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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society of Clinical Oncology 2019
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.
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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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