Androgen receptor cytosine-adenine-guanine repeat polymorphisms modulate EGFR signaling in epithelial ovarian carcinomas

PRER: A patient representation with pairwise relative expression of proteins on biological networks

Changes in protein and gene expression levels are often used as features in predictive modeling such as survival prediction. A common strategy to aggregate information contained in individual proteins is to integrate the expression levels with the biological networks. In this work, we propose a novel patient representation where we integrate proteins’ expression levels with the protein-protein interaction (PPI) networks: Patient representation with PRER (Pairwise Relative Expressions with Random walks). PRER captures the dysregulation patterns of proteins based on the neighborhood of a protein in the PPI network. Specifically, PRER computes a feature vector for a patient by comparing the source protein’s expression level with other proteins’ levels that are within its neighborhood. The neighborhood of the source protein is derived by biased random-walk strategy on the network. We test PRER’s performance in survival prediction task in 10 different cancers using random forest survival models. PRER yields a statistically significant predictive performance in 9 out of 10 cancers when compared to the same model trained with features based on individual protein expressions. Furthermore, we identified the pairs of proteins that their interactions are predictive of patient survival but their individual expression levels are not. The set of identified relations provides a valuable collection of protein biomarkers with high prognostic value. PRER can be used for other complex diseases and prediction tasks that use molecular expression profiles as input. PRER is freely available at: https://github.com/hikuru/PRER.

Cancer remains to be one of the most prevalent and challenging diseases to treat. Cancer is a complex disease with several disrupted molecular mechanisms at play. The protein expression level is a fundamental indicator of how the molecular mechanisms are altered in each tumor. Predicting patient survival based on the changes is essential for understanding the cancer mechanisms and arriving at patient-specific treatment plans. For this task, existing machine learning models are used, such as random survival forest, which requires a feature-based representation of each patient based on her tumors. Most of these models use the individual molecular quantities of the tumors. However, cancer is a complex disease in which molecular mechanisms are dysregulated in various ways. In this work, we present a new patient representation scheme in which we integrate each tumor’s protein expression levels with their neighboring proteins’ expression levels in a protein-protein interaction network to capture patient-specific dysregulation patterns. Our results suggest that proteins’ relative expressions are more predictive than their individual expressions. We also analyze which of the protein interactions are more predictive of patient survival. The identified set of important protein interactions can be potentially used for cancer prognosis.

Abiraterone in patients with recurrent epithelial ovarian cancer: principal results of the phase II Cancer of the Ovary Abiraterone (CORAL) trial (CRUK - A16037)

BACKGROUND

Recurrent epithelial ovarian cancer (EOC) remains difficult to treat, with an urgent need for more therapy options. Androgens bind to the androgen receptor (AR), commonly expressed in EOC. CYP17 inhibitor abiraterone irreversibly inhibits androgen biosynthesis. The Cancer of the Ovary Abiraterone (CORAL) trial was designed to evaluate the clinical activity of abiraterone in EOC.

PATIENTS & METHODS

CORAL was a multi-centre, open-label, non-randomised, 2-stage phase II clinical trial. Eligible patients had progression within 12 months of last systemic therapy and no prior hormonal anti-cancer agents. Patients received abiraterone 1000 mg daily plus 5 mg prednisone until progression. The primary endpoint was objective response rate (ORR) according to combined Response Evaluation Criteria in Solid Tumours/Gynaecological Cancer Intergroup (RECIST/GCIG) criteria at 12 weeks. Secondary endpoints included clinical benefit rate (CBR) at 12 weeks.

RESULTS

A total of 42 patients were recruited; median age 65 (range 34-85) years; 37 (88.1%) had high-grade serous tumours; 20 (48%) had at least three prior lines of therapy; 29/40 (72.5%) were AR+. In stage 1, 1/26 response was observed (in an AR+, low-grade serous EOC); response lasted 47 weeks. Overall, 12 week ORR was 1/42 (2%), CBR was 11/42 (26%) (8/29 (28%) in AR+ patients). Disease control was ⩾6 months for 4/29 (14%). One patient (AR+, low-grade serous) had a RECIST response at 82 weeks. Four (10%) had grade ⩾3 hypokalaemia; 11 (26%) had dose delays.

