Predicting prognosis using molecular profiling in estrogen receptor-positive breast cancer treated with tamoxifen

Functional Genomics Unit, Jules Bordet Institute, Brussels, Belgium.
BMC Genomics (Impact Factor: 3.99). 02/2008; 9(1):239. DOI: 10.1186/1471-2164-9-239
Source: PubMed

ABSTRACT Estrogen receptor positive (ER+) breast cancers (BC) are heterogeneous with regard to their clinical behavior and response to therapies. The ER is currently the best predictor of response to the anti-estrogen agent tamoxifen, yet up to 30-40% of ER+BC will relapse despite tamoxifen treatment. New prognostic biomarkers and further biological understanding of tamoxifen resistance are required. We used gene expression profiling to develop an outcome-based predictor using a training set of 255 ER+ BC samples from women treated with adjuvant tamoxifen monotherapy. We used clusters of highly correlated genes to develop our predictor to facilitate both signature stability and biological interpretation. Independent validation was performed using 362 tamoxifen-treated ER+ BC samples obtained from multiple institutions and treated with tamoxifen only in the adjuvant and metastatic settings.
We developed a gene classifier consisting of 181 genes belonging to 13 biological clusters. In the independent set of adjuvantly-treated samples, it was able to define two distinct prognostic groups (HR 2.01 95%CI: 1.29-3.13; p = 0.002). Six of the 13 gene clusters represented pathways involved in cell cycle and proliferation. In 112 metastatic breast cancer patients treated with tamoxifen, one of the classifier components suggesting a cellular inflammatory mechanism was significantly predictive of response.
We have developed a gene classifier that can predict clinical outcome in tamoxifen-treated ER+ BC patients. Whilst our study emphasizes the important role of proliferation genes in prognosis, our approach proposes other genes and pathways that may elucidate further mechanisms that influence clinical outcome and prediction of response to tamoxifen.

