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Classification and risk stratification of invasive breast carcinomas using a real-time quantitative RT-PCR assay

INTRODUCTION: Predicting the clinical course of breast cancer is often difficult because it is a diverse disease comprised of many biological subtypes. Gene expression profiling by microarray analysis has identified breast cancer signatures that are important for prognosis and treatment. In the curr...

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Autores principales: Perreard, Laurent, Fan, Cheng, Quackenbush, John F, Mullins, Michael, Gauthier, Nicholas P, Nelson, Edward, Mone, Mary, Hansen, Heidi, Buys, Saundra S, Rasmussen, Karen, Orrico, Alejandra Ruiz, Dreher, Donna, Walters, Rhonda, Parker, Joel, Hu, Zhiyuan, He, Xiaping, Palazzo, Juan P, Olopade, Olufunmilayo I, Szabo, Aniko, Perou, Charles M, Bernard, Philip S
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2006
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1557722/
https://www.ncbi.nlm.nih.gov/pubmed/16626501
http://dx.doi.org/10.1186/bcr1399
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author Perreard, Laurent
Fan, Cheng
Quackenbush, John F
Mullins, Michael
Gauthier, Nicholas P
Nelson, Edward
Mone, Mary
Hansen, Heidi
Buys, Saundra S
Rasmussen, Karen
Orrico, Alejandra Ruiz
Dreher, Donna
Walters, Rhonda
Parker, Joel
Hu, Zhiyuan
He, Xiaping
Palazzo, Juan P
Olopade, Olufunmilayo I
Szabo, Aniko
Perou, Charles M
Bernard, Philip S
author_facet Perreard, Laurent
Fan, Cheng
Quackenbush, John F
Mullins, Michael
Gauthier, Nicholas P
Nelson, Edward
Mone, Mary
Hansen, Heidi
Buys, Saundra S
Rasmussen, Karen
Orrico, Alejandra Ruiz
Dreher, Donna
Walters, Rhonda
Parker, Joel
Hu, Zhiyuan
He, Xiaping
Palazzo, Juan P
Olopade, Olufunmilayo I
Szabo, Aniko
Perou, Charles M
Bernard, Philip S
author_sort Perreard, Laurent
collection PubMed
description INTRODUCTION: Predicting the clinical course of breast cancer is often difficult because it is a diverse disease comprised of many biological subtypes. Gene expression profiling by microarray analysis has identified breast cancer signatures that are important for prognosis and treatment. In the current article, we use microarray analysis and a real-time quantitative reverse-transcription (qRT)-PCR assay to risk-stratify breast cancers based on biological 'intrinsic' subtypes and proliferation. METHODS: Gene sets were selected from microarray data to assess proliferation and to classify breast cancers into four different molecular subtypes, designated Luminal, Normal-like, HER2+/ER-, and Basal-like. One-hundred and twenty-three breast samples (117 invasive carcinomas, one fibroadenoma and five normal tissues) and three breast cancer cell lines were prospectively analyzed using a microarray (Agilent) and a qRT-PCR assay comprised of 53 genes. Biological subtypes were assigned from the microarray and qRT-PCR data by hierarchical clustering. A proliferation signature was used as a single meta-gene (log(2 )average of 14 genes) to predict outcome within the context of estrogen receptor status and biological 'intrinsic' subtype. RESULTS: We found that the qRT-PCR assay could determine the intrinsic subtype (93% concordance with microarray-based assignments) and that the intrinsic subtypes were predictive of outcome. The proliferation meta-gene provided additional prognostic information for patients with the Luminal subtype (P = 0.0012), and for patients with estrogen receptor-positive tumors (P = 3.4 × 10(-6)). High proliferation in the Luminal subtype conferred a 19-fold relative risk of relapse (confidence interval = 95%) compared with Luminal tumors with low proliferation. CONCLUSION: A real-time qRT-PCR assay can recapitulate microarray classifications of breast cancer and can risk-stratify patients using the intrinsic subtype and proliferation. The proliferation meta-gene offers an objective and quantitative measurement for grade and adds significant prognostic information to the biological subtypes.
