Characterization of microRNA expression in serous ovarian carcinoma

ExplORRNet: An interactive web tool to explore stage-wise miRNA expression profiles and their interactions with mRNA and lncRNA in human breast and gynecological cancers

Background

MicroRNAs (miRNAs) are key regulators of gene expression that have been implicated in gynecological and breast cancers. Understanding the cancer stage-wise expression patterns of miRNAs and their interactions with other RNA molecules in cancer is crucial to improve cancer diagnosis and treatment planning. Comprehensive web tools that integrate data on the transcriptome, circulating miRNAs, and their validated targets to derive beneficial conclusions in cancer research are lacking.

Methods

Using the Shiny R package, we developed a web tool called ExplORRNet that integrates transcriptomic profiles from The Cancer Genome Atlas and miRNA expression data derived from various sources, including tissues, cell lines, exosomes, serum, and plasma, available in the Gene Expression Omnibus database. Differential expression analyses between normal and tumor tissue samples as well as different stages of cancer, accompanied by gene enrichment and survival analyses, can be performed using specialized R packages. Additionally, a miRNA-messenger RNA (mRNA)-long non-coding RNA (lncRNA) networks are constructed to identify regulatory modules.

Results

Our tool identifies cancer stage-wise differentially regulated miRNAs, mRNAs, and lncRNAs in gynecological and breast cancers. Survival analysis identifies miRNAs associated with patient survival, and functional enrichment analysis provides insights into dysregulated miRNA-related biological processes and pathways. The miRNA-mRNA-lncRNA networks highlight interconnected regulatory molecular modules driving cancer progression. Case studies demonstrate the utility of the ExplORRNet for studying gynecological and breast cancers.

Conclusion

ExplORRNet is an intuitive and user-friendly web tool that provides a deeper understanding of dysregulated miRNAs and their functional implications in gynecological and breast cancers. We hope our ExplORRNet tool has potential utility among the clinical and basic researchers and will be beneficial to the entire cancer genomics community to encourage and facilitate mining the rapidly growing public databases to progress the field of precision oncology. The ExplORRNet is available at https://mirna.cs.ut.ee.

Identifying potential circulating miRNA biomarkers for the diagnosis and prediction of ovarian cancer using machine-learning approach: application of Boruta

Introduction

In gynecologic oncology, ovarian cancer is a great clinical challenge. Because of the lack of typical symptoms and effective biomarkers for noninvasive screening, most patients develop advanced-stage ovarian cancer by the time of diagnosis. MicroRNAs (miRNAs) are a type of non-coding RNA molecule that has been linked to human cancers. Specifying diagnostic biomarkers to determine non-cancer and cancer samples is difficult.

Methods

By using Boruta, a novel random forest-based feature selection in the machine-learning techniques, we aimed to identify biomarkers associated with ovarian cancer using cancerous and non-cancer samples from the Gene Expression Omnibus (GEO) database: GSE106817. In this study, we used two independent GEO data sets as external validation, including GSE113486 and GSE113740. We utilized five state-of-the-art machine-learning algorithms for classification: logistic regression, random forest, decision trees, artificial neural networks, and XGBoost.

Results

Four models discovered in GSE113486 had an AUC of 100%, three in GSE113740 with AUC of over 94%, and four in GSE113486 with AUC of over 94%. We identified 10 miRNAs to distinguish ovarian cancer cases from normal controls: hsa-miR-1290, hsa-miR-1233-5p, hsa-miR-1914-5p, hsa-miR-1469, hsa-miR-4675, hsa-miR-1228-5p, hsa-miR-3184-5p, hsa-miR-6784-5p, hsa-miR-6800-5p, and hsa-miR-5100. Our findings suggest that miRNAs could be used as possible biomarkers for ovarian cancer screening, for possible intervention.

