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LobSig is a multigene predictor of outcome in invasive lobular carcinoma
Invasive lobular carcinoma (ILC) is the most common special type of breast cancer, and is characterized by functional loss of E-cadherin, resulting in cellular adhesion defects. ILC typically present as estrogen receptor positive, grade 2 breast cancers, with a good short-term prognosis. Several lar...
Autores principales: | , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6597578/ https://www.ncbi.nlm.nih.gov/pubmed/31263747 http://dx.doi.org/10.1038/s41523-019-0113-y |
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author | McCart Reed, Amy E. Lal, Samir Kutasovic, Jamie R. Wockner, Leesa Robertson, Alan de Luca, Xavier M. Kalita-de Croft, Priyakshi Dalley, Andrew J. Coorey, Craig P. Kuo, Luyu Ferguson, Kaltin Niland, Colleen Miller, Gregory Johnson, Julie Reid, Lynne E. Males, Renique Saunus, Jodi M. Chenevix-Trench, Georgia Coin, Lachlan Lakhani, Sunil R. Simpson, Peter T. |
author_facet | McCart Reed, Amy E. Lal, Samir Kutasovic, Jamie R. Wockner, Leesa Robertson, Alan de Luca, Xavier M. Kalita-de Croft, Priyakshi Dalley, Andrew J. Coorey, Craig P. Kuo, Luyu Ferguson, Kaltin Niland, Colleen Miller, Gregory Johnson, Julie Reid, Lynne E. Males, Renique Saunus, Jodi M. Chenevix-Trench, Georgia Coin, Lachlan Lakhani, Sunil R. Simpson, Peter T. |
author_sort | McCart Reed, Amy E. |
collection | PubMed |
description | Invasive lobular carcinoma (ILC) is the most common special type of breast cancer, and is characterized by functional loss of E-cadherin, resulting in cellular adhesion defects. ILC typically present as estrogen receptor positive, grade 2 breast cancers, with a good short-term prognosis. Several large-scale molecular profiling studies have now dissected the unique genomics of ILC. We have undertaken an integrative analysis of gene expression and DNA copy number to identify novel drivers and prognostic biomarkers, using in-house (n = 25), METABRIC (n = 125) and TCGA (n = 146) samples. Using in silico integrative analyses, a 194-gene set was derived that is highly prognostic in ILC (P = 1.20 × 10(−5))—we named this metagene ‘LobSig’. Assessing a 10-year follow-up period, LobSig outperformed the Nottingham Prognostic Index, PAM50 risk-of-recurrence (Prosigna), OncotypeDx, and Genomic Grade Index (MapQuantDx) in a stepwise, multivariate Cox proportional hazards model, particularly in grade 2 ILC cases (χ(2), P = 9.0 × 10(−6)), which are difficult to prognosticate clinically. Importantly, LobSig status predicted outcome with 94.6% accuracy amongst cases classified as ‘moderate-risk’ according to Nottingham Prognostic Index in the METABRIC cohort. Network analysis identified few candidate pathways, though genesets related to proliferation were identified, and a LobSig-high phenotype was associated with the TCGA proliferative subtype (χ(2), P < 8.86 × 10(−4)). ILC with a poor outcome as predicted by LobSig were enriched with mutations in ERBB2, ERBB3, TP53, AKT1 and ROS1. LobSig has the potential to be a clinically relevant prognostic signature and warrants further development. |
format | Online Article Text |
id | pubmed-6597578 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-65975782019-07-01 LobSig is a multigene predictor of outcome in invasive lobular carcinoma McCart Reed, Amy E. Lal, Samir Kutasovic, Jamie R. Wockner, Leesa Robertson, Alan de Luca, Xavier M. Kalita-de Croft, Priyakshi Dalley, Andrew J. Coorey, Craig P. Kuo, Luyu Ferguson, Kaltin Niland, Colleen Miller, Gregory Johnson, Julie Reid, Lynne E. Males, Renique Saunus, Jodi M. Chenevix-Trench, Georgia Coin, Lachlan Lakhani, Sunil R. Simpson, Peter T. NPJ Breast Cancer Article Invasive lobular carcinoma (ILC) is the most common special type of breast cancer, and is characterized by functional loss of E-cadherin, resulting in cellular adhesion defects. ILC typically present as estrogen receptor positive, grade 2 breast cancers, with a good short-term prognosis. Several large-scale molecular profiling studies have now dissected the unique genomics of ILC. We have undertaken an integrative analysis of gene expression and DNA copy number to identify novel drivers and prognostic biomarkers, using in-house (n = 25), METABRIC (n = 125) and TCGA (n = 146) samples. Using in silico integrative analyses, a 194-gene set was derived that is highly prognostic in ILC (P = 1.20 × 10(−5))—we named this metagene ‘LobSig’. Assessing a 10-year follow-up period, LobSig outperformed the Nottingham Prognostic Index, PAM50 risk-of-recurrence (Prosigna), OncotypeDx, and Genomic Grade Index (MapQuantDx) in a stepwise, multivariate Cox proportional hazards model, particularly in grade 2 ILC cases (χ(2), P = 9.0 × 10(−6)), which are difficult to prognosticate clinically. Importantly, LobSig status predicted outcome with 94.6% accuracy amongst cases classified as ‘moderate-risk’ according to Nottingham Prognostic Index in the METABRIC cohort. Network analysis identified few candidate pathways, though genesets related to proliferation were identified, and a LobSig-high phenotype was associated with the TCGA proliferative subtype (χ(2), P < 8.86 × 10(−4)). ILC with a poor outcome as predicted by LobSig were enriched with mutations in ERBB2, ERBB3, TP53, AKT1 and ROS1. LobSig has the potential to be a clinically relevant prognostic signature and warrants further development. Nature Publishing Group UK 2019-06-27 /pmc/articles/PMC6597578/ /pubmed/31263747 http://dx.doi.org/10.1038/s41523-019-0113-y Text en © The Author(s) 2019 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 McCart Reed, Amy E. Lal, Samir Kutasovic, Jamie R. Wockner, Leesa Robertson, Alan de Luca, Xavier M. Kalita-de Croft, Priyakshi Dalley, Andrew J. Coorey, Craig P. Kuo, Luyu Ferguson, Kaltin Niland, Colleen Miller, Gregory Johnson, Julie Reid, Lynne E. Males, Renique Saunus, Jodi M. Chenevix-Trench, Georgia Coin, Lachlan Lakhani, Sunil R. Simpson, Peter T. LobSig is a multigene predictor of outcome in invasive lobular carcinoma |
title | LobSig is a multigene predictor of outcome in invasive lobular carcinoma |
title_full | LobSig is a multigene predictor of outcome in invasive lobular carcinoma |
title_fullStr | LobSig is a multigene predictor of outcome in invasive lobular carcinoma |
title_full_unstemmed | LobSig is a multigene predictor of outcome in invasive lobular carcinoma |
title_short | LobSig is a multigene predictor of outcome in invasive lobular carcinoma |
title_sort | lobsig is a multigene predictor of outcome in invasive lobular carcinoma |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6597578/ https://www.ncbi.nlm.nih.gov/pubmed/31263747 http://dx.doi.org/10.1038/s41523-019-0113-y |
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