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

Authors :
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
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
Source :
Department of Pathology, Anatomy, and Cell Biology Faculty Papers
Publication Year :
2006

Abstract

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 (log2 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 x 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

Details

Database :
OAIster
Journal :
Department of Pathology, Anatomy, and Cell Biology Faculty Papers
Notes :
application/pdf
Publication Type :
Electronic Resource
Accession number :
edsoai.ocn857634785
Document Type :
Electronic Resource