Estrogen receptor co-activator (AIB1) protein expression by automated quantitative analysis (AQUA) in a breast cancer tissue microarray and association with patient outcome.

TitleEstrogen receptor co-activator (AIB1) protein expression by automated quantitative analysis (AQUA) in a breast cancer tissue microarray and association with patient outcome.
Publication TypeJournal Article
Year of Publication2009
AuthorsHarigopal M, Heymann J, Ghosh S, Anagnostou V, Camp RL, Rimm DL
JournalBreast Cancer Res Treat
Volume115
Issue1
Pagination77-85
Date Published2009 May
ISSN1573-7217
KeywordsAlgorithms, Automation, Biomarkers, Tumor, Breast Neoplasms, Female, Gene Expression Regulation, Neoplastic, Humans, Multivariate Analysis, Nuclear Receptor Coactivator 3, Oligonucleotide Array Sequence Analysis, Prognosis, Proportional Hazards Models, Receptors, Estrogen, Receptors, Progesterone, Regression Analysis, Transcription Factors, Treatment Outcome
Abstract

PURPOSE: Amplified in breast cancer (AIB1 or SRC-3) is an estrogen receptor coregulatory protein that together with other co-activators like transcription intermediary factor 2 (TIF2) and nuclear receptor co-repressor (NCoR), is implicated in estrogen signaling pathway and estrogen regulated tumor progression. We investigated the prognostic significance of AIB1, TIF2 & NCoR protein expression breast tissue microarray (TMA), and studied the relationship of coregulatory proteins to prognostic biomarkers like estrogen (ER), progesterone (PR) & HER2/neu and between coregulatory proteins.

METHODS: AIBI, TIF2 & NCoR were studied by fluorescent immunohistochemical staining of a TMA with 670 breast cancer specimens, using AQUA software.

RESULT: Using Cox univariate survival analyses, high AIB1 expression was associated with poor patient outcome (P = 0.002), while no association was noted for TIF2 (P = 0.376) & NCoR (P = 0.12). When subclassified by nodal or ER status, AIB1 was not prognostic in the node positive and ER positive subsets. However, in the ER negative and node negative subsets, high AIB1 expression was associated with poor patient outcome (P = 0.02 and P = 0.007 respectively). AIB1 retained its independent association with survival by multivariate analyses (P = 0.028). There was significant positive correlation between AIB1 and ER and PR status and with other cofators (TIF2 and NCoR) but not with HER2/neu status.

CONCLUSION: High AIB1 expression was predictive of worse overall survival in our study, suggesting that AIB1 may be critical in breast carcinogenesis.

DOI10.1007/s10549-008-0063-9
Alternate JournalBreast Cancer Res Treat
PubMed ID18521745
Grant ListR33 CA 106709 / CA / NCI NIH HHS / United States
R33 CA 110511 / CA / NCI NIH HHS / United States
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