The molecular mechanisms involved in epithelial ovarian cancer initiation and progression are just beginning to be elucidated. In particular, it has become evident that microRNAs (miRNAs or miRs), a class of molecules that post-transcriptionally regulate gene expression, play a major role in ovarian tumorigenesis. Several microRNA profiling studies have identified changes in microRNA patterns that take place during ovarian cancer development. While most deregulated microRNAs are down-regulated in cancer, and may therefore act as tumor suppressors, others are elevated and may represent novel oncogenes in this disease. A number of microRNAs identified as aberrantly expressed in ovarian carcinoma have been shown to have important functional roles in cancer development and may therefore represent targets for therapy. In addition, some of the microRNA patterns may have prognostic significance. The identification of functional targets represents a major hurdle in our understanding of microRNA function in ovarian carcinoma, but significant progress is being made. It is hoped that a better understanding of the microRNA expression and roles in ovarian cancer may provide new avenues for the detection, diagnosis, and therapy of this deadly disease.
Ovarian cancer is the sixth most common gynecologic malignancy in women worldwide (over 230 000 new cases yearly) with a highly aggressive natural history and causing over 140 000 deaths every year ( Garcia et al. 2007). While the survival rates of women with early stage ovarian cancer are high, most cases are diagnosed late, when the likelihood of successful therapy is low ( Piver et al. 1992, Ahmed et al. 1996, Wright et al. 2009). Indeed, cytotoxic chemotherapy for ovarian carcinoma is often unsuccessful due to common resistance to the current chemotherapeutic regimens ( Fung-Kee-Fung et al. 2007). MicroRNAs (miRNAs or miRs), a recently discovered class of regulatory RNAs, are frequently deregulated in cancer and have been suggested to have important roles in cancer initiation and development. In ovarian carcinoma, various miRs have been found altered and some of these genes may represent ideal targets for detection, diagnosis, and/or therapy ( Bartels & Tsongalis 2009). In addition, several research groups have observed altered expression of miRs in ovarian cancer and studied their roles in ovarian tumorigenesis. This review will focus on the recent advances in this exciting field.
miRs are small non-coding RNAs of 20–22 nucleotides, which were first discovered in Caenorhabditis elegans ( Lee et al. 1993) but have now been found to be present and highly conserved among a wide range of species ( Wheeler et al. 2009). Similar to other small regulatory RNAs, miRs are generally involved in post-transcriptional gene regulation. miR genes are synthesized in the nucleus by DNA polymerase II as a long double-stranded precursor called primary (pri)-miR that is processed by two enzymes, Drosha and Pasha, into a precursor (pre)-miR that is exported to the cytoplasm by exportin 5 ( Bohnsack et al. 2004, Cullen 2004, Zeng & Cullen 2004). Once the pre-miR reaches the cytoplasm, it is cleaved by Dicer into a ∼22 nt long functional mature miR. The mature miR can then assemble into a ribonucleoprotein complex known as the RNA-induced silencing complex (RISC) to participate in RNA interference ( Pratt & MacRae 2009). While the exact composition of the RISC is not fully known and may be somewhat variable, the main components are: 1) members of the Argonaute family of proteins, which bind directly to the small regulatory RNA, and 2) a small regulatory RNA (such as miR or siRNA) that directs the complex to its mRNA targets through direct base-pairing. Through the RISC, miRs can down-regulate their targets by inhibiting mRNA translation and/or promoting mRNA degradation. The mode of repression may depend, in part, on the level of complementarity of the miRs (with perfect or near-perfect complementarity favoring mRNA degradation). The mechanism of target regulation is complex, but recent work suggests a two-step process by which translation inhibition occurs first and is then followed by mRNA decay due to deadenylation of the mRNA ( Fabian et al. 2009). The extent of each of these processes may be variable, and this may account for the observation that target mRNAs are sometimes found to be inhibited exclusively at the mRNA stability level, exclusively at the translational level, or through a combination of both mechanisms.
The 5′ region of a miR, called the ‘seed region’ (nucleotides 2–8 of the miR), is crucial for miR targeting and function, although other factors are also important ( Bartel 2004, Grimson et al. 2007). In mammals, miR target sites are often imperfect and located in the 3′ UTR of the target genes ( Gu et al. 2009), although they can also be found in the 5′ UTR or even in the coding region. Because miRs do not require perfect complementarity for functional interactions with mRNA targets, a single miR can regulate multiple targets and conversely, multiple miRs are known to regulate individual mRNAs ( Lewis et al. 2003). In addition to down-regulating their target genes, miRs have also been reported to activate some targets ( Vasudevan et al. 2007).
