Development and validation for research assessment of Oncotype DX® Breast Recurrence Score, EndoPredict® and Prosigna®
Abstract 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,...
| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2021-02-01
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| Series: | npj Breast Cancer |
| Online Access: | https://doi.org/10.1038/s41523-021-00216-w |
| _version_ | 1797423372872712192 |
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| author | Richard Buus Zsolt Szijgyarto Eugene F. Schuster Hui Xiao Ben P. Haynes Ivana Sestak Jack Cuzick Laia Paré Elia Seguí Nuria Chic Aleix Prat Mitch Dowsett Maggie Chon U. Cheang |
| author_facet | Richard Buus Zsolt Szijgyarto Eugene F. Schuster Hui Xiao Ben P. Haynes Ivana Sestak Jack Cuzick Laia Paré Elia Seguí Nuria Chic Aleix Prat Mitch Dowsett Maggie Chon U. Cheang |
| author_sort | Richard Buus |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-03-09T07:46:59Z |
| format | Article |
| id | doaj.art-ab6604a1505e46ae8d5a30ae6561a42c |
| institution | Directory Open Access Journal |
| issn | 2374-4677 |
| language | English |
| last_indexed | 2024-03-09T07:46:59Z |
| publishDate | 2021-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Breast Cancer |
| spelling | doaj.art-ab6604a1505e46ae8d5a30ae6561a42c2023-12-03T03:08:36ZengNature Portfolionpj Breast Cancer2374-46772021-02-01711810.1038/s41523-021-00216-wDevelopment and validation for research assessment of Oncotype DX® Breast Recurrence Score, EndoPredict® and Prosigna®Richard Buus0Zsolt Szijgyarto1Eugene F. Schuster2Hui Xiao3Ben P. Haynes4Ivana Sestak5Jack Cuzick6Laia Paré7Elia Seguí8Nuria Chic9Aleix Prat10Mitch Dowsett11Maggie Chon U. Cheang12Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer ResearchClinical Trials and Statistics Unit (ICR-CTSU), Division of Clinical Studies, The Institute of Cancer ResearchBreast Cancer Now Toby Robins Research Centre, The Institute of Cancer ResearchBreast Cancer Now Toby Robins Research Centre, The Institute of Cancer ResearchRalph Lauren Centre for Breast Cancer Research, Royal Marsden HospitalQueen Mary University of LondonQueen Mary University of LondonDepartment of Medical Oncology, Hospital ClinicDepartment of Medical Oncology, Hospital ClinicDepartment of Medical Oncology, Hospital ClinicDepartment of Medical Oncology, Hospital ClinicBreast Cancer Now Toby Robins Research Centre, The Institute of Cancer ResearchClinical Trials and Statistics Unit (ICR-CTSU), Division of Clinical Studies, The Institute of Cancer ResearchAbstract 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.https://doi.org/10.1038/s41523-021-00216-w |
| spellingShingle | Richard Buus Zsolt Szijgyarto Eugene F. Schuster Hui Xiao Ben P. Haynes Ivana Sestak Jack Cuzick Laia Paré Elia Seguí Nuria Chic Aleix Prat Mitch Dowsett Maggie Chon U. Cheang Development and validation for research assessment of Oncotype DX® Breast Recurrence Score, EndoPredict® and Prosigna® npj Breast Cancer |
| 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 r breast recurrence score endopredict r and prosigna r |
| url | https://doi.org/10.1038/s41523-021-00216-w |
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