Genome-wide reprogramming of the chromatin landscape underlies endocrine therapy resistance in breast cancer

The estrogen receptor (ER)α drives growth in two-thirds of all breast cancers. Several targeted therapies, collectively termed endocrine therapy, impingeonestrogen-induced ERα activationtoblock tumor growth. However, half ofERα-positive breast cancers are tolerant or acquire resistance to endocrine therapy. We demonstrate that genome-wide reprogramming of the chromatin landscape, defined by epigenomic maps for regulatory elements or transcriptional activation and chromatin openness, underlies resistance to endocrine therapy. This annotation reveals endocrine therapy-response specific regulatory networks where NOTCH pathway is overactivated in resistant breast cancer cells, whereas classical ERα signaling is epige-netically disengaged. Blocking NOTCH signaling abrogates growth of resistant breast cancer cells. Its activation state in primary breast tumors is a prognostic factor of resistance in endocrine treated patients. Overall, our work demonstrates that chromatin landscape reprogramming underlies changes in regulatory networks driving endocrine therapy resistance in breast cancer

Independent validation of induced overexpression efficiency across 242 experiments shows a success rate of 39%

Although numerous studies containing induced gene expression have already been published, independent authentication of their results has not yet been performed. Here, we utilized available transcriptomic data to validate the achieved efficiency in overexpression studies. Microarray data of experiments containing cell lines with induced overexpression in one or more genes were analyzed. All together 342 studies were processed, these include 242 different genes overexpressed in 184 cell lines. The final database includes 4,755 treatment-control sample pairs. Successful gene induction (fold change induction over 1.44) was validated in 39.3% of all genes at p < 0.05. Number of repetitions within a study (p < 0.0001) and type of used vector (p = 0.023) had significant impact on successful overexpression efficacy. In summary, over 60% of studies failed to deliver a reproducible overexpression. To achieve higher efficiency, robust and strict study design with multi-level quality control will be necessary

A meta-analysis of gene expression-based biomarkers predicting outcome after tamoxifen treatment in breast cancer

To date, three molecular markers (ER, PR, and CYP2D6) have been used in clinical setting to predict the benefit of the anti-estrogen tamoxifen therapy. Our aim was to validate new biomarker candidates predicting response to tamoxifen treatment in breast cancer by evaluating these in a meta-analysis of available transcriptomic datasets with known treatment and follow-up. Biomarker candidates were identified in Pubmed and in the 2007-2012 ASCO and 2011-2012 SABCS abstracts. Breast cancer microarray datasets of endocrine therapy-treated patients were downloaded from GEO and EGA and RNAseq datasets from TCGA. Of the biomarker candidates, only those identified or already validated in a clinical cohort were included. Relapse-free survival (RFS) up to 5 years was used as endpoint in a ROC analysis in the GEO and RNAseq datasets. In the EGA dataset, Kaplan-Meier analysis was performed for overall survival. Statistical significance was set at p < 0.005. The transcriptomic datasets included 665 GEO-based and 1,208 EGA-based patient samples. All together 68 biomarker candidates were identified. Of these, the best performing genes were PGR (AUC = 0.64, p = 2.3E-07), MAPT (AUC = 0.62, p = 7.8E-05), and SLC7A5 (AUC = 0.62, p = 9.2E-05). Further genes significantly correlated to RFS include FOS, TP53, BTG2, HOXB7, DRG1, CXCL10, and TPM4. In the RNAseq dataset, only ERBB2, EDF1, and MAPK1 reached statistical significance. We evaluated tamoxifen-resistance genes in three independent platforms and identified PGR, MAPT, and SLC7A5 as the most promising prognostic biomarkers in tamoxifen treated patients

The miRNA-449 family mediates doxorubicin resistance in triple-negative breast cancer by regulating cell cycle factors

The mechanisms of chemotherapy resistance in triple negative breast cancer remain unclear, and so, new molecules which might mediate this resistance could optimize treatment response. Here we analyzed the involvement of the miRNA-449 family in the response to doxorubicin. The cell viability, cell-cycle phases, and the expression of in silico target genes and proteins of sensitive/resistant triple negative breast cancer cell lines were evaluated in response to doxorubicin treatment and after gain/loss of miRNAs-449 function achieved by transient transfection. Triple negative breast cancer patients were selected for ex vivo experiments and to evaluate gene and miRNAs expression changes after treatment, as well as survival analysis by Kaplan-Meier. Doxorubicin treatment upregulated miRNAs-449 and DNA-damage responder factors E2F1 and E2F3 in triple negative breast cancer sensitive breast cancer cells, while expression remained unaltered in resistant ones. In vitro overexpression of miRNAs-449 sensitized cells to the treatment and significantly reduced the resistance to doxorubicin. These changes showed also a strong effect on cell cycle regulation. Finally, elevated levels of miRNA-449a associated significantly with better survival in chemotherapy-treated triple negative breast cancer patients. These results reveal for the first time the involvement of the miRNA-449 family in doxorubicin resistance and their predictive and prognostic value in triple negative breast cancer patients

The orphan GPR50 receptor promotes constitutive TGFβ receptor signaling and protects against cancer development

Transforming growth factor-β (TGFβ) regulates many cellular processes. Here the authors show that the orphan G-protein coupled receptor GPR50 can activate the TGFβ receptor I, in the absence of TGFβ, by stabilizing its active conformation and show antitumor activity in a mouse model of breast cancer