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Available from: Els M J J Berns, Sep 28, 2015
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    • "The data revealed three gene signatures consisting of a total of 14 genes (AKT1, BCAR3, BCL2, CDKN1A, CGA, EGFR, ESR1, IGF1R, NAT1, NCOA1, NRG1, PRKCD, PRKCE and TFF1). The strongest prediction of outcome (75% accuracy) was obtained with a 2-gene combination of BCL2 and CDKN1A and confirmed by independent examination of 4 previouslyreported microarray datasets of tamoxifen-treated patient samples in the adjuvant setting (n ¼ 503)(Chanrion et al., 2008; Loi et al., 2008; Ma et al., 2004; Zhang et al., 2009). The predictive value was further validated by comparing the ability of the genes to predict recurrence in an additional, previouslypublished , cohort (Loi et al., 2007) consisting of both adjuvant tamoxifen-treated and untreated patients (Lyng et al., 2013). "
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    ABSTRACT: To identify molecular markers indicative of response to tamoxifen and easily implemented in the in the routine setting, we recently reported three gene signatures that could stratify post-menopausal tamoxifen-treated, estrogen receptor-positive (ER+) patients according to outcome in the adjuvant setting. Here, we evaluated the predictive potential of the total of 14 genes included in the 3 gene signatures using 2 hormone-naïve Dutch ER+ cohorts of a total of 285 recurrent breast cancer patients treated with first-line tamoxifen. mRNA levels were measured by reverse transcriptase quantitative PCR (RT-qPCR) and the length of progression-free survival (PFS) was used as the primary endpoint. A Mann-Whitney U test was used to select for differentially expressed genes between tumors of patients who showed or did not show progressive disease within 6 months after start of tamoxifen treatment. Cox univariate and multivariate regression analysis for PFS were used to further assess their (independent) predictive potential. Five (BCAR3, BCL2, ESR1, IGF1R, and NCOA1) of the 14 genes analyzed showed significantly higher mRNA levels in tumors of patients who showed no disease progression within 6 months. Only BCAR3, BCL2 and NAT1 were significantly associated with a favorable PFS in multivariate analysis that included the traditional predictive factors: age, dominant relapse site, disease-free interval, ER and progesterone receptor (PGR), and adjuvant chemotherapy. This study shows that BCAR3, BCL2 and NAT1 in particular exhibit predictive promise regarding the efficacy of tamoxifen treatment in recurrent disease, in addition to the previously shown favorable outcome in the adjuvant setting.
    Molecular Oncology 12/2014; DOI:10.1016/j.molonc.2014.07.003 · 5.33 Impact Factor
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    • "cytokines, chemokines and proteases that have multiple effects on tumour biology and tumour cell gene regulation, and ultimately tumour progression and response to therapy (Fig. 1). Results from gene-profiling studies have revealed inflammation-related gene clusters that predict recurrence in breast cancer patients receiving tamoxifen (Loi et al. 2008) and anastrozole (Ignatiadis et al. 2012). It is therefore important to decipher the key cytokines and cellular factors that determine the balance between beneficial and deleterious 'types' of inflammation within the tumour. "
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    ABSTRACT: It is increasingly clear that inflammation-associated mechanisms can affect breast cancer progression and modulate response to treatment. Estrogen receptor alpha (ERα) is the principal biomarker and therapeutic target for endocrine therapies in breast cancer. Over 70% of patients are ERα positive at diagnosis and are candidates for endocrine therapy. However, ERα positive tumors can become resistant to endocrine therapy. Multiple mechanisms of endocrine resistance have been proposed including ERα suppression. This review discusses the relationship between intratumoral inflammation and endocrine resistance with a particular focus on inflammation-mediated suppression of ERα.
    Endocrine Related Cancer 11/2014; 22(1). DOI:10.1530/ERC-14-0096 · 4.81 Impact Factor
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    • "The clinical relevance of ZNF217 mRNA levels was demonstrated in two independent ERD breast cancer cohorts treated with Tam only, where high levels of ZNF217 mRNA (RTQ-PCR) were prognostic for poor RFS (Figure 7A and 7B). Retrospective analysis of the gene-expression array data from the GUYT2 cohort (n ¼ 77, Loi et al., 2008) and the Chanrion's cohort (n ¼ 147, Chanrion et al., 2008) again revealed that high levels of ZNF217 mRNA expression were significantly associated with shorter RFS in ERþ patients treated with Tam only (Supplementary Figure S10). Interestingly, a high IHC ZNF217 index was also associated with failure in endocrine therapy response in the ERþ breast tumours of the CRB1 cohort treated with endocrine therapy only (n ¼ 46, p ¼ 0.02, c 2 test, "
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    ABSTRACT: We aimed at highlighting the role of ZNF217, a Krüppel-like finger protein, in Estrogen Receptor-α (ERα)-positive (ER+) and luminal breast cancers. Here we report for the first time that ZNF217 and ERα proteins bind to each other in both breast cancer cells and breast tumour samples, via the ERα hinge domain and the ZNF217 C-terminal domain. ZNF217 enhances the recruitment of ERα to its estrogen response elements (ERE) and the ERα-dependent transcription of the GREB1 estrogen-regulated gene. The prognostic power of ZNF217 mRNA expression levels is most discriminatory in breast cancers classified with a "good prognosis", particularly the Luminal-A subclass. A new immunohistochemistry ZNF217 index, based on nuclear and cytoplasmic ZNF217 staining, also allowed the identification of intermediate/poor relapse-free survivors in the Luminal-A subgroup. ZNF217 confers tamoxifen resistance in ER+ breast cancer cells and is a predictor of relapse under endocrine therapy in patients with ER+ breast cancer. ZNF217 thus allows the re-stratification of patients with ER+ breast cancers considered as cancers with good prognosis where no other biomarkers are currently available and widely used. Here we propose a model in ER+ breast cancer where ZNF217-driven aggressiveness incorporates ZNF217 as a positive enhancer of ERα direct genomic activity and where ZNF217 possesses its highest discriminatory prognostic value.
    Molecular Oncology 06/2014; 8(8). DOI:10.1016/j.molonc.2014.05.013 · 5.33 Impact Factor
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