About this Journal Submit a Manuscript Table of Contents
BioMed Research International
Volume 2014 (2014), Article ID 765207, 12 pages
Review Article

Novel RNA Markers in Prostate Cancer: Functional Considerations and Clinical Translation

Working Group Cancer Genome Research, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), National Center for Tumor Diseases (NCT), Im Neuenheimer Feld 460, 69120 Heidelberg, Germany

Received 7 March 2014; Revised 1 August 2014; Accepted 5 August 2014; Published 28 August 2014

Academic Editor: Andreas Doll

Copyright © 2014 Julia M. A. Pickl et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The availability of ultra-high throughput DNA and RNA sequencing technologies in recent years has led to the identification of numerous novel transcripts, whose functions are unknown as yet. Evidence is accumulating that many of these molecules are deregulated in diseases, including prostate cancer, and potentially represent novel targets for diagnosis and therapy. In particular, functional genomic analysis of microRNA (miRNA) and long noncoding RNA (lncRNA) in cancer is likely to contribute insights into tumor development. Here, we compile recent efforts to catalog differential expression of miRNA and lncRNA in prostate cancer and to understand RNA function in tumor progression. We further highlight technologies for molecular characterization of noncoding RNAs and provide an overview of current activities to exploit them for the diagnosis and therapy of this complex tumor.

1. Introduction

Prostate cancer (PCa) is the most frequent tumor in men and a major cause of cancer-related morbidity and mortality. The diagnostic application of the prostate specific antigen (PSA) has led to widespread overdiagnosis and subsequent overtreatment of clinically insignificant tumors. This problem will extensively aggravate in the future: with rising life time expectancy, the number of men diagnosed with PCa will increase since the frequency of PCa is steeply rising in elderly men. Thus, there is a huge demand for novel markers for improved PCa diagnosis, prognosis, and therapy decision.

Facilitated by the implementation of ultra-high throughput sequencing technologies, the recent discoveries of the ENCODE consortium (http://encodeproject.org/ENCODE/) confirmed that 80% of the human genome is transcribed [14]. The GENCODE effort has provided the annotation of more than 9000 lncRNAs [5], as well as micro- (mi-) RNA, small nucleolar (sno) RNA, piwi-interacting (pi) RNA, and others. In parallel, the number of investigations covering the functional analysis of these molecules has increased substantially. Based on these data, it is becoming obvious that many noncoding RNAs are involved in the regulation of gene expression in health and disease, including cancer (Figure 1). For example, global analyses of miRNA expression in cancers revealed robust signatures differentiating between malignant and benign tissues [6], between tumors of several origins, and between primary tumors and metastases [7]. The characterization of miRNA and lncRNA involvement in PCa is likely to result in a better understanding of tumor progression and the identification of novel therapy targets. Here, we provide a summary of recent progress in analyzing noncoding RNA in PCa and in attempting to advance miRNAs and lncRNAs into diagnostic and therapeutic markers.

Figure 1: Schematic view of functional networks of different RNA species in cancer. Hypothetical interactions are symbolized with dashed arrows. AGO: Argonaute protein (yellow); miR: miRNA (green); lncRNA: long noncoding RNA (red); mRNA: messenger RNA (blue); circRNA: circular RNA (blue).

2. miRNA in Prostate Cancer

MiRNAs are ~20–22 nt short noncoding RNAs, which regulate gene expression at the posttranscriptional level by mRNA repression and/or degradation. MiRNAs are transcribed as pri-miRNAs by RNA polymerase II (RNA Pol II) and processed by the RNase III enzyme Drosha to generate precursor miRNAs (pre-miRNAs; Figure 1) [8]. Dicer, another RNase III enzyme, then cleaves the pre-miRNA into ~20–22 long RNA duplexes. Subsequently, the strand with the stable 5′ end is removed, whereas the complementary strand with the less stable 5′ end is incorporated into Argonaute (AGO) proteins to form the RNA induced silencing complex (RISC). MiRNAs guide the RISC to target mRNAs via sequence complementarity [811].

Many miRNAs are known to be deregulated in cancer [6]. For instance, miRNAs are differentially expressed between benign prostate and PCa tissues: in a genomewide microarray-based microRNA expression study, 25 miRNAs were found to be deregulated [12]. Here, miR-375 and miR-200c showed highest upregulation in PCa tumor tissue, whereas miR-221 and miR-222 were the most downregulated miRNAs [12]. Using a sequencing-based approach, the same group identified 33 miRNAs being up- or downregulated >1.5-fold in PCa tissue [13]. Here, miR-143 and miR-145 were the highest downregulated ones in PCa [13]. Consistent with these data, an independent study found miR-145, miR-221, and miR-222 among the five most significantly downregulated miRNAs [14], and we identified miR-375 and miR-141 as significantly upregulated in PCa tissue [15].

Other analyses revealed the association of miRNA expression with distinct PCa: for instance, miR-375 expression was reported to be dependent on pT and pN status (TNM staging system) of PCa patients, with the highest enrichment in pN1 tumors [16]. Moreover, ten miRNAs (including miR-145, miR-221, and miR-222) were downregulated and five (including miR-375and miR-96) upregulated in advanced PCa, whereas miR-96 was associated with tumor recurrence after radical prostatectomy [17]. MiRNAs are also known to correlate with Gleason score: in high-grade PCa, increased expression of miR-31, miR-182, and miR-205 was identified when compared to intermediate-grade PCa [18].

The functional consequences of differential expression of various miRNAs have been studied in vitro by many groups. Here, we can address only the most prominent examples: miR-375 was found upregulated in several PCa studies and was known to target Sec23 homolog A(SEC23A) [19], which was involved in trafficking from ER to Golgi [20]. The authors suggested that miR-375-mediated SEC23A downregulation impairs cellular immunogenicity of PCa by reducing HLA class I cell surface receptors [19]. MiR-375 was also shown to downregulate the phosphatase PHLPP2 and to strongly increase prostate carcinoma cell growth [16]. MiR-141, which is upregulated in PCa tissue, was found to downregulate the gene coding for the nuclear receptor subfamily 0, group B, member 2 (NR0B2) in prostate epithelial cells. In this way, miR-141 prevented the inhibitory effects of NR0B2 on androgen receptor- (AR-) regulated genes [21]. In contrast, miR-143 and miR-145 were found to be downregulated in PCa tissue and to be involved in PCa development via regulation of myosin VI (MYO6) [13]. MYO6 was involved in cancer cell dissemination and described as a potential PCa marker [22, 23].

Interestingly, miRNAs, which have not been described as highly deregulated in PCa tissues, were also found to play crucial roles in prostate carcinogenesis. For instance, miR-200b attenuated PCa cell growth and invasiveness [24, 25]. Studies in the PCa cell line PC-3 suggested that miR-200b mediates the reversal of the epithelial-to-mesenchymal transition (EMT) by targeting the prometastatic transcription factors Zinc finger E-box binding homeobox 1 and 2 (ZEB1 and ZEB2) [25]. Overexpression of miR-200b led to increased levels of the epithelial markers E-cadherin, cytokeratins 8 and 18, as well as downregulation of the mesenchymal markers fibronectin and vimentin [25, 26]. Another study found miR-1 to be reduced with PCa progression. SLUG is a regulator of mesenchymal differentiation and was assumed to repress miR-1 and miR-200 transcription whereas miR-1 and miR-200 are also able to regulate SLUG by a mutually inhibitory feedforward loop [27]. Moreover, miR-1 was found to act as a mediator of oncogenic pathways in the PCa cell lines PC-3 and LNCaP: the heat-shock protein HSPB1 reduced miR-1 levels leading to an activation of AR and TGFB1 signaling cascades [28].