CONCLUSIONS

CORAL represents the first trial of an AR targeted agent in ovarian cancer. While responses were rare, a subset of patients achieved sustained clinical benefit. Targeting AR in EOC including low-grade serous cancer warrants further investigation.

TRIAL REGISTRATION

CORAL is registered on the ISRCTN registry: ISRCTN63407050; http://www.isrctn.com/ISRCTN63407050.

The Role of Androgen Receptor Signaling in Ovarian Cancer

Emerging evidence has suggested that androgen receptor signaling plays an important role in ovarian cancer outgrowth. Specifically, androgen receptor activation appears to be associated with increased risks of developing ovarian cancer and inducing tumor progression. However, conflicting findings have also been reported. This review summarizes and discusses the available data indicating the involvement of androgens as well as androgen receptor and related signals in ovarian carcinogenesis and cancer growth. Although the underlying molecular mechanisms for androgen receptor functions in ovarian cancer remain far from being fully understood, current observations may offer effective chemopreventive and therapeutic approaches, via modulation of androgen receptor activity, against ovarian cancer. Indeed, several clinical trials have been conducted to determine the efficacy of androgen deprivation therapy in patients with ovarian cancer.

Nanog interaction with the androgen receptor signaling axis induce ovarian cancer stem cell regulation: studies based on the CRISPR/Cas9 system

Background

Ovarian cancer stem cells (OCSCs) contribute to the poor prognosis of ovarian cancer. Involvement of the androgen receptor (AR) in the malignant behaviors of other tumors has been reported. However, whether AR associates with Nanog (a stem cell marker) and participates in OCSC functions remain unclear. In this study, we investigated the interaction of Nanog with AR and examined whether this interaction induced stem-like properties in ovarian cancer cells.

Methods

AR and Nanog expression in ovarian tumors was evaluated. Using the CRISPR/Cas9 system, we constructed a Nanog green fluorescent protein (GFP) marker cell model to investigate the expression and co-localization of Nanog and AR. Then, we examined the effect of androgen on the Nanog promoter in ovarian cancer cell lines (A2780 and SKOV3). After androgen or anti-androgen treatment, cell proliferation, migration, sphere formation, colony formation and tumorigenesis were assessed in vitro and in vivo.

Results

Both AR and Nanog expression were obviously high in ovarian tumors. Our results showed that Nanog expression was correlated with AR expression. The androgen 5α-dihydrotestosterone (DHT) activated Nanog promoter transcription. Meanwhile, Nanog GFP-positive cells treated with DHT exhibited higher levels of proliferation, migration, sphere formation and colony formation. We also observed that the tumorigenesis of Nanog GFP-positive cells was significantly higher than that of the GFP-negative cells. Xenografts of Nanog GFP-positive cells showed significant differences when treated with androgen or anti-androgen drugs in vivo.

Conclusions

The interaction of Nanog with the AR signaling axis might induce or contribute to OCSC regulation. In addition, androgen might promote stemness characteristics in ovarian cancer cells by activating the Nanog promoter. This finding merits further study because it may provide a new understanding of OCSC regulation from a hormone perspective and lead to the reevaluation of stem cell therapy for ovarian cancer.

Electronic supplementary material

The online version of this article (10.1186/s13048-018-0403-2) contains supplementary material, which is available to authorized users.

