RB-pathway disruption in breast cancer: Differential association with disease subtypes,disease-specific prognosis and therapeutic response

In breast cancer, inactivation of the RB tumor suppressor gene is believed to occur via multiple mechanisms to facilitate tumorigenesis. However, the prognostic and predictive value of RB status in disease-specific clinical outcomes has remained uncertain. We investigated RB pathway deregulation in the context of both ER-positive and ER-negative disease using combined microarray datasets encompassing over 900 breast cancer patient samples. Disease-specific characteristics of RB pathway deregulation were investigated in this dataset by evaluating correlation among pathway genes as well as differential expression across patient tumor populations defined by ER status. Survival analysis among these breast cancer samples demonstrates that the RB-loss signature is associated with poor disease outcome within several independent cohorts. Within the ER-negative subpopulation, the RB-loss signature is associated with improved response to chemotherapy and longer relapse-free survival. Additionally, while individual genes in the RB target signature closely reproduce its prognostic value, they also serve to predict and monitor response to therapeutic compounds, such as the cytostatic agent PD-0332991. These results indicate that the RB-loss signature expression is associated with poor outcome in breast cancer, but predicts improved response to chemotherapy based on data in ER-negative populations. While the RB-loss signature, as a whole, demonstrates prognostic and predictive utility, a small subset of markers could be sufficient to stratify patients based on RB function and inform the selection of appropriate therapeutic regimens.Key words: RB, breast cancer, microarray, proliferation, cytostatics     

Prognostic breast cancer signature identified from 3D culture model accurately predicts clinical outcome across independent datasets

Background

One of the major tenets in breast cancer research is that early detection is vital for patient survival by increasing treatment options. To that end, we have previously used a novel unsupervised approach to identify a set of genes whose expression predicts prognosis of breast cancer patients. The predictive genes were selected in a well-defined three dimensional (3D) cell culture model of non-malignant human mammary epithelial cell morphogenesis as down-regulated during breast epithelial cell acinar formation and cell cycle arrest. Here we examine the ability of this gene signature (3D-signature) to predict prognosis in three independent breast cancer microarray datasets having 295, 286, and 118 samples, respectively.

Methods and Findings

Our results show that the 3D-signature accurately predicts prognosis in three unrelated patient datasets. At 10 years, the probability of positive outcome was 52, 51, and 47 percent in the group with a poor-prognosis signature and 91, 75, and 71 percent in the group with a good-prognosis signature for the three datasets, respectively (Kaplan-Meier survival analysis, p<0.05). Hazard ratios for poor outcome were 5.5 (95% CI 3.0 to 12.2, p<0.0001), 2.4 (95% CI 1.6 to 3.6, p<0.0001) and 1.9 (95% CI 1.1 to 3.2, p = 0.016) and remained significant for the two larger datasets when corrected for estrogen receptor (ER) status. Hence the 3D-signature accurately predicts breast cancer outcome in both ER-positive and ER-negative tumors, though individual genes differed in their prognostic ability in the two subtypes. Genes that were prognostic in ER+ patients are AURKA, CEP55, RRM2, EPHA2, FGFBP1, and VRK1, while genes prognostic in ER− patients include ACTB, FOXM1 and SERPINE2 (Kaplan-Meier p<0.05). Multivariable Cox regression analysis in the largest dataset showed that the 3D-signature was a strong independent factor in predicting breast cancer outcome.

Conclusions

The 3D-signature accurately predicts breast cancer outcome across multiple datasets and holds prognostic value for both ER-positive and ER-negative breast cancer. The signature was selected using a novel biological approach and hence holds promise to represent the key biological processes of breast cancer.     