While miR genes are typically expressed from their own promoters in intergenic regions, a significant portion of miR genes are located within other transcriptional units ( Baskerville & Bartel 2005), usually in intronic regions, but sometimes in exonic regions as well. The exact mechanisms by which these intragenic miRs are processed still remain to be elucidated but appear to be Drosha-independent. The expression of these miRs is coupled with their host genes and subjected to the same regulatory controls ( Baskerville & Bartel 2005). Intronic miRs can regulate genes involved in pathways of the host genes, adding to the complexity of these regulatory loops ( Barik 2008).
miRs exert their functions through the regulation of specific sets of target mRNAs. Because of imperfect complementarity requirements and other factors that affect site accessibility, target prediction has been a difficult task particularly ( John et al. 2006). Several sequence-matching algorithms, such as TargetScan ( Lewis et al. 2003), miRanda ( John et al. 2004), RNAhybrid ( Rehmsmeier et al. 2004), PicTar ( Krek et al. 2005), and DIANA-micro T ( Maragkakis et al. 2009) have been developed and are an excellent starting point for identifying putative miR targets. The next generation target prediction and miR databases use combinations of the programs above, as well as additional features such as sequence conservation and gene ontology ( Nam et al. 2008b, Roubelakis et al. 2009). It is clear that experimental approaches are necessary in order to identify an accurate full complement of miR targets ( John et al. 2006, Creighton et al. 2008), and databases that include lists of experimentally verified miR targets are being constructed ( Sethupathy et al. 2006). Similarly, a database that lists miRs that have been implicated in human disease is also available ( Jiang et al. 2009).
As indicated above, in addition to computational methods, several functional approaches are being used to identify actual targets of miRs. A straightforward approach consists of over-expressing or down-regulating specific miRs in cultured cells and examining the effects on mRNA and/or protein levels using gene expression profiling or proteomics approaches. This approach was used, for example, to identify mRNAs regulated by miR-1 and miR-124 ( Lim et al. 2005), and this was done by over-expressing those miRs and observing the resulting changes in gene expression using microarrays. While this type of experiments identifies regulation at the mRNA stability levels, translational regulation can be addressed by performing proteomics analyses (Grosshans & Filipowicz 2008). Stable isotope labeling by amino acids in cell culture (SILAC) followed by mass spectroscopy has been a particularly useful approach in the investigation of the translational effects of miRs. SILAC has been used to identify miR-1 targets in HeLa cells ( Vinther et al. 2006), and these targets exhibited a significant overlap with targets identified using microarrays. Similarly, other studies confirmed that the levels of hundreds of proteins were affected following changes in the expression of specific miRs ( Baek et al. 2008, Selbach et al. 2008). As a whole, these studies showed that miR expression often led to simultaneous mRNA degradation and protein translation inhibition of the targets, and that these effects were dependent on the presence of seed sequences in the 3′ UTR of the target mRNAs.
Finally, a number of biochemical methods have been designed to directly identify the interactions between the miRs and their corresponding targets. For example, labeled/tagged miRs have been used in pull-down experiments to identify mRNAs that these miRs can bind to Orom & Lund (2007) and Hsu et al. (2009). In addition, it is well known that miRs are part of the RISC complex along with different members of the Argonaute (Ago) family, and this property has been used to enrich for targets of specific miRs. For example, following forced expression of miR-124a, immunoprecipitation of Ago2 led to the enrichment of known miR-124a targets ( Karginov et al. 2007). Interestingly, the mRNAs that were significantly enriched by immunoprecipitation included targets that were also down-regulated in total mRNA, and these targets were very likely to contain the seed site. Another approach consists of synthesizing cDNA clones from known mRNA templates using endogenous miRs as primers ( Vatolin et al. 2006). Sequencing of the synthesized cDNAs then allows the identification of the miRs as well as the binding sites on the mRNA.
miRs and cancer
miRs are conserved in distantly related organisms ( Wheeler et al. 2009) suggesting important roles in vital cellular processes such as development, differentiation, cell cycle, apoptosis, metabolism, and proliferation ( Flynt & Lai 2008). A possible link between miRs and cancer was first reported in chronic lymphocytic leukemia, where miR-15 and miR-16 were found to be deleted or down-regulated in the vast majority of tumors ( Calin et al. 2002). Since then, a large number of studies have found various miRs abnormally expressed in several human malignancies ( Zhang et al. 2007). Similar to their protein-coding counterparts, miRs involved in tumorigenesis can be classified as oncogenes or tumor suppressors, depending on their expression pattern and their function ( Calin & Croce 2006a). Several mechanisms leading to abnormal expression of miRs in cancer have been reported, including chromosomal rearrangements ( Calin et al. 2005, Tagawa & Seto 2005, Calin & Croce 2007), genomic copy number change ( Calin et al. 2004, Zhang et al. 2006, Giannakakis et al. 2008), epigenetic modifications ( Saito et al. 2006, Iorio et al. 2007), defects in miR biogenesis pathway ( Kumar et al. 2007), and regulation by transcriptional factors ( He et al. 2007).
