Reconstructing tumor history in breast cancer: signatures of mutational processes and response to neoadjuvant chemotherapy
breast cancer
mutational signatures
neoadjuvant therapy
prognosis
response
whole exome sequencing
Journal
Annals of oncology : official journal of the European Society for Medical Oncology
ISSN: 1569-8041
Titre abrégé: Ann Oncol
Pays: England
ID NLM: 9007735
Informations de publication
Date de publication:
04 2021
04 2021
Historique:
received:
04
09
2020
revised:
13
11
2020
accepted:
20
12
2020
pubmed:
9
1
2021
medline:
1
4
2021
entrez:
8
1
2021
Statut:
ppublish
Résumé
Different endogenous and exogenous mutational processes act over the evolutionary history of a malignant tumor, driven by abnormal DNA editing, mutagens or age-related DNA alterations, among others, to generate the specific mutational landscape of each individual tumor. The signatures of these mutational processes can be identified in large genomic datasets. We investigated the hypothesis that genomic patterns of mutational signatures are associated with the clinical behavior of breast cancer, in particular chemotherapy response and survival, with a particular focus on therapy-resistant disease. Whole exome sequencing was carried out in 405 pretherapeutic samples from the prospective neoadjuvant multicenter GeparSepto study. We analyzed 11 mutational signatures including biological processes such as APOBEC-mutagenesis, homologous recombination deficiency (HRD), mismatch repair deficiency and also age-related or tobacco-induced alterations. Different subgroups of breast carcinomas were defined mainly by differences in HRD-related and APOBEC-related mutational signatures and significant differences between hormone-receptor (HR)-negative and HR-positive tumors as well as correlations with age, Ki-67 and immunological parameters were observed. We could identify mutational processes that were linked to increased pathological complete response rates to neoadjuvant chemotherapy with high significance. In univariate analyses for HR-positive tumors signatures, S3 (HRD, P < 0.001) and S13 (APOBEC, P = 0.001) as well as exonic mutation rate (P = 0.002) were significantly correlated with increased pathological complete response rates. The signatures S3 (HRD, P = 0.006) and S4 (tobacco, P = 0.011) were prognostic for reduced disease-free survival of patients with chemotherapy-resistant tumors. The results of this investigation suggest that the clinical behavior of a tumor, in particular, response to neoadjuvant chemotherapy and disease-free survival of therapy-resistant tumors, could be predicted by the composition of mutational signatures as an indicator of the individual genomic history of a tumor. After additional validations, mutational signatures might be used to identify tumors with an increased response rate to neoadjuvant chemotherapy and to define therapy-resistant subgroups for future therapeutic interventions.
Sections du résumé
BACKGROUND
Different endogenous and exogenous mutational processes act over the evolutionary history of a malignant tumor, driven by abnormal DNA editing, mutagens or age-related DNA alterations, among others, to generate the specific mutational landscape of each individual tumor. The signatures of these mutational processes can be identified in large genomic datasets. We investigated the hypothesis that genomic patterns of mutational signatures are associated with the clinical behavior of breast cancer, in particular chemotherapy response and survival, with a particular focus on therapy-resistant disease.
PATIENTS AND METHODS
Whole exome sequencing was carried out in 405 pretherapeutic samples from the prospective neoadjuvant multicenter GeparSepto study. We analyzed 11 mutational signatures including biological processes such as APOBEC-mutagenesis, homologous recombination deficiency (HRD), mismatch repair deficiency and also age-related or tobacco-induced alterations.
RESULTS
Different subgroups of breast carcinomas were defined mainly by differences in HRD-related and APOBEC-related mutational signatures and significant differences between hormone-receptor (HR)-negative and HR-positive tumors as well as correlations with age, Ki-67 and immunological parameters were observed. We could identify mutational processes that were linked to increased pathological complete response rates to neoadjuvant chemotherapy with high significance. In univariate analyses for HR-positive tumors signatures, S3 (HRD, P < 0.001) and S13 (APOBEC, P = 0.001) as well as exonic mutation rate (P = 0.002) were significantly correlated with increased pathological complete response rates. The signatures S3 (HRD, P = 0.006) and S4 (tobacco, P = 0.011) were prognostic for reduced disease-free survival of patients with chemotherapy-resistant tumors.
CONCLUSION
The results of this investigation suggest that the clinical behavior of a tumor, in particular, response to neoadjuvant chemotherapy and disease-free survival of therapy-resistant tumors, could be predicted by the composition of mutational signatures as an indicator of the individual genomic history of a tumor. After additional validations, mutational signatures might be used to identify tumors with an increased response rate to neoadjuvant chemotherapy and to define therapy-resistant subgroups for future therapeutic interventions.
Identifiants
pubmed: 33418062
pii: S0923-7534(20)43224-7
doi: 10.1016/j.annonc.2020.12.016
pii:
doi:
Types de publication
Journal Article
Multicenter Study
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
500-511Informations de copyright
Copyright © 2021 European Society for Medical Oncology. Published by Elsevier Ltd. All rights reserved.