NF-κB Signaling Modulates miR-452-5p and miR-335-5p Expression to Functionally Decrease Epithelial Ovarian Cancer Progression in Tumor-Initiating Cells

Epithelial ovarian cancer (EOC) remains the fifth leading cause of cancer-related death in women worldwide, partly due to the survival of chemoresistant, stem-like tumor-initiating cells (TICs) that promote disease relapse. We previously described a role for the NF-κB pathway in promoting TIC chemoresistance and survival through NF-κB transcription factors (TFs) RelA and RelB, which regulate genes important for the inflammatory response and those associated with cancer, including microRNAs (miRNAs). We hypothesized that NF-κB signaling differentially regulates miRNA expression through RelA and RelB to support TIC persistence. Inducible shRNA was stably expressed in OV90 cells to knockdown RELA or RELB; miR-seq analyses identified differentially expressed miRNAs hsa-miR-452-5p and hsa-miR-335-5p in cells grown in TIC versus adherent conditions. We validated the miR-seq findings via qPCR in TIC or adherent conditions with RELA or RELB knocked-down. We confirmed decreased expression of hsa-miR-452-5p when either RELA or RELB were depleted and increased expression of hsa-miR-335-5p when RELA was depleted. Either inhibiting miR-452-5p or mimicking miR-335-5p functionally decreased the stem-like potential of the TICs. These results highlight a novel role of NF-κB TFs in modulating miRNA expression in EOC cells, thus opening a better understanding toward preventing recurrence of EOC.

Strategies for data normalization and missing data imputation and consequences for potential diagnostic microRNA biomarkers in epithelial ovarian cancer

MicroRNAs (miRNAs) are small non-coding RNA molecules regulating gene expression with diagnostic potential in different diseases, including epithelial ovarian carcinomas (EOC). As only a few studies have been published on the identification of stable endogenous miRNA in EOC, there is no consensus which miRNAs should be used aiming standardization. Currently, U6-snRNA is widely adopted as a normalization control in RT-qPCR when investigating miRNAs in EOC; despite its variable expression across cancers being reported. Therefore, our goal was to compare different missing data and normalization approaches to investigate their impact on the choice of stable endogenous controls and subsequent survival analysis while performing expression analysis of miRNAs by RT-qPCR in most frequent subtype of EOC: high-grade serous carcinoma (HGSC). 40 miRNAs were included based on their potential as stable endogenous controls or as biomarkers in EOC. Following RNA extraction from formalin-fixed paraffin embedded tissues from 63 HGSC patients, RT-qPCR was performed with a custom panel covering 40 target miRNAs and 8 controls. The raw data was analyzed by applying various strategies regarding choosing stable endogenous controls (geNorm, BestKeeper, NormFinder, the comparative ΔCt method and RefFinder), missing data (single/multiple imputation), and normalization (endogenous miRNA controls, U6-snRNA or global mean). Based on our study, we propose hsa-miR-23a-3p and hsa-miR-193a-5p, but not U6-snRNA as endogenous controls in HGSC patients. Our findings are validated in two external cohorts retrieved from the NCBI Gene Expression Omnibus database. We present that the outcome of stability analysis depends on the histological composition of the cohort, and it might suggest unique pattern of miRNA stability profiles for each subtype of EOC. Moreover, our data demonstrates the challenge of miRNA data analysis by presenting various outcomes from normalization and missing data imputation strategies on survival analysis.

Identification of key genes and miRNAs related to polycystic ovary syndrome by comprehensive analysis of microarray

BACKGROUND

We aimed to explore mechanisms of development and progression of polycystic ovary syndrome (PCOS).

METHODS

The microRNA expression microarray GSE37914 and gene expression profiles GSE43264 and GSE98421 were downloaded from the Gene Expression Omnibus database. The differentially expressed miRNAs (DEmiRNAs) and genes (DEGs) were screened using Limma package. Then, the DEGs and DEmiRNAs were combined to use for the subsequent analysis, including the functional enrichment analysis, protein-protein interaction (PPI) network and module analysis, drug-gene interaction network analysis, and DEmiRNAs-DEGs interactive network construction.

RESULTS

A total of 26 DEmiRNAs and 80 DEGs were screened. The PPI network contained 68 nodes and 259 interactions. A significant clustering module with 8 nodes and 25 interactions was obtained. Three PCOS-related overlapping pathways were obtained based on PPI-degree top10 and module genes, including prion diseases, Staphylococcus aureus infection, and Chagas disease (American trypanosomiasis). A total of 44 drug-gene interaction pairs were obtained, which included 2 up-regulated genes (LDLR and VCAM1), 4 down-regulated genes (C1QA, C1QB, IL6 and ACAN) and 26 small molecules drugs. A total of 52 nodes and 57 interactions were obtained in the DEmiRNA-DEGs regulatory network, LDLR was regulated by miR-152-3p, miR-1207-5p, miR-378a-5p and miR-150-5p.

