Cancer stem cells in prostate cancer: implications for targeted therapy

Prostate cancer (PCa) is the most frequently diagnosed cancer in men and the second most common cause of cancer-related mortality among men in the developed world. Conventional anti-PCa therapies include surgery, radiation, hormonal ablation, and chemotherapy. Despite increasing efforts, these therapies are not effective for patients with advanced and/or metastatic disease. In most cases, cancer therapies fail due to an incomplete depletion of tumor cells, resulting in tumor relapse. The cancer stem cell (CSC) hypothesis is an emerging model that explains many of the molecular characteristics of oncological disease as well as the tendency of cancers to relapse, metastasize, and develop resistance to conventional therapies. CSCs are a reservoir of cancer cells that exhibit properties of self-renewal and the ability to reestablish the heterogeneous tumor cell population. The existence of PCa stem cells offers a theoretical explanation for many uncertainties regarding PCa and also for treatment resistance and disease progression once clinical cure is achieved. Therapies targeting CSCs might therefore lead to more effective cancer treatments, divergent from a traditional anti-proliferative approach, based on tumor bulk reduction accompanied by CSC-specific inhibition. Here, we focus on reviewing the historical perspective as well as concepts regarding stem cells and CSCs in PCa. In addition, we will report possible strategies and new clinical approaches that address the CSC-based concept of tumorigenesis in PCa. (C) 2017 S. Karger AG, Base

MicroRNA applications for prostate, ovarian and breast cancer in the era of precision medicine.

The high degree of conservation in microRNA from Caenorhabditiselegans to humans has enabled relatively rapid implementation of findings in model systems to the clinic. The convergence of the capacity for genomic screening being implemented in the prevailing precision medicine initiative and the capabilities of microRNA to address these changes holds significant promise. However, prostate, ovarian and breast cancers are heterogeneous and face issues of evolving therapeutic resistance. The transforming growth factor-beta (TGFβ) signaling axis plays an important role in the progression of these cancers by regulating microRNAs. Reciprocally, microRNAs regulate TGFβ actions during cancer progression. One must consider the expression of miRNA in the tumor microenvironment a source of biomarkers of disease progression and a viable target for therapeutic targeting. The differential expression pattern of microRNAs in health and disease, therapeutic response and resistance has resulted in its application as robust biomarkers. With two microRNA mimetics in ongoing restorative clinical trials, the paradigm for future clinical studies rests on the current observational trials to validate microRNA markers of disease progression. Some of today's biomarkers can be translated to the next generation of microRNA-based therapies

MicroRNA and transcription factor co-regulatory networks and subtype classification of seminoma and non-seminoma in testicular germ cell tumors

Recent studies have revealed that feed-forward loops (FFLs) as regulatory motifs have synergistic roles in cellular systems and their disruption may cause diseases including cancer. FFLs may include two regulators such as transcription factors (TFs) and microRNAs (miRNAs). In this study, we extensively investigated TF and miRNA regulation pairs, their FFLs, and TF-miRNA mediated regulatory networks in two major types of testicular germ cell tumors (TGCT): seminoma (SE) and non-seminoma (NSE). Specifically, we identified differentially expressed mRNA genes and miRNAs in 103 tumors using the transcriptomic data from The Cancer Genome Atlas. Next, we determined significantly correlated TF-gene/miRNA and miRNA-gene/TF pairs with regulation direction. Subsequently, we determined 288 and 664 dysregulated TF-miRNA-gene FFLs in SE and NSE, respectively. By constructing dysregulated FFL networks, we found that many hub nodes (12 out of 30 for SE and 8 out of 32 for NSE) in the top ranked FFLs could predict subtype-classification (Random Forest classifier, average accuracy ≥90%). These hub molecules were validated by an independent dataset. Our network analysis pinpointed several SE-specific dysregulated miRNAs (miR-200c-3p, miR-25-3p, and miR-302a-3p) and genes (EPHA2, JUN, KLF4, PLXDC2, RND3, SPI1, and TIMP3) and NSE-specific dysregulated miRNAs (miR-367-3p, miR-519d-3p, and miR-96-5p) and genes (NR2F1 and NR2F2). This study is the first systematic investigation of TF and miRNA regulation and their co-regulation in two major TGCT subtypes

