A ten-microRNA signature identified from a genome-wide microRNA expression profiling in human epithelial ovarian cancer.
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ABSTRACT:
SUBMITTER: Wang L
PROVIDER: S-EPMC4015980 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Human Ovarian tissue samples including 15 normal tissue samples and 48 malignant ovarian tissue were collected at Zhongshan Hospital of Fudan University. All tissue samples were immediately frozen in liquid nitrogen after being removed from body and stored at -80°C. Biovue's Sharpvue miRNA qPCR array panels (A-E) including 1721 unique assays were used to quantitate genome-wide miRNA gene expression from the collected ovarian tissue samples.
2014-12-31 | GSE53829 | GEO
Project description:Glioblastoma (GBM) is the most common and aggressive primary brain tumor with very poor patient median survival. To identify a microRNA (miRNA) expression signature that can predict GBM patient survival, we analyzed the miRNA expression data of GBM patients (n=222) derived from The Cancer Genome Atlas (TCGA) dataset. We divided the patients randomly into training and testing sets with equal number in each group. We identified 10 significant miRNAs using Cox regression analysis on the training set and formulated a risk score based on the expression signature of these miRNAs that segregated the patients into high and low risk groups with significantly different survival times (hazard ratio [HR]=2.4; 95% CI=1.4-3.8; p<0.0001). Of these 10 miRNAs, 7 were found to be risky miRNAs and 3 were found to be protective. This signature was independently validated in the testing set (HR=1.7; 95% CI=1.1-2.8; p=0.002). GBM patients with high risk scores had overall poor survival compared to the patients with low risk scores. Overall survival among the entire patient set was 35.0% at 2 years, 21.5% at 3 years, 18.5% at 4 years and 11.8% at 5 years in the low risk group, versus 11.0%, 5.5%, 0.0 and 0.0% respectively in the high risk group (HR=2.0; 95% CI=1.4-2.8; p<0.0001). Cox multivariate analysis with patient age as a covariate on the entire patient set identified risk score based on the 10 miRNA expression signature to be an independent predictor of patient survival (HR=1.120; 95% CI=1.04-1.20; p=0.003). Thus we have identified a miRNA expression signature that can predict GBM patient survival. These findings may have implications in the understanding of gliomagenesis, development of targeted therapy and selection of high risk cancer patients for adjuvant therapy.
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Project description:MicroRNAs (miRNAs) have been proposed as biomarkers for cancer and other diseases due to their stability in serum. In epilepsy, miRNAs have almost been studied in brain tissues and in animals' circulation, but not in circulation of human. To date, a major challenge is to develop biomarkers to improve the current diagnosis of epilepsy. The aim of this study was to evaluate whether circulating miRNAs can be used as biomarkers for epilepsy. We measured the differences in serum miRNA levels between 30 epilepsy patients and 30 healthy controls in discovery and training phases using Illumina HiSeq2000 sequencing followed by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) assays. The selected miRNAs were then validated in 117 epilepsy patients and 112 healthy controls by qRT-PCR. Let-7d-5p, miR-106b-5p, -130a-3p and -146a-5p were found up-regulated, whereas miR-15a-5p and -194-5p were down-regulated in epilepsy patients compared to controls (P < 0.0001). Among these miRNAs, miR-106b-5p had the best diagnostic value for epilepsy with 80.3% sensitivity and 81.2% specificity. Circulating miRNAs were differentially regulated in epilepsy patients as compared with controls. MiR-106b-5p may serve as a novel, noninvasive biomarker to improve the current diagnosis of epilepsy.