CONCLUSIONS

Our research has identified several key genes and pathways related to PCOS. These results can improve our understanding of PCOS and provide new basis for drug target research.

miR-450a exerts oncosuppressive effects in breast carcinoma by targeting CREB1

Emerging evidence greatly implicates that microRNA-450a (miR-450a) plays an essential role in cancer pathobiology. While the pathological role of miR-450a in breast carcinogenesis remains enigmatic. Herein, we showed that miR-450a was lowly expressed in breast cancer cell lines compared with normal, and low miR-450a expression was associated with poor survival in patients with breast cancer. We revealed that miR-450a mimic transfected breast cancer cells (T47D and BT474) exhibited attenuated capacities of proliferation, migration, and invasion in vitro, and miR-450a suppressed T47D cell growth in a xenograft tumor model. Mechanistically, cAMP response element-binding protein 1 (CREB1) was negatively targeted by miR-450a, and CREB1 deletion mimicked the effects of miR-450a mimic treatment. Bioinformatics analysis further revealed that elevated expression of CREB1 correlated with poor prognosis in patients with breast cancer and miR-450a level was negatively correlated with CREB1 level in breast cancer. Additionally, miR-450a inhibited the phosphorylation of phosphatidylinositol 3-kinase/V-akt murine thymoma viral oncogene homolog (PI3K/AKT) and the activities of matrix metalloproteinase-2/9 (MMP-2/9). The following rescue assay indicated that CREB1 was implicated in the anti-tumoral effect of mR-450a in breast carcinoma. All these observations disclosed that miR-450a negatively regulates the growth and metastatic property of breast carcinoma cells.

An Insight into miR-1290: An Oncogenic miRNA with Diagnostic Potential

For more than two decades, the view of the roles of non-coding RNAs (ncRNAs) has been radically changing. These RNA molecules that are transcribed from our genome do not have the capacity to encode proteins, but are critical regulators of gene expression at different levels. Our knowledge is constantly enriched by new reports revealing the role of these new molecular players in the development of many pathological conditions, including cancer. One of the ncRNA classes includes short RNA molecules called microRNAs (miRNAs), which are involved in the post-transcriptional control of gene expression affecting various cellular processes. The aberrant expression of miRNAs with oncogenic and tumor-suppressive function is associated with cancer initiation, promotion, malignant transformation, progression and metastasis. Oncogenic miRNAs, also known as oncomirs, mediate the downregulation of tumor-suppressor genes and their expression is upregulated in cancer. Nowadays, miRNAs show promising application in diagnosis, prediction, disease monitoring and therapy response. Our review presents a current view of the oncogenic role of miR-1290 with emphasis on its properties as a cancer biomarker in clinical medicine.

Applications of Multi-omics Approaches for Exploring the Molecular Mechanism of Ovarian Carcinogenesis

Ovarian cancer ranks as the fifth most common cause of cancer-related death in females. The molecular mechanisms of ovarian carcinogenesis need to be explored in order to identify effective clinical therapies for ovarian cancer. Recently, multi-omics approaches have been applied to determine the mechanisms of ovarian oncogenesis at genomics (DNA), transcriptomics (RNA), proteomics (proteins), and metabolomics (metabolites) levels. Multi-omics approaches can identify some diagnostic and prognostic biomarkers and therapeutic targets for ovarian cancer, and these molecular signatures are beneficial for clarifying the development and progression of ovarian cancer. Moreover, the discovery of molecular signatures and targeted therapy strategies could noticeably improve the prognosis of ovarian cancer patients.