RB loss contributes to aggressive tumor phenotypes in MYC-driven triple negative breast cancer

Triple negative breast cancer (TNBC) is characterized by multiple genetic events occurring in concert to drive pathogenic features of the disease. Here we interrogated the coordinate impact of p53, RB, and MYC in a genetic model of TNBC, in parallel with the analysis of clinical specimens. Primary mouse mammary epithelial cells (mMEC) with defined genetic features were used to delineate the combined action of RB and/or p53 in the genesis of TNBC. In this context, the deletion of either RB or p53 alone and in combination increased the proliferation of mMEC; however, the cells did not have the capacity to invade in matrigel. Gene expression profiling revealed that loss of each tumor suppressor has effects related to proliferation, but RB loss in particular leads to alterations in gene expression associated with the epithelial-to-mesenchymal transition. The overexpression of MYC in combination with p53 loss or combined RB/p53 loss drove rapid cell growth. While the effects of MYC overexpression had a dominant impact on gene expression, loss of RB further enhanced the deregulation of a gene expression signature associated with invasion. Specific RB loss lead to enhanced invasion in boyden chambers assays and gave rise to tumors with minimal epithelial characteristics relative to RB-proficient models. Therapeutic screening revealed that RB-deficient cells were particularly resistant to agents targeting PI3K and MEK pathway. Consistent with the aggressive behavior of the preclinical models of MYC overexpression and RB loss, human TNBC tumors that express high levels of MYC and are devoid of RB have a particularly poor outcome. Together these results underscore the potency of tumor suppressor pathways in specifying the biology of breast cancer. Further, they demonstrate that MYC overexpression in concert with RB can promote a particularly aggressive form of TNBC.     

A prognostic gene expression profile that predicts circulating tumor cell presence in breast cancer patients

The detection of circulating tumor cells (CTCs) in the peripheral blood and microarray gene expression profiling of the primary tumor are two promising new technologies able to provide valuable prognostic data for patients with breast cancer. Meta-analyses of several established prognostic breast cancer gene expression profiles in large patient cohorts have demonstrated that despite sharing few genes, their delineation of patients into "good prognosis" or "poor prognosis" are frequently very highly correlated, and combining prognostic profiles does not increase prognostic power. In the current study, we aimed to develop a novel profile which provided independent prognostic data by building a signature predictive of CTC status rather than outcome. Microarray gene expression data from an initial training cohort of 72 breast cancer patients for which CTC status had been determined in a previous study using a multimarker QPCR-based assay was used to develop a CTC-predictive profile. The generated profile was validated in two independent datasets of 49 and 123 patients and confirmed to be both predictive of CTC status, and independently prognostic. Importantly, the "CTC profile" also provided prognostic information independent of the well-established and powerful '70-gene' prognostic breast cancer signature. This profile therefore has the potential to not only add prognostic information to currently-available microarray tests but in some circumstances even replace blood-based prognostic CTC tests at time of diagnosis for those patients already undergoing testing by multigene assays.     

Heregulin-β1-induced GPR30 upregulation promotes the migration and invasion potential of SkBr3 breast cancer cells via ErbB2/ErbB3-MAPK/ERK pathway

Estrogen receptor (ER)-negative breast cancer cells are probably more aggressive with larger metastatic potential than ER-positive cells. Loss of ER in recurrent breast cancer is associated with poor response to endocrine therapy. G protein-coupled receptor 30 (GPR30) is expressed in half of ER-negative breast cancers. Tumor cell-derived heregulin-β1 (HRG-β1) is also found mainly in ER-negative cancer. In SkBr3 breast cancer cells that lack ER but express GPR30, HRG-β1 upregulates mRNA and protein levels of GPR30 by promoting ErbB2-ErbB3 heterodimerization and activating the downstream MAPK-ERK signaling pathway. Moreover, GPR30 boosts HRG-β1-induced migration and invasion of SkBr3 cells after combinative treatment with E2, 4-hydroxy-tamoxifen or the specific GPR30 agonist G-1, which are blocked by the specific GPR30 antagonist G-15 or the transfection with the small interfering RNA for GPR30. The ErbB2 inhibitor AG825 and the MEK1/2 inhibitor U0126 also partly inhibit the enhanced migration and invasion. Therefore, HRG-β1-induced migration and invasion partly depend on the upregulation of GPR30 expression through activation of the ErbB2-ERK pathway in SkBr3 cells. The results of this study indicate that the crosstalk between GPR30 and HRGs signaling is important for endocrine therapy resistance and may provide a new therapeutic way to treat breast cancer.     

