Browsing by Author "Nephew, Kenneth P"

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    Prognosis of hormone-dependent breast cancers: implications of the presence of dysfunctional transcriptional networks activated by insulin via the immune transcription factor T-bet
    (American Association for Cancer Research, 2010-01-15) McCune, Kasi; Bhat-Nakshatri, Poornima; Thorat, Mangesh A; Nephew, Kenneth P; Badve, Sunil; Nakshatri, Harikrishna
    Estrogen receptor alpha (ERα)-positive breast cancers that co-express trans cription factors GATA-3 and FOXA1 have a favorable prognosis. These transcription factors form an autoregulatory hormonal network that influences estrogen responsiveness and sensitivity to hormonal therapy. Disruption of this network may be a mechanism whereby ERα positive breast cancers become resistant to therapy. The transcription factor T-bet is a negative regulator of GATA-3 in the immune system. In this study, we report that insulin increases the expression of T-bet in breast cancer cells, which correlates with reduced expression of GATA-3, FOXA1 and the ERα:FOXA1:GATA-3 target gene GREB-1. The effects of insulin on GATA-3 and FOXA1 could be recapitulated through overexpression of T-bet in MCF-7 cells (MCF-7-T-bet). Chromatin immunoprecipitation assays revealed reduced ERα binding to GREB-1 enhancer regions in MCF-7-T-bet cells and in insulin treated MCF-7 cells. MCF-7-T-bet cells were resistant to tamoxifen in the presence of insulin and displayed prolonged ERK and AKT activation in response to epidermal growth factor treatment. ERα-positive cells with intrinsic tamoxifen resistance as well as MCF-7 cells with acquired tamoxifen and fulvestrant resistance expressed elevated levels of T-bet and/or reduced levels of FOXA1 and GATA-3. Analysis of publicly available databases revealed ERα-positive/T-bet-positive breast cancers expressing lower levels of FOXA1 (p=0.0137) and GATA-3 (p=0.0063) compared to ERα-positive/T-bet-negative breast cancers. Thus, T-bet expression in primary tumors and circulating insulin levels may serve as surrogate biomarkers to identify ERα-positive breast cancers with a dysfunctional hormonal network, enhanced growth factor signaling, and resistance to hormonal therapy.