MiRNAs are also able to regulate the expression of important epigenetic marker genes. For instance, miR-34b targeted methyltransferases and deacetylases in PCa [29]. MiR-34b is also an example for epigenetic miRNA regulation via a positive feedback loop. MiR-34b was found to directly target the AKT pathway like AKT itself and its downstream genes GSK3B, CTNNB1, MYC, and CCND1, which were involved in cell proliferation and survival [29]. In a PCa xenograft model, miR-34b exhibited antitumor properties by decreasing prostate tumor growth [29]. This was probably due to affecting EMT since miR-34b expression decreased the mesenchymal markers vimentin, ZO1, N-cadherin, and SNAIL, and increased E-cadherin [29]. Furthermore, miR-152 was reported to downregulate DNA (cytosine-5)-methyltransferase 1 (DNMT1) in LNCaP, PC-3, and MDA-PCa-2b cells. DNMT1 siRNA caused an increase of miR-152 expression, suggesting a reciprocal relationship between DNMT1 and miR-152. Increased DNMT1 and depletion of miR-152 were assumed to arise during the progression to advanced PCa [30]. The miR-200 family was downregulated by the histone methyltransferase enhancer of zeste homolog 2 (EZH2) [24]. EZH2 is a component of the polycomb repressive complex 2 (PRC2), which is involved in epigenetic regulation of cell homeostasis. EZH2 expression was elevated in aggressive forms of PCa [31]. MiR-200 family on the other hand represses PRC1 proteins BMI1 and RING2. Therefore, increased PRC2 levels lead to an increase of PRC1 expression due to miRNA linkage, suggesting crucial roles for miRNA in regulating the epigenetic silencing machinery [24].

MiRNAs are primarily known as key regulators of active genes. However, it has recently been shown that the expression of the PTEN pseudogene (PTENP1) is able to rescue the expression levels of its ancestral gene PTEN by competing for the same set of miRNAs (miR-20a, miR-19b, miR-21, miR-26a, and miR-214) [32]. Similarly, the pseudogene KRASP1 derepressed KRAS in DU145 cells, probably by sharing common sites for miR-143 and let-7 [32]. Thus, expressed pseudogenes can display tumor suppressive or oncogenic properties by acting as competitive endogenous RNAs (ceRNAs) for their corresponding active genes: the increased number of miRNA binding sites upon pseudogene expression was able to titrate the pool of available miRNAs in PCa cells, and miRNA concentrations are regulated by the abundances of their target genes. In this concept, target RNAs are not only passive substrates of miRNAs but also active players in the regulatory networks leading to PCa progression.

The identification of their target genes is essential to estimate the potential of miRNAs as biomarkers. Many bioinformatic tools are able to predict miRNA target genes (Table 1). However, since these tools are based on certain assumptions (e.g., base complementarity in the 3′UTR, thermodynamic stability, target-site accessibility, and evolutionary conservation of miRNA binding sites), their predictions are accompanied by large numbers of false positives. Thus, experimental approaches for targetome identification in vitro are required. For example, using AGO-RNA immunoprecipitation, followed by sequencing (AGO-RIP-Seq) AGO2/miRNA/RNA target complexes are captured from cells stably expressing a miRNA of interest. MiRNA-associated targets are then identified and quantified by deep transcriptome sequencing. AGO-RIP-Seq also enables the identification of novel nonannotated RNA targets like lncRNAs or pseudogenes. Other methods (AGO-HITS-CLIP [33, 34], AGO-PAR-CLIP [35], and CLASH [36]) use crosslinking of the AGO complex to obtain more information about miRNA binding to target genes. These techniques have revealed that some miRNAs can also bind their targets in the coding regions of genes and that other miRNAs do not require base complementarity at all in order to regulate target gene expression [3336]. These methods are rather novel, and systematic studies reporting the experimental analysis of genomewide miRNA targetomes in PCa have not been described to the best of our knowledge.

Table 1: Databases and tools for functional annotation of miRNAs and lncRNAs.

MiRNAs are also known to be present in the nucleus [3740]. Nuclear miRNAs are considered as regulators of gene expression at the transcriptional level (reviewed in [41]). For instance, miRNAs are supposed to bind to promoter sequences in an AGO-dependent manner to regulate gene transcription in the PCa cell line PC-3. This hypothesis was supported by the finding that AGO1-bound promoter sequences contain putative miRNA binding sites [39] and suggest a role for miRNAs in PCa not only in the cytoplasm, but also in the nucleus.

3. Long Noncoding RNA in Prostate Cancer

Long noncoding RNAs (lncRNAs) are defined by their length, which ranges from 200 bases up to 100 kb. LncRNAs have adopted the transcriptional machinery from protein-coding genes (Figure 1): they are primarily transcribed by RNA Pol II, frequently contain a 5′ terminal methylguanosine cap, and are often spliced and polyadenylated [42]. However, a set of nonpolyadenylated lncRNAs has also been identified to be transcribed from RNA polymerase III promoters [43, 44]. The fact that lncRNAs have been found to bind to ribosomes raises the possibility that they are potentially translatable into proteins. Indeed, ribosome profiling [45] and mass spectrometry approaches [46] detected small peptides potentially derived from lncRNAs. However, the lack of conserved long open reading frames supports the idea that lncRNAs do not encode proteins but rather exert regulatory functions. LncRNAs are cataloged according to their genomic localization: long intergenic noncoding RNAs (lincRNAs) are derived from regions that are devoid of other genes, whereas intronic lncRNAs are transcribed from introns of protein coding genes. LncRNAs originating from opposite strands of the same genomic locus are called sense/antisense pairs and are divided into convergent (head-to-head), divergent (tail-to-tail), and fully overlapping transcripts [47]. LncRNAs are expressed at much lower levels and with much higher cell-type specificity than mRNAs [5]. Although lncRNAs are observed in many species, their degrees of evolutionary conservation are low, and some of the human lncRNAs are thought to have arisen solely in primates [5].

In PCa, the most prominent and clinically relevant RNA biomarker is the antisense lncRNA PCA3, which is overexpressed in >95% of primary tumors [48]. PCA3 is a diagnostic biomarker detectable in urine [49], with higher specificity compared to PSA [50]. One of the first lncRNAs suggested as a marker for PCa incidence, androgen-dependent proliferation, and antiapoptotic signaling in cell lines was the PCa gene expression marker 1 (PCGEM1) [5154]. Overexpression of PCGEM1 in tumor cells inhibited PARP (poly-ADP-ribose-polymerase) cleavage and delayed the induction of p53 and p21 [52], resulting in increased chemoresistance. PCGEM1 was found to bind to AR at methylated K349 and to regulate the expression of AR target genes, which stimulated tumor growth in a PCa xenograft mouse model [54]. Additionally, two single-nucleotide polymorphisms (SNP) contributing to cancer risk were identified in PCGEM1 [55].

In a more recent and comprehensive study, Prensner and colleagues, by analyzing the transcriptomes of 102 prostate tumors and cell lines using next generation sequencing [56], identified 121 so far nonannotated PCa-associated noncoding RNA transcripts (PCATs). PCAT-1 was upregulated in a subset of metastatic and high-grade localized prostate tumors. PCAT-1, a transcriptional target of EZH2, stimulated cell proliferation [56] and impaired homologous recombination by repressing of the BRCA2 gene [57]. PCa noncoding RNA 1 (PRNCR1; PCAT-8), which is located immediately adjacent to PCAT-1 and the c-MYC oncogene at the well-known PCa risk locus on chromosome 8q24 [58, 59], was identified to be upregulated in aggressive prostate tumors [54]. PRNCR1-bound DOT1-like histone H3K79 methyltransferase (DOT1L) methylated the AR at position K349, which mediated the interaction of AR with PCGEM1, thereby resulting in ligand-independent activation of AR signaling and cell proliferation [54]. PCAT-18 was recently suggested as a biomarker for metastatic PCa [60]. Knockdown of PCAT-18 decreased cell proliferation, migration, and invasion but also triggered apoptosis by promoting caspase activity [60]. In another study, PCAT-114 (SCHLAP1) expression correlated with high-grade, metastatic PCa (see below). By analyzing the transcriptomes of 14 prostate tumors and adjacent benign tissues in another genomewide approach, 137 new lncRNAs were identified [61]. One of these, the metastasis associated in lung adenocarcinoma transcript 1 (MALAT-1), was suggested to be a novel marker for PCa diagnosis [62]: high expression of MALAT-1 correlated with high Gleason score, PSA, tumor stage, and castration-resistant PCa (CRPC).