Age-specific differences in oncogenic pathway deregulation seen in human breast tumors

Purpose

To define the biology driving the aggressive nature of breast cancer arising in young women.

Experimental Design

Among 784 patients with early stage breast cancer, using prospectively-defined, age-specific cohorts (young ≤45 years; older ≥65 years), 411 eligible patients (n = 200≤45 years; n = 211≥65 years) with clinically-annotated Affymetrix microarray data were identified. GSEA, signatures of oncogenic pathway deregulation and predictors of chemotherapy sensitivity were evaluated within the two age-defined cohorts.

Results

In comparing deregulation of oncogenic pathways between age groups, a higher probability of PI3K (p = 0.006) and Myc (p = 0.03) pathway deregulation was observed in breast tumors arising in younger women. When evaluating unique patterns of pathway deregulation, a low probability of Src and E2F deregulation in tumors of younger women, concurrent with a higher probability of PI3K, Myc, and β-catenin, conferred a worse prognosis (HR = 4.15). In contrast, a higher probability of Src and E2F pathway activation in tumors of older women, with concurrent low probability of PI3K, Myc and β-catenin deregulation, was associated with poorer outcome (HR = 2.7). In multivariate analyses, genomic clusters of pathway deregulation illustrate prognostic value.

Conclusion

Results demonstrate that breast cancer arising in young women represents a distinct biologic entity characterized by unique patterns of deregulated signaling pathways that are prognostic, independent of currently available clinico-pathologic variables. These results should enable refinement of targeted treatment strategies in this clinically challenging situation.     

Proteomics of mouse BRCA1-deficient mammary tumors identifies DNA repair proteins with potential diagnostic and prognostic value in human breast cancer

Breast cancer 1, early onset (BRCA1) hereditary breast cancer, a type of cancer with defects in the homology-directed DNA repair pathway, would benefit from the identification of proteins for diagnosis, which might also be of potential use as screening, prognostic, or predictive markers. Sporadic breast cancers with defects in the BRCA1 pathway might also be diagnosed. We employed proteomics based on one-dimensional gel electrophoresis in combination with nano-LC-MS/MS and spectral counting to compare the protein profiles of mammary tumor tissues of genetic mouse models either deficient or proficient in BRCA1. We identified a total of 3,545 proteins, of which 801 were significantly differentially regulated between the BRCA1-deficient and -proficient breast tumors. Pathway and protein complex analysis identified DNA repair and related functions as the major processes associated with the up-regulated proteins in the BRCA1-deficient tumors. In addition, by selecting highly connected nodes, we identified a BRCA1 deficiency signature of 45 proteins that enriches for homology-directed DNA repair deficiency in human gene expression breast cancer data sets. This signature also exhibits prognostic power across multiple data sets, with optimal performance in a data set enriched in tumors deficient in homology-directed DNA repair. In conclusion, by comparing mouse proteomes from BRCA1-proficient and -deficient mammary tumors, we were able to identify several markers associated with BRCA1 deficiency and a prognostic signature for human breast cancer deficient in homology-directed DNA repair.     

RB1CC1 together with RB1 and p53 predicts long-term survival in Japanese breast cancer patients

