A Functional Genomic Screen Identifies the Deubiquitinase USP11 as a Novel Transcriptional Regulator of ERα in Breast Cancer.

Approximately 70% of breast cancers express estrogen receptor α (ERα) and depend on this key transcriptional regulator for proliferation and differentiation. While patients with this disease can be treated with targeted antiendocrine agents, drug resistance remains a significant issue, with almost half of patients ultimately relapsing. Elucidating the mechanisms that control ERα function may further our understanding of breast carcinogenesis and reveal new therapeutic opportunities. Here, we investigated the role of deubiquitinases (DUB) in regulating ERα in breast cancer. An RNAi loss-of-function screen in breast cancer cells targeting all DUBs identified USP11 as a regulator of ERα transcriptional activity, which was further validated by assessment of direct transcriptional targets of ERα. USP11 expression was induced by estradiol, an effect that was blocked by tamoxifen and not observed in ERα-negative cells. Mass spectrometry revealed a significant change to the proteome and ubiquitinome in USP11-knockdown (KD) cells in the presence of estradiol. RNA sequencing in LCC1 USP11-KD cells revealed significant suppression of cell-cycle-associated and ERα target genes, phenotypes that were not observed in LCC9 USP11-KD, antiendocrine-resistant cells. In a breast cancer patient cohort coupled with in silico analysis of publicly available cohorts, high expression of USP11 was significantly associated with poor survival in ERα-positive (ERα+) patients. Overall, this study highlights a novel role for USP11 in the regulation of ERα activity, where USP11 may represent a prognostic marker in ERα+ breast cancer. SIGNIFICANCE: A newly identified role for USP11 in ERα transcriptional activity represents a novel mechanism of ERα regulation and a pathway to be exploited for the management of ER-positive breast cancer.

Assessment of Significance of Novel Proteins in Breast Cancer Using Tissue Microarray Technology.

The arraying of formalin-fixed paraffin-embedded (FFPE) tissue, or less commonly frozen tissue, in tissue microarrays (TMAs) is an invaluable method with which to assess the association of novel proteins with a myriad of diseases in large cohorts of patients allowing high throughput evaluation as potential biomarkers. TMAs are most frequently used in cancer studies although they are not limited to this application. The most common method of evaluation of TMAs is via immunohistochemistry (IHC) which is an antibody-based protein localisation method routinely used in the clinical laboratory. However, significant issues still exist with respect to the validation of antibodies for use on TMA sections, with a large number of published studies failing to do so correctly [O'Hurley et al. Mol Oncol, doi:10.1016/j.molonc.2014.03.008, 2014]. Here, we present a method to determine the antibody specificity for use in immunohistochemistry (IHC), as well as the analysis and interpretation of results from an IHC-stained TMA.

FKBPL: a marker of good prognosis in breast cancer.

FK506-binding protein-like (FKBPL) has established roles as an anti-tumor protein, with a therapeutic peptide based on this protein, ALM201, shortly entering phase I/II clinical trials. Here, we evaluated FKBPL's prognostic ability in primary breast cancer tissue, represented on tissue microarrays (TMA) from 3277 women recruited into five independent retrospective studies, using immunohistochemistry (IHC). In a meta-analysis, FKBPL levels were a significant predictor of BCSS; low FKBPL levels indicated poorer breast cancer specific survival (BCSS) (hazard ratio (HR) = 1.30, 95% confidence interval (CI) 1.14-1.49, p < 0.001). The prognostic impact of FKBPL remained significant after adjusting for other known prognostic factors (HR = 1.25, 95% CI 1.07-1.45, p = 0.004). For the sub-groups of 2365 estrogen receptor (ER) positive patients and 1649 tamoxifen treated patients, FKBPL was significantly associated with BCSS (HR = 1.34, 95% CI 1.13-1.58, p < 0.001, and HR = 1.25, 95% CI 1.04-1.49, p = 0.02, respectively). A univariate analysis revealed that FKBPL was also a significant predictor of relapse free interval (RFI) within the ER positive patient group, but it was only borderline significant within the smaller tamoxifen treated patient group (HR = 1.32 95% CI 1.05-1.65, p = 0.02 and HR = 1.23 95% CI 0.99-1.54, p = 0.06, respectively). The data suggests a role for FKBPL as a prognostic factor for BCSS, with the potential to be routinely evaluated within the clinic.

microRNAs: a new class of breast cancer biomarkers.