The majority of PCa are driven by androgen signaling. Various studies have highlighted the functions of androgen-responsive or AR-interacting lncRNAs: Takayama and colleagues identified the antisense lncRNA C-terminal binding protein (CTBP1-AS) as highly upregulated in PCa, by repressing its sense gene CTBP1, an AR corepressor. This is achieved by recruitment of the transcriptional repressor SFPQ (splicing factor proline/glutamine-rich) and histone deacetylases to the promoter of CTBP1 [63], thereby promoting androgen-dependent and castration-resistant tumor growth [63]. The PCa-upregulated lncRNA PlncRNA-1 modulates apoptosis and proliferation through regulation of the AR [64]. Recently, PCAT-29 was identified as an androgen-repressed suppressor of growth and metastases of prostate tumors [65]. The same group contradicted the prognostic value of PCGEM1 and PRNCR1 in aggressive PCa [54]: in a large high-risk PCa patient cohort, Prensner and colleagues could not find any evidence for the binding of these lncRNAs to the AR [66].

As lncRNAs do not encode proteins, their functions are closely associated with their abundance. Bioinformatic tools such as the “guilt by association analysis” [67] are capable of predicting the function of an lncRNA. This method uses coexpression analysis of lncRNAs with protein coding genes in signaling pathways to predict the functions of the lncRNAs. This approach has led to the prediction of various roles for lncRNAs, ranging from stem cell pluripotency to cancer [42]. Besides such bioinformatic approaches and databases listing annotated lncRNAs and functional assignment (Table 1), several crosslinking methodologies have been developed to experimentally elucidate the interactomes of lncRNAs in vitro. Chromatin isolation with RNA purification (ChIRP) [68] and capture analysis of RNA targets (CHART) [69] are able to copurify lncRNA-bound proteins and DNA in juxtaposition. In DHT- (dihydrotestosterone-) stimulated LNCaP PCa cells, ChIRP uncovered thousands of PCGEM1 occupancy sites, colocalizing with ARE and H3K4me1-marked enhancers [54].

The regulatory potential of lncRNAs, in particular lincRNAs, has been best characterized in the context of their roles as epigenetic modulators. It was observed that 20% of cellular lncRNAs are associated with specific chromatin modification complexes, such as PRC2, which mediates histone H3 lysine 27 trimethylation (H3K27me3) [70, 71]. ANRIL, an lncRNA overexpressed in PCa, mediated epigenetic silencing of the adjacent tumor suppressor p15 via H3K27 trimethylation of the CDKN2A (INK4A/ARF) locus by directly interacting with SUZ12, a component of PRC2, and CBX7, a PRC1-associated chromodomain-containing protein [72, 73]. In aggressive PCa, aberrantly high expression of PCAT-114 inhibited SWI/SNF-mediated epigenetic regulation, due to direct disruption of SNF5 activity, a core unit of the SWI/SNF complex [74]. As it has been shown that the expression of PCa-associated lncRNAs can be regulated by long terminal repeats (LTRs) [75], PCAT-114 might be regulated through an LTR in its 5′UTR (own unpublished observations).

Currently, there is little evidence for a direct interaction between lncRNAs and DNA [68]. In contrast, the crosstalk of lncRNA with other RNA species has been studied in detail [35, 76]. Antisense lncRNAs can regulate the stability and translation of complementary mRNAs. For example, translation of the UCHL1 mRNA was found to be regulated by its antisense lncRNA through complementary 5′ overlap and an embedded inverted SINEB2 element [77]. In another example, imperfect base pairing between Alu elements in lncRNAs and the 3′UTR of translationally active mRNAs resulted in a double-stranded RNA, which is bound by staufen double-stranded RNA binding protein 1 (STAU1) and subsequently targeted for degradation [78].

The ceRNA concept [32] also suggests that lncRNAs—like mRNAs—act as natural sponges (Figure 1). In this context, a long noncoding circular RNA (circRNA) was identified to harbor more than 70 target sites for miR-7. Binding of this miRNA to the sponge circRNA suppressed miRNA activity, resulting in miRNA target derepression [79, 80]. CircRNA datasets are publically available via http://www.circbase.org/ (Table 1).

The noncoding part of the human genome offers comprehensive prospects to identify the genetic factors and mechanisms, which are critical for PCa initiation, development, and progression. However, a recent study suggests that a particular lncRNA may exert both oncogenic and tumor-suppressive functions in PCa [81]. This indicates that lncRNA action is highly context-dependent, and further efforts are required to understand the increasing complexity of lncRNA function in health and disease.

4. PCa Diagnosis and Treatment Monitoring Using Circulating RNA Markers

The remarkable stability of noncoding RNAs prompted efforts to evaluate their potential as diagnostic or prognostic molecular markers. In particular, genetic material released from tumor cells into the blood or other body fluids (“liquid biopsy”) could provide a rich source of such markers that can be exploited to gain insights into the molecular alterations associated with disease progression [82]. In PCa, liquid biopsies could be highly valuable since the heterogeneity of the tumors often precludes precise staging and grading. In addition, a faithful representation of tumor aggressiveness in easily accessible liquids could lead to an improved therapy decision.

MiRNAs circulating freely in blood have been studied as potential biomarkers for PCa [83, 84]. Several miRNAs were demonstrated to discriminate between PCa and healthy controls or patients with benign prostate hyperplasia (BPH) [83, 85], as well as between localized and metastatic PCa [86]. Brase et al. observed an overall higher level of circulating miRNAs in serum samples of patients with advanced PCa compared to those with primary PCa [15]. Of 667 miRNAs screened, 69 miRNAs were found to be more abundant in sera of lymph-node positive versus negative PCa patients. MiR-375 and miR-141 showed statistically significant correlation with clinical patient parameters and were identified as the best serum markers for aggressive PCa [15]. Significantly higher abundance of miR-141 in localized PCa compared to metastatic disease in plasma samples was also seen by other groups [87, 88], while miR-21 distinguished best between early-stage disease and healthy controls and was correlated with resistance to docetaxel [89]. Serum miR-194 correlated with biochemical recurrence and poor prognosis [88]. The first clinical studies are ongoing which examine the benefit of circulating miRNAs for PCa diagnosis and disease monitoring (Table 2). These include investigations to determine whether specific miRNA profiles are related to PCa outcome in high-risk PCa patients as well as screening studies for novel markers (including miRNA and lncRNA) associated with tumor progression in general (e.g., http://www.mdanderson.org/) or with locally recurrent or metastatic PCa. Furthermore, the potential of circulating miRNA markers as tools for companion diagnostics in clinical trials (prediction of therapy response against abiraterone or combination therapies; Table 2) is currently being explored.

Table 2: MiRNA-based biomarker studies in prostate cancer.

Two recent studies suggested the detection of transcript levels of selected mRNAs in whole-blood samples of patients with CRPC as useful prognostic markers [90, 91]: a panel consisting of six circulating mRNA markers (ABL2, C1QA, SEMA4D, TIMP1, ITGAL, and CDKN1A) predicted survival when compared to clinical and histopathological parameters of prognostic significance in CRPC [91]. Poor prognosis and poor overall survival of patients with CRPC were correlated with a nine-gene model (RHAG, CA1, HEPACAM2, SNCA, HEMGN, SOX6, TMEM56, OSBP2, and RHD) [90]. The determination of PCA3 in peripheral blood in combination with increased PSA level (>10 ng/mL) showed high specificity and improved diagnostic accuracy to distinguish BPH from PCa [92]. Since PCa often carries genomic rearrangements involving androgen-regulated genes, the role of rearrangement-associated biomarkers could also be exploited for diagnostic purposes. Urine-based combined detection of PCA3 and TMPRSS2:ERG DNA was used for improved risk stratification of men with elevated serum PSA levels to guide further disease management [93], and changes in PCA3 and TMPRSS2:ERG levels are currently used as marker to evaluate the effect of treatment with the gonadotropin-releasing hormone agonist Triptorelin (Decapeptyl) in a Phase III multicenter study in patients with advanced PCa (NCT01020448; https://clinicaltrials.gov/). A multiplex marker panel consisting of PCA3, TMPRSS2:ERG, annexin A3, sarcosine, and serum PSA showed improved diagnostic accuracy for PCa [94].