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Project description:PurposeThis study investigates the diagnostic and prognostic biomarker potential of miRNAs in prostate cancer (PC).ResultsWe identified several new deregulated miRNAs between non-malignant (NM) and PC tissue samples and between more/less aggressive PC subgroups. We also developed and validated a novel 13-miRNA diagnostic classifier with high sensitivity and specificity for PC. Finally, we trained a new 3-miRNA prognostic classifier (miR-185-5p+miR-221-3p+miR-326) that predicted time to biochemical recurrence (BCR) independently of routine clinicopathological variables in a training radical prostatectomy (RP) cohort (n = 126) as well as in two independent validation cohorts (n = 110 and n = 99).Experimental designAfter RT-qPCR-based profiling of 752 miRNAs in 13 NM and 134 PC tissue samples (cohort 1), we selected 93 top candidate diagnostic/prognostic miRNAs for validation in two independent patient sets (cohort 2: 19 NM and 138 PC; cohort 3: 28 NM and 113 PC samples). Diagnostic potential was assessed by ROC curve analysis and prognostic potential by Kaplan-Meier, uni- and multivariate Cox regression analyses. BCR after RP was used as endpoint.ConclusionsThis is the first report of a miRNA signature with significant independent prognostic value demonstrated in three PC patient cohorts.
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Project description:Epithelial ovarian cancer (EOC) remains the most lethal gynecologic malignancy in the United States. EZH2 silences gene expression through trimethylating lysine 27 on histone H3 (H3K27Me3). EZH2 is often overexpressed in EOC and has been suggested as a target for EOC intervention. However, EZH2 target genes in EOC remain poorly understood. Here, we mapped the genomic loci occupied by EZH2/H3K27Me3 using chromatin immunoprecipitation followed by next-generation sequencing (ChIP-seq) and globally profiled gene expression in EZH2-knockdown EOC cells. Cross-examination of gene expression and ChIP-seq revealed a list of 60 EZH2 direct target genes whose expression was upregulated more than 1.5-fold upon EZH2 knockdown. For three selected genes (ALDH1A1, SSTR1, and DACT3), we validated their upregulation upon EZH2 knockdown and confirmed the binding of EZH2/H3K27Me3 to their genomic loci. Furthermore, the presence of H3K27Me3 at the genomic loci of these EZH2 target genes was dependent upon EZH2. Interestingly, expression of ALDH1A1, a putative marker for EOC stem cells, was significantly downregulated in high-grade serous EOC (n = 53) compared with ovarian surface epithelial cells (n = 10, P < 0.001). Notably, expression of ALDH1A1 negatively correlated with expression of EZH2 (n = 63, Spearman r = -0.41, P < 0.001). Thus, we identified a list of 60 EZH2 target genes and established that ALDH1A1 is a novel EZH2 target gene in EOC cells. Our results suggest a role for EZH2 in regulating EOC stem cell equilibrium via regulation of ALDH1A1 expression.
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Project description:BackgroundFrozen-thawed embryo transfer (FET) is increasingly available for the improvement of the success rate of assisted reproductive technologies other than fresh embryo transfer (ET). There have been numerous findings that FET provides better obstetric and perinatal outcomes. However, the birth weight of infants conceived using FET is heavier than that of those conceived via ET. In addition, some reports have suggested that FET is associated with perinatal diseases such as placenta accreta and pregnancy-induced hypertension (PIH).ResultsIn this study, we compared the microRNA (miRNA) expression profiles in term placentae derived from FET, ET, and spontaneous pregnancy (SP). We identified four miRNAs, miR-130a-3p, miR-149-5p, miR-423-5p, and miR-487b-3p, that were significantly downregulated in FET placentae compared with those from SP and ET. We found that DNA methylation of MEG3-DMR, not but IG-DMR, was associated with miRNA expression of the DLK1-DIO3 imprinted domain in the human placenta. In functional analyses, GO terms and signaling pathways related to positive regulation of gene expression, growth, development, cell migration, and type II diabetes mellitus (T2DM) were enriched.ConclusionsThis study supports the hypothesis that the process of FET may increase exposure of epigenome to external influences.