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spelling pubmed-15577222006-09-01 Classification and risk stratification of invasive breast carcinomas using a real-time quantitative RT-PCR assay Perreard, Laurent Fan, Cheng Quackenbush, John F Mullins, Michael Gauthier, Nicholas P Nelson, Edward Mone, Mary Hansen, Heidi Buys, Saundra S Rasmussen, Karen Orrico, Alejandra Ruiz Dreher, Donna Walters, Rhonda Parker, Joel Hu, Zhiyuan He, Xiaping Palazzo, Juan P Olopade, Olufunmilayo I Szabo, Aniko Perou, Charles M Bernard, Philip S Breast Cancer Res Research Article INTRODUCTION: Predicting the clinical course of breast cancer is often difficult because it is a diverse disease comprised of many biological subtypes. Gene expression profiling by microarray analysis has identified breast cancer signatures that are important for prognosis and treatment. In the current article, we use microarray analysis and a real-time quantitative reverse-transcription (qRT)-PCR assay to risk-stratify breast cancers based on biological 'intrinsic' subtypes and proliferation. METHODS: Gene sets were selected from microarray data to assess proliferation and to classify breast cancers into four different molecular subtypes, designated Luminal, Normal-like, HER2+/ER-, and Basal-like. One-hundred and twenty-three breast samples (117 invasive carcinomas, one fibroadenoma and five normal tissues) and three breast cancer cell lines were prospectively analyzed using a microarray (Agilent) and a qRT-PCR assay comprised of 53 genes. Biological subtypes were assigned from the microarray and qRT-PCR data by hierarchical clustering. A proliferation signature was used as a single meta-gene (log(2 )average of 14 genes) to predict outcome within the context of estrogen receptor status and biological 'intrinsic' subtype. RESULTS: We found that the qRT-PCR assay could determine the intrinsic subtype (93% concordance with microarray-based assignments) and that the intrinsic subtypes were predictive of outcome. The proliferation meta-gene provided additional prognostic information for patients with the Luminal subtype (P = 0.0012), and for patients with estrogen receptor-positive tumors (P = 3.4 × 10(-6)). High proliferation in the Luminal subtype conferred a 19-fold relative risk of relapse (confidence interval = 95%) compared with Luminal tumors with low proliferation. CONCLUSION: A real-time qRT-PCR assay can recapitulate microarray classifications of breast cancer and can risk-stratify patients using the intrinsic subtype and proliferation. The proliferation meta-gene offers an objective and quantitative measurement for grade and adds significant prognostic information to the biological subtypes. BioMed Central 2006 2006-04-20 /pmc/articles/PMC1557722/ /pubmed/16626501 http://dx.doi.org/10.1186/bcr1399 Text en Copyright © 2006 Perreard et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Perreard, Laurent
Fan, Cheng
Quackenbush, John F
Mullins, Michael
Gauthier, Nicholas P
Nelson, Edward
Mone, Mary
Hansen, Heidi
Buys, Saundra S
Rasmussen, Karen
Orrico, Alejandra Ruiz
Dreher, Donna
Walters, Rhonda
Parker, Joel
Hu, Zhiyuan
He, Xiaping
Palazzo, Juan P
Olopade, Olufunmilayo I
Szabo, Aniko
Perou, Charles M
Bernard, Philip S
Classification and risk stratification of invasive breast carcinomas using a real-time quantitative RT-PCR assay
title Classification and risk stratification of invasive breast carcinomas using a real-time quantitative RT-PCR assay
title_full Classification and risk stratification of invasive breast carcinomas using a real-time quantitative RT-PCR assay
title_fullStr Classification and risk stratification of invasive breast carcinomas using a real-time quantitative RT-PCR assay
title_full_unstemmed Classification and risk stratification of invasive breast carcinomas using a real-time quantitative RT-PCR assay
title_short Classification and risk stratification of invasive breast carcinomas using a real-time quantitative RT-PCR assay
title_sort classification and risk stratification of invasive breast carcinomas using a real-time quantitative rt-pcr assay
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1557722/
https://www.ncbi.nlm.nih.gov/pubmed/16626501
http://dx.doi.org/10.1186/bcr1399
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