The role of the androgen receptor in ovarian cancer carcinogenesis and its clinical implications

Ovarian cancer is the major cause of death in women with gynecologic malignancies. There is emerging evidence that Androgen/androgen receptor (AR) signaling plays a critical role in the etiology and progression of this disease. Androgen receptor is frequently expressed in various subtypes of ovarian cancers and androgen/AR signaling has been shown to promote proliferation, migration, and invasion of ovarian cancer cells. Furthermore, shorter AR CAG repeats length and increased AR activity are associated with increased ovarian cancer risk and may be a useful prognosticator under certain circumstances. Here, we summarize current findings regarding the role of the AR in ovarian cancer and discuss agents that target this pathway as potential therapeutics for ovarian cancer.

Androgen receptor gene CAG repeat polymorphism and ovarian cancer risk: A meta-analysis

Ovarian cancer is one of the common gynecological malignancies worldwide. It is usually diagnosed at a later stage, thus missing the best opportunity for treatment. Despite the advancement of ovarian cancer treatment, the prognosis is still poor. Androgen receptor (AR) may play a role in ovarian carcinogenesis. Previous studies regarding the association between AR CAG repeat length and ovarian cancer risk reported inconsistent results. Therefore, we conducted a meta-analysis to evaluate the association between AR CAG repeat length and ovarian cancer risk following the MOOSE guidelines. PubMed, Web of Science, EBSCO and other databases were searched up to September 15^th 2016. Case control studies with clear definition of CAG repeat length and detailed genotype information were included. Two authors independently reviewed and extracted data. Pooled analysis and subgroup analysis stratified by ethnicity were performed for different genetic models. Begg's funnel plot and Egger's test were performed for publication bias estimation. Overall, there was no association between the AR CAG repeat polymorphism and ovarian cancer risk. However, short CAG repeat polymorphism was associated with increased ovarian cancer risk in African Americans and Chinese under the dominant model, whereas a reverse association was observed in Caucasians and Italians under the other three models. Our study results should be interpreted with caution. Further well-designed epidemiological and functional studies are needed to elucidate the role of AR in ovarian carcinogenesis.

Predicting time to ovarian carcinoma recurrence using protein markers

Patients with ovarian cancer are at high risk of tumor recurrence. Prediction of therapy outcome may provide therapeutic avenues to improve patient outcomes. Using reverse-phase protein arrays, we generated ovarian carcinoma protein expression profiles on 412 cases from TCGA and constructed a PRotein-driven index of OVARian cancer (PROVAR). PROVAR significantly discriminated an independent cohort of 226 high-grade serous ovarian carcinomas into groups of high risk and low risk of tumor recurrence as well as short-term and long-term survivors. Comparison with gene expression-based outcome classification models showed a significantly improved capacity of the protein-based PROVAR to predict tumor progression. Identification of protein markers linked to disease recurrence may yield insights into tumor biology. When combined with features known to be associated with outcome, such as BRCA mutation, PROVAR may provide clinically useful predictions of time to tumor recurrence.

Revisiting the role of antiandrogen strategies in ovarian cancer

Androgen receptors are frequently expressed in epithelial ovarian cancer (EOC). Their role in the development of EOC is not fully understood. In the present review we first discuss the epidemiological data linking a hyperandrogen state to a higher risk for ovarian cancer, second describe in vitro studies of the role of androgens in influencing the growth of EOC, and finally review the completed clinical trials with compounds that exploit the androgen axis in patients with ovarian cancer. The therapeutic approaches that inhibit androgen signaling have so far produced only modest response rates. In the light of new data regarding the role of androgen stimulation in the evolution of EOC and the emergence of new compounds used for the treatment of other hormone-driven malignancies, such as prostate and breast cancer, we provide suggestions for new studies of antiandrogen therapeutics in the treatment of EOC. A specific example is the new agent abiraterone. In addition, we propose a panel of molecules that could be assessed as potential biomarkers that may aid patient selection for this approach in the future.