Circulating miRNAs have been found to be present in microvesicles such as exosomes (Figure 1). Exosomes are nanosized (40–100 nm) extracellular vesicles secreted from cells via the endosomal pathway. Tumor cells release exosomes at increased levels, which are then detectable in different body fluids. Exosomal miRNAs reflect the miRNA signature of the tumor, and differences in miRNA content and expression were found in exosomes derived from cancerous versus noncancerous cell lines and in tumor-derived exosomes compared to those from healthy individuals [9597]: in PC-3 cell lines, miRNA profiling identified 31 miRNAs that were exclusively present in exosomes [96]. In larger extracellular vesicles (>200 nm), miR-141, miR-375, and miR-205, known to be associated with PCa progression, and miR-31 (which targets AR) were differentially expressed [97]. So far, there are only few reports analyzing miRNAs in microvesicles derived from PCa patients. However, a recent study found differential expression of eleven miRNAs, of which miR-107 exhibited the largest differential expression in circulating microvesicles from PCa patients compared to controls [86]. Additionally, 16 miRNAs were found to be enriched in microvesicles of patients with metastatic PCa compared to patients with organ-confined disease [86]. In this study, miR-375 and miR-141 were significantly enriched in plasma-derived microvesicles from patients with metastatic disease. Exosomal TMPRSS2:ERG and PCA3 mRNA from urine samples of untreated PCa patients have also been proposed as a potential diagnostic test [98].

All exosomal content is derived from their parental cells. However, the precise mechanism of miRNA/lncRNA/protein delivery into exosomes is not fully understood. Notably, the RNA and protein cargo within exosomes was shown to be functionally active in recipient cells, which suggests that tumor cells can exploit circulating exosomes as a means to “communicate” with their regional or distal environment [95, 99, 100].

5. Preclinical Studies for ncRNA-Based PCa Therapy

With the identification of PCa-specific miRNA expression patterns and the understanding of their role in PCa biology, novel opportunities for miRNA-based therapies arise. These include targeting the 3′UTRs of oncogenes using specific miRNAs, restoring normal intracellular miRNA pools, or enhancing therapeutic response by combining miRNA with existing anticancer drugs, attempting to exploit the concept of synthetic lethality. In this section, we highlight in vivo studies that support the implementation of miRNA-based therapeutics (Table 3).

Table 3: MiRNA-based therapeutics in prostate cancer preclinical trials.

The ability of let-7 to inhibit tumor initiation was first demonstrated in a murine CD44-positive xenograft model, where overexpression and therapeutic injection of let-7 resulted in delayed tumor formation [101103]. Intratumoral administration of miR-199a-3p mimics into a murine PCa xenograft model led to decreased expression of the oncogene Aurora kinase A (AurkA), which is associated with a malignant PCa phenotype [104]. In another murine xenograft model, using transfected PCa cell lines [103], miR-128 showed antiproliferative as well as proapoptotic effects and negatively regulated PCa stem cells by directly targeting the stem cell related genes Bmi-1 and Nanog (Nanog homeobox). Additionally, clonogenic and tumorigenic properties of PCa cells were inhibited in a dose-dependent manner by different levels of endogenous miR-128. MiR-16 replacement therapy in a luciferase PCa xenograft substantially reduced bone metastatic tumor growth compared to untreated mice [105]. MiR-26a, which is downregulated in PCa, was shown to inhibit growth and metastatic progression of human-tumor xenografts, probably by targeting lin-28 homolog B (Lin28B) and zinc finger CCHC domain containing 11 (ZCCHC11) [106]. Finally, downregulation of the lncRNA MALAT-1 delayed tumor growth in vivo and reduced metastasis of PCa xenografts in castrated male nude mice [62].

Intratumoral and systemic injection of miR-34a into mice grafted with human PCa tumors resulted in reduced tumor volumes and lung metastasis and was associated with prolonged survival by suppressing the adhesion molecule CD44 [107]. Deregulated miR-34a expression was also linked to drug resistance, showing a sevenfold decrease in paclitaxel-resistant PC-3 cells compared to wild-type PC-3 cells [108]. Overexpression of miR-34a in paclitaxel-resistant PC-3 cells recovered paclitaxel sensitivity, while miR-34a antagomir transfection attenuated it [108].

Liu et al. [107] and Kojima et al. [108] presented a rationale for miR-34a-based therapy to target PCa stem cells and drug-resistant PCa. MiR-34a has emerged as therapeutical agent under the name MRX34, a liposome-encapsulated miR-34 mimic (http://www.mirnatherapeutics.com) and is currently being studied in a multicenter Phase I clinical trial in patients with unresectable primary liver cancer and liver metastases derived from tumors of other primary origin (NCT01829971; https://clinicaltrials.gov/).

Restoration of miR-30b expression by src tyrosine kinase (Src) inhibitors was able to prolong survival and reduce metastatic disease of VCaP-derived xenograft mice by negatively regulating TMPRSS2:ERG and downregulating EMT-associated as well as ERG target genes [109]. Consequently, inhibitors of the AR activator Src are currently being tested in Phase I and II clinical trials for the treatment of PCa patients. Similar to the reconstitution of silenced miRNAs, suppression of overexpressed miRNAs was also shown to be a potential therapeutic approach: Mercatelli et al. established an antagomir targeting miR-221 [110]. Inverse correlation of miR-221 and p27 protein level was validated in primary cells from 18 patients with stage II-III PCa. In mouse xenograft models, intratumoral injection of a miR-221 antagomir led to significantly reduced tumor growth, which was correlated with p27 upregulation [110].

There are currently no clinical trials studying miRNAs as therapeutics in human PCa. However, the data from these and other preclinical in vivo models using miRNA-based therapeutic approaches provide promising results for potential future applications in human PCa.

6. Summary

The advent of ultra-high throughput sequencing technologies has caused a vast expansion of the catalog of noncoding RNA molecules. Thus, on the one hand, we are closer to an overview of the transcriptional landscapes in health and disease. On the other hand, the complexity of regulatory factors has grown substantially, and we have just started to uncover some underlying principles: although miRNAs are probably the best investigated class of noncoding RNAs, the recent discoveries of complex miRNA and ceRNA networks and nuclear miRNAs indicate that our understanding of miRNAs in PCa progression is far from complete. Similarly, the analysis of lncRNAs has just commenced, and the roles of the majority of PCATs and other lncRNAs in PCa remain to be investigated. The reports on novel diagnostic PCa biomarkers from liquid biopsies are encouraging. However, the data are mostly based on discovery-driven approaches that frequently have limited validity due to small sample sizes, nonstandardized settings, and different experimental designs. Thus, the diagnostic and therapeutic benefits of many potential RNA markers in PCa still need to be proven in well-controlled and standardized large-scale prospective clinical studies.


BPH:Benign prostate hyperplasia
ceRNA:Competitive endogenous RNA
CHART:Capture analysis of RNA targets
ChIP:Chromatin immunoprecipitation
ChIRP:Chromatin isolation with RNA purification
circRNA:Circular RNA
CLASH:Crosslinking, ligation, and sequencing of hybrids
CRPC:Castration-resistant prostate cancer
EMT:Epithelial-to-mesenchymal transition
HITS-CLIP:High throughput sequencing of RNA isolated by UV crosslinking immunoprecipitation
lincRNAs:Long intergenic noncoding RNAs
lncRNA:Long noncoding RNA
PAR-CLIP:Photoactivatable-ribonucleoside-enhanced crosslinking and immunoprecipitation
PCa:Prostate cancer
PCAT:Prostate cancer associated transcript (nonprotein coding)
piRNA:piwi-interacting RNA
PRC2:Polycomb repressive complex 2
PSA:Prostate-specific antigen
RIP-Seq:RNA immunoprecipitation sequencing
RISC:RNA-induced silencing complex.

Conflict of Interests

The authors declare that there is no conflict of interests regarding the publication of this paper.

Authors’ Contribution

Julia M. A. Pickl and Doreen Heckmann contributed equally to this work.


This work was supported by the German Federal Ministry of Education and Science in the framework of the Program for Medical Genome Research (FKZ 01KU1001A), the Bruno und Helene Jöster Stiftung, and the German Cancer Consortium (DKTK).