Circulating Exosomal miRNAs as Biomarkers in Epithelial Ovarian Cancer

Failure to detect early-stage epithelial ovarian cancer (EOC) is a major contributing factor to its low survival rate. Increasing evidence suggests that different subtypes of EOC may behave as distinct diseases due to their different cells of origins, histology and treatment responses. Therefore, the identification of EOC subtype-specific biomarkers that can early detect the disease should be clinically beneficial. Exosomes are extracellular vesicles secreted by different types of cells and carry biological molecules, which play important roles in cell-cell communication and regulation of various biological processes. Multiple studies have proposed that exosomal miRNAs present in the circulation are good biomarkers for non-invasive early detection of cancer. In this review, the potential use of exosomal miRNAs as early detection biomarkers for EOCs and their accuracy are discussed. We also review the differential expression of circulating exosomal miRNAs and cell-free miRNAs between different biofluid sources, i.e., plasma and serum, and touch on the issue of endogenous reference miRNA selection. Additionally, the current clinical trials using miRNAs for detecting EOCs are summarized. In conclusion, circulating exosomal miRNAs as the non-invasive biomarkers have a high potential for early detection of EOC and its subtypes, and are likely to be clinically important in the future.

OCaMIR-A Noninvasive, Diagnostic Signature for Early-Stage Ovarian Cancer: A Multi-cohort Retrospective and Prospective Study

PURPOSE

Due to the lack of effective screening approaches and early detection biomarkers, ovarian cancer has the highest mortality rates among gynecologic cancers. Herein, we undertook a systematic biomarker discovery and validation approach to identify microRNA (miRNA) biomarkers for the early detection of ovarian cancer.

EXPERIMENTAL DESIGN

During the discovery phase, we performed small RNA sequencing in stage I high-grade serous ovarian cancer (n = 31), which was subsequently validated in multiple, independent data sets (TCGA, n = 543; GSE65819, n = 87). Subsequently, we performed multivariate logistic regression-based training in a serum data set (GSE106817, n = 640), followed by its independent validation in three retrospective data sets (GSE31568, n = 85; GSE113486, n = 140; Czech Republic cohort, n = 192) and one prospective serum cohort (n = 95). In addition, we evaluated the specificity of OCaMIR, by comparing its performance in several other cancers (GSE31568 cohort, n = 369).

RESULTS

The OCaMIR demonstrated a robust diagnostic accuracy in the stage I high-grade serous ovarian cancer patients in the discovery cohort (AUC = 0.99), which was consistently reproducible in both stage I (AUC = 0.96) and all stage patients (AUC = 0.89) in the TCGA cohort. Logistic regression-based training and validation of OCaMIR achieved AUC values of 0.89 (GSE106817), 0.85 (GSE31568), 0.86 (GSE113486), and 0.82 (Czech Republic cohort) in the retrospective serum validation cohorts, as well as prospective validation cohort (AUC = 0.92). More importantly, OCaMIR demonstrated a significantly superior diagnostic performance compared with CA125 levels, even in stage I patients, and was more cost-effective, highlighting its potential role for screening and early detection of ovarian cancer.

CONCLUSIONS

Small RNA sequencing identified a robust noninvasive miRNA signature for early-stage serous ovarian cancer detection.

Current Implications of microRNAs in Genome Stability and Stress Responses of Ovarian Cancer

Genomic alterations and aberrant DNA damage signaling are hallmarks of ovarian cancer (OC), the leading cause of mortality among gynecological cancers worldwide. Owing to the lack of specific symptoms and late-stage diagnosis, survival chances of patients are significantly reduced. Poly (ADP-ribose) polymerase (PARP) inhibitors and replication stress response inhibitors present attractive therapeutic strategies for OC. Recent research has focused on ovarian cancer-associated microRNAs (miRNAs) that play significant regulatory roles in various cellular processes. While miRNAs have been shown to participate in regulation of tumorigenesis and drug responses through modulating the DNA damage response (DDR), little is known about their potential influence on sensitivity to chemotherapy. The main objective of this review is to summarize recent findings on the utility of miRNAs as cancer biomarkers, in particular, ovarian cancer, and their regulation of DDR or modified replication stress response proteins. We further discuss the suppressive and promotional effects of various miRNAs on ovarian cancer and their participation in cell cycle disturbance, response to DNA damage, and therapeutic functions in multiple cancer types, with particular focus on ovarian cancer. Improved understanding of the mechanisms by which miRNAs regulate drug resistance should facilitate the development of effective combination therapies for ovarian cancer.

