GSTP1 DNA Methylation and Expression Status Is Indicative of 5-aza-2′-Deoxycytidine Efficacy in Human Prostate Cancer Cells

DNA methylation plays an important role in carcinogenesis and the reversibility of this epigenetic modification makes it a potential therapeutic target. To date, DNA methyltransferase inhibitors (DNMTi) have not demonstrated clinical efficacy in prostate cancer, with one of the major obstacles being the inability to monitor drug activity during the trial. Given the high frequency and specificity of GSTP1 DNA methylation in prostate cancer, we investigated whether GSTP1 is a useful marker of DNMTi treatment efficacy. LNCaP prostate cancer cells were treated with 5-aza-2′-deoxycytidine (5-aza-CdR) either with a single high dose (5–20 µM), every alternate day (0.1–10 µM) or daily (0.005–2.5 µM). A daily treatment regimen with 5-aza-CdR was optimal, with significant suppression of cell proliferation achieved with doses of 0.05 µM or greater (p<0.0001) and induction of cell death from 0.5 µM (p<0.0001). In contrast, treatment with a single high dose of 20 µM 5-aza-CdR inhibited cell proliferation but was not able to induce cell death. Demethylation of GSTP1 was observed with doses of 5-aza-CdR that induced significant suppression of cell proliferation (≥0.05 µM). Re-expression of the GSTP1 protein was observed only at doses of 5-aza-CdR (≥0.5 µM) associated with induction of cell death. Treatment of LNCaP cells with a more stable DNMTi, Zebularine required at least a 100-fold higher dose (≥50 µM) to inhibit proliferation and was less potent in inducing cell death, which corresponded to a lack of GSTP1 protein re-expression. We have shown that GSTP1 DNA methylation and protein expression status is correlated with DNMTi treatment response in prostate cancer cells. Since GSTP1 is methylated in nearly all prostate cancers, our results warrant its testing as a marker of epigenetic therapy response in future clinical trials. We conclude that the DNA methylation and protein expression status of GSTP1 are good indicators of DNMTi efficacy

Androgen receptor signaling in prostate cancer genomic subtypes

While many prostate cancer (PCa) cases remain indolent and treatable, others are aggressive and progress to the metastatic stage where there are limited curative therapies. Androgen receptor (AR) signaling remains an important pathway for proliferative and survival programs in PCa, making disruption of AR signaling a viable therapy option. However, most patients develop resistance to AR-targeted therapies or inherently never respond. The field has turned to PCa genomics to aid in stratifying high risk patients, and to better understand the mechanisms driving aggressive PCa and therapy resistance. While alterations to the AR gene itself occur at later stages, genomic changes at the primary stage can affect the AR axis and impact response to AR-directed therapies. Here, we review common genomic alterations in primary PCa and their influence on AR function and activity. Through a meta-analysis of multiple independent primary PCa databases, we also identified subtypes of significantly co-occurring alterations and examined their combinatorial effects on the AR axis. Further, we discussed the subsequent implications for response to AR-targeted therapies and other treatments. We identified multiple primary PCa genomic subtypes, and given their differing effects on AR activity, patient tumor genetics may be an important stratifying factor for AR therapy resistance.</p

Breast cancer prognosis predicted by nuclear receptor-coregulator networks

Although molecular signatures based on transcript expression in breast cancer samples have provided new insights into breast cancer classification and prognosis, there are acknowledged limitations in current signatures. To provide rational, pathway-based signatures of disrupted physiology in cancer tissues that may be relevant to prognosis, this study has directly quantitated changed gene expression, between normal breast and cancer tissue, as a basis for signature development. The nuclear receptor (NR) family of transcription factors, and their coregulators, are fundamental regulators of every aspect of metazoan life, and were rigorously quantified in normal breast tissues and ERα positive and ERα negative breast cancers. Coregulator expression was highly correlated with that of selected NR in normal breast, particularly from postmenopausal women. These associations were markedly decreased in breast cancer, and the expression of the majority of coregulators was down-regulated in cancer tissues compared with normal. While in cancer the loss of NR-coregulator associations observed in normal breast was common, a small number of NR (Rev-ERBβ, GR, NOR1, LRH-1 and PGR) acquired new associations with coregulators in cancer tissues. Elevated expression of these NR in cancers was associated with poorer outcome in large clinical cohorts, as well as suggesting the activation of ERα -related, but ERα-independent, pathways in ERα negative cancers. In addition, the combined expression of small numbers of NR and coregulators in breast cancer was identified as a signature predicting outcome in ERα negative breast cancer patients, not linked to proliferation and with predictive power superior to existing signatures containing many more genes. These findings highlight the power of predictive signatures derived from the quantitative determination of altered gene expression between normal breast and breast cancers. Taken together, the findings of this study identify networks of NR-coregulator associations active in normal breast but disrupted in breast cancer, and moreover provide evidence that signatures based on NR networks disrupted in cancer can provide important prognostic information in breast cancer patients

