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Clinicogenomic Radiotherapy Classifier Predicting the Need for Intensified Locoregional Treatment After Breast-Conserving Surgery for Early-Stage Breast Cancer
PURPOSE: Most patients with early-stage breast cancer are treated with adjuvant radiotherapy (RT) after breast-conserving surgery (BCS) to prevent locoregional recurrence (LRR). However, no genomic tools are used currently to select the optimal RT strategy. METHODS: We profiled the transcriptome of...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Society of Clinical Oncology
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6901281/ https://www.ncbi.nlm.nih.gov/pubmed/31618132 http://dx.doi.org/10.1200/JCO.19.00761 |
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author | Sjöström, Martin Chang, S. Laura Fishbane, Nick Davicioni, Elai Zhao, Shuang G. Hartman, Linda Holmberg, Erik Feng, Felix Y. Speers, Corey W. Pierce, Lori J. Malmström, Per Fernö, Mårten Karlsson, Per |
author_facet | Sjöström, Martin Chang, S. Laura Fishbane, Nick Davicioni, Elai Zhao, Shuang G. Hartman, Linda Holmberg, Erik Feng, Felix Y. Speers, Corey W. Pierce, Lori J. Malmström, Per Fernö, Mårten Karlsson, Per |
author_sort | Sjöström, Martin |
collection | PubMed |
description | PURPOSE: Most patients with early-stage breast cancer are treated with adjuvant radiotherapy (RT) after breast-conserving surgery (BCS) to prevent locoregional recurrence (LRR). However, no genomic tools are used currently to select the optimal RT strategy. METHODS: We profiled the transcriptome of primary tumors on a clinical grade assay from the SweBCG91-RT trial, in which patients with node-negative breast cancer were randomly assigned to either whole-breast RT after BCS or no RT. We derived a new classifier, Adjuvant Radiotherapy Intensification Classifier (ARTIC), comprising 27 genes and patient age, in three publicly available cohorts, then independently validated ARTIC for LRR in 748 patients in SweBCG91-RT. We also compared previously published genomic signatures for ability to predict benefit from RT in SweBCG91-RT. RESULTS: ARTIC was highly prognostic for LRR in patients treated with RT (hazard ratio [HR], 3.4; 95% CI, 2.0 to 5.9; P < .001) and predictive of RT benefit (P(interaction) = .005). Patients with low ARTIC scores had a large benefit from RT (HR, 0.33 [95% CI, 0.21 to 0.52], P < .001; 10-year cumulative incidence of LRR, 6% v 21%), whereas those with high ARTIC scores benefited less from RT (HR, 0.73 [95% CI, 0.44 to 1.2], P = .23; 10-year cumulative incidence of LRR, 25% v 32%). In contrast, none of the eight previously published signatures were predictive of benefit from RT in SweBCG91-RT. CONCLUSION: ARTIC identified women with a substantial benefit from RT as well as women with a particularly elevated LRR risk in whom whole-breast RT was not sufficiently effective and, thus, in whom intensified treatment strategies such as tumor-bed boost, and possibly regional nodal RT, should be considered. To our knowledge, ARTIC is the first classifier validated as predictive of benefit from RT in a phase III clinical trial with patients randomly assigned to receive or not receive RT. |
format | Online Article Text |
id | pubmed-6901281 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | American Society of Clinical Oncology |
record_format | MEDLINE/PubMed |
