Development and validation for research assessment of Oncotype DX® Breast Recurrence Score, EndoPredict® and Prosigna®.
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Embargo End Date
ICR Authors
Authors
Buus, R
Szijgyarto, Z
Schuster, EF
Xiao, H
Haynes, BP
Sestak, I
Cuzick, J
Paré, L
Seguí, E
Chic, N
Prat, A
Dowsett, M
Cheang, MCU
Szijgyarto, Z
Schuster, EF
Xiao, H
Haynes, BP
Sestak, I
Cuzick, J
Paré, L
Seguí, E
Chic, N
Prat, A
Dowsett, M
Cheang, MCU
Document Type
Journal Article
Date
2021-02-12
Date Accepted
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 (rc(RS) = 0.96, 95% CI 0.93-0.97 with level of agreement (LoA) of -7.69 to 8.12; rc(EP) = 0.97, 95% CI 0.96-0.98 with LoA of -0.64 to 1.26 and rc(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.
Citation
npj Breast Cancer
DOI
Source Title
Publisher
NATURE PORTFOLIO
ISSN
2374-4677
eISSN
Research Team
Genomic Analysis – Clinical Trials
Endocrinology
Endocrinology