Small Non-Coding-RNA in Gynecological Malignancies

Gynecologic malignancies, which include cancers of the cervix, ovary, uterus, vulva, vagina, and fallopian tube, are among the leading causes of female mortality worldwide, with the most prevalent being endometrial, ovarian, and cervical cancer. Gynecologic malignancies are complex, heterogeneous diseases, and despite extensive research efforts, the molecular mechanisms underlying their development and pathology remain largely unclear. Currently, mechanistic and therapeutic research in cancer is largely focused on protein targets that are encoded by about 1% of the human genome. Our current understanding of 99% of the genome, which includes noncoding RNA, is limited. The discovery of tens of thousands of noncoding RNAs (ncRNAs), possessing either structural or regulatory functions, has fundamentally altered our understanding of genetics, physiology, pathophysiology, and disease treatment as they relate to gynecologic malignancies. In recent years, it has become clear that ncRNAs are relatively stable, and can serve as biomarkers for cancer diagnosis and prognosis, as well as guide therapy choices. Here we discuss the role of small non-coding RNAs, i.e., microRNAs (miRs), P-Element induced wimpy testis interacting (PIWI) RNAs (piRNAs), and tRNA-derived small RNAs in gynecological malignancies, specifically focusing on ovarian, endometrial, and cervical cancer.

Cadmium exposure during prenatal development causes progesterone disruptors in multiple generations via steroidogenic enzymes in rat ovarian granulosa cells

Exposure to the heavy metal cadmium (Cd) in the environment is linked to adverse health. To fully understand the adverse effects of this important endocrine-disrupting compound (EDC) requires studies that address multigenerational effects and epigenetic mechanisms. The present study orally dosed pregnant SD rats with Cd from gestation day 1 until birth. First filial generation (F1) female rats were mated with untreated males to generate the secondary filial generation (F2). Ovarian granulosa cells (OGCs) were collected at postnatal day (PND) 56 from both generations after prenatal Cd exposure, and hormone secretion examinations showed a progesterone disorder. Significant decreases in steroidogenic enzymes (steroidogenic acute regulatory protein (StAR) and P450 cholesterol side-chain cleavage enzyme (CYP11A1)) were observed in F1 and F2 rats. However, F1 and F2 rats had different patterns of mRNA and protein expression of steroidogenic factor 1 (SF-1). We also found that microRNAs were significantly changed using a microarray, and miR-10b-5p and miR-27a-3p were upregulated in F1 and F2 rats. The COV434 cell line microRNA-knockdown model showed that these two important microRNAs regulated the StAR-induced Cd effect on progesterone secretion. Overall, the results of this study indicate that prenatal Cd exposure causes cytotoxicity problems, progesterone disorder and microRNAs expression changed in a multigenerational manner. And progesterone disorder may interfere with the steroidogenic enzymes in offspring. The present study also revealed that environmental pollution produces multigenerational effects.

MiR-450a-5p strengthens the drug sensitivity of gefitinib in glioma chemotherapy via regulating autophagy by targeting EGFR

Glioma reported to be refractory to EGFR tyrosine kinase inhibitor is the most common malignant tumor in central nervous system. Our research showed the low expression of miR-450a-5p and high expression of EGFR in glioma tissues. MiR-450a-5p was also observed to synergize with gefitinib to inhibit the proliferation, migration and invasion and induce the apoptosis and autophagy of glioma cells. Furthermore, miR-450a-5p was demonstrated to target 3'UTR of EGFR, and regulated EGFR-induced PI3K/AKT/mTOR signaling pathway. Moreover, the above effects induced by miR-450a-5p in glioma cells were reversed by WIPI1 silencing. The inhibition role of miR-450a-5p on glioma growth was also confirmed in vivo by subcutaneous and intracranial tumor xenografts. Therefore, we conclude that miR-450a-5p synergizes with gefitinib to inhibit the glioma tumorigenesis through inducing autophagy by regulating the EGFR-induced PI3K/AKT/mTOR signaling pathway, thereby enhancing the drug sensitivity of gefitinib.

The prognostic role of microRNA in epithelial ovarian cancer: a systematic review of literature with an overall survival meta-analysis

Objective: To accomplish a systematic review of literature with overall survival meta-analysis about the role of microRNA in epithelial ovarian cancer as prognostic and predictive factor to chemotherapy response.

Methods: A search was conducted in the PubMed database, using the keywords “microRNA” and “ovarian cancer” or “miRNA” and “ovarian cancer”. Original articles published before 02/02/2019 that had as main subject microRNA (miRNA) and ovarian cancer were included. We considered for inclusion only studies that associated microRNA to chemotherapy-related diagnosis, prognosis, or response in ovarian cancer.