RB1-inducible coiled-coil 1 (RB1CC1) plays a significant role in the enhancement of the retinoblastoma tumor suppressor (RB1) pathway and is involved in breast cancer development. However, RB1CC1's role in clinical progression of breast cancer has not yet been evaluated, so, as a first step, it is necessary to establish its usefulness as a tool to evaluate breast cancer patients. In this report, we have analyzed the correlation between abnormalities in the RB1CC1 pathway and long-term prognosis, because disease-specific death in later periods (>5 years) of the disease is a serious problem in breast cancer. Breast cancer tissues from a large cohort in Japan were evaluated by conventional immunohistochemical methods for the presence of the molecules involved in the RB1CC1 pathway, including RB1CC1, RB1, p53, and other well-known prognostic markers for breast cancer, such as estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2. The correlation between the immunohistochemical results and clinical outcomes of 323 breast cancer patients was analyzed using a Kaplan-Meier log-rank test and a multivariate Cox proportional hazards regression analysis. Absence of nuclear RB1CC1 expression was associated with the worst prognosis (Log-rank test, Chi-Square value = 17.462, p<0.0001). Dysfunction of either one of RB1CC1, RB1, or p53 was associated with the highest risk for cancer-specific death, especially related to survival lasting more than 5 years (multivariate Cox proportional hazard ratio = 3.951, 95% Confidence Interval =1.566-9.967, p = 0.0036). Our present data demonstrate that the combined evaluation of RB1CC1, RB1 and p53 by conventional immunohistochemical analysis provides an accurate prediction of the long-term prognoses of breast cancer patients, which can be carried out as a routine clinical examination.     

LSD1 Overexpression Is Associated with Poor Prognosis in Basal-Like Breast Cancer,and Sensitivity to PARP Inhibition

LSD1, a lysine-specific histone demethylase, is overexpressed in several types of cancers and linked to poor outcomes. In breast cancer, the significance of LSD1 overexpression is not clear. We have performed an in silico analysis to assess the relationship of LSD1 expression to clinical outcome. We demonstrate that LSD1 overexpression is a poor prognostic factor in breast cancer, especially in basal-like breast cancer, a subtype of breast cancer with aggressive clinical features. This link is also observed in samples of triple negative breast cancer. Interestingly, we note that overexpression of LSD1 correlates with down-regulation of BRCA1 in triple negative breast cancer. This phenomenon is also observed in in vitro models of basal-like breast cancer, and is associated with an increased sensitivity to PARP inhibitors. We propose therefore that high expression levels of the demethylase LSD1 is a potential prognostic factor of poor outcome in basal-like breast cancer, and that PARP inhibition may be a therapeutic strategy of interest in this poor prognostic subtype with overexpression of LSD1.     

CDK4/6 inhibition antagonizes the cytotoxic response to anthracycline therapy

Triple-negative breast cancer (TNBC) is an aggressive disease that lacks established markers to direct therapeutic intervention. Thus, these tumors are routinely treated with cytotoxic chemotherapies (e.g., anthracyclines), which can cause severe side effects that impact quality of life. Recent studies indicate that the retinoblastoma tumor suppressor (RB) pathway is an important determinant in TNBC disease progression and therapeutic outcome. Furthermore, new therapeutic agents have been developed that specifically target the RB pathway, potentially positioning RB as a novel molecular marker for directing treatment. The current study evaluates the efficacy of pharmacological CDK4/6 inhibition in combination with the widely used genotoxic agent doxorubicin in the treatment of TNBC. Results demonstrate that in RB-proficient TNBC models, pharmacological CDK4/6 inhibition yields a cooperative cytostatic effect with doxorubicin but ultimately protects RB-proficient cells from doxorubicin-mediated cytotoxicity. In contrast, CDK4/6 inhibition does not alter the therapeutic response of RB-deficient TNBC cells to doxorubicin-mediated cytotoxicity, indicating that the effects of doxorubicin are indeed dependent on RB-mediated cell cycle control. Finally, the ability of CDK4/6 inhibition to protect TNBC cells from doxorubicin-mediated cytotoxicity resulted in recurrent populations of cells specifically in RB-proficient cell models, indicating that CDK4/6 inhibition can preserve cell viability in the presence of genotoxic agents. Combined, these studies suggest that while targeting the RB pathway represents a novel means of treatment in aggressive diseases such as TNBC, there should be a certain degree of caution when considering combination regimens of CDK4/6 inhibitors with genotoxic compounds that rely heavily on cell proliferation for their cytotoxic effects.     