Important insights into the mechanisms of miR function in cancer have been provided through the demonstration that miRs are involved in known oncogenic pathways. For example, the three human RAS oncogenes (H-, K-, and N-RAS) all contain let-7 sites in their 3′ UTR ( Johnson et al. 2005). Interestingly, the let-7 family of miRs, which is typically down-regulated in various tumors, has been shown to negatively regulate the RAS oncogenes in lung tumors, therefore acting as tumor suppressor genes ( Johnson et al. 2005, Kumar et al. 2008). Similarly, miR-15 and miR-16 have been shown to target the BCL2 oncogene, leading to its down-regulation and apoptosis in leukemic cells ( Cimmino et al. 2005). As an example of miRs acting as oncogenes, miR-221 and miR-222 can target and inhibit the expression of the p27Kip tumor suppressor ( le Sage et al. 2007). Indeed, high levels of these miRs were shown to maintain low p27 protein and elevated proliferation. Another oncogenic pathway, the p53 pathway, also includes miR components. In fact, the p53 tumor suppressor has been shown to transcriptionally induce miR-34 following genotoxic stress and this induction is important in mediating p53 function ( Chang et al. 2007, He et al. 2007, Raver-Shapira et al. 2007, Tarasov et al. 2007).
There is evidence that miR expression patterns may be useful in cancer diagnosis and outcome prediction. Indeed, miR profiling of normal versus tumor tissues using various techniques has consistently shown a large number of deregulated miR genes, most of which are typically down-regulated ( Calin & Croce 2006b). Interestingly, in a pioneering study that included 334 cancer samples from multiple cancers, the global expression patterns of miRs were found to be extremely accurate in distinguishing lineage and differentiation state ( Lu et al. 2005). Most of the changes were again found to be down-regulation of the miRs and a subsequent study showed that a general down-regulation of miRs in cells (achieved through a knockdown of miR processing enzymes) led to enhanced cellular transformation and tumorigenesis, suggesting a crucial role for these genes in the process of transformation ( Kumar et al. 2007).
miR expression in ovarian carcinoma
A number of studies have used various gene expression profiling approaches to study miR expression in ovarian carcinoma. In order to clearly present these important data, we will describe each study individually. The summary of the differentially expressed miRs for each study is included in Table 1.
MicroRNAs (miRs) with altered expression in ovarian carcinoma
|miR-221, miR-146b, miR-508||let-7f, miR-106b, miR-134, miR-155, miR-21, miR-346, miR-422a, miR-424, miR-519a, miR-648, miR-662||Ovarian carcinoma cell lines and tissues versus normal||Dahiya et al. (2008)|
|miR-26b, miR-182, miR-103, miR-26a||miR-127, miR-134, miR-154*, miR-410, miR-377, miR-100, miR-432, miR-368, miR-154, miR-495, miR-376a, miR-323, miR-376b, miR-370, miR-299, let7d, miR-155, miR-140, miR-222, miR-337, miR-124a, miR-99a, miR-331, miR-104, miR-150, miR-184, miR-152, miR-145, miR-424, miR-224, miR-302c||EOC cell lines versus normal||Zhang et al. (2008)|
|None||miR-509, miR-514, miR-513, miR-196, miR-376a, miR-184, miR-519d, miR-495, miR-424, miR-1, miR-368miR-362 miR-22, miR-376b, miR-337, miR-133a, miR-508, miR-492, miR-137, miR-95, miR-448, miR-518, miR-491, miR-455, miR-365, miR-147, miR-488, miR-34a, miR–372, miR-202, miR-503, miR-520e, miR-410, miR-519e, miR-375, miR-346, miR-15a, miR-507, miR-450, miR-377, miR-34b, miR-518a, miR-432, miR-516||Early-stage cancer versus late-stage cancer||Zhang et al. (2008)|
|None||miR-514, miR-509, miR-508, miR-34c, miR-513, miR-368, miR-379, miR-154, miR-337, miR-507, miR-503, miR-376||Low-grade cancer versus high-grade cancer||Zhang et al. (2008)|