Results: The literature search returned 1,482 articles, 497 of which fulfilled inclusion criteria, yielding 350 miRNAs. The status of each miRNA was assessed in serum and tissue of ovarian cancer, benign tumors, and healthy tissue. The status of up-/downregulation of miRNAs was related to prognostic features (overall survival and disease-free survival) and response predictive features such as platinum and paclitaxel sensitivity/resistance. The miRNAs that had been cited three or more times were selected for prognostic and response predictive features analysis. Twelve miRNAs fulfilled all these criteria and were included in the overall survival meta-analysis.

Conclusions: miRNAs affect virtually all mechanisms of carcinogenesis, working as either oncogenes or tumor suppressor genes. In this systematic review we identified miRNAs that may be related to prognosis, diagnosis, and chemotherapy sensitivity. The 12 miRNAs identified here should be included in future studies for validation.

miR-450a Acts as a Tumor Suppressor in Ovarian Cancer by Regulating Energy Metabolism

Dysregulation of miRNA expression is associated with multiple diseases, including cancers, in which small RNAs can have either oncogenic or tumor suppressive functions. Here we investigated the potential tumor suppressive function of miR-450a, one of the most significantly downregulated miRNAs in ovarian cancer. RNA-seq analysis of the ovarian cancer cell line A2780 revealed that overexpression of miR-450a suppressed multiple genes involved in the epithelial-to-mesenchymal transition (EMT). Overexpression of miR-450a reduced tumor migration and invasion and increased anoikis in A2780 and SKOV-3 cell lines and reduced tumor growth in an ovarian tumor xenographic model. Combined AGO-PAR-CLIP and RNA-seq analysis identified a panel of potential miR-450a targets, of which many, including TIMMDC1, MT-ND2, ACO2, and ATP5B, regulate energetic metabolism. Following glutamine withdrawal, miR-450a overexpression decreased mitochondrial membrane potential but increased glucose uptake and viability, characteristics of less invasive ovarian cancer cell lines. In summary, we propose that miR-450a acts as a tumor suppressor in ovarian cancer cells by modulating targets associated with glutaminolysis, which leads to decreased production of lipids, amino acids, and nucleic acids, as well as inhibition of signaling pathways associated with EMT. SIGNIFICANCE: miR-450a limits the metastatic potential of ovarian cancer cells by targeting a set of mitochondrial mRNAs to reduce glycolysis and glutaminolysis.Graphical Abstract: http://cancerres.aacrjournals.org/content/canres/79/13/3294/F1.large.jpg.

Serum exosomal miRNA-145 and miRNA-200c as promising biomarkers for preoperative diagnosis of ovarian carcinomas

Background: Exosomes are extracellular microvesicles that are released by most cells and widely distributed in various body fluids. Malignant cells secrete large amounts of exosomes containing various molecular constituents reflecting the originating tumor. We investigated the difference in microRNA (miRNA) expression in serum exosomes from the patients with benign, borderline and malignant ovarian masses to assess the diagnostic relevance of serum exosomal miRNAs as biomarkers for preoperative diagnosis of ovarian carcinoma.

Methods: A total of 68 cases of ovarian masses were enrolled, comprising benign ovarian cysts (benign; n=10), borderline ovarian tumors (BOT, n=10), high-grade serous ovarian carcinomas (HGSOC, n=39) and non-HGSOCs (n=9). Exosomal RNA was extracted from the serum, and expression levels of seven miRNAs (miRNA-21, -93, -141, -145, -200a, -200b and -200c), which were reportedly dysregulated in serous ovarian cancer in previous studies, were quantified by real-time PCR, and compared between the four groups.

Results: MiR-93, -145, and -200c, showed significantly higher expression in serum exosomes of the cancer group (HGSOC and non-HGSOC) than of the non-cancer group (benign and BOT; all p<0.05). The remaining three miRs (miR-141, -200a, and -200b) were expressed at extremely low levels, and not appropriate as serological biomarkers. To test discrimination of cancer from non-cancer, the area under the receiver operating characteristic curves determined for cancer antigen 125 (CA125), miR-145, miR-200c, miR-21, and miR-93 were 0.801 (p<0.001), 0.910 (p<0.001), 0.802 (p<0.001), 0.585 (p=0.303), and 0.755 (p=0.002), respectively. MiR-145 showed superior sensitivity (91.6%), and miR-200c showed superior specificity (90.0%), compared with CA125.