Targeting the epidermal growth factor receptor in epithelial ovarian cancer: current knowledge and future challenges

The epidermal growth factor receptor is overexpressed in up to 60% of ovarian epithelial malignancies. EGFR regulates complex cellular events due to the large number of ligands, dimerization partners, and diverse signaling pathways engaged. In ovarian cancer, EGFR activation is associated with increased malignant tumor phenotype and poorer patient outcome. However, unlike some other EGFR-positive solid tumors, treatment of ovarian tumors with anti-EGFR agents has induced minimal response. While the amount of information regarding EGFR-mediated signaling is considerable, current data provides little insight for the lack of efficacy of anti-EGFR agents in ovarian cancer. More comprehensive, systematic, and well-defined approaches are needed to dissect the roles that EGFR plays in the complex signaling processes in ovarian cancer as well as to identify biomarkers that can accurately predict sensitivity toward EGFR-targeted therapeutic agents. This new knowledge could facilitate the development of rational combinatorial therapies to sensitize tumor cells toward EGFR-targeted therapies.

Impact of androgen receptor cytosine-adenine-guanine polymorphisms on clinical outcome in BRCA mutation-associated epithelial ovarian cancers

PURPOSE

Androgen signaling may function in the pathobiology of epithelial ovarian cancers associated with mutations in the BRCA1/2 genes. Androgen receptor (AR) activity correlates inversely with length of a polymorphic cytosine-adenine-guanine (CAG) repeat in exon 1. We hypothesized that AR CAG allele length is a modifier of clinical outcome in BRCA1/2 mutation positive women with ovarian cancer.

EXPERIMENTAL DESIGN

We identified BRCA1/2 ovarian cancer patients with banked serum from which we PCR amplified the CAG repeat region. We abstracted clinical and survival data, and examined CAG repeat length <19 as a short AR allelotype. We calculated a sample size of 60 patients to determine a 24-month difference in survival.

RESULT

In 62 patients, 43 (69%) had BRCA1 mutations and 19 (31%) had BRCA2 mutations. Fifteen (24%) were found to have a short AR allelotype. Patients with a short AR did not demonstrate statistical differences in progression-free survival (43 months vs. 28 months for long AR) or overall survival (78 months vs. 142 months for long AR). In patients with BRCA2 mutations alone, a short AR correlated with decreased overall survival (31 months) compared to 126 months for those with a long AR (p=0.01).

CONCLUSIONS

AR allelotype length did not correlate with survival in this statistically representative cohort of patients with BRCA1/2 mutations. Potential associations between short AR and outcome in BRCA2-associated ovarian cancers remain to be determined.

Mutations in mitochondrial DNA polymerase-gamma promote breast tumorigenesis

Decreased mitochondrial oxidative phosphorylation (OXPHOS) is one of the hallmarks of cancer. To date, the identity of nuclear gene(s) responsible for decreased OXPHOS in tumors remains unknown. It is also unclear whether mutations in nuclear gene(s) responsible for decreased OXPHOS affect tumorigenesis. Polymerase-gamma (POLG) is the only DNA polymerase known to function in human mitochondria. Mutations in POLG are known to cause mitochondrial DNA (mtDNA) depletion and decreased OXPHOS, resulting in mtDNA depletion syndrome in humans. We therefore sequenced all coding exons (2-23) and flanking intron/splice junctions of POLG in breast tumors. We found that the POLG gene was mutated in 63% of breast tumors. We identified a total of 17 mutations across the POLG gene. Mutations were found in all three domains of the POLG protein, including T251I (the exonuclease domain), P587L (the linker region) and E1143G (the polymerase domain). We identified two novel mutations that include one silent (A703A) and one missense (R628Q) mutation in the evolutionarily conserved POLG linker region. In addition, we identified three novel mutations in the intronic region. Our study also revealed that mtDNA was depleted in breast tumors. Consistently, mutant POLG, when expressed in breast cancer cells, induced a depletion of mtDNA, decreased mitochondrial activity, decreased mitochondrial membrane potential, increased levels of reactive oxygen species and increased Matrigel invasion. Together, our study provides the first comprehensive analysis of the POLG gene mutation in human cancer and suggests a function for POLG (1) in decreased OXPHOS in cancers and (2) in promoting tumorigenicity.