|miR-200b, miR-21, miR-200c, miR-141, miR-20a, miR-27a, miR-16, miR-93||miR-145, miR-125b, miR-100, miR-99a, miR-26a, miR-10b, miR-143, miR-214, let-7b, miR-29a, miR-125a||Serous ovarian carcinoma versus normal ovarian tissues||Nam et al. (2008a)|
|miR-182, miR-200c, miR-142-3p, miR-200b, miR-135b, miR-200a, miR-195, miR-126*, miR-26b, miR-10b, miR-126, miR-199b-5p, miR-107, miR-30b, miR-192, miR-335, miR-32, miR-20a, miR-30c, miR-143, miR-92a, miR-199b-3p, miR-99a, miR-26a, miR-18a, miR-16, miR-15a, miR-30e, miR-194, miR-29c, miR-30d, miR-106b||miR-127-3p, miR-377*, miR-382, miR-493, miR-409-3p, miR-193a-5p, miR-210, miR-935, miR-100, miR-31, miR-22, miR-152, miR-379, miR-185, miR-221, miR-744, miR-21*, let-7a*, miR-574-5p, miR-31*, miR-130b, miR-149, miR-423-5p, miR-1308, miR-629, miR-320a||Stage III/IV epithelial ovarian carcinoma versus normal (only miRs differentially expressed between all OC subtypes versus normal are included in this table)||Wyman et al. (2009)|
|miR-223, miR-206, let-7i, miR-30a3p, miR-368, miR-10b, miR-338, miR-195, miR-93, miR-23a, miR-185, miR-22, miR-339, miR-321, miR-29b, miR-186, miR-128a, miR-374, miR-193, miR-106b, miR-194, miR-370, miR-128b, miR-198, miR-224, miR-222, miR-29c, miR-21, miR-34c, miR-139, miR-197, miR-15a, miR-218, miR-106a, miR-340, miR-219, miR-155, miR-92, let-7g, miR-328, miR-149, miR-23b, miR-221, miR-150, miR-190, miR-107, miR-331, miR-181c, miR-133b||miR-326, miR-30d, miR-125b, miR-31, miR-99a, miR-100, miR-137, miR-9||Primary versus recurrent serous papillary ovarian carcinomas||Laios et al. (2008)|
|miR-200a, miR-200b, miR-200c, miR-141||miR-140, miR-199a, miR-199b, miR-145, miR-143, miR-125a, miR-125b, miR-101, miR-212, miR-222||Normal versus cancer||Iorio et al. (2007)|
|miR-199a, miR-424, miR-302d, miR-320, miR-214, miR-200a, miR-29a||miR-493, miR-494, miR-125b, miR-100, let-7a, let-7b, let-7c||Normal versus primary tumors||Yang et al. (2008a)|
Integrative analysis of miR changes in ovarian carcinoma
An integrative genomic approach that included miR microarray, array-based comparative genomic hybridization, cDNA microarray, and tissue array was used to evaluate miR changes in epithelial ovarian cancer ( Zhang et al. 2008). The authors found that both genomic losses and epigenetic alterations may be responsible for miR down-regulation. Out of 35 miRs deregulated between ovarian carcinoma and the normal controls (immortalized ovarian surface epithelial cells), 31 (88.6%) were down-regulated in cancer tissues compared with non-cancer tissues. The down-regulated genes included miRs let-7d and miR-127, which had been previously implicated in cancer. Thirteen miRs were down-regulated in high-grade tumors compared with low-grade tumors. Furthermore, down-regulation was higher in late-stage cancers as compared with early-stage cancers, suggesting a tumor suppressor function for the down-regulated miRs. Among 44 miRs down-regulated in late-stage tumors, three miRs, miR-15a, miR-34a, and miR-34b are believed to be tumor suppressors.
The region containing miR-182 was amplified in 28.9% of EOC, implying an oncogene-type function for this miR, whereas, miR-15a was deleted in 23.9% of EOC suggesting a tumor suppressive role. DNA copy number amplification and deletion were correlated with miR-182 and miR-15a expressions respectively, in both primary tumors and cell lines. However, DNA copy number changes could explain the expression of only 6 of the 33 abnormally expressed miRs. EOC cell lines that were treated with DNA demethylating and histone deacetylase (HDAC) inhibitors exhibited up-regulation of 16 miRs, which suggests epigenetic modification as another crucial factor determining the expression of miRs in EOC. In the tumors, loss of miR-377, miR-368, and miR-495 cluster, which is localized at Dlk1–Gtl2 domain, results in higher proliferation and in shorter survival of the patients ( Zhang et al. 2008).