An immune response gene expression module identifies a good prognosis subtype in estrogen receptor negative breast cancer

Background  

Estrogen receptor (ER)-negative breast cancer specimens are predominantly of high grade, have frequent p53 mutations, and are broadly divided into HER2-positive and basal subtypes. Although ER-negative disease has overall worse prognosis than does ER-positive breast cancer, not all ER-negative breast cancer patients have poor clinical outcome. Reliable identification of ER-negative tumors that have a good prognosis is not yet possible.     

Identification of DNA methylation changes associated with human gastric cancer

Background

Multiple breast cancer gene expression profiles have been developed that appear to provide similar abilities to predict outcome and may outperform clinical-pathologic criteria; however, the extent to which seemingly disparate profiles provide additive prognostic information is not known, nor do we know whether prognostic profiles perform equally across clinically defined breast cancer subtypes. We evaluated whether combining the prognostic powers of standard breast cancer clinical variables with a large set of gene expression signatures could improve on our ability to predict patient outcomes.

Methods

Using clinical-pathological variables and a collection of 323 gene expression "modules", including 115 previously published signatures, we build multivariate Cox proportional hazards models using a dataset of 550 node-negative systemically untreated breast cancer patients. Models predictive of pathological complete response (pCR) to neoadjuvant chemotherapy were also built using this approach.

Results

We identified statistically significant prognostic models for relapse-free survival (RFS) at 7 years for the entire population, and for the subgroups of patients with ER-positive, or Luminal tumors. Furthermore, we found that combined models that included both clinical and genomic parameters improved prognostication compared with models with either clinical or genomic variables alone. Finally, we were able to build statistically significant combined models for pathological complete response (pCR) predictions for the entire population.

Conclusions

Integration of gene expression signatures and clinical-pathological factors is an improved method over either variable type alone. Highly prognostic models could be created when using all patients, and for the subset of patients with lymph node-negative and ER-positive breast cancers. Other variables beyond gene expression and clinical-pathological variables, like gene mutation status or DNA copy number changes, will be needed to build robust prognostic models for ER-negative breast cancer patients. This combined clinical and genomics model approach can also be used to build predictors of therapy responsiveness, and could ultimately be applied to other tumor types.     

A prognostic eight-gene expression signature for patients with breast cancer receiving adjuvant chemotherapy

Breast cancer is a popularly diagnosed malignant tumor. Genomic profiling studies suggest that breast cancer is a disease with heterogeneity. Chemotherapy is one of the chief means to treat breast cancer, while its responses and clinical outcomes vary largely due to the conventional clinicopathological factors and inherent chemosensitivity of breast cancer. Using the least absolute shrinkage and selection operator (LASSO) Cox regression model, our study established a multi-mRNA-based signature model and constructed a relative nomogram in predicting distant-recurrence-free survival for patients receiving surgery and following chemotherapy. We constructed a signature of eight mRNAs (IPCEF1, SYNDIG1, TIGIT, SPESP1, C2CD4A, CLCA2, RLN2, and CCL19) with the LASSO model, which was employed to separate subjects into groups with high- and low-risk scores. Obvious differences of distant-recurrence-free survival were found between these two groups. This eight-mRNA-based signature was independently associated with the prognosis and had better prognostic value than classical clinicopathologic factors according to multivariate Cox regression results. Receiver operating characteristic results demonstrated excellent performance in diagnosing 3-year distant-recurrence by the eight-mRNA signature. A nomogram that combined both the eight-mRNA-based signature and clinicopathological risk factors was constructed. Comparing with an ideal model, the nomograms worked well both in the training and validation sets. Through the results that the eight-mRNA signature effectively classified patients into low- and high-risk of distant recurrence, we concluded that this eight-mRNA-based signature played a promising predictive role in prognosis and could be clinically applied in breast cancer patients receiving adjuvant chemotherapy.     