  1. G. K. Wong, D. A. Passey, and J. Yu, “Most of the human genome is transcribed,” Genome Research, vol. 11, no. 12, pp. 1975–1977, 2001. View at Publisher · View at Google Scholar · View at Scopus
  2. P. Kapranov, S. E. Cawley, J. Drenkow et al., “Large-scale transcriptional activity in chromosomes 21 and 22,” Science, vol. 296, no. 5569, pp. 916–919, 2002. View at Publisher · View at Google Scholar · View at Scopus
  3. P. Bertone, V. Stolc, T. E. Royce et al., “Global identification of human transcribed sequences with genome tiling arrays,” Science, vol. 306, no. 5705, pp. 2242–2246, 2004. View at Publisher · View at Google Scholar · View at Scopus
  4. S. Djebali, C. A. Davis, A. Merkel et al., “Landscape of transcription in human cells,” Nature, vol. 489, no. 7414, pp. 101–108, 2012. View at Publisher · View at Google Scholar · View at Scopus
  5. T. Derrien, R. Johnson, G. Bussotti et al., “The GENCODE v7 catalog of human long noncoding RNAs: analysis of their gene structure, evolution, and expression,” Genome Research, vol. 22, no. 9, pp. 1775–1789, 2012. View at Publisher · View at Google Scholar · View at Scopus
  6. J. Lu, G. Getz, E. A. Miska et al., “MicroRNA expression profiles classify human cancers,” Nature, vol. 435, no. 7043, pp. 834–838, 2005. View at Publisher · View at Google Scholar · View at Scopus
  7. Z. Du, T. Fei, R. G. W. Verhaak et al., “Integrative genomic analyses reveal clinically relevant long noncoding RNAs in human cancer,” Nature Structural and Molecular Biology, vol. 20, no. 7, pp. 908–913, 2013. View at Publisher · View at Google Scholar · View at Scopus
  8. S. Djuranovic, A. Nahvi, and R. Green, “miRNA-mediated gene silencing by translational repression followed by mRNA deadenylation and decay,” Science, vol. 336, no. 6078, pp. 237–240, 2012. View at Publisher · View at Google Scholar · View at Scopus
  9. H. Guo, N. T. Ingolia, J. S. Weissman, and D. P. Bartel, “Mammalian microRNAs predominantly act to decrease target mRNA levels,” Nature, vol. 466, no. 7308, pp. 835–840, 2010. View at Publisher · View at Google Scholar · View at Scopus
  10. J. E. Braun, E. Huntzinger, M. Fauser, and E. Izaurralde, “GW182 proteins directly recruit cytoplasmic deadenylase complexes to miRNA targets,” Molecular Cell, vol. 44, no. 1, pp. 120–133, 2011. View at Publisher · View at Google Scholar · View at Scopus
  11. D. P. Bartel, “MicroRNAs: target recognition and regulatory functions,” Cell, vol. 136, no. 2, pp. 215–233, 2009. View at Publisher · View at Google Scholar · View at Scopus
  12. S. Wach, E. Nolte, J. Szczyrba et al., “MicroRNA profiles of prostate carcinoma detected by multiplatform microRNA screening,” International Journal of Cancer, vol. 130, no. 3, pp. 611–621, 2012. View at Publisher · View at Google Scholar · View at Scopus
  13. J. Szczyrba, E. Löprich, S. Wach et al., “The microRNA profile of prostate carcinoma obtained by deep sequencing,” Molecular Cancer Research, vol. 8, no. 4, pp. 529–538, 2010. View at Publisher · View at Google Scholar · View at Scopus
  14. A. W. Tong, P. Fulgham, C. Jay et al., “MicroRNA profile analysis of human prostate cancers,” Cancer Gene Therapy, vol. 16, no. 3, pp. 206–216, 2009. View at Publisher · View at Google Scholar · View at Scopus
  15. J. C. Brase, M. Johannes, T. Schlomm et al., “Circulating miRNAs are correlated with tumor progression in prostate cancer,” International Journal of Cancer, vol. 128, no. 3, pp. 608–616, 2011. View at Publisher · View at Google Scholar · View at Scopus
  16. M. Hart, E. Nolte, S. Wach et al., “Comparative microRNA profiling of prostate carcinomas with increasing tumor stage by deep sequencing,” Molecular Cancer Research, vol. 12, no. 2, pp. 250–263, 2014. View at Publisher · View at Google Scholar
  17. A. Schaefer, M. Jung, H. Mollenkopf et al., “Diagnostic and prognostic implications of microRNA profiling in prostate carcinoma,” International Journal of Cancer, vol. 126, no. 5, pp. 1166–1176, 2010. View at Publisher · View at Google Scholar · View at Scopus
  18. K. Tsuchiyama, H. Ito, M. Taga et al., “Expression of microRNAs associated with Gleason grading system in prostate cancer: miR-182-5p is a useful marker for high grade prostate cancer,” Prostate, vol. 73, no. 8, pp. 827–834, 2013. View at Publisher · View at Google Scholar · View at Scopus
  19. J. Szczyrba, E. Nolte, S. Wach et al., “Downregulation of Sec23A protein by miRNA-375 in prostate carcinoma,” Molecular Cancer Research, vol. 9, no. 6, pp. 791–800, 2011. View at Publisher · View at Google Scholar · View at Scopus
  20. M. R. Lang, L. A. Lapierre, M. Frotscher, J. R. Goldenring, and E. W. Knapik, “Secretory COPII coat component Sec23a is essential for craniofacial chondrocyte maturation,” Nature Genetics, vol. 38, no. 10, pp. 1198–1203, 2006. View at Publisher · View at Google Scholar · View at Scopus
  21. J. Xiao, A. Gong, A. N. Eischeid et al., “MiR-141 modulates androgen receptor transcriptional activity in human prostate cancer cells through targeting the small heterodimer partner protein,” Prostate, vol. 72, no. 14, pp. 1514–1522, 2012. View at Publisher · View at Google Scholar · View at Scopus
  22. S. Wei, T. A. Dunn, W. B. Isaacs, A. M. de Marzo, and J. Luo, “GOLPH2 and MYO6: putative prostate cancer markers localized to the Golgi apparatus,” Prostate, vol. 68, no. 13, pp. 1387–1395, 2008. View at Publisher · View at Google Scholar · View at Scopus
  23. T. A. Dunn, S. Chen, D. A. Faith et al., “A novel role of myosin VI in human prostate cancer,” The American Journal of Pathology, vol. 169, no. 5, pp. 1843–1854, 2006. View at Publisher · View at Google Scholar · View at Scopus
  24. Q. Cao, R. Mani, B. Ateeq et al., “Coordinated regulation of polycomb group complexes through microRNAs in cancer,” Cancer Cell, vol. 20, no. 2, pp. 187–199, 2011. View at Publisher · View at Google Scholar · View at Scopus
  25. L. V. Williams, D. Veliceasa, E. Vinokour, and O. V. Volpert, “miR-200b inhibits prostate cancer EMT, growth and metastasis,” PLoS ONE, vol. 8, no. 12, Article ID e83991, 2013.
  26. P. A. Gregory, A. G. Bert, E. L. Paterson et al., “The miR-200 family and miR-205 regulate epithelial to mesenchymal transition by targeting ZEB1 and SIP1,” Nature Cell Biology, vol. 10, no. 5, pp. 593–601, 2008. View at Publisher · View at Google Scholar · View at Scopus
  27. Y.-. Liu, J. J. Yin, W. Abou-Kheir et al., “MiR-1 and miR-200 inhibit EMT via Slug-dependent and tumorigenesis via Slug-independent mechanisms,” Oncogene, vol. 32, no. 3, pp. 296–306, 2013. View at Publisher · View at Google Scholar · View at Scopus
  28. M. B. Stope, C. Stender, T. Schubert et al., “Heat-shock protein HSPB1 attenuates microRNA miR-1 expression thereby restoring oncogenic pathways in prostate cancer cells,” Anticancer Research, vol. 34, no. 7, pp. 3475–3480, 2014.
  29. S. Majid, A. A. Dar, S. Saini et al., “miRNA-34b inhibits prostate cancer through demethylation, active chromatin modifications, and AKT pathways,” Clinical Cancer Research, vol. 19, no. 1, pp. 73–84, 2013. View at Publisher · View at Google Scholar · View at Scopus