Genome-wide analysis of miR copy number abnormalities in ovarian carcinoma
Using array-based comparative genomic hybridization, these authors found that genomic regions containing miR genes frequently exhibited copy number abnormalities ( Zhang et al. 2006). In particular, copy number losses of the region containing miR-218-1 and SLIT2 were observed in 15.5% of ovarian carcinomas. There was a positive correlation between miR copy number changes and the miR expression levels of 73.1% of the miR genes. In addition, experiments with demethylating agents suggested that up to 33% of miRs may be regulated by epigenetic mechanisms.
Hypoxia-responsive miRs in ovarian carcinoma
The screening of a panel of 157 miRs allowed the identification of miR-210 as the most highly and consistently up-regulated miR, following hypoxia induction ( Giannakakis et al. 2008). Interestingly, miR-210 is located at chromosome 11p15.5 within a frequent region of loss of heterozygosity in ovarian carcinoma. The gene copy number of miR-210 was reduced in 64% of ovarian carcinomas, and these alterations were associated with decreased levels of miR-210, suggesting a tumor suppressive function for this gene.
miR expression signature in ovarian carcinoma
In another study, 15 normal ovarian samples, 69 ovarian malignant tumors, and five ovarian carcinoma cell lines were studied by miR microarray analysis ( Iorio et al. 2007). The unsupervised hierarchical clustering classified the samples into two distinct categories representing ‘normal’ and ‘cancer samples/cell lines’. A total of 29 and 39 miRs were found to be aberrantly expressed by significance analysis of microarrays (SAM) and prediction analysis of microarrays (PAM) analysis respectively. MiR-200a and miR-141 were highly up-regulated, whereas miR-199a, miR-140, miR-145, and miR-125b1 were most significantly down-regulated. Although some of the miRs were deregulated in all the subtypes, certain miRs could differentiate different subtypes (serous, endometrioid, and clear cell) of ovarian carcinomas. For example, miR-200a and miR-200c were up-regulated in all the three subtypes, miR-200b and miR-141 were up-regulated in serous as well as endometrioid, and miR-21, miR-203, and miR-205 were up-regulated only in endometrioid. Among the down-regulated miRs, miR-145 was down-regulated in serous and clear cell carcinomas, while miR-222 was down-regulated in both endometrioid and clear cell carcinomas. miR expression profiles were not dependent on the grade or stage of the disease. The treatment of ovarian carcinoma cell lines with the demethylating agent 5-aza-2′-deoxycytidine resulted in induction of miR-21, miR-203, miR-146b, miR-205, miR-30-5p, and miR-30c. Since miR-21, miR-203, and miR-205 were observed over-expressed in ovarian carcinoma, these experiments suggest that hypomethylation could be responsible for the observed expression patterns of these miRs in cancer. However, it was also interesting to observe that the most significantly up-regulated miRs belong to the same family and were localized in pairs: miR-200a and miR-200b at chromosome 1p36.33, and miR-200c and miR-141 at chromosome 12p13.31. This study is consistent with others showing that mechanisms of miR deregulation in ovarian carcinoma include copy number changes as well as epigenetic mechanisms ( Zhang et al. 2006, 2008).
Identification of differentially expressed miRs in ovarian carcinoma and identification of PTEN as a target of miR-214
Using miR microarrays, 36 miRs were found deregulated between normal ovarian cells and epithelial ovarian tumors, with miR-199a*, miR-214, miR-200a, and miR-100 being the most highly differentially expressed candidates ( Yang et al. 2008a). miR-199a*, miR-214, and miR-200a were up-regulated in 53, 56, and 43% tumor tissues respectively, and their expression was associated with high-grade and late-stage tumors. miR-100 was down-regulated in 76% of tumors. The authors selected miR-214 for further study and found PTEN as one of its potential targets, implicating this miR in the regulation of the AKT survival pathway.
miR expression profiles in serous ovarian carcinoma
In this study, 23 miRs were found aberrantly expressed in at least 60% of ovarian cancer samples ( Nam et al. 2008a). Among 11 up-regulated miRs, miR-21 topped the list showing its expression in 85% samples; whereas among 12 down-regulated, miR-125b was the most significant and exhibited down-regulation in 95% tumor samples. Fifty percent of miRs reported in this study were also found in the Iorio study ( Iorio et al. 2007). The most significantly altered miRs in both studies were: miR-200a/b/c, miR-141, miR-21, miR-145, miR-99a, let-7, and miR-125b.