MicroRNAs (miRNAs) are regulatory molecules known to be aberrantly expressed in cancer and contribute to numerous aspects of tumor biology including the initiation, growth and spread of the tumor. With such diverse roles, it is becoming apparent that some may also provide valuable information which may be of use in a clinical setting, demonstrating the potential to act as both screening tools for the stratification of high-risk patients, while informing the treatment decision-making process. There is mounting evidence to suggest that some miRNAs may even provide assistance in the diagnosis of patients with breast cancer. In addition, miRNAs may themselves be considered therapeutic targets, with inhibition or reintroduction of a particular miRNA capable of inducing a response in vivo. This review focuses on miRNAs that have prognostic, diagnostic or predictive potential in breast cancer as well as the possible challenges in the translation of such observations to the clinic.

A novel mechanism of regulation of the anti-metastatic miR-31 by EMSY in breast cancer.

miR-31 is well known as an anti-metastatic microRNA (miRNA) in the context of breast cancer. However, to date the mechanism of regulation of this miRNA has yet to be elucidated. The recent publication by Viré et al. in Molecular Cell demonstrates for the first time that one mechanism of regulation of miR-31 is through the putative oncogene EMSY, whose amplification in breast cancer patients correlates with reduced expression of the miRNA. This regulation is dependent on the DNA-binding transcription factor ETS-1 which recruits EMSY and the histone demethylase KDM5B to the miR-31 promoter, thus repressing its transcription.

miRNA dysregulation in breast cancer.

miRNAs have emerged, in the last decade, as key players in the carcinogenic process, with many candidates identified as playing important roles in many aspects of tumor development, growth, metastasis, and drug resistance. More recently, polymorphisms in miRNAs themselves or in their binding sites in target genes have been identified to incur increased risk of breast cancer in certain populations. In addition, epigenetic regulation and differential expression of processing enzymes has been shown to contribute to the aberrant expression of miRNAs in breast cancer. This review focuses on the area of miRNA dysregulation in breast cancer through both genetic and epigenetic mechanisms, and the impact of this dysregulation on breast cancer risk and resistance to therapies.

miR-187 is an independent prognostic factor in breast cancer and confers increased invasive potential in vitro.

PURPOSE: Here, we describe an integrated bioinformatics, functional analysis, and translational pathology approach to identify novel miRNAs involved in breast cancer progression. EXPERIMENTAL DESIGN: Coinertia analysis (CIA) was used to combine a database of predicted miRNA target sites and gene expression data. Using two independent breast cancer cohorts, CIA was combined with correspondence analysis and between group analysis to produce a ranked list of miRNAs associated with disease progression. Ectopic expression studies were carried out in MCF7 cells and miRNA expression evaluated in two additional cohorts of patients with breast cancer by in situ hybridization on tissue microarrays. RESULTS: CIA identified miR-187 as a key miRNA associated with poor outcome in breast cancer. Ectopic expression of miR-187 in breast cancer cells resulted in a more aggressive phenotype. In a test cohort (n = 117), high expression of miR-187 was associated with a trend toward reduced breast cancer-specific survival (BCSS; P = 0.058), and a significant association with reduced BCSS in lymph node-positive patients (P = 0.036). In a validation cohort (n = 470), high miR-187 was significantly associated with reduced BCSS in the entire cohort (P = 0.021) and in lymph node-positive patients (P = 0.012). Multivariate Cox regression analysis revealed that miR-187 is an independent prognostic factor in both cohorts [cohort 1: HR, 7.37; 95% confidence interval (CI), 2.05-26.51; P = 0.002; cohort 2: HR, 2.80; 95% CI, 1.52-5.16; P = 0.001] and in lymph node-positive patients in both cohorts (cohort 1: HR, 13.74; 95% CI, 2.62-72.03; P = 0.002; cohort 2: HR, 2.77; 95% CI, 1.32-5.81; P = 0.007). CONCLUSIONS: miR-187 expression in breast cancer leads to a more aggressive, invasive phenotype and acts as an independent predictor of outcome.