  30. S. C. Theodore, M. Davis, F. Zhao et al., “MicroRNA profiling of novel African American and Caucasian Prostate Cancer cell lines reveals a reciprocal regulatory relationship of miR-152 and DNA methyltranferase 1,” Oncotarget, vol. 5, no. 11, pp. 3512–3525, 2014.
  31. S. Varambally, J. Yu, B. Laxman et al., “Integrative genomic and proteomic analysis of prostate cancer reveals signatures of metastatic progression,” Cancer Cell, vol. 8, no. 5, pp. 393–406, 2005. View at Publisher · View at Google Scholar · View at Scopus
  32. L. Poliseno, L. Salmena, J. Zhang, B. Carver, W. J. Haveman, and P. P. Pandolfi, “A coding-independent function of gene and pseudogene mRNAs regulates tumour biology,” Nature, vol. 465, no. 7301, pp. 1033–1038, 2010. View at Publisher · View at Google Scholar · View at Scopus
  33. J. Schug, L. B. McKenna, G. Walton et al., “Dynamic recruitment of microRNAs to their mRNA targets in the regenerating liver,” BMC Genomics, vol. 14, no. 1, article 264, 2013. View at Publisher · View at Google Scholar · View at Scopus
  34. G. B. Loeb, A. A. Khan, D. Canner et al., “Transcriptome-wide miR-155 binding map reveals widespread noncanonical microRNA targeting,” Molecular Cell, vol. 48, no. 5, pp. 760–770, 2012. View at Publisher · View at Google Scholar · View at Scopus
  35. M. Hafner, M. Landthaler, L. Burger et al., “Transcriptome-wide identification of RNA-binding protein and microRNA target sites by PAR-CLIP,” Cell, vol. 141, no. 1, pp. 129–141, 2010. View at Publisher · View at Google Scholar · View at Scopus
  36. A. Helwak, G. Kudla, T. Dudnakova, and D. Tollervey, “Mapping the human miRNA interactome by CLASH reveals frequent noncanonical binding,” Cell, vol. 153, no. 3, pp. 654–665, 2013. View at Publisher · View at Google Scholar · View at Scopus
  37. R. Tang, L. Li, D. Zhu et al., “Mouse miRNA-709 directly regulates miRNA-15a/16-1 biogenesis at the posttranscriptional level in the nucleus: evidence for a microRNA hierarchy system,” Cell Research, vol. 22, no. 3, pp. 504–515, 2012. View at Publisher · View at Google Scholar · View at Scopus
  38. S. A. Khudayberdiev, F. Zampa, M. Rajman, and G. Schratt, “A comprehensive characterization of the nuclear microRNA repertoire of post-mitotic neurons,” Frontiers in Molecular Neuroscience, vol. 6, article 43, 2013.
  39. V. Huang, J. Zheng, Z. Qi et al., “Ago1 Interacts with RNA polymerase II and binds to the promoters of actively transcribed genes in human cancer cells,” PLoS Genetics, vol. 9, no. 9, Article ID e1003821, 2013. View at Publisher · View at Google Scholar
  40. J. Liao, L. Ma, Y. Guo et al., “Deep sequencing of human nuclear and cytoplasmic small RNAS reveals an unexpectedly complex subcellular distribution of mirnas and tRNA 3′ trailers,” PLoS ONE, vol. 5, no. 5, Article ID e10563, 2010. View at Publisher · View at Google Scholar · View at Scopus
  41. M. Salmanidis, K. Pillman, G. Goodall, and C. Bracken, “Direct transcriptional regulation by nuclear microRNAs,” International Journal of Biochemistry & Cell Biology, 2014. View at Publisher · View at Google Scholar
  42. M. Guttman, I. Amit, M. Garber et al., “Chromatin signature reveals over a thousand highly conserved large non-coding RNAs in mammals,” Nature, vol. 458, no. 7235, pp. 223–227, 2009. View at Publisher · View at Google Scholar · View at Scopus
  43. G. Dieci, G. Fiorino, M. Castelnuovo, M. Teichmann, and A. Pagano, “The expanding RNA polymerase III transcriptome,” Trends in Genetics, vol. 23, no. 12, pp. 614–622, 2007. View at Publisher · View at Google Scholar · View at Scopus
  44. P. Kapranov, J. Cheng, S. Dike et al., “RNA maps reveal new RNA classes and a possible function for pervasive transcription,” Science, vol. 316, no. 5830, pp. 1484–1488, 2007. View at Publisher · View at Google Scholar · View at Scopus
  45. N. T. Ingolia, L. F. Lareau, and J. S. Weissman, “Ribosome profiling of mouse embryonic stem cells reveals the complexity and dynamics of mammalian proteomes,” Cell, vol. 147, no. 4, pp. 789–802, 2011. View at Publisher · View at Google Scholar · View at Scopus
  46. B. Bánfai, H. Jia, J. Khatun et al., “Long noncoding RNAs are rarely translated in two human cell lines,” Genome Research, vol. 22, no. 9, pp. 1646–1657, 2012. View at Publisher · View at Google Scholar · View at Scopus
  47. S. Katayama, Y. Tomaru, T. Kasukawa, et al., “Antisense transcription in the mammalian transcriptome,” Science, vol. 309, no. 5740, pp. 1564–1566, 2005. View at Publisher · View at Google Scholar
  48. M. J. G. Bussemakers, A. رan Bokhoven, G. W. Verhaegh et al., “DD3: a new prostate-specific gene, highly overexpressed in prostate cancer,” Cancer Research, vol. 59, no. 23, pp. 5975–5979, 1999. View at Scopus
  49. L. S. Marks, Y. Fradet, I. Lim Deras et al., “PCA3 molecular urine assay for prostate cancer in men undergoing repeat biopsy,” Urology, vol. 69, no. 3, pp. 532–535, 2007. View at Publisher · View at Google Scholar · View at Scopus
  50. D. Hessels and J. A. Schalken, “The use of PCA3 in the diagnosis of prostate cancer,” Nature Reviews Urology, vol. 6, no. 5, pp. 255–261, 2009. View at Publisher · View at Google Scholar · View at Scopus
  51. V. Srikantan, Z. Zou, G. Petrovics et al., “PCGEM1, a prostate-specific gene, is overexpressed in prostate cancer,” Proceedings of the National Academy of Sciences of the United States of America, vol. 97, no. 22, pp. 12216–12221, 2000. View at Publisher · View at Google Scholar · View at Scopus
  52. X. Fu, L. Ravindranath, N. Tran, G. Petrovics, and S. Srivastava, “Regulation of apoptosis by a prostate-specific and prostate cancer-associated noncoding gene, PCGEM1,” DNA and Cell Biology, vol. 25, no. 3, pp. 135–141, 2006. View at Publisher · View at Google Scholar · View at Scopus
  53. G. Petrovics, W. Zhang, M. Makarem et al., “Elevated expression of PCGEM1, a prostate-specific gene with cell growth-promoting function, is associated with high-risk prostate cancer patients,” Oncogene, vol. 23, no. 2, pp. 605–611, 2004. View at Publisher · View at Google Scholar · View at Scopus
  54. L. Yang, C. Lin, C. Jin et al., “LncRNA-dependent mechanisms of androgen-receptor-regulated gene activation programs,” Nature, vol. 500, no. 7464, pp. 598–602, 2013. View at Publisher · View at Google Scholar · View at Scopus
  55. Y. Xue, M. Wang, M. Kang et al., “Association between lncrna PCGEM1 polymorphisms and prostate cancer risk,” Prostate Cancer and Prostatic Diseases, vol. 16, no. 2, pp. 139–144, 2013. View at Publisher · View at Google Scholar · View at Scopus
  56. J. R. Prensner, M. K. Iyer, O. A. Balbin et al., “Transcriptome sequencing across a prostate cancer cohort identifies PCAT-1, an unannotated lincRNA implicated in disease progression,” Nature Biotechnology, vol. 29, no. 8, pp. 742–749, 2011. View at Publisher · View at Google Scholar · View at Scopus