Conclusion: Expression of exosomal miR-93, miR-145 and miR-200c was significantly elevated in the serum of ovarian cancer patients. Serum exosomal miR-145 in particular appeared to be the most promising biomarker for preoperative diagnosis of ovarian cancer.

A computational framework for complex disease stratification from multiple large-scale datasets

BACKGROUND

Multilevel data integration is becoming a major area of research in systems biology. Within this area, multi-'omics datasets on complex diseases are becoming more readily available and there is a need to set standards and good practices for integrated analysis of biological, clinical and environmental data. We present a framework to plan and generate single and multi-'omics signatures of disease states.

METHODS

The framework is divided into four major steps: dataset subsetting, feature filtering, 'omics-based clustering and biomarker identification.

RESULTS

We illustrate the usefulness of this framework by identifying potential patient clusters based on integrated multi-'omics signatures in a publicly available ovarian cystadenocarcinoma dataset. The analysis generated a higher number of stable and clinically relevant clusters than previously reported, and enabled the generation of predictive models of patient outcomes.

CONCLUSIONS

This framework will help health researchers plan and perform multi-'omics big data analyses to generate hypotheses and make sense of their rich, diverse and ever growing datasets, to enable implementation of translational P4 medicine.

miRNA-200a/c as potential biomarker in epithelial ovarian cancer (EOC): evidence based on miRNA meta-signature and clinical investigations

Extensive effort has been put on miRNA expression signatures in epithelial ovarian cancer (EOC). Unfortunately, consistent conclusion rarely yielded from diverse studies, mainly due to the high inter-lab variability and small sample sizes. To overcome above limitations, an integrated analysis of miRNA expression signature was performed by employing Robust Rank Aggregation (RRA) method. Diagnostic analysis, Kaplan-Meier survival curves and pathway enrichment analysis were used to investigate the clinical values and biological functions of meta-signature miRNAs. A total of 519 EOC and 248 noncancerous samples were included. Seven mostly dysregulated miRNAs were identified by RRA method and two miRNAs (miR-200a-3p and miR-200c-3p) remained statistically significant after Bonferroni-correction. Diagnostic meta-analysis showed reliable diagnostic capacity of miR-200a-3p (with a pooled sensitivity of 0.84 and specificity of 0.83) and miR-200c-3p (with a pooled sensitivity of 0.75 and specificity of 0.66) for EOC. Pathway enrichment analysis and expression correlation analysis suggested miR-200a/c might contribute EOC progression by affecting cellular adhesion process. Kaplan-Meier survival analysis based on two independent cohorts revealed a strong association between miR-200a/c and overall survival in EOC patients. miR-200a/c was identified as the mostly dysregulated miRNAs in EOC and might be novel diagnostic and prognostic biomarkers for patients with EOC.

MicroRNAs miR-19, miR-340, miR-374 and miR-542 regulate MID1 protein expression

The MID1 ubiquitin ligase activates mTOR signaling and regulates mRNA translation. Misregulation of MID1 expression is associated with various diseases including midline malformation syndromes, cancer and neurodegenerative diseases. While this indicates that MID1 expression must be tightly regulated to prevent disease states specific mechanisms involved have not been identified. We examined miRNAs to determine mechanisms that regulate MID1 expression. MicroRNAs (miRNA) are small non-coding RNAs that recognize specific sequences in their target mRNAs. Upon binding, miRNAs typically downregulate expression of these targets. Here, we identified four miRNAs, miR-19, miR-340, miR-374 and miR-542 that bind to the 3'-UTR of the MID1 mRNA. These miRNAs not only regulate MID1 expression but also mTOR signaling and translation of disease associated mRNAs and could therefore serve as potential drugs for future therapy development.

