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Identification of Subtypes in Human Epidermal Growth Factor Receptor 2-Positive Breast Cancer Reveals a Gene Signature Prognostic of Outcome.

Staaf, Johan LU ; Ringnér, Markus LU ; Vallon-Christersson, Johan LU ; Jönsson, Göran B LU ; Bendahl, Pär-Ola LU ; Holm, Karolina LU ; Arason, Adalgeir; Gunnarsson, Haukur; Hegardt, Cecilia LU and Agnarsson, Bjarni A, et al. (2010) In Journal of Clinical Oncology 28(11). p.1813-1820
Abstract
PURPOSE: Human epidermal growth factor receptor 2 (HER2) gene amplification or protein overexpression (HER2 positivity) defines a clinically challenging subgroup of patients with breast cancer (BC) with variable prognosis and response to therapy. We aimed to investigate the heterogeneous biologic appearance and clinical behavior of HER2-positive tumors using molecular profiling. PATIENTS AND METHODS: Hierarchical clustering of gene expression data from 58 HER2-amplified tumors of various stage, histologic grade, and estrogen receptor (ER) status was used to construct a HER2-derived prognostic predictor that was further evaluated in several large independent BC data sets. RESULTS: Unsupervised analysis identified three subtypes of... (More)
PURPOSE: Human epidermal growth factor receptor 2 (HER2) gene amplification or protein overexpression (HER2 positivity) defines a clinically challenging subgroup of patients with breast cancer (BC) with variable prognosis and response to therapy. We aimed to investigate the heterogeneous biologic appearance and clinical behavior of HER2-positive tumors using molecular profiling. PATIENTS AND METHODS: Hierarchical clustering of gene expression data from 58 HER2-amplified tumors of various stage, histologic grade, and estrogen receptor (ER) status was used to construct a HER2-derived prognostic predictor that was further evaluated in several large independent BC data sets. RESULTS: Unsupervised analysis identified three subtypes of HER2-positive tumors with mixed stage, histologic grade, and ER status. One subtype had a significantly worse clinical outcome. A prognostic predictor was created based on differentially expressed genes between the subtype with worse outcome and the other subtypes. The predictor was able to define patient groups with better and worse outcome in HER2-positive BC across multiple independent BC data sets and identify a sizable HER2-positive group with long disease-free survival and low mortality. Significant correlation to prognosis was also observed in basal-like, ER-negative, lymph node-positive, and high-grade tumors, irrespective of HER2 status. The predictor included genes associated with immune response, tumor invasion, and metastasis. CONCLUSION: The HER2-derived prognostic predictor provides further insight into the heterogeneous biology of HER2-positive tumors and may become useful for improved selection of patients who need additional treatment with new drugs targeting the HER2 pathway. (Less)
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Contribution to journal
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published
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Journal of Clinical Oncology
volume
28
issue
11
pages
1813 - 1820
publisher
American Society of Clinical Oncology
external identifiers
  • wos:000276457800003
  • pmid:20231686
  • scopus:77951641554
ISSN
1527-7755
DOI
10.1200/JCO.2009.22.8775
project
CREATE Health
language
English
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yes
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60bb77cd-413a-4b12-93a1-439c289726b9 (old id 1582117)
alternative location
http://www.ncbi.nlm.nih.gov/pubmed/20231686?dopt=Abstract
date added to LUP
2010-04-07 16:31:30
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2018-09-23 04:25:16
@article{60bb77cd-413a-4b12-93a1-439c289726b9,
  abstract     = {PURPOSE: Human epidermal growth factor receptor 2 (HER2) gene amplification or protein overexpression (HER2 positivity) defines a clinically challenging subgroup of patients with breast cancer (BC) with variable prognosis and response to therapy. We aimed to investigate the heterogeneous biologic appearance and clinical behavior of HER2-positive tumors using molecular profiling. PATIENTS AND METHODS: Hierarchical clustering of gene expression data from 58 HER2-amplified tumors of various stage, histologic grade, and estrogen receptor (ER) status was used to construct a HER2-derived prognostic predictor that was further evaluated in several large independent BC data sets. RESULTS: Unsupervised analysis identified three subtypes of HER2-positive tumors with mixed stage, histologic grade, and ER status. One subtype had a significantly worse clinical outcome. A prognostic predictor was created based on differentially expressed genes between the subtype with worse outcome and the other subtypes. The predictor was able to define patient groups with better and worse outcome in HER2-positive BC across multiple independent BC data sets and identify a sizable HER2-positive group with long disease-free survival and low mortality. Significant correlation to prognosis was also observed in basal-like, ER-negative, lymph node-positive, and high-grade tumors, irrespective of HER2 status. The predictor included genes associated with immune response, tumor invasion, and metastasis. CONCLUSION: The HER2-derived prognostic predictor provides further insight into the heterogeneous biology of HER2-positive tumors and may become useful for improved selection of patients who need additional treatment with new drugs targeting the HER2 pathway.},
  author       = {Staaf, Johan and Ringnér, Markus and Vallon-Christersson, Johan and Jönsson, Göran B and Bendahl, Pär-Ola and Holm, Karolina and Arason, Adalgeir and Gunnarsson, Haukur and Hegardt, Cecilia and Agnarsson, Bjarni A and Luts, Lena and Grabau, Dorthe and Fernö, Mårten and Malmström, Per and Johannsson, Oskar Th and Loman, Niklas and Barkardottir, Rosa B and Borg, Åke},
  issn         = {1527-7755},
  language     = {eng},
  number       = {11},
  pages        = {1813--1820},
  publisher    = {American Society of Clinical Oncology},
  series       = {Journal of Clinical Oncology},
  title        = {Identification of Subtypes in Human Epidermal Growth Factor Receptor 2-Positive Breast Cancer Reveals a Gene Signature Prognostic of Outcome.},
  url          = {http://dx.doi.org/10.1200/JCO.2009.22.8775},
  volume       = {28},
  year         = {2010},
}