Genomic agonism and phenotypic antagonism between estrogen and progesterone receptors in breast cancer

The functional role of progesterone receptor (PR) and its impact on estrogen signaling in breast cancer remain controversial. In primary ER+ (estrogen receptor-positive)/PR+ human tumors, we report that PR reprograms estrogen signaling as a genomic agonist and a phenotypic antagonist. In isolation, estrogen and progestin act as genomic agonists by regulating the expression of common target genes in similar directions, but at different levels. Similarly, in isolation, progestin is also a weak phenotypic agonist of estrogen action. However, in the presence of both hormones, progestin behaves as a phenotypic estrogen antagonist. PR remodels nucleosomes to noncompetitively redirect ER genomic binding to distal enhancers enriched for BRCA1 binding motifs and sites that link PR and ER/PR complexes. When both hormones are present, progestin modulates estrogen action, such that responsive transcriptomes, cellular processes, and ER/PR recruitment to genomic sites correlate with those observedwith PR alone, but not ER alone. Despite this overall correlation, the transcriptome patterns modulated by dual treatment are sufficiently different from individual treatments, such that antagonism of oncogenic processes is both predicted and observed. Combination therapies using the selective PRmodulator/antagonist (SPRM) CDB4124 in combination with tamoxifen elicited 70% cytotoxic tumor regression of T47D tumor xenografts, whereas individual therapies inhibited tumor growth without net regression. Our findings demonstrate that PR redirects ER chromatin binding to antagonize estrogen signaling and that SPRMs can potentiate responses to antiestrogens, suggesting that cotargeting of ER and PR in ER+/PR+ breast cancers should be explored

Novel Selective Agents for the Degradation of Androgen Receptor Variants to Treat Castration-Resistant Prostate Cancer

Acknowledgements: The authors thank Mr. Maron Lee Barrett and Ms. Mayra Star for their technical help. The authors thank Dr. Dejian Ma for his technical help with the NMR studies. The authors thank the UTHSC and St. Jude NMR core for their help with the NMR studies. The authors thank Drs. Robert Getzenberg and Michael Mohler for providing useful comments on the manuscript. The authors thank Ms. Brandy Grimes for her help with tissue procurement. The authors thank Dr. Daniel Johnson of UT BioCore for microarray data analysis and Mr. Lorne Rose of UT-MRC core for microarray studies. Funding Source: The research presented in this manuscript was supported by a research funding provided by GTx, Inc. Memphis, TN to R. Narayanan and by a research funding provided by West Cancer Center to R. Narayanan.Peer reviewedPostprin

The Magnitude of Androgen Receptor Positivity in Breast Cancer Is Critical for Reliable Prediction of Disease Outcome

Purpose: Consensus is lacking regarding the androgen receptor (AR) as a prognostic marker in breast cancer. The objectives of this study were to comprehensively review the literature on AR prognostication and determine optimal criteria for AR as an independent predictor of breast cancer survival. Experimental Design: AR positivity was assessed by immunostaining in two clinically validated primary breast cancer cohorts [training cohort, n = 219; validation cohort, n = 418; 77% and 79% estrogen receptor alpha (ERα) positive, respectively]. The optimal AR cut-point was determined by ROC analysis in the training cohort and applied to both cohorts. Results: AR was an independent prognostic marker of breast cancer outcome in 22 of 46 (48%) previous studies that performed multivariate analyses. Most studies used cut-points of 1% or 10% nuclear positivity. Herein, neither 1% nor 10% cut-points were robustly prognostic. ROC analysis revealed that a higher AR cut-point (78% positivity) provided optimal sensitivity and specificity to predict breast cancer survival in the training (HR, 0.41; P = 0.015) and validation (HR, 0.50; P = 0.014) cohorts. Tenfold cross-validation confirmed the robustness of this AR cut-point. Patients with ERα-positive tumors and AR positivity ≥78% had the best survival in both cohorts (P 0.87) had the best outcomes (P < 0.0001). Conclusions: This study defines an optimal AR cut-point to reliably predict breast cancer survival. Testing this cut-point in prospective cohorts is warranted for implementation of AR as a prognostic factor in the clinical management of breast cancer

Progesterone receptor modulates ERα action in breast cancer.