Screening of potentially crucial genes and regulatory factors involved in epithelial ovarian cancer using microarray analysis

The present study aimed to screen potential genes implicated in epithelial ovarian cancer (EOC) and to further understand the molecular pathogenesis of EOC. In order to do this, datasets GSE14407 (containing 12 human ovarian cancer epithelia samples and 12 normal epithelia samples) and GSE29220 (containing 11 salivary transcriptomes from ovarian cancer patients with serous papillary adenocarcinoma and 11 matched controls) were obtained from the Gene Expression Omnibus. Differentially expressed genes (DEGs) within these datasets were screened using the Linear Models for Microarray Data package, and potential gene functions were predicted by functional and pathway enrichment analyses. Additionally, module analysis of protein-protein interaction networks was performed using MCODE software in Cytoscape. The potential microRNAs (miRNAs/miRs) and transcription factors (TFs) regulating DEGs were also analyzed, and the integrated TF-DEG and miRNA-DEG regulatory networks were visualized with Cytoscape. In total, 31 upregulated DEGs and 64 downregulated DEGs were screened. The upregulated DEGs, such as centromere protein F (CENPF) and ubiquitin like with PHD and ring finger domains 1 (UHRF1), were significantly associated with the cell cycle and were regulated by the TF nuclear transcription factor Y (NF-Y). CENPF was modulated by miR-373, and UHRF1 was regulated by miR-146a. The downregulated DEGs, such as aldehyde dehydrogenase 1 family member A2 (ALDH1A2), were distinctly involved in the response to estrogen stimulus and modulated by tumor protein 53 (TP53); protocadherin 9 (PCDH9) was regulated by TP53, miR-92b-3p and miR-137. The DEGs, including CENPF, UHRF1, ALDH1A2 and PCDH9, and a set of gene regulators, including all NFY genes, TP53, miR-373, miR-146a, miR-92b-3p and miR-137, may be involved in the pathogenesis of EOC.

Expression of microRNA-30a-5p in drug-resistant and drug-sensitive ovarian cancer cell lines

The present study aimed to explore the expression of microRNA (miRNA or miR) in drug-resistant and drug-sensitive ovarian cancer cell lines, and to seek the potential therapeutic target of ovarian cancer drug-resistant mechanism in order to improve drug resistance by altering miRNA levels. The drug-resistant characteristics of SKOV3/DDP, SKOV3, COC1/DDP and COC1 cell lines were studied. The miRNAs that were differentially expressed between cisplatin-resistant cells and its parental cells in ovarian cancer were screened with a miRNA chip. The effect of miRNAs was detected, and their drug-resistant mechanism was investigated by transfection and 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide methods. Among the expression screening of miRNAs, 41 mRNAs, including Homo sapiens (hsa)-miR-30a-5p and hsa-miR-34c-5p, were highly expressed in the drug-resistant cells, whereas 44 miRNAs, including hsa-miR-96-5p and hsa-miR-200c-3p, were lowly expressed. The expression levels of hsa-miR-30a-5p in two types of ovarian cancer chemotherapy-resistant cell lines were significantly higher than those in chemotherapy-sensitive cell lines, which was associated with ovarian cancer chemotherapy resistance. In conclusion, high expression of miRNA-30a-5p was able to promote cell growth and colony forming ability, and enhance cell migration and invasion. Thus, miRNA-30a-5p is expected to become a meaningful novel target for ovarian cancer resistant treatment.

MicroRNA: a new and promising potential biomarker for diagnosis and prognosis of ovarian cancer

Epithelial ovarian cancer (EOC) is the leading cause of death among all gynecological malignancies. Despite the technological and medical advances over the past four decades, such as the development of several biological markers (mRNA and proteins biomarkers), the mortality rate of ovarian cancer remains a challenge because of its late diagnosis, which is specifically attributed to low specificities and sensitivities. Under this compulsive scenario, recent advances in expression biology have shifted in identifying and developing specific and sensitive biomarkers, such as microRNAs (miRNAs) for cancer diagnosis and prognosis. MiRNAs are a novel class of small non-coding RNAs that deregulate gene expression at the posttranscriptional level, either by translational repression or by mRNA degradation. These mechanisms may be involved in a complex cascade of cellular events associated with the pathophysiology of many types of cancer. MiRNAs are easily detectable in tissue and blood samples of cancer patients. Therefore, miRNAs hold good promise as potential biomarkers in ovarian cancer. In this review, we attempted to provide a comprehensive profile of key miRNAs involved in ovarian carcinoma to establish miRNAs as more reliable non-invasive clinical biomarkers for early detection of ovarian cancer compared with protein and DNA biomarkers.