spelling | pubmed-69012812020-12-10 Clinicogenomic Radiotherapy Classifier Predicting the Need for Intensified Locoregional Treatment After Breast-Conserving Surgery for Early-Stage Breast Cancer Sjöström, Martin Chang, S. Laura Fishbane, Nick Davicioni, Elai Zhao, Shuang G. Hartman, Linda Holmberg, Erik Feng, Felix Y. Speers, Corey W. Pierce, Lori J. Malmström, Per Fernö, Mårten Karlsson, Per J Clin Oncol ORIGINAL REPORTS PURPOSE: Most patients with early-stage breast cancer are treated with adjuvant radiotherapy (RT) after breast-conserving surgery (BCS) to prevent locoregional recurrence (LRR). However, no genomic tools are used currently to select the optimal RT strategy. METHODS: We profiled the transcriptome of primary tumors on a clinical grade assay from the SweBCG91-RT trial, in which patients with node-negative breast cancer were randomly assigned to either whole-breast RT after BCS or no RT. We derived a new classifier, Adjuvant Radiotherapy Intensification Classifier (ARTIC), comprising 27 genes and patient age, in three publicly available cohorts, then independently validated ARTIC for LRR in 748 patients in SweBCG91-RT. We also compared previously published genomic signatures for ability to predict benefit from RT in SweBCG91-RT. RESULTS: ARTIC was highly prognostic for LRR in patients treated with RT (hazard ratio [HR], 3.4; 95% CI, 2.0 to 5.9; P < .001) and predictive of RT benefit (P(interaction) = .005). Patients with low ARTIC scores had a large benefit from RT (HR, 0.33 [95% CI, 0.21 to 0.52], P < .001; 10-year cumulative incidence of LRR, 6% v 21%), whereas those with high ARTIC scores benefited less from RT (HR, 0.73 [95% CI, 0.44 to 1.2], P = .23; 10-year cumulative incidence of LRR, 25% v 32%). In contrast, none of the eight previously published signatures were predictive of benefit from RT in SweBCG91-RT. CONCLUSION: ARTIC identified women with a substantial benefit from RT as well as women with a particularly elevated LRR risk in whom whole-breast RT was not sufficiently effective and, thus, in whom intensified treatment strategies such as tumor-bed boost, and possibly regional nodal RT, should be considered. To our knowledge, ARTIC is the first classifier validated as predictive of benefit from RT in a phase III clinical trial with patients randomly assigned to receive or not receive RT. American Society of Clinical Oncology 2019-12-10 2019-10-16 /pmc/articles/PMC6901281/ /pubmed/31618132 http://dx.doi.org/10.1200/JCO.19.00761 Text en © 2019 by American Society of Clinical Oncology https://creativecommons.org/licenses/by-nc-nd/4.0/ Creative Commons Attribution Non-Commercial No Derivatives 4.0 License: https://creativecommons.org/licenses/by-nc-nd/4.0/ |
spellingShingle | ORIGINAL REPORTS Sjöström, Martin Chang, S. Laura Fishbane, Nick Davicioni, Elai Zhao, Shuang G. Hartman, Linda Holmberg, Erik Feng, Felix Y. Speers, Corey W. Pierce, Lori J. Malmström, Per Fernö, Mårten Karlsson, Per Clinicogenomic Radiotherapy Classifier Predicting the Need for Intensified Locoregional Treatment After Breast-Conserving Surgery for Early-Stage Breast Cancer |
title | Clinicogenomic Radiotherapy Classifier Predicting the Need for Intensified Locoregional Treatment After Breast-Conserving Surgery for Early-Stage Breast Cancer |
title_full | Clinicogenomic Radiotherapy Classifier Predicting the Need for Intensified Locoregional Treatment After Breast-Conserving Surgery for Early-Stage Breast Cancer |
title_fullStr | Clinicogenomic Radiotherapy Classifier Predicting the Need for Intensified Locoregional Treatment After Breast-Conserving Surgery for Early-Stage Breast Cancer |
title_full_unstemmed | Clinicogenomic Radiotherapy Classifier Predicting the Need for Intensified Locoregional Treatment After Breast-Conserving Surgery for Early-Stage Breast Cancer |
title_short | Clinicogenomic Radiotherapy Classifier Predicting the Need for Intensified Locoregional Treatment After Breast-Conserving Surgery for Early-Stage Breast Cancer |
title_sort | clinicogenomic radiotherapy classifier predicting the need for intensified locoregional treatment after breast-conserving surgery for early-stage breast cancer |
topic | ORIGINAL REPORTS |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6901281/ https://www.ncbi.nlm.nih.gov/pubmed/31618132 http://dx.doi.org/10.1200/JCO.19.00761 |
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