Identification of miRs that are differentially expressed in ovarian carcinoma: importance of the let-7 family
Our laboratory investigated miR expression profiles in 34 ovarian carcinoma tissues as well as ten ovarian carcinoma cell lines ( Dahiya et al. 2008). A total of 25 up-regulated and 31 down-regulated miRs were identified. We also found five up-regulated and 23 down-regulated miRs in ovarian carcinoma cell lines compared with non-neoplastic cells. Fourteen miRs were deregulated in both tissues and cell lines ( Table 1). MiR-221 was the most highly elevated miR in both tissues and cell lines (ninefold and sevenfold respectively), while miR-21 was significantly decreased in both sample types (threefold and ninefold respectively). Among the different let-7 family members, let-7e and let-7f showed more than twofold deregulation in at least 60% of the tumor samples. The other let-7 family members (let-7g, let-7d, let-7c, let-7a-e, let-7i, let-7a, and let-7b) were not down-regulated as consistently, but each one of them was found decreased twofold or more in at least 20% of the tumors. Overall, 94% of the tumors had at least one let-7 family member down-regulated at least twofold. Cell lines exhibited down-regulation of the let-7 family members as well. This study suggested an important role for let-7 family members in ovarian carcinoma.
Comprehensive analysis of miR repertoire in ovarian carcinoma using massively parallel sequencing technologies
Using novel massively parallel sequencing technology (454 sequencing) to sequence small RNA cDNA libraries derived from epithelial ovarian cancers and normal samples, this group was able to generate comprehensive miR digital profiles for these tissues ( Wyman et al. 2009). In their data, the investigators identified 498 previously annotated miRs, six novel and 39 candidate miRs. They found 124 miRs that were differentially expressed in cancers of various subtypes compared with the normal ovarian cells. A subset of 37 miRs were over-expressed in all epithelial ovarian cancer subtypes and 21 were under-expressed ( Table 1). Among those, several were validated by RT-PCR. The validated over-expressed miRs included several members of the miR-200 family, while the down-regulated genes included miR-100, miR-210, miR-22, and miR-222.
Roles of miRs in ovarian carcinoma chemotherapy
Cisplatin is the most efficacious chemotherapeutic agent against ovarian carcinoma with initial response rates varying between 40 and 80% ( Ozols & Young 1984). Platinum-based combination therapy, especially carboplatin/paclitaxel, offers a modest but significant improvement over cisplatin alone, and this regimen is now standard for women with advanced epithelial ovarian cancer ( McGuire et al. 1996). Unfortunately, many women with tumors that initially respond to chemotherapy eventually relapse with drug-resistant disease ( Ozols & Young 1984). Overall, fewer than 25% of the women diagnosed with advanced ovarian carcinoma will show progression-free survival after 4 years, in spite of treatment ( McGuire et al. 1996). In this context, a better understanding of drug resistance may lead to the development of novel approaches for the treatment of ovarian and other cancers. A number of investigators have now reported possible roles for miR in the establishment of drug resistance in ovarian cancer.
In a recent report where primary and recurrent cases of ovarian cancers were compared, 60 miRs were found deregulated more than twofold between primary and recurrent disease ( Laios et al. 2008). In contrast to several studies reporting a majority of miRs to be down-regulated in cancer tissues, a marked up-regulation of miRs in recurrent compared with primary tumors was observed (52 miRs showed over-expression and 8 showed under-expression of >twofold in recurrent versus primary tumors). miR-223 (up) and miR-9 (down) were the most highly deregulated genes in the recurrent versus primary samples ( Laios et al. 2008).
When cisplatin resistance was specifically examined for miR expression, and tumors from responders were compared with those of non-responders, 34 statistically significant changes were found (24 miRs were higher in the non-response group and 10 were higher in the complete response group; Yang et al. 2008b). Let-7i was the most down-regulated miR in the chemotherapy resistant patients. In addition, functional analyses confirmed that reduced let-7i expression increased the resistance of ovarian and breast cancer cells to cisplatin. In another study, elevation of miR-214 was found to be responsible for development of resistance against cisplatin ( Yang et al. 2008a). miR-214 also has anti-apoptotic functions, as blocking miR-214 expression made A2780 cells more sensitive to cisplatin-induced apoptosis ( Yang et al. 2008a). Another expression profiling study in a panel of cisplatin-, paclitaxel-, and cyclosporin A-resistant ovarian carcinoma cells revealed the expressions of let-7e, miR-30c, miR-125b, miR-130a, and miR-335 in all the resistant cell lines ( Sorrentino et al. 2008). While analyzing their downstream targets, the investigators found a direct relationship between down-regulation of miR-130a with up-regulation of M-CSF, a gene already known to be up-regulated in ovarian carcinoma.