Epidermal growth factor-induced GnRH-II synthesis contributes to ovarian cancer cell invasion

GnRH-II modulates ovarian cancer cells invasion and is expressed in normal ovary and ovarian epithelial cancer cells; however, the upstream regulator(s) of GnRH-II expression in these cells remains unclear. We now demonstrate that epidermal growth factor (EGF) increases GnRH-II mRNA levels in several human ovarian carcinoma cell lines and up-regulates GnRH-II promoter activity in OVCAR-3 cells in a dose-dependent manner, whereas an EGF receptor inhibitor (AG148) abolishes EGF-induced increases in GnRH-II promoter activity and GnRH-II mRNA levels. EGF increases the phosphorylation of cAMP-responsive element-binding protein (p-CREB) and its association with the coregulator, CCAAT/enhancer binding protein beta, whereas blocking the EGF-induced ERK1/2 phosphorylation with MAPK inhibitors (PD98059/U0126) markedly reduced these effects. Moreover, depletion of CREB using small interfering RNA attenuated EGF-induced GnRH-II promoter activity. Chromatin immunoprecipitation assays demonstrated that EGF induces p-CREB binding to a cAMP responsive-element within the GnRH-II promoter, likely in association with CCAAT/enhancer binding protein beta, and mutagenesis of this cAMP responsive-element prevented EGF-induced GnRH-II promoter activity in OVCAR-3 cells. Importantly, GnRH-II acts additively with EGF to promote invasion of OVCAR-3 and CaOV-3 cells, but not SKOV-3 cells that express low levels of GnRH receptor (GnRHR). Treatment with GnRHR small interfering RNA also partially inhibited the EGF-induced invasion of OVCAR-3 and CaOV-3 cells. Furthermore, EGF treatment transiently increases GnRHR levels in OVCAR-3 and CaOV-3, which likely accentuates the effects of increase GnRH-II production on cell invasion. These results provide evidence that EGF is an upstream regulator of the autocrine actions of GnRH-II on the invasive properties of ovarian cancer cells.

PRK1 distribution in normal tissues and carcinomas: overexpression and activation in ovarian serous carcinoma

Protein kinase C-related kinases are regulated by phosphatidylinositol-3-kinase and Rho family GTPases. The isoform PRK1 has been characterized in detail in prostate cancer, but not in other carcinomas. We analyzed our prior microarray data for PRK1 gene expression in 175 carcinomas and evaluated tissue microarrays for protein expression in 251 carcinomas and a comprehensive group of normal tissues. We also used immunoblotting to determine the levels and phosphoactivation status of PRK1, PRK2, and PDK1 in 12 ovarian serous carcinomas, SKOV3 cells, and 3 samples of normal ovarian surface epithelium (OSE). The highest average level of PRK1 messenger RNA was observed in ovarian serous carcinomas compared with all other carcinomas, including those of the prostate, bladder/ureter, breast, colon, stomach/esophagus, kidney, liver, pancreas, and lung (P = .05). By immunohistochemistry, PRK1 was observed in selected normal cells, including epithelium from the gynecologic tract and hematolymphoid elements. All serous ovarian and endometrial endometrioid adenocarcinomas and mesotheliomas were immunoreactive for PRK1. The findings in nonserous ovarian and most carcinomas from the prostate, breast, and pancreas were also positive but less consistently so. In comparison with OSE, the serous carcinomas typically had greater pPRK1/total PRK1 (P = .02) as well as greater pPDK/total PDK (P = .01). The relative phosphorylation status of these 2 kinases correlated within each sample. In summary, PRK1 is present in various malignancies, but especially in serous carcinomas, where the increased activation status of PRK1 and its upstream regulator, PDK, as compared with normal OSE suggests a role in ovarian cancer development or progression.