  57. J. R. Prensner, W. Chen, M. K. Iyer, et al., “PCAT-1, a long noncoding RNA, regulates BRCA2 and controls homologous recombination in cancer,” Cancer Research, vol. 74, no. 6, pp. 1651–1660, 2014.
  58. S. Chung, H. Nakagawa, M. Uemura et al., “Association of a novel long non-coding RNA in 8q24 with prostate cancer susceptibility,” Cancer Science, vol. 102, no. 1, pp. 245–252, 2011. View at Publisher · View at Google Scholar · View at Scopus
  59. A. A. Al Olama, Z. Kote-Jarai, G. G. Giles et al., “Multiple loci on 8q24 associated with prostate cancer susceptibility,” Nature Genetics, vol. 41, no. 10, pp. 1058–1060, 2009. View at Publisher · View at Google Scholar · View at Scopus
  60. F. Crea, A. Watahiki, L. Quagliata et al., “Identification of a long non-coding RNA as a novel biomarker and potential therapeutic target for metastatic prostate cancer,” Oncotarget, vol. 5, no. 3, pp. 764–774, 2014.
  61. S. Ren, Z. Peng, J. Mao et al., “RNA-seq analysis of prostate cancer in the Chinese population identifies recurrent gene fusions, cancer-associated long noncoding RNAs and aberrant alternative splicings,” Cell Research, vol. 22, no. 5, pp. 806–821, 2012. View at Publisher · View at Google Scholar · View at Scopus
  62. S. Ren, Y. Liu, W. Xu et al., “Long noncoding RNA MALAT-1 is a new potential therapeutic target for castration resistant prostate cancer,” Journal of Urology, vol. 190, no. 6, pp. 2278–2287, 2013.
  63. K. Takayama, K. Horie-Inoue, S. Katayama et al., “Androgen-responsive long noncoding RNA CTBP1-AS promotes prostate cancer,” EMBO Journal, vol. 32, no. 12, pp. 1665–1680, 2013. View at Publisher · View at Google Scholar · View at Scopus
  64. Z. Cui, S. Ren, J. Lu et al., “The prostate cancer-up-regulated long noncoding RNA PlncRNA-1 modulates apoptosis and proliferation through reciprocal regulation of androgen receptor,” Urologic Oncology: Seminars and Original Investigations, vol. 31, no. 7, pp. 1117–1123, 2013. View at Publisher · View at Google Scholar · View at Scopus
  65. R. Malik, L. Patel, and J. R. Prensner, “The lncRNA PCAT29 inhibits oncogenic phenotypes in prostate cancer,” Molecular Cancer Research, vol. 12, no. 8, pp. 1081–1087, 2014. View at Publisher · View at Google Scholar
  66. J. R. Prensner, A. Sahu, M. K. Iyer et al., “The IncRNAs PCGEM1 and PRNCR1 are not implicated in castration resistant prostate cancer,” Oncotarget, vol. 5, no. 6, pp. 1434–1438, 2014.
  67. J. A. Klomp and K. A. Furge, “Genome-wide matching of genes to cellular roles using guilt-by-association models derived from single sample analysis,” BMC Research Notes, vol. 5, p. 370, 2012. View at Publisher · View at Google Scholar · View at Scopus
  68. C. Chu, K. Qu, F. Zhong, S. Artandi, and H. Chang, “Genomic maps of long noncoding RNA occupancy reveal principles of RNA-chromatin interactions,” Molecular Cell, vol. 44, no. 4, pp. 667–678, 2011. View at Publisher · View at Google Scholar · View at Scopus
  69. M. D. Simon, C. I. Wang, P. V. Kharchenko et al., “The genomic binding sites of a noncoding RNA,” Proceedings of the National Academy of Sciences of the United States of America, vol. 108, no. 51, pp. 20497–20502, 2011. View at Publisher · View at Google Scholar · View at Scopus
  70. A. M. Khalil, M. Guttman, M. Huarte et al., “Many human large intergenic noncoding RNAs associate with chromatin-modifying complexes and affect gene expression,” Proceedings of the National Academy of Sciences of the United States of America, vol. 106, no. 28, pp. 11667–11672, 2009. View at Publisher · View at Google Scholar · View at Scopus
  71. J. Zhao, T. K. Ohsumi, J. T. Kung et al., “Genome-wide identification of polycomb-associated RNAs by RIP-seq,” Molecular Cell, vol. 40, no. 6, pp. 939–953, 2010. View at Publisher · View at Google Scholar · View at Scopus
  72. K. L. Yap, S. Li, A. M. Muñoz-Cabello et al., “Molecular interplay of the noncoding RNA ANRIL and methylated histone H3 lysine 27 by polycomb CBX7 in transcriptional silencing of INK4a,” Molecular Cell, vol. 38, no. 5, pp. 662–674, 2010. View at Publisher · View at Google Scholar · View at Scopus
  73. W. Yu, D. Gius, P. Onyango et al., “Epigenetic silencing of tumour suppressor gene p15 by its antisense RNA,” Nature, vol. 451, no. 7175, pp. 202–206, 2008. View at Publisher · View at Google Scholar · View at Scopus
  74. J. R. Prensner, M. K. Iyer, A. Sahu et al., “The long noncoding RNA SChLAP1 promotes aggressive prostate cancer and antagonizes the SWI/SNF complex,” Nature Genetics, vol. 45, no. 11, pp. 1392–1398, 2013.
  75. P. Perot, V. Cheynet, M. Decaussin-Petrucci et al., “Microarray-based identification of individual HERV loci expression: application to biomarker discovery in prostate cancer,” Journal of Visualized Experiments, no. 81, Article ID e50713, 2013.
  76. J. H. Li, S. Liu, H. Zhou, L. H. Qu, and J. H. Yang, “StarBase v2.0: decoding miRNA-ceRNA, miRNA-ncRNA and protein-RNA interaction networks from large-scale CLIP-Seq data,” Nucleic Acids Research, vol. 42, no. 1, pp. D92–D97, 2014.
  77. C. Carrieri, L. Cimatti, M. Biagioli et al., “Long non-coding antisense RNA controls Uchl1 translation through an embedded SINEB2 repeat,” Nature, vol. 491, no. 7424, pp. 454–457, 2012. View at Publisher · View at Google Scholar · View at Scopus
  78. C. Gong and L. E. Maquat, “LncRNAs transactivate STAU1-mediated mRNA decay by duplexing with 3′ UTRs via Alu eleme,” Nature, vol. 470, no. 7333, pp. 284–288, 2011. View at Publisher · View at Google Scholar · View at Scopus
  79. T. B. Hansen, T. I. Jensen, B. H. Clausen et al., “Natural RNA circles function as efficient microRNA sponges,” Nature, vol. 495, no. 7441, pp. 384–388, 2013. View at Publisher · View at Google Scholar · View at Scopus
  80. S. Memczak, M. Jens, A. Elefsinioti et al., “Circular RNAs are a large class of animal RNAs with regulatory potency,” Nature, vol. 495, no. 7441, pp. 333–338, 2013. View at Publisher · View at Google Scholar · View at Scopus
  81. G. Wang, A. Lunardi, J. Zhang et al., “Zbtb7a suppresses prostate cancer through repression of a Sox9-dependent pathway for cellular senescence bypass and tumor invasion,” Nature Genetics, vol. 45, no. 7, pp. 739–746, 2013. View at Publisher · View at Google Scholar · View at Scopus
  82. E. Heitzer, P. Ulz, J. Belic et al., “Tumor-associated copy number changes in the circulation of patients with prostate cancer identified through whole-genome sequencing,” Genome Medicine, vol. 5, no. 4, article 30, 2013. View at Publisher · View at Google Scholar · View at Scopus
  83. Z. H. Chen, G. L. Zhang, H. R. Li et al., “A panel of five circulating microRNAs as potential biomarkers for prostate cancer,” Prostate, vol. 72, no. 13, pp. 1443–1452, 2012. View at Publisher · View at Google Scholar · View at Scopus
  84. F. Moltzahn, A. B. Olshen, L. Baehner et al., “Microfluidic-based multiplex qRT-PCR identifies diagnostic and prognostic microRNA signatures in the sera of prostate cancer patients,” Cancer Research, vol. 71, no. 2, pp. 550–560, 2011. View at Publisher · View at Google Scholar · View at Scopus