miR targets and pathways in ovarian carcinoma
There have been relatively few miR targets that have been specifically shown to be relevant to ovarian tumorigenesis, but work in other systems allows us to make educated guesses concerning the pathways and targets of some of the miRs found aberrantly expressed in ovarian carcinoma ( Fig. 1). For example, the RAS oncogenes are well-known targets of the let-7 cluster ( Johnson et al. 2005), which have been reported to be down-regulated in ovarian carcinoma by several groups ( Table 1). Other let-7 targets, such as HMGA2, CDK6, and cMYC, are likely relevant to tumorigenesis ( Peter 2009). Similarly, the tumor suppressor gene WT1, which encodes a transcription factor, is a putative target of miR-212.
Unlike the previous examples, which were elucidated in other systems, miR-214 was shown to target PTEN in ovarian carcinoma, explaining its ability to regulate survival and drug resistance ( Yang et al. 2008a). The p53 pathway is another pathway with important miR components that were studied in ovarian carcinoma. miR-34b and miR-34c, two known transcriptional targets of p53, have been shown to be down-regulated in ovarian carcinoma ( Zhang et al. 2008). Interestingly, their over-expression can suppress proliferation and colony formation in soft agar in neoplastic epithelial ovarian cells, providing functional relevance of this pathway in ovarian tumorigenesis ( Corney et al. 2007). miR-146 was found elevated in epithelial ovarian cancer ( Volinia et al. 2006) and may target BRCA1 and BRCA2 ( Shen et al. 2008), two well-documented tumor suppressors in breast and ovarian cancers ( Fig. 2).
In a recent study, putative targets for a number of miR genes were identified using a microarray approach in ovarian carcinoma cells ( Dahiya et al. 2008). Intriguingly, the experimental targets varied depending on the cell line used for the experiment, suggesting a significant influence of the molecular background on miR target selection. It will therefore be important to methodically study each miRs in several ovarian models in order to fully understand their roles in ovarian carcinoma. These findings also imply that targets identified in other cell models may not necessarily be relevant to ovarian cancer.
miRs in detection and diagnosis of ovarian carcinoma
A number of studies have shown that miRs may be useful in predicting ovarian carcinoma outcome. For example, it was shown that patients with low let-7a-3 methylation had worse overall survival than those with high methylation ( Lu et al. 2007). In another study, the miR-200b-429 cluster, which harbors miR-200a, miR-200b, and miR-429, could predict poor survival when the miR-200 genes were expressed at low levels ( Hu et al. 2009). The targets of miR-200 miRs have known roles in cancer development. A promising study reported that the HMGA2/let-7 ratio was able to categorize ovarian carcinoma patients into two groups with significantly different prognosis ( Shell et al. 2007). The group with lower HMGA2/let-7 ratio exhibited increased 5-year progression-free survival (∼40%) compared with the group with a higher HMGA2/let-7 ratio (<10%). Another study showed that miR-214, miR-199*, and miR-200a were associated with high-grade and late-stage tumors ( Yang et al. 2008a). Tumors with higher expression of miR-200a had a median overall survival of 27.5 months compared with 61 months for those with no significant expression ( Nam et al. 2008a). Interestingly, polymorphisms in miRs may affect their function and be of prognostic value. For example, the precursor miR-146a, which targets BRCA1 and BRCA2, exhibits a G to C polymorphism in ovarian and breast cancers ( Shen et al. 2008). This polymorphism results in a change from G:U pair to a C:U mismatch in the miR stem region. Ovarian cancer patients showing G to C polymorphism were typically diagnosed younger than the patients having common mir-146a allele ( Shen et al. 2008). Additionally, with the presence of the variant allele, there was increased production of mature mir-146a that may be responsible for early onset of the disease.
Interestingly, miRs can also be detected in serum samples ( Feng et al. 2008, Lawrie et al. 2008, Lodes et al. 2009), suggesting that they may represent useful detection biomarkers. By RT-PCR analysis, miR-21, miR-92, miR-93, miR-126, and miR-29a were found up-regulated, while miR-155, miR-127, and miR-99b were found down-regulated in serum collected from ovarian carcinoma patients ( Resnick et al. 2009). Up-regulation of miR-21, miR-92, and miR-93 in the serum of three cancer patients with normal CA-125 level suggests that miRs may be complementary to current detection approaches. Interestingly, circulating tumor-derived exosomes (small lipid vesicles) have been found to contain miRs that could potentially be used as detection and/or diagnostic markers ( Taylor & Gercel-Taylor 2008). The use of exosomes-derived miRs in diagnosis may circumvent the need for biopsy material.
