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Identification and validation of single-sample breast cancer radiosensitivity gene expression predictors
BACKGROUND: Adjuvant radiotherapy is the standard of care after breast-conserving surgery for primary breast cancer, despite a majority of patients being over- or under-treated. In contrast to adjuvant endocrine therapy and chemotherapy, no diagnostic tests are in clinical use that can stratify pati...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6033283/ https://www.ncbi.nlm.nih.gov/pubmed/29973242 http://dx.doi.org/10.1186/s13058-018-0978-y |
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author | Sjöström, Martin Staaf, Johan Edén, Patrik Wärnberg, Fredrik Bergh, Jonas Malmström, Per Fernö, Mårten Niméus, Emma Fredriksson, Irma |
author_facet | Sjöström, Martin Staaf, Johan Edén, Patrik Wärnberg, Fredrik Bergh, Jonas Malmström, Per Fernö, Mårten Niméus, Emma Fredriksson, Irma |
author_sort | Sjöström, Martin |
collection | PubMed |
description | BACKGROUND: Adjuvant radiotherapy is the standard of care after breast-conserving surgery for primary breast cancer, despite a majority of patients being over- or under-treated. In contrast to adjuvant endocrine therapy and chemotherapy, no diagnostic tests are in clinical use that can stratify patients for adjuvant radiotherapy. This study presents the development and validation of a targeted gene expression assay to predict the risk of ipsilateral breast tumor recurrence and response to adjuvant radiotherapy after breast-conserving surgery in primary breast cancer. METHODS: Fresh-frozen primary tumors from 336 patients radically (clear margins) operated on with breast-conserving surgery with or without radiotherapy were collected. Patients were split into a discovery cohort (N = 172) and a validation cohort (N = 164). Genes predicting ipsilateral breast tumor recurrence in an Illumina HT12 v4 whole transcriptome analysis were combined with genes identified in the literature (248 genes in total) to develop a targeted radiosensitivity assay on the Nanostring nCounter platform. Single-sample predictors for ipsilateral breast tumor recurrence based on a k-top scoring pairs algorithm were trained, stratified for estrogen receptor (ER) status and radiotherapy. Two previously published profiles, the radiosensitivity signature of Speers et al., and the 10-gene signature of Eschrich et al., were also included in the targeted panel. RESULTS: Derived single-sample predictors were prognostic for ipsilateral breast tumor recurrence in radiotherapy-treated ER+ patients (AUC 0.67, p = 0.01), ER+ patients without radiotherapy (AUC = 0.89, p = 0.02), and radiotherapy-treated ER- patients (AUC = 0.78, p < 0.001). Among ER+ patients, radiotherapy had an excellent effect on tumors classified as radiosensitive (p < 0.001), while radiotherapy had no effect on tumors classified as radioresistant (p = 0.36) and there was a high risk of ipsilateral breast tumor recurrence (55% at 10 years). Our single-sample predictors developed in ER+ tumors and the radiosensitivity signature correlated with proliferation, while single-sample predictors developed in ER- tumors correlated with immune response. The 10-gene signature negatively correlated with both proliferation and immune response. CONCLUSIONS: Our targeted single-sample predictors were prognostic for ipsilateral breast tumor recurrence and have the potential to stratify patients for adjuvant radiotherapy. The correlation of models with biology may explain the different performance in subgroups of breast cancer. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13058-018-0978-y) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6033283 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-60332832018-07-12 Identification and validation of single-sample breast cancer radiosensitivity gene expression predictors Sjöström, Martin Staaf, Johan Edén, Patrik Wärnberg, Fredrik Bergh, Jonas Malmström, Per Fernö, Mårten Niméus, Emma Fredriksson, Irma Breast Cancer Res Research Article BACKGROUND: Adjuvant radiotherapy is the standard of care after breast-conserving surgery for primary breast cancer, despite a majority of patients being over- or under-treated. In contrast to adjuvant endocrine therapy and chemotherapy, no diagnostic tests are in clinical use that can stratify patients for adjuvant radiotherapy. This study presents the development and validation of a targeted gene expression assay to predict the risk of ipsilateral breast tumor recurrence and response to adjuvant radiotherapy after breast-conserving surgery in primary breast cancer. METHODS: Fresh-frozen primary tumors from 336 patients radically (clear margins) operated on with breast-conserving surgery with or without radiotherapy were collected. Patients were split into a discovery cohort (N = 172) and a validation cohort (N = 164). Genes predicting ipsilateral breast tumor recurrence in an Illumina HT12 v4 whole transcriptome analysis were combined with genes identified in the literature (248 genes in total) to develop a targeted radiosensitivity assay on the Nanostring nCounter platform. Single-sample predictors for ipsilateral breast tumor recurrence based on a k-top scoring pairs algorithm were trained, stratified for estrogen receptor (ER) status and radiotherapy. Two previously published profiles, the radiosensitivity signature of Speers et al., and the 10-gene signature of Eschrich et al., were also included in the targeted panel. RESULTS: Derived single-sample predictors were prognostic for ipsilateral breast tumor recurrence in radiotherapy-treated ER+ patients (AUC 0.67, p = 0.01), ER+ patients without radiotherapy (AUC = 0.89, p = 0.02), and radiotherapy-treated ER- patients (AUC = 0.78, p < 0.001). Among ER+ patients, radiotherapy had an excellent effect on tumors classified as radiosensitive (p < 0.001), while radiotherapy had no effect on tumors classified as radioresistant (p = 0.36) and there was a high risk of ipsilateral breast tumor recurrence (55% at 10 years). Our single-sample predictors developed in ER+ tumors and the radiosensitivity signature correlated with proliferation, while single-sample predictors developed in ER- tumors correlated with immune response. The 10-gene signature negatively correlated with both proliferation and immune response. CONCLUSIONS: Our targeted single-sample predictors were prognostic for ipsilateral breast tumor recurrence and have the potential to stratify patients for adjuvant radiotherapy. The correlation of models with biology may explain the different performance in subgroups of breast cancer. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13058-018-0978-y) contains supplementary material, which is available to authorized users. BioMed Central 2018-07-04 2018 /pmc/articles/PMC6033283/ /pubmed/29973242 http://dx.doi.org/10.1186/s13058-018-0978-y Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Sjöström, Martin Staaf, Johan Edén, Patrik Wärnberg, Fredrik Bergh, Jonas Malmström, Per Fernö, Mårten Niméus, Emma Fredriksson, Irma Identification and validation of single-sample breast cancer radiosensitivity gene expression predictors |
title | Identification and validation of single-sample breast cancer radiosensitivity gene expression predictors |
title_full | Identification and validation of single-sample breast cancer radiosensitivity gene expression predictors |
title_fullStr | Identification and validation of single-sample breast cancer radiosensitivity gene expression predictors |
title_full_unstemmed | Identification and validation of single-sample breast cancer radiosensitivity gene expression predictors |
title_short | Identification and validation of single-sample breast cancer radiosensitivity gene expression predictors |
title_sort | identification and validation of single-sample breast cancer radiosensitivity gene expression predictors |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6033283/ https://www.ncbi.nlm.nih.gov/pubmed/29973242 http://dx.doi.org/10.1186/s13058-018-0978-y |
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