miRNAs as Influencers of Cell-Cell Communication in Tumor Microenvironment

microRNAs (miRNAs) are small noncoding RNAs that regulate gene expression at the posttranscriptional level, inducing the degradation of the target mRNA or translational repression. MiRNAs are involved in the control of a multiplicity of biological processes, and their absence or altered expression has been associated with a variety of human diseases, including cancer. Recently, extracellular miRNAs (ECmiRNAs) have been described as mediators of intercellular communication in multiple contexts, including tumor microenvironment. Cancer cells cooperate with stromal cells and elements of the extracellular matrix (ECM) to establish a comfortable niche to grow, to evade the immune system, and to expand. Within the tumor microenvironment, cells release ECmiRNAs and other factors in order to influence and hijack the physiological processes of surrounding cells, fostering tumor progression. Here, we discuss the role of miRNAs in the pathogenesis of multicomplex diseases, such as Alzheimer's disease, obesity, and cancer, focusing on the contribution of both intracellular miRNAs, and of released ECmiRNAs in the establishment and development of cancer niche. We also review growing evidence suggesting the use of miRNAs as novel targets or potential tools for therapeutic applications

Estrogen-dependent dynamic profile of eNOS-DNA associations in prostate cancer

In previous work we have documented the nuclear translocation of endothelial NOS (eNOS) and its participation in combinatorial complexes with Estrogen Receptor Beta (ERβ) and Hypoxia Inducible Factors (HIFs) that determine localized chromatin remodeling in response to estrogen (E2) and hypoxia stimuli, resulting in transcriptional regulation of genes associated with adverse prognosis in prostate cancer (PCa). To explore the role of nuclear eNOS in the acquisition of aggressive phenotype in PCa, we performed ChIP-Sequencing on chromatin-associated eNOS from cells from a primary tumor with poor outcome and from metastatic LNCaP cells. We found that: 1. the eNOS-bound regions (peaks) are widely distributed across the genome encompassing multiple transcription factors binding sites, including Estrogen Response Elements. 2. E2 increased the number of peaks, indicating hormone-dependent eNOS re-localization. 3. Peak distribution was similar with/without E2 with ≈ 55% of them in extragenic DNA regions and an intriguing involvement of the 5′ domain of several miRs deregulated in PCa. Numerous potentially novel eNOS-targeted genes have been identified suggesting that eNOS participates in the regulation of large gene sets. The parallel finding of downregulation of a cluster of miRs, including miR-34a, in PCa cells associated with poor outcome led us to unveil a molecular link between eNOS and SIRT1, an epigenetic regulator of aging and tumorigenicity, negatively regulated by miR-34a and in turn activating eNOS. E2 potentiates miR-34a downregulation thus enhancing SIRT1 expression, depicting a novel eNOS/SIRT1 interplay fine-tuned by E2-activated ER signaling, and suggesting that eNOS may play an important role in aggressive PCa

miR-9 Acts as an OncomiR in Prostate Cancer through Multiple Pathways That Drive Tumour Progression and Metastasis

Identification of dysregulated microRNAs (miRNAs) in prostate cancer is critical not only for diagnosis, but also differentiation between the aggressive and indolent forms of the disease. miR-9 was identified as an oncomiR through both miRNA panel RT-qPCR as well as high-throughput sequencing analysis of the human P69 prostate cell line as compared to its highly tumorigenic and metastatic subline M12, and found to be consistently upregulated in other prostate cell lines including DU-145 and PC3. While miR-9 has been characterized as dysregulated either as an oncomiR or tumour suppressor in a variety of other cancers including breast, ovarian, and nasopharyngeal carcinomas, it has not been previously evaluated and proven as an oncomiR in prostate cancer. miR-9 was confirmed an oncomiR when found to be overexpressed in tumour tissue as compared to adjacent benign glandular epithelium through laser-capture microdissection of radical prostatectomy biopsies. Inhibition of miR-9 resulted in reduced migratory and invasive potential of the M12 cell line, and reduced tumour growth and metastases in male athymic nude mice. Analysis showed that miR-9 targets e-cadherin and suppressor of cytokine signalling 5 (SOCS5), but not NF-ĸB mRNA. Expression of these proteins was shown to be affected by modulation in expression of miR-9

Random walks on mutual microRNA-target gene interaction network improve the prediction of disease-associated microRNAs