Progesterone receptor (PR) expression is used as a biomarker of oestrogen receptor-α (ERα) function and breast cancer prognosis. Here we show that PR is not merely an ERα-induced gene target, but is also an ERα-associated protein that modulates its behaviour. In the presence of agonist ligands, PR associates with ERα to direct ERα chromatin binding events within breast cancer cells, resulting in a unique gene expression programme that is associated with good clinical outcome. Progesterone inhibited oestrogen-mediated growth of ERα(+) cell line xenografts and primary ERα(+) breast tumour explants, and had increased anti-proliferative effects when coupled with an ERα antagonist. Copy number loss of PGR, the gene coding for PR, is a common feature in ERα(+) breast cancers, explaining lower PR levels in a subset of cases. Our findings indicate that PR functions as a molecular rheostat to control ERα chromatin binding and transcriptional activity, which has important implications for prognosis and therapeutic interventions.We would like to acknowledge the support of the University of Cambridge, Cancer Research UK and Hutchison Whampoa Limited. Research reported in this manuscript was supported by the National Cancer Institute of the National Institutes of Health under award number 5P30CA142543 (to UT Southwestern) and Department of Defense grants W81XWH-12-1-0288-03 (GVR). W.D.T. is supported by grants from the National Health and Medical Research Council of Australia (ID 1008349; ID 1084416) and Cancer Australia (ID 627229) T.E.H held a Fellowship Award from the US Department of Defense Breast Cancer Research Program (BCRP; #W81XWH-11-1-0592) and currently is supported by a Florey Fellowship from the Royal Adelaide Hospital Research Foundation. J.S.C is supported by an ERC starting grant and an EMBO Young investigator award.This is the accepted manuscript. The final version is available at www.nature.com/nature/journal/v523/n7560/full/nature14583.htm

Novel Androgen Receptor Coregulator GRHL2 Exerts Both Oncogenic and Antimetastatic Functions in Prostate Cancer.

Alteration to the expression and activity of androgen receptor (AR) coregulators in prostate cancer is an important mechanism driving disease progression and therapy resistance. Using a novel proteomic technique, we identified a new AR coregulator, the transcription factor Grainyhead-like 2 (GRHL2), and demonstrated its essential role in the oncogenic AR signaling axis. GRHL2 colocalized with AR in prostate tumors and was frequently amplified and upregulated in prostate cancer. Importantly, GRHL2 maintained AR expression in multiple prostate cancer model systems, was required for cell proliferation, enhanced AR's transcriptional activity, and colocated with AR at specific sites on chromatin to regulate genes relevant to disease progression. GRHL2 is itself an AR-regulated gene, creating a positive feedback loop between the two factors. The link between GRHL2 and AR also applied to constitutively active truncated AR variants (ARV), as GRHL2 interacted with and regulated ARVs and vice versa. These oncogenic functions of GRHL2 were counterbalanced by its ability to suppress epithelial-mesenchymal transition and cell invasion. Mechanistic evidence suggested that AR assisted GRHL2 in maintaining the epithelial phenotype. In summary, this study has identified a new AR coregulator with a multifaceted role in prostate cancer, functioning as an enhancer of the oncogenic AR signaling pathway but also as a suppressor of metastasis-related phenotypes. Cancer Res; 77(13); 3417-30. ©2017 AACR

Regulators of genetic risk of breast cancer identified by integrative network analysis.

Genetic risk for breast cancer is conferred by a combination of multiple variants of small effect. To better understand how risk loci might combine, we examined whether risk-associated genes share regulatory mechanisms. We created a breast cancer gene regulatory network comprising transcription factors and groups of putative target genes (regulons) and asked whether specific regulons are enriched for genes associated with risk loci via expression quantitative trait loci (eQTLs). We identified 36 overlapping regulons that were enriched for risk loci and formed a distinct cluster within the network, suggesting shared biology. The risk transcription factors driving these regulons are frequently mutated in cancer and lie in two opposing subgroups, which relate to estrogen receptor (ER)(+) luminal A or luminal B and ER(-) basal-like cancers and to different luminal epithelial cell populations in the adult mammary gland. Our network approach provides a foundation for determining the regulatory circuits governing breast cancer, to identify targets for intervention, and is transferable to other disease settings.This work was funded by Cancer Research UK and the Breast Cancer Research Foundation. MAAC is funded by the National Research Council (CNPq) of Brazil. TEH held a fellowship from the US DOD Breast Cancer Research Program (W81XWH-11-1-0592) and is currently supported by an RAH Career Development Fellowship (Australia). TEH and WDT are funded by the NHMRC of Australia (NHMRC) (ID: 1008349 WDT; 1084416 WDT, TEH) and Cancer Australia/National Breast Cancer Foundation (ID 627229; WDT, TEH). BAJP is a Gibb Fellow of Cancer Research UK. We would like to acknowledge the support of The University of Cambridge, Cancer Research UK and Hutchison Whampoa Limited.This is the author accepted manuscript. The final version is available from NPG via http://dx.doi.org/10.1038/ng.345