  85. R. Mahn, L. C. Heukamp, S. Rogenhofer, A. Von Ruecker, S. C. Müller, and J. Ellinger, “Circulating microRNAs (miRNA) in serum of patients with prostate cancer,” Urology, vol. 77, no. 5, pp. 1265.e9–1265.e16, 2011. View at Publisher · View at Google Scholar · View at Scopus
  86. R. J. Bryant, T. Pawlowski, J. W. F. Catto et al., “Changes in circulating microRNA levels associated with prostate cancer,” British Journal of Cancer, vol. 106, no. 4, pp. 768–774, 2012. View at Publisher · View at Google Scholar · View at Scopus
  87. F. Y. Agaoglu, M. Kovancilar, Y. Dizdar et al., “Investigation of miR-21, miR-141, and miR-221 in blood circulation of patients with prostate cancer,” Tumor Biology, vol. 32, no. 3, pp. 583–588, 2011. View at Publisher · View at Google Scholar · View at Scopus
  88. L. A. Selth, S. L. Townley, A. G. Bert et al., “Circulating microRNAs predict biochemical recurrence in prostate cancer patients,” British Journal of Cancer, vol. 109, no. 3, pp. 641–650, 2013. View at Publisher · View at Google Scholar · View at Scopus
  89. H.-L. Zhang, L.-F. Yang, Y. Zhu et al., “Serum miRNA-21: elevated levels in patients with metastatic hormone-refractory prostate cancer and potential predictive factor for the efficacy of docetaxel-based chemotherapy,” Prostate, vol. 71, no. 3, pp. 326–331, 2011. View at Publisher · View at Google Scholar · View at Scopus
  90. D. Olmos, D. Brewer, J. Clark et al., “Prognostic value of blood mRNA expression signatures in castration-resistant prostate cancer: a prospective, two-stage study,” The Lancet Oncology, vol. 13, no. 11, pp. 1114–1124, 2012. View at Publisher · View at Google Scholar · View at Scopus
  91. R. W. Ross, M. D. Galsky, H. I. Scher et al., “A whole-blood RNA transcript-based prognostic model in men with castration-resistant prostate cancer: a prospective study,” The Lancet Oncology, vol. 13, no. 11, pp. 1105–1113, 2012. View at Publisher · View at Google Scholar · View at Scopus
  92. A. F. Neves, J. D. D. Dias-Oliveira, T. G. Araújo, K. Marangoni, and L. R. Goulart, “Prostate cancer antigen 3 (PCA3) RNA detection in blood and tissue samples for prostate cancer diagnosis,” Clinical Chemistry and Laboratory Medicine, vol. 51, no. 4, pp. 881–887, 2013. View at Publisher · View at Google Scholar · View at Scopus
  93. S. A. Tomlins, S. M. J. Aubin, J. Siddiqui et al., “Urine TMPRSS2:ERG fusion transcript stratifies prostate cancer risk in men with elevated serum PSA,” Science Translational Medicine, vol. 3, no. 94, Article ID 94ra72, 2011. View at Publisher · View at Google Scholar · View at Scopus
  94. D. Cao, D. Ye, H. Zhang, Y. Zhu, Y. Wang, and X. Yao, “A multiplex model of combining gene-based, protein-based, and metabolite-based with positive and negative markers in urine for the early diagnosis of prostate cancer,” Prostate, vol. 71, no. 7, pp. 700–710, 2011. View at Publisher · View at Google Scholar · View at Scopus
  95. M. Mittelbrunn, C. Gutiérrez-Vázquez, C. Villarroya-Beltri et al., “Unidirectional transfer of microRNA-loaded exosomes from T cells to antigen-presenting cells,” Nature Communications, vol. 2, no. 1, article 282, 2011. View at Publisher · View at Google Scholar · View at Scopus
  96. N. P. Hessvik, S. Phuyal, A. Brech, K. Sandvig, and A. Llorente, “Profiling of microRNAs in exosomes released from PC-3 prostate cancer cells,” Biochimica et Biophysica Acta, vol. 1819, no. 11-12, pp. 1154–1163, 2012. View at Publisher · View at Google Scholar · View at Scopus
  97. M. Morello, V. R. Minciacchi, P. de Candia et al., “Large oncosomes mediate intercellular transfer of functional microRNA,” Cell Cycle, vol. 12, no. 22, pp. 3526–3536, 2013.
  98. J. Nilsson, J. Skog, A. Nordstrand et al., “Prostate cancer-derived urine exosomes: a novel approach to biomarkers for prostate cancer,” British Journal of Cancer, vol. 100, no. 10, pp. 1603–1607, 2009. View at Publisher · View at Google Scholar · View at Scopus
  99. K. Gabriel, A. Ingram, R. Austin et al., “Regulation of the tumor suppressor PTEN through exosomes: a diagnostic potential for prostate cancer,” PLoS ONE, vol. 8, no. 7, Article ID e70047, 2013. View at Publisher · View at Google Scholar · View at Scopus
  100. J. C. Gross, V. Chaudhary, K. Bartscherer, and M. Boutros, “Active Wnt proteins are secreted on exosomes,” Nature Cell Biology, vol. 14, no. 10, pp. 1036–1045, 2012. View at Publisher · View at Google Scholar · View at Scopus
  101. C. Liu, K. Kelnar, A. V. Vlassov, D. Brown, J. Wang, and D. G. Tang, “Distinct microRNA expression profiles in prostate cancer stem/progenitor cells and tumor-suppressive functions of let-7,” Cancer Research, vol. 72, no. 13, pp. 3393–3405, 2012. View at Publisher · View at Google Scholar · View at Scopus
  102. N. Nadiminty, R. Tummala, W. Lou et al., “MicroRNA let-7c is downregulated in prostate cancer and suppresses prostate cancer growth,” PLoS ONE, vol. 7, no. 3, Article ID e32832, 2012. View at Publisher · View at Google Scholar · View at Scopus
  103. M. Jin, T. Zhang, and C. Liu, “miRNA-128 suppresses prostate cancer by inhibiting BMI-1 to inhibit tumor-initiating cells,” Cancer Research, vol. 74, no. 15, pp. 4183–4195, 2014. View at Publisher · View at Google Scholar
  104. Y. Qu, X. Huang, Z. Li et al., “miR-199a-3p inhibits aurora kinase A and attenuates prostate cancer growth: new avenue for prostate cancer treatment,” The American Journal of Pathology, vol. 184, no. 5, pp. 1541–1549, 2014.
  105. F. Takeshita, L. Patrawala, M. Osaki et al., “Systemic delivery of synthetic microRNA-16 inhibits the growth of metastatic prostate tumors via downregulation of multiple cell-cycle genes,” Molecular Therapy, vol. 18, no. 1, pp. 181–187, 2010. View at Publisher · View at Google Scholar · View at Scopus
  106. X. Fu, Z. Meng, W. Liang et al., “miR-26a enhances miRNA biogenesis by targeting Lin28B and Zcchc11 to suppress tumor growth and metastasis,” Oncogene, 2013. View at Publisher · View at Google Scholar
  107. C. Liu, K. Kelnar, B. Liu et al., “The microRNA miR-34a inhibits prostate cancer stem cells and metastasis by directly repressing CD44,” Nature Medicine, vol. 17, no. 2, pp. 211–216, 2011. View at Publisher · View at Google Scholar · View at Scopus
  108. K. Kojima, Y. Fujita, Y. Nozawa, T. Deguchi, and M. Ito, “MiR-34a attenuates paclitaxel-resistance of hormone-refractory prostate cancer PC3 cells through direct and indirect mechanisms,” Prostate, vol. 70, no. 14, pp. 1501–1512, 2010. View at Publisher · View at Google Scholar · View at Scopus
  109. C.-J. Kao, A. Martiniez, X.-B. Shi et al., “miR-30 as a tumor suppressor connects EGF/Src signal to ERG and EMT,” Oncogene, vol. 33, no. 19, pp. 2495–2503, 2014. View at Publisher · View at Google Scholar · View at Scopus
  110. N. Mercatelli, V. Coppola, D. Bonci et al., “The inhibition of the highly expressed mir-221 and mir-222 impairs the growth of prostate carcinoma xenografts in mice,” PLoS ONE, vol. 3, no. 12, Article ID e4029, 2008. View at Publisher · View at Google Scholar · View at Scopus