Oncology Group, Department of Molecular Medicine, Royal College of Surgeons in IrelandDepartment of Medical Oncology, Beaumont HospitalGenomic Oncology Research Group, Department of Physiology and Medical Physics, RCSI University of Medicine and Health SciencesAbstract 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.https://doi.org/10.1038/s41523-023-00572-9 |
| spellingShingle | Nicola Cosgrove Alex J. Eustace Peter O’Donovan Stephen F. Madden Bruce Moran John Crown Brian Moulton Patrick G. Morris Liam Grogan Oscar Breathnach Colm Power Michael Allen Janice M. Walshe Arnold D. Hill Anna Blümel Darren O’Connor Sudipto Das Małgorzata Milewska Joanna Fay Elaine Kay Sinead Toomey Bryan T. Hennessy Simon J. Furney Predictive modelling of response to neoadjuvant therapy in HER2+ breast cancer npj 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 |
| url | https://doi.org/10.1038/s41523-023-00572-9 |
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