Background: MicroRNAs (miRNAs) have been shown to play an important role in pathological initiation, progression and maintenance. Because identification in the laboratory of disease-related miRNAs is not straightforward, numerous network-based methods have been developed to predict novel miRNAs in silico. Homogeneous networks (in which every node is a miRNA) based on the targets shared between miRNAs have been widely used to predict their role in disease phenotypes. Although such homogeneous networks can predict potential disease-associated miRNAs, they do not consider the roles of the target genes of the miRNAs. Here, we introduce a novel method based on a heterogeneous network that not only considers miRNAs but also the corresponding target genes in the network model. Results: Instead of constructing homogeneous miRNA networks, we built heterogeneous miRNA networks consisting of both miRNAs and their target genes, using databases of known miRNA-target gene interactions. In addition, as recent studies demonstrated reciprocal regulatory relations between miRNAs and their target genes, we considered these heterogeneous miRNA networks to be undirected, assuming mutual miRNA-target interactions. Next, we introduced a novel method (RWRMTN) operating on these mutual heterogeneous miRNA networks to rank candidate disease-related miRNAs using a random walk with restart (RWR) based algorithm. Using both known disease-associated miRNAs and their target genes as seed nodes, the method can identify additional miRNAs involved in the disease phenotype. Experiments indicated that RWRMTN outperformed two existing state-of-the-art methods: RWRMDA, a network-based method that also uses a RWR on homogeneous (rather than heterogeneous) miRNA networks, and RLSMDA, a machine learning-based method. Interestingly, we could relate this performance gain to the emergence of "disease modules" in the heterogeneous miRNA networks used as input for the algorithm. Moreover, we could demonstrate that RWRMTN is stable, performing well when using both experimentally validated and predicted miRNA-target gene interaction data for network construction. Finally, using RWRMTN, we identified 76 novel miRNAs associated with 23 disease phenotypes which were present in a recent database of known disease-miRNA associations. Conclusions: Summarizing, using random walks on mutual miRNA-target networks improves the prediction of novel disease-associated miRNAs because of the existence of "disease modules" in these networks

A new method for discovering disease-specific miRNA-target regulatory networks

Genes and their expression regulation are among the key factors in the comprehension of the genesis and development of complex diseases. In this context, microRNAs (miRNAs) are post-transcriptional regulators that play an important role in gene expression since they are frequently deregulated in pathologies like cardiovascular disease and cancer. In vitro validation of miRNA - targets regulation is often too expensive and time consuming to be carried out for every possible alternative. As a result, a tool able to provide some criteria to prioritize trials is becoming a pressing need. Moreover, before planning in vitro experiments, the scientist needs to evaluate the miRNA-target genes interaction network. In this paper we describe the miRable method whose purpose is to identify new potentially relevant genes and their interaction networks associate to a specific pathology. To achieve this goal miRable follows a system biology approach integrating together general-purpose medical knowledge (literature, Protein-Protein Interaction networks, prediction tools) and pathology specific data (gene expression data). A case study on Prostate Cancer has shown that miRable is able to: 1) find new potential miRNA-targets pairs, 2) highlight novel genes potentially involved in a disease but never or little studied before, 3) reconstruct all possible regulatory subnetworks starting from the literature to expand the knowledge on the regulation of miRNA regulatory mechanisms

EMT/MET at the crossroad of stemness, regeneration and oncogenesis. The Ying-Yang equilibrium recapitulated in cell spheroids

The epithelial-to-mesenchymal transition (EMT) is an essential trans-differentiation process, which plays a critical role in embryonic development, wound healing, tissue regeneration, organ fibrosis, and cancer progression. It is the fundamental mechanism by which epithelial cells lose many of their characteristics while acquiring features typical of mesenchymal cells, such as migratory capacity and invasiveness. Depending on the contest, EMT is complemented and balanced by the reverse process, the mesenchymal-to-epithelial transition (MET). In the saving economy of the living organisms, the same (Ying-Yang) tool is integrated as a physiological strategy in embryonic development, as well as in the course of reparative or disease processes, prominently fibrosis, tumor invasion and metastasis. These mechanisms and their related signaling (e.g., TGF-β and BMPs) have been effectively studied in vitro by tissue-derived cell spheroids models. These three-dimensional (3D) cell culture systems, whose phenotype has been shown to be strongly dependent on TGF-β-regulated EMT/MET processes, present the advantage of recapitulating in vitro the hypoxic in vivo micro-environment of tissue stem cell niches and their formation. These spheroids, therefore, nicely reproduce the finely regulated Ying-Yang equilibrium, which, together with other mechanisms, can be determinant in cell fate decisions in many pathophysiological scenarios, such as differentiation, fibrosis, regeneration, and oncogenesis. In this review, current progress in the knowledge of signaling pathways affecting EMT/MET and stemness regulation will be outlined by comparing data obtained from cellular spheroids systems, as ex vivo niches of stem cells derived from normal and tumoral tissues. The mechanistic correspondence in vivo and the possible pharmacological perspective will be also explored, focusing especially on the TGF-β-related networks, as well as others, such as SNAI1, PTEN, and EGR1. This latter, in particular, for its ability to convey multiple types of stimuli into relevant changes of the cell transcriptional program, can be regarded as a heterogeneous "stress-sensor" for EMT-related inducers (growth factor, hypoxia, mechano-stress), and thus as a therapeutic target