Therapeutic potential of miRs
Because of their properties, miRs have been suggested as possible therapeutic tools. The approaches suggested include manipulating the expression of tumor suppressor or oncogenic miRs ( Mishra & Merlino 2009) using specific miR to down-regulate oncogenic genes ( Cimmino et al. 2005) and using miR to confer tissue specificity to transgene expression in gene therapy ( Brown & Naldini 2009). When considering altering miR expression for therapeutic purposes, the regulation of multiple genes by a single miR suggests the possible targeting of pathways involved in the development or progression of the disease. Normal levels of tumor suppressor miRs that are down-regulated in cancer could potentially be restored by over-expression ( Mishra & Merlino 2009). miRs can be introduced into cells by infecting cells with retrovirus or lentivirus expressing the miR of interest. This method has the advantage of making the system inducible or cell-specific, thereby reducing toxicity. For miRs that are over-expressed in cancer, miR inhibitors can be used to modulate their levels. For example, sequence-specific antisense oligonucleotides against an individual miR can be transfected into mammalian cells, preventing the miR from binding its targets ( Hutvagner et al. 2004, Meister et al. 2004, Horwich & Zamore 2008). Another approach consists of high expression of artificial target genes containing multiple tandem binding sites for the miR of interest ( Ebert et al. 2007). This competitive inhibition approach, known as ‘miR sponge’, results in the release of miR-mediated repression of endogenous targets ( Ebert et al. 2007). While the specific targets useful for ovarian cancer therapy remain to be determined, miR-31 inhibition using a ‘sponge’ strategy has recently been shown to inhibit breast cancer metastasis in vivo ( Valastyan et al. 2009). The determination of useful miR targets for therapy will likely be a major focus of future research in ovarian cancer.
In addition, miRs against known oncogenes could potentially be used to repress the expression of these genes in tumors. For example, over-expression of miR-15 and miR-16 was shown to induce apoptosis in leukemic cells through the ability of these miRs to target BCL2 ( Cimmino et al. 2005). Similarly, miR-34a was shown to target E2F3 and induce apoptosis in neuroblastoma cells ( Welch et al. 2007). In ovarian carcinoma, let-7 is commonly down-regulated and is shown to target HMGA2 ( Shell et al. 2007), a gene that may be responsible for de-differentiation during ovarian carcinoma progression ( Park et al. 2007, Shell et al. 2007). Re-introduction of let-7 has therefore been suggested as a possible approach for the therapy of ovarian carcinoma ( Park et al. 2007).
Finally, miR may be useful in ensuring tight tissue-specific control of transgene expression in gene therapy. Indeed, by incorporating carefully chosen specific miR target sites into a therapeutic mRNA, it may be possible to inhibit this mRNA in tissues where its expression is not wanted, thereby minimizing its toxicity and side effects ( Brown & Naldini 2009). In cancer, expression of a toxic gene such as thymidine kinase, or re-expression of a tumor suppressor gene, could potentially be made more specific by including, in these transgenes, sites for miRs that are expressed in normal tissues, but not in cancer cells. Clearly, a detailed knowledge of miR expression in normal and neoplastic tissues will be crucial for the success of these approaches.
While a large amount of information have been gained on the roles and possible therapeutic use of miRs in ovarian carcinoma, much remain to be done. In particular, more thorough miR expression profiling will be necessary to clarify expression in ovarian carcinoma of various grades, stages, or drug resistance status. The next step, the identification of relevant targets, will likely be a tedious task, complicated by the fact that miRs can have several functional targets and that these targets may be dependent on several factors, including the expression of other miRs. Once relevant miRs and functional targets are identified, the investigation of possible clinical use for these molecules will represent the next frontier, and may, ultimately lead to novel strategies for ovarian cancer detection and therapy.
Declaration of interest
The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.
This work was supported entirely by the Intramural Research Program of the National Institutes of Health, National Institute on Aging.
We thank Drs Ashani Weeraratna and Myriam Gorospe, as well as the members of our laboratory for helpful comments on the manuscript.
Garcia M Jemal A Ward EM Center MM Hao Y Siegel R & Thun MJ 2007 In Global Cancer Facts & Figures 2007 Available: www.cancer.org. Atlanta GA: American Cancer Society.
This paper is one of 6 papers that form part of a special Focus Section on microRNAs. The Guest Editors for this section were Professor Alfredo Fusco, Naples, Italy, and Professor Carlo M Croce, Columbus, OH, USA.