Characterisation and manipulation of docetaxel resistant prostate cancer cell lines.

BACKGROUND: There is no effective treatment strategy for advanced castration-resistant prostate cancer. Although Docetaxel (Taxotere®) represents the most active chemotherapeutic agent it only gives a modest survival advantage with most patients eventually progressing because of inherent or acquired drug resistance. The aims of this study were to further investigate the mechanisms of resistance to Docetaxel. Three Docetaxel resistant sub-lines were generated and confirmed to be resistant to the apoptotic and anti-proliferative effects of increasing concentrations of Docetaxel. RESULTS: The resistant DU-145 R and 22RV1 R had expression of P-glycoprotein and its inhibition with Elacridar partially and totally reversed the resistant phenotype in the two cell lines respectively, which was not seen in the PC-3 resistant sublines. Resistance was also not mediated in the PC-3 cells by cellular senescence or autophagy but multiple changes in pro- and anti-apoptotic genes and proteins were demonstrated. Even though there were lower basal levels of NF-κB activity in the PC-3 D12 cells compared to the Parental PC-3, docetaxel induced higher NF-κB activity and IκB phosphorylation at 3 and 6 hours with only minor changes in the DU-145 cells. Inhibition of NF-κB with the BAY 11-7082 inhibitor reversed the resistance to Docetaxel. CONCLUSION: This study confirms that multiple mechanisms contribute to Docetaxel resistance and the central transcription factor NF-κB plays an immensely important role in determining docetaxel-resistance which may represent an appropriate therapeutic target.

Tissue microarrays and digital image analysis.

Tissue microarrays (TMAs) have recently emerged as very valuable tools for high-throughput pathological assessment, especially in the cancer research arena. This important technology, however, has yet to fully penetrate into the area of toxicology. Here, we describe the creation of TMAs representative of samples produced from conventional toxicology studies within a large-scale, multi-institutional pan-European project, PredTox. PredTox, short for Predictive Toxicology, formed part of an EU FP6 Integrated Project, Innovative Medicines for Europe (InnoMed), and aimed to study pre-clinically 16 compounds of known liver and/or kidney toxicity. In more detail, TMAs were constructed from materials corresponding to the full face sections of liver and kidney from rats treated with different drug candidates by members of the consortium. We also describe the process of digital slide scanning of kidney and liver sections, in the context of creating an online resource of histopathological data.

Automated image analysis in histopathology: a valuable tool in medical diagnostics.

Virtual pathology, the process of assessing digital images of histological slides, is gaining momentum in today's laboratory environment. Indeed, digital image acquisition systems are becoming commonplace, and associated image analysis solutions are viewed by most as the next critical step in automated histological analysis. Here, we document the advances in the technology, with reference to past and current techniques in histological assessment. In addition, the demand for these technologies is analyzed with major players profiled. As there are several image analysis software programs focusing on the quantification of immunohistochemical staining, particular attention is paid to this application in this review. Oncology has been a primary target area for these approaches, with example studies in this therapeutic area being covered here. Toxicology-based image analysis solutions are also profiled as these are steadily increasing in popularity, especially within the pharmaceutical industry. Reinforced by the phenomenal growth of the virtual pathology field, it is envisioned that the market for automated image analysis tools will greatly expand over the next 10 years.