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Development and validation for research assessment of Oncotype DX® Breast Recurrence Score, EndoPredict® and Prosigna®

Multi-gene prognostic signatures including the Oncotype® DX Recurrence Score (RS), EndoPredict® (EP) and Prosigna® (Risk Of Recurrence, ROR) are widely used to predict the likelihood of distant recurrence in patients with oestrogen-receptor-positive (ER+), HER2-negative breast cancer. Here, we descr...

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Autores principales: Buus, Richard, Szijgyarto, Zsolt, Schuster, Eugene F., Xiao, Hui, Haynes, Ben P., Sestak, Ivana, Cuzick, Jack, Paré, Laia, Seguí, Elia, Chic, Nuria, Prat, Aleix, Dowsett, Mitch, Cheang, Maggie Chon U.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7881187/
https://www.ncbi.nlm.nih.gov/pubmed/33579961
http://dx.doi.org/10.1038/s41523-021-00216-w
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author Buus, Richard
Szijgyarto, Zsolt
Schuster, Eugene F.
Xiao, Hui
Haynes, Ben P.
Sestak, Ivana
Cuzick, Jack
Paré, Laia
Seguí, Elia
Chic, Nuria
Prat, Aleix
Dowsett, Mitch
Cheang, Maggie Chon U.
author_facet Buus, Richard
Szijgyarto, Zsolt
Schuster, Eugene F.
Xiao, Hui
Haynes, Ben P.
Sestak, Ivana
Cuzick, Jack
Paré, Laia
Seguí, Elia
Chic, Nuria
Prat, Aleix
Dowsett, Mitch
Cheang, Maggie Chon U.
author_sort Buus, Richard
collection PubMed
description Multi-gene prognostic signatures including the Oncotype® DX Recurrence Score (RS), EndoPredict® (EP) and Prosigna® (Risk Of Recurrence, ROR) are widely used to predict the likelihood of distant recurrence in patients with oestrogen-receptor-positive (ER+), HER2-negative breast cancer. Here, we describe the development and validation of methods to recapitulate RS, EP and ROR scores from NanoString expression data. RNA was available from 107 tumours from postmenopausal women with early-stage, ER+, HER2− breast cancer from the translational Arimidex, Tamoxifen, Alone or in Combination study (TransATAC) where previously these signatures had been assessed with commercial methodology. Gene expression was measured using NanoString nCounter. For RS and EP, conversion factors to adjust for cross-platform variation were estimated using linear regression. For ROR, the steps to perform subgroup-specific normalisation of the gene expression data and calibration factors to calculate the 46-gene ROR score were assessed and verified. Training with bootstrapping (n = 59) was followed by validation (n = 48) using adjusted, research use only (RUO) NanoString-based algorithms. In the validation set, there was excellent concordance between the RUO scores and their commercial counterparts (r(c)(RS) = 0.96, 95% CI 0.93–0.97 with level of agreement (LoA) of −7.69 to 8.12; r(c)(EP) = 0.97, 95% CI 0.96–0.98 with LoA of −0.64 to 1.26 and r(c)(ROR) = 0.97 (95% CI 0.94–0.98) with LoA of −8.65 to 10.54). There was also a strong agreement in risk stratification: (RS: κ = 0.86, p < 0.0001; EP: κ = 0.87, p < 0.0001; ROR: κ = 0.92, p < 0.001). In conclusion, the calibrated algorithms recapitulate the commercial RS and EP scores on individual biopsies and ROR scores on samples based on subgroup-centreing method using NanoString expression data.
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spelling pubmed-78811872021-02-25 Development and validation for research assessment of Oncotype DX® Breast Recurrence Score, EndoPredict® and Prosigna® Buus, Richard Szijgyarto, Zsolt Schuster, Eugene F. Xiao, Hui Haynes, Ben P. Sestak, Ivana Cuzick, Jack Paré, Laia Seguí, Elia Chic, Nuria Prat, Aleix Dowsett, Mitch Cheang, Maggie Chon U. NPJ Breast Cancer Article Multi-gene prognostic signatures including the Oncotype® DX Recurrence Score (RS), EndoPredict® (EP) and Prosigna® (Risk Of Recurrence, ROR) are widely used to predict the likelihood of distant recurrence in patients with oestrogen-receptor-positive (ER+), HER2-negative breast cancer. Here, we describe the development and validation of methods to recapitulate RS, EP and ROR scores from NanoString expression data. RNA was available from 107 tumours from postmenopausal women with early-stage, ER+, HER2− breast cancer from the translational Arimidex, Tamoxifen, Alone or in Combination study (TransATAC) where previously these signatures had been assessed with commercial methodology. Gene expression was measured using NanoString nCounter. For RS and EP, conversion factors to adjust for cross-platform variation were estimated using linear regression. For ROR, the steps to perform subgroup-specific normalisation of the gene expression data and calibration factors to calculate the 46-gene ROR score were assessed and verified. Training with bootstrapping (n = 59) was followed by validation (n = 48) using adjusted, research use only (RUO) NanoString-based algorithms. In the validation set, there was excellent concordance between the RUO scores and their commercial counterparts (r(c)(RS) = 0.96, 95% CI 0.93–0.97 with level of agreement (LoA) of −7.69 to 8.12; r(c)(EP) = 0.97, 95% CI 0.96–0.98 with LoA of −0.64 to 1.26 and r(c)(ROR) = 0.97 (95% CI 0.94–0.98) with LoA of −8.65 to 10.54). There was also a strong agreement in risk stratification: (RS: κ = 0.86, p < 0.0001; EP: κ = 0.87, p < 0.0001; ROR: κ = 0.92, p < 0.001). In conclusion, the calibrated algorithms recapitulate the commercial RS and EP scores on individual biopsies and ROR scores on samples based on subgroup-centreing method using NanoString expression data. Nature Publishing Group UK 2021-02-12 /pmc/articles/PMC7881187/ /pubmed/33579961 http://dx.doi.org/10.1038/s41523-021-00216-w Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Buus, Richard
Szijgyarto, Zsolt
Schuster, Eugene F.
Xiao, Hui
Haynes, Ben P.
Sestak, Ivana
Cuzick, Jack
Paré, Laia
Seguí, Elia
Chic, Nuria
Prat, Aleix
Dowsett, Mitch
Cheang, Maggie Chon U.
Development and validation for research assessment of Oncotype DX® Breast Recurrence Score, EndoPredict® and Prosigna®
title Development and validation for research assessment of Oncotype DX® Breast Recurrence Score, EndoPredict® and Prosigna®
title_full Development and validation for research assessment of Oncotype DX® Breast Recurrence Score, EndoPredict® and Prosigna®
title_fullStr Development and validation for research assessment of Oncotype DX® Breast Recurrence Score, EndoPredict® and Prosigna®
title_full_unstemmed Development and validation for research assessment of Oncotype DX® Breast Recurrence Score, EndoPredict® and Prosigna®
title_short Development and validation for research assessment of Oncotype DX® Breast Recurrence Score, EndoPredict® and Prosigna®
title_sort development and validation for research assessment of oncotype dx® breast recurrence score, endopredict® and prosigna®
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7881187/
https://www.ncbi.nlm.nih.gov/pubmed/33579961
http://dx.doi.org/10.1038/s41523-021-00216-w
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