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Clinicogenomic Radiotherapy Classifier Predicting the Need for Intensified Locoregional Treatment After Breast-Conserving Surgery for Early-Stage Breast Cancer.

Sjöström, Martin (författare)
Skåne University Hospital
Chang, S Laura (författare)
Fishbane, Nick (författare)
Decipher Biosciences Inc
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Davicioni, Elai (författare)
Decipher Biosciences Inc
Zhao, Shuang G (författare)
Hartman, Linda (författare)
Holmberg, Erik, 1951 (författare)
Gothenburg University,Göteborgs universitet,Institutionen för kliniska vetenskaper, Avdelningen för onkologi,Institute of Clinical Sciences, Department of Oncology,Sahlgrenska University Hospital
Feng, Felix Y (författare)
Speers, Corey W (författare)
Pierce, Lori J (författare)
Malmström, Per (författare)
Lund University,Lunds universitet,Tumörmikromiljö,Sektion I,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,Bröstca-genetik,Institutionen för kliniska vetenskaper, Lund,Tumor microenvironment,Section I,Department of Clinical Sciences, Lund,Faculty of Medicine,Breastca-genetics,Department of Clinical Sciences, Lund,Skåne University Hospital
Fernö, Mårten (författare)
Lund University,Lunds universitet,Bröstca-genetik,Sektion I,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,Individuell Bröstcancerbehandling,Forskargrupper vid Lunds universitet,LUCC - Lunds universitets cancercentrum,Övriga starka forskningsmiljöer,Breastca-genetics,Section I,Department of Clinical Sciences, Lund,Faculty of Medicine,Personalized Breast Cancer Treatment,Lund University Research Groups,LUCC - Lund University Cancer Centre,Other Strong Research Environments,Skåne University Hospital
Karlsson, Per, 1963 (författare)
Gothenburg University,Göteborgs universitet,Institutionen för kliniska vetenskaper, Avdelningen för onkologi,Institute of Clinical Sciences, Department of Oncology,Sahlgrenska University Hospital
Feng, Felix Y. (författare)
University of California, San Francisco
Laura Chang, S. (författare)
PFS Genomics INC
Speers, Corey W. (författare)
University of Michigan
Pierce, Lori J. (författare)
University of Michigan
Zhao, Shuang G. (författare)
University of Michigan
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American Society of Clinical Oncology, 2019
2019
Engelska.
Ingår i: Journal of clinical oncology : official journal of the American Society of Clinical Oncology. - : American Society of Clinical Oncology. - 1527-7755. ; 37:35, s. 3340-3349
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
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  • 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.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.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 (Pinteraction = .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.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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