Déclaration de conflit d'intérêts
Disclosure CD reports personal fees from Novartis, personal fees and travel support from Roche, personal fees from MSD Oncology, from Daiichi Sankyo, grants from Myriad Genetics and GBG, other from Sividon Diagnostics/Myriad, outside the submitted work. In addition, CD has a patent EP18209672 pending, a patent EP20150702464 pending and a patent Software (VMscope digital pathology) pending. MU reports personal fees and non-financial support from Abbvie, personal fees and non-financial support from Amgen GmbH, personal fees and non-financial support from AstraZeneca, personal fees from Bristol Myers Squibb (BMS), personal fees and non-financial support from Celgene GmbH, personal fees and non-financial support from Daiji Sankyo, personal fees and non-financial support from Eisai GmbH, personal fees from Lilly Deutschland, personal fees and non-financial support from Lilly Int., personal fees and non-financial support from MSD Merck, personal fees and non-financial support from Mundipharma, personal fees and non-financial support from Myriad Genetics, personal fees and non-financial support from Odonate, personal fees and non-financial support from Pfizer GmbH, personal fees from PUMA Biotechnology, personal fees and non-financial support from Roche Pharma AG, personal fees and non-financial support from Sanofi Aventis Deutschland GmbH, personal fees and non-financial support from TEVA Pharmaceuticals Ind Ltd, personal fees and non-financial support from Novartis, personal fees from Pierre Fabre, personal fees and non-financial support from Clovis Oncology, outside the submitted work. SB reports other from NantOmics, LLC, during the conduct of the study; other from NantOmics, LLC, outside the submitted work; and Employee of NantOmics, LLC with equity interest. AS reports grants from Celgene, grants from Roche, grants from AbbVie, grants from Molecular Partner, personal fees from Roche, personal fees from AstraZeneca, personal fees from Celgene, personal fees from Roche, personal fees from Celgene, personal fees from Pfizer, personal fees from AstraZeneca, personal fees from Novartis, personal fees from MSD, personal fees from Tesaro, personal fees from Lilly, other from Roche, outside the submitted work. CJ reports personal fees from Roche, personal fees from Celgene, personal fees from Amgen, during the conduct of the study. TL reports non-financial support from Pharma Mar, non-financial support from Daiichi Sankyo, personal fees and non-financial support from MSD, personal fees from Amgen, personal fees and non-financial support from Pfizer, personal fees from Novartis, personal fees from Teva, personal fees from Tesaro, personal fees and non-financial support from Roche, personal fees and non-financial support from Clovis, non-financial support from Celgene, outside the submitted work. WDS reports grants from German Breast Group, during the conduct of the study; personal fees from AstraZeneca, outside the submitted work. VM reports grants and personal fees from Roche, during the conduct of the study; personal fees from Amgen, Astra Zeneca, Daiichi-Sankyo, Eisai, Pfizer, MSD, Novartis, Roche, Teva, Seattle Genetics and consultancy honoraria from Genomic Health, Hexal, Roche, Pierre Fabre, Amgen, ClinSol, Novartis, MSD, Daiichi-Sankyo, Eisai, Lilly, Tesaro, Nektar, personal fees from Genomic Health, Hexal, Roche, Pierre Fabre, Amgen, ClinSol, Novartis, MSD, Daiichi-Sankyo, Eisai, Lilly, Tesaro and Nektar, other from I Novartis, Roche, Seattle Genetics, Genentech, outside the submitted work. PSS is the CEO of NantOmics and reports non-financial support from NantOmics, outside the submitted work. MvM reports honoraria from Roche, Amgen, Genomic Health, Astra Zeneca, as well as travel support from Lilly and Novartis. PAF reports grants from Novartis, grants from BioNTech, personal fees from Novartis, personal fees from Roche, personal fees from Pfizer, personal fees from Celgene, personal fees from Daiichi-Sankyo, personal fees from AstraZeneca, personal fees from Merck Sharp & Dohme, personal fees from Eisai, personal fees from Puma, grants from Cepheid, personal fees from Lilly, personal fees from Seattle Genetics, during the conduct of the study. SR is the Chief Scientific Officer for NantOmics and reports non-financial support from NantOmics, outside the submitted work. SL reports grants and other from Celgene, grants and other from Roche, during the conduct of the study; grants and other from Abbvie, grants and other from Amgen, grants and other from AstraZeneca, grants and other from Novartis, grants and other from Pfizer, other from Seattle Genetics, other from PriME/Medscape, personal fees from Chugai, grants from Teva, grants from Vifor, grants and other from Daiichi-Sankyo, other from Lilly, other from Samsung, other from Eirgenix, other from BMS, other from Puma, other from MSD, grants from Immunomedics, outside the submitted work. In addition, SL has a patent EP14153692.0 pending. All other authors have declared no conflicts of interest.