Cargando…

Novel 18-gene signature for predicting relapse in ER-positive, HER2-negative breast cancer

BACKGROUND: Several prognostic signatures for early oestrogen receptor-positive (ER+) breast cancer have been established with a 10-year follow-up. We tested the hypothesis that signatures optimised for 0–5-year and 5–10-year follow-up separately are more prognostic than a single signature optimised...

Descripción completa

Detalles Bibliográficos
Autores principales: Buus, Richard, Yeo, Belinda, Brentnall, Adam R., Klintman, Marie, Cheang, Maggie Chon U., Khabra, Komel, Sestak, Ivana, Gao, Qiong, Cuzick, Jack, Dowsett, Mitch
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6122470/
https://www.ncbi.nlm.nih.gov/pubmed/30180877
http://dx.doi.org/10.1186/s13058-018-1040-9
_version_ 1783352663217274880
author Buus, Richard
Yeo, Belinda
Brentnall, Adam R.
Klintman, Marie
Cheang, Maggie Chon U.
Khabra, Komel
Sestak, Ivana
Gao, Qiong
Cuzick, Jack
Dowsett, Mitch
author_facet Buus, Richard
Yeo, Belinda
Brentnall, Adam R.
Klintman, Marie
Cheang, Maggie Chon U.
Khabra, Komel
Sestak, Ivana
Gao, Qiong
Cuzick, Jack
Dowsett, Mitch
author_sort Buus, Richard
collection PubMed
description BACKGROUND: Several prognostic signatures for early oestrogen receptor-positive (ER+) breast cancer have been established with a 10-year follow-up. We tested the hypothesis that signatures optimised for 0–5-year and 5–10-year follow-up separately are more prognostic than a single signature optimised for 10 years. METHODS: Genes previously identified as prognostic or associated with endocrine resistance were tested in publicly available microarray data set using Cox regression of 747 ER+/HER2− samples from post-menopausal patients treated with 5 years of endocrine therapy. RNA expression of the selected genes was assayed in primary ER+/HER2− tumours from 948 post-menopausal patients treated with 5 years of anastrozole or tamoxifen in the TransATAC cohort. Prognostic signatures for 0–10, 0–5 and 5–10 years were derived using a penalised Cox regression (elastic net). Signature comparison was performed with likelihood ratio statistics. Validation was done by a case-control (POLAR) study in 422 samples derived from a cohort of 1449. RESULTS: Ninety-three genes were selected by the modelling of microarray data; 63 of these were significantly prognostic in TransATAC, most similarly across each time period. Contrary to our hypothesis, the derived early and late signatures were not significantly more prognostic than the 18-gene 10-year signature. The 18-gene 10-year signature was internally validated in the TransATAC validation set, showing prognostic information similar to that of Oncotype DX Recurrence Score, PAM50 risk of recurrence score, Breast Cancer Index and IHC4 (score based on four IHC markers), as well as in the external POLAR case-control set. CONCLUSIONS: The derived 10-year signature predicts risk of metastasis in patients with ER+/HER2− breast cancer similar to commercial signatures. The hypothesis that early and late prognostic signatures are significantly more informative than a single signature was rejected. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13058-018-1040-9) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-6122470
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-61224702018-09-05 Novel 18-gene signature for predicting relapse in ER-positive, HER2-negative breast cancer Buus, Richard Yeo, Belinda Brentnall, Adam R. Klintman, Marie Cheang, Maggie Chon U. Khabra, Komel Sestak, Ivana Gao, Qiong Cuzick, Jack Dowsett, Mitch Breast Cancer Res Research Article BACKGROUND: Several prognostic signatures for early oestrogen receptor-positive (ER+) breast cancer have been established with a 10-year follow-up. We tested the hypothesis that signatures optimised for 0–5-year and 5–10-year follow-up separately are more prognostic than a single signature optimised for 10 years. METHODS: Genes previously identified as prognostic or associated with endocrine resistance were tested in publicly available microarray data set using Cox regression of 747 ER+/HER2− samples from post-menopausal patients treated with 5 years of endocrine therapy. RNA expression of the selected genes was assayed in primary ER+/HER2− tumours from 948 post-menopausal patients treated with 5 years of anastrozole or tamoxifen in the TransATAC cohort. Prognostic signatures for 0–10, 0–5 and 5–10 years were derived using a penalised Cox regression (elastic net). Signature comparison was performed with likelihood ratio statistics. Validation was done by a case-control (POLAR) study in 422 samples derived from a cohort of 1449. RESULTS: Ninety-three genes were selected by the modelling of microarray data; 63 of these were significantly prognostic in TransATAC, most similarly across each time period. Contrary to our hypothesis, the derived early and late signatures were not significantly more prognostic than the 18-gene 10-year signature. The 18-gene 10-year signature was internally validated in the TransATAC validation set, showing prognostic information similar to that of Oncotype DX Recurrence Score, PAM50 risk of recurrence score, Breast Cancer Index and IHC4 (score based on four IHC markers), as well as in the external POLAR case-control set. CONCLUSIONS: The derived 10-year signature predicts risk of metastasis in patients with ER+/HER2− breast cancer similar to commercial signatures. The hypothesis that early and late prognostic signatures are significantly more informative than a single signature was rejected. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13058-018-1040-9) contains supplementary material, which is available to authorized users. BioMed Central 2018-09-04 2018 /pmc/articles/PMC6122470/ /pubmed/30180877 http://dx.doi.org/10.1186/s13058-018-1040-9 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
Buus, Richard
Yeo, Belinda
Brentnall, Adam R.
Klintman, Marie
Cheang, Maggie Chon U.
Khabra, Komel
Sestak, Ivana
Gao, Qiong
Cuzick, Jack
Dowsett, Mitch
Novel 18-gene signature for predicting relapse in ER-positive, HER2-negative breast cancer
title Novel 18-gene signature for predicting relapse in ER-positive, HER2-negative breast cancer
title_full Novel 18-gene signature for predicting relapse in ER-positive, HER2-negative breast cancer
title_fullStr Novel 18-gene signature for predicting relapse in ER-positive, HER2-negative breast cancer
title_full_unstemmed Novel 18-gene signature for predicting relapse in ER-positive, HER2-negative breast cancer
title_short Novel 18-gene signature for predicting relapse in ER-positive, HER2-negative breast cancer
title_sort novel 18-gene signature for predicting relapse in er-positive, her2-negative breast cancer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6122470/
https://www.ncbi.nlm.nih.gov/pubmed/30180877
http://dx.doi.org/10.1186/s13058-018-1040-9
work_keys_str_mv AT buusrichard novel18genesignatureforpredictingrelapseinerpositiveher2negativebreastcancer
AT yeobelinda novel18genesignatureforpredictingrelapseinerpositiveher2negativebreastcancer
AT brentnalladamr novel18genesignatureforpredictingrelapseinerpositiveher2negativebreastcancer
AT klintmanmarie novel18genesignatureforpredictingrelapseinerpositiveher2negativebreastcancer
AT cheangmaggiechonu novel18genesignatureforpredictingrelapseinerpositiveher2negativebreastcancer
AT khabrakomel novel18genesignatureforpredictingrelapseinerpositiveher2negativebreastcancer
AT sestakivana novel18genesignatureforpredictingrelapseinerpositiveher2negativebreastcancer
AT gaoqiong novel18genesignatureforpredictingrelapseinerpositiveher2negativebreastcancer
AT cuzickjack novel18genesignatureforpredictingrelapseinerpositiveher2negativebreastcancer
AT dowsettmitch novel18genesignatureforpredictingrelapseinerpositiveher2negativebreastcancer