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Project description:PIWI-interacting (piRNAs), ~23-36 nucleotide-long small non-coding RNAs (sncRNAs), earlier believed to be germline-specific, have now been identified in somatic cells, including cancer cells. These sncRNAs impact critical biological processes by fine-tuning gene expression at post-transcriptional and epigenetic levels. The expression of piRNAs in ovarian cancer, the most lethal gynecologic cancer is largely uncharted. In this study, we investigated the expression of PIWILs by qRT-PCR and western blotting and then identified piRNA transcriptomes in tissues of normal ovary and two most prevalent epithelial ovarian cancer subtypes, serous and endometrioid by small RNA sequencing. We detected 219, 256 and 234 piRNAs in normal ovary, endometrioid and serous ovarian cancer samples respectively. We observed piRNAs are encoded from various genomic regions, among which introns harbor the majority of them. Surprisingly, piRNAs originated from different genomic contexts showed the varied level of conservations across vertebrates. The functional analysis of predicted targets of differentially expressed piRNAs revealed these could modulate key processes and pathways involved in ovarian oncogenesis. Our study provides the first comprehensive piRNA landscape in these samples and a useful resource for further functional studies to decipher new mechanistic views of piRNA-mediated gene regulatory networks affecting ovarian oncogenesis. The RNA-seq data is submitted to GEO database (GSE83794).
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Project description:Ovarian germ cell tumors (OGCTs) and sex cord stromal tumors (SCSTs) are rare gynecologic tumors that are derived from germ and stromal cells, respectively. Unlike their epithelial counterparts, molecular pathogenesis of these tumor types is still poorly understood. Here, we characterized microRNA (miRNA) expression profiles of 9 OGCTs (2 malignant and 7 benign) and 3 SCSTs using small RNA sequencing. We observed significant miRNA expression variations among the three tumor groups. To further demonstrate the biological relevance of our findings, we selected 12 miRNAs for validation in an extended cohort of 16 OGCTs (9 benign and 7 malignant) and 7 SCSTs by reverse transcription-quantitative polymerase chain reaction. Higher expression of miR?373?3p, miR?372?3p and miR?302c?3p and lower expression of miR?199a?5p, miR?214?5p and miR?202?3p were reproducibly observed in malignant OGCTs as compared to benign OGCTs or SCSTs. Comparing with benign OGCTs, miR?202c?3p and miR?513c?5p were more abundant in SCSTs. Additionally, we examined Beclin 1 (BECN1), a target of miR?199a?5p, in the clinical samples using western blot analysis. Our results show that BECN1 expression was higher in malignant OGCTs than benign OGCTs, which is concordant with their lower miR?199a?5p expression. This study suggests that these miRNAs may have potential value as tumor markers and implications for further understanding the molecular basis of these tumor types.
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Project description:MicroRNAs (miRNAs) constitute a class of small noncoding RNAs that plays an important role in the post-transcriptional regulation of gene expression. Much evidence has demonstrated that miRNAs are involved in regulating the human and mouse pluripotency. Nevertheless, to our knowledge, miRNAs in the pluripotent stem cells of one of the most commonly used model organisms - the Rattus norvegicus have not been studied. In the present study, we performed deep sequencing of small RNA molecules in the embryonic fibroblasts, embryonic stem cells, and induced pluripotent stem cells of laboratory rats. Bioinformatics analysis revealed 674 known miRNAs and 394 novel miRNA candidates in all of the samples. Expression of known pluripotency-associated miRNAs, such as the miR-290-295 and miR-183-96-182 clusters as well as members of the miR-200 family, was detected in rat pluripotent stem cells. Analysis of the targets of differentially expressed known and novel miRNAs showed their involvement in the regulation of pluripotency and the reprogramming process in rats. Bioinformatics and systems biology approaches identified potential pathways that are regulated by these miRNAs. This study contributes to our understanding of miRNAs in the regulation of pluripotency and cell reprogramming in the laboratory rat.
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Project description:BackgroundLymph node (LN) status is vital to evaluate the curative potential of relatively early gastric cancer (GC; T1-T2) treatment (endoscopic or surgery). Currently, there is a lack of robust and convenient methods to identify LN metastasis before therapeutic decision-making.MethodsGenome-wide expression profiles of long noncoding RNA (lncRNA) in primary T1 gastric cancer data from The Cancer Genome Atlas (TCGA) was used to identify lncRNA expression signature capable of detecting LN metastasis of GC and establish a 10-lncRNA risk-prediction model based on deep learning. The performance of the lncRNA panel in diