Metabolic differences in estrogen receptor-negative breast cancer based on androgen receptor status

Songmi Noh, Ji Ye Kim, JaSeung Koo

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

This study investigated the relationship between steroid hormone receptor signaling and cellular metabolism in tumorigenesis by examining the expression of metabolic proteins with respect to androgen receptor (AR) and human epidermal growth factor receptor-2 (HER-2) status in estrogen receptor-negative (ER−) breast cancer. ER− breast cancer cases (n = 334) were selected from a microarray analysis, including those that were AR+ and AR− (n = 127 and 207, respectively) and HER-2+ and HER-2− (n = 140 and 194, respectively). The expression of proteins involved in glycolysis, glutaminolysis, and mitochondrial and intermediary (i.e., serine/glycine) metabolism was determined by immunohistochemistry and correlated with AR and HER-2 status. The expression of several proteins involved in glycolysis, glutaminolysis, and serine/glycine metabolism was higher (p < 0.01) in the AR− than in the AR+ group. In the former, the expression of the glycolytic protein carbonic anhydrase (CA)IX was associated with a shorter disease-free survival period (p = 0.029) and overall survival rate (p = 0.001). In a multivariate Cox analysis, immunoreactivity for CAIX (hazard ratio 15.89, 95 % confidence interval (CI) 1.820–131.6; p = 0.010) was an independent factor in predicting the survival of the AR+ group. In conclusion, differential expression patterns of metabolism-related proteins were noted in ER− breast cancer according to AR status. These findings highlight the link between hormone receptor signaling and metabolic pathways whose dysregulation could underlie breast tumorigenesis.

Original languageEnglish
Pages (from-to)8179-8192
Number of pages14
JournalTumor Biology
Volume35
Issue number8
DOIs
Publication statusPublished - 2014 Jan 1

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Androgen Receptors
Estrogen Receptors
Breast Neoplasms
Glycolysis
Proteins
Glycine
Serine
Carcinogenesis
Hormones
Steroid Receptors
Microarray Analysis
Metabolic Networks and Pathways
Disease-Free Survival
Breast
Multivariate Analysis
Immunohistochemistry
Confidence Intervals
human ERBB2 protein

All Science Journal Classification (ASJC) codes

  • Cancer Research

Cite this

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abstract = "This study investigated the relationship between steroid hormone receptor signaling and cellular metabolism in tumorigenesis by examining the expression of metabolic proteins with respect to androgen receptor (AR) and human epidermal growth factor receptor-2 (HER-2) status in estrogen receptor-negative (ER−) breast cancer. ER− breast cancer cases (n = 334) were selected from a microarray analysis, including those that were AR+ and AR− (n = 127 and 207, respectively) and HER-2+ and HER-2− (n = 140 and 194, respectively). The expression of proteins involved in glycolysis, glutaminolysis, and mitochondrial and intermediary (i.e., serine/glycine) metabolism was determined by immunohistochemistry and correlated with AR and HER-2 status. The expression of several proteins involved in glycolysis, glutaminolysis, and serine/glycine metabolism was higher (p < 0.01) in the AR− than in the AR+ group. In the former, the expression of the glycolytic protein carbonic anhydrase (CA)IX was associated with a shorter disease-free survival period (p = 0.029) and overall survival rate (p = 0.001). In a multivariate Cox analysis, immunoreactivity for CAIX (hazard ratio 15.89, 95 {\%} confidence interval (CI) 1.820–131.6; p = 0.010) was an independent factor in predicting the survival of the AR+ group. In conclusion, differential expression patterns of metabolism-related proteins were noted in ER− breast cancer according to AR status. These findings highlight the link between hormone receptor signaling and metabolic pathways whose dysregulation could underlie breast tumorigenesis.",
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Metabolic differences in estrogen receptor-negative breast cancer based on androgen receptor status. / Noh, Songmi; Kim, Ji Ye; Koo, JaSeung.

In: Tumor Biology, Vol. 35, No. 8, 01.01.2014, p. 8179-8192.

Research output: Contribution to journalArticle

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