A non-functional retinoblastoma tumor suppressor (RB) pathway in premenopausal breast cancer is associated with resistance to tamoxifen

The retinoblastoma tumor suppressor (RB) is important for retaining cell cycle control and loss of RB function is commonly observed in various malignancies. Experimental and animal studies have shown that RB knockdown in ER+ (estrogen receptor) cell lines and xenografts leads to resistance to tamoxifen, indicating that RB-inactivation could be linked to impaired response to specific cancer treatments. To address this issue, we utilized a unique randomized trial including 500 premenopausal breast cancer patients receiving either two years of adjuvant tamoxifen treatment or no treatment after surgery, and defined the tamoxifen response in RB-subgroups. Non-functional RB tumors were defined by lack of concordance between RB-phosphorylation and proliferation, in comparison to RB-functional tumors displaying comparable RB-phosphorylation and proliferation. In the ER+ tumors harboring a functional RB pathway (N=204), patients benefited from adjuvant tamoxifen with fewer breast cancer recurrences (HR=0.53, 95% CI 0.34-0.81, P=0.003). In the small subgroup of ER+ and RB non-functional tumors there was no benefit of tamoxifen (HR=2.28, 95% CI 0.51-10.3, P=0.28). In a multivariate analysis, the interaction between status of the RB pathway and treatment was significant (P=0.010), validating that despite being a small subgroup of ER+ breast cancer, RB functional status appears to be linked to response to tamoxifen treatment. These findings are in line with earlier experimental data altogether suggesting that analyses of RB status in breast cancer have the potential to be one among other future predictive factors that needs to be analyzed in order to successfully identify patients that will benefit from tamoxifen treatment.     

CDK4/6 inhibition antagonizes the cytotoxic response to anthracycline therapy

Triple-negative breast cancer (TNBC) is an aggressive disease that lacks established markers to direct therapeutic intervention. Thus, these tumors are routinely treated with cytotoxic chemotherapies (e.g., anthracyclines), which can cause severe side effects that impact quality of life. Recent studies indicate that the retinoblastoma tumor suppressor (RB) pathway is an important determinant in TNBC disease progression and therapeutic outcome. Furthermore, new therapeutic agents have been developed that specifically target the RB pathway, potentially positioning RB as a novel molecular marker for directing treatment. The current study evaluates the efficacy of pharmacological CDK4/6 inhibition in combination with the widely used genotoxic agent doxorubicin in the treatment of TNBC. Results demonstrate that in RB-proficient TNBC models, pharmacological CDK4/6 inhibition yields a cooperative cytostatic effect with doxorubicin but ultimately protects RB-proficient cells from doxorubicin-mediated cytotoxicity. In contrast, CDK4/6 inhibition does not alter the therapeutic response of RB-deficient TNBC cells to doxorubicin-mediated cytotoxicity, indicating that the effects of doxorubicin are indeed dependent on RB-mediated cell cycle control. Finally, the ability of CDK4/6 inhibition to protect TNBC cells from doxorubicin-mediated cytotoxicity resulted in recurrent populations of cells specifically in RB-proficient cell models, indicating that CDK4/6 inhibition can preserve cell viability in the presence of genotoxic agents. Combined, these studies suggest that while targeting the RB pathway represents a novel means of treatment in aggressive diseases such as TNBC, there should be a certain degree of caution when considering combination regimens of CDK4/6 inhibitors with genotoxic compounds that rely heavily on cell proliferation for their cytotoxic effects.     

Homogeneous datasets of triple negative breast cancers enable the identification of novel prognostic and predictive signatures

Background

Current prognostic gene signatures for breast cancer mainly reflect proliferation status and have limited value in triple-negative (TNBC) cancers. The identification of prognostic signatures from TNBC cohorts was limited in the past due to small sample sizes.

Methodology/Principal Findings

We assembled all currently publically available TNBC gene expression datasets generated on Affymetrix gene chips. Inter-laboratory variation was minimized by filtering methods for both samples and genes. Supervised analysis was performed to identify prognostic signatures from 394 cases which were subsequently tested on an independent validation cohort (n = 261 cases).

Conclusions/Significance

Using two distinct false discovery rate thresholds, 25% and <3.5%, a larger (n = 264 probesets) and a smaller (n = 26 probesets) prognostic gene sets were identified and used as prognostic predictors. Most of these genes were positively associated with poor prognosis and correlated to metagenes for inflammation and angiogenesis. No correlation to other previously published prognostic signatures (recurrence score, genomic grade index, 70-gene signature, wound response signature, 7-gene immune response module, stroma derived prognostic predictor, and a medullary like signature) was observed. In multivariate analyses in the validation cohort the two signatures showed hazard ratios of 4.03 (95% confidence interval [CI] 1.71–9.48; P = 0.001) and 4.08 (95% CI 1.79–9.28; P = 0.001), respectively. The 10-year event-free survival was 70% for the good risk and 20% for the high risk group. The 26-gene signatures had modest predictive value (AUC = 0.588) to predict response to neoadjuvant chemotherapy, however, the combination of a B-cell metagene with the prognostic signatures increased its response predictive value. We identified a 264-gene prognostic signature for TNBC which is unrelated to previously known prognostic signatures.     

RB in Breast Cancer: The Crossroads of Tumorigenesis and Treatment

Cancer is a highly heterogeneous disease, wherein specific determinants modulate disease severity and therapeutic outcomes. In breast cancer, significant effort has been channeled into defining critical genetic effectors of disease behavior. One key molecular determinant is the retinoblastoma tumor suppressor (RB), which is functionally inactivated in the majority of human cancers, and aberrant in nearly half of breast cancers. Deficiency in RB function compromises cell cycle checkpoints, contributes to aggressive tumor proliferation, and is associated with advanced disease. Recent investigation indicates that RB-deficiency has dramatic and disparate effects on the response to therapeutic modalities utilized in the treatment of breast cancer. Loss of RB function promotes inappropriate cell cycle progression during therapeutic challenge. In the context of cytotoxic therapies, this lack of checkpoint function leads to increased sensitivity to the agent. However, RB-deficiency efficiently bypasses the anti-mitogenic function of hormonal therapies and is associated with early disease recurrence following tamoxifen therapy. Thus, RB-pathway status has powerful effects on both tumorigenic proliferation and therapeutic response, and may represent a critical basis for informing breast cancer therapy.     

Arsenic induces functional re-expression of estrogen receptor α by demethylation of DNA in estrogen receptor-negative human breast cancer

Estrogen receptor α (ERα) is a marker predictive for response of breast cancers to endocrine therapy. About 30% of breast cancers, however, are hormone- independent because of lack of ERα expression. New strategies are needed for re-expression of ERα and sensitization of ER-negative breast cancer cells to selective ER modulators. The present report shows that arsenic trioxide induces reactivated ERα, providing a target for therapy with ER antagonists. Exposure of ER-negative breast cancer cells to arsenic trioxide leads to re-expression of ERα mRNA and functional ERα protein in in vitro and in vivo. Luciferase reporter gene assays and 3-(4,5-dimethylthiazol-2-yl)- 5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium (MTS) assays show that, upon exposure to arsenic trioxide, formerly unresponsive, ER-negative MDA-MB-231 breast cancer cells become responsive to ER antagonists, 4-hydroxytamoxifen and ICI 182,780. Furthermore, methylation- specific PCR and bisulfite-sequencing PCR assays show that arsenic trioxide induces partial demethylation of the ERα promoter. A methyl donor, S-adenosylmethionine (SAM), reduces the degree of arsenic trioxide-induced re-expression of ERα and demethylation. Moreover, Western blot and ChIP assays show that arsenic trioxide represses expression of DNMT1 and DNMT3a along with partial dissociation of DNMT1 from the ERα promoter. Thus, arsenic trioxide exhibits a previously undefined function which induces re-expression ERα in ER-negative breast cancer cells through demethylation of the ERα promoter. These findings could provide important information regarding the application of therapeutic agents targeting epigenetic changes in breast cancers and potential implication of arsenic trioxide as a new drug for the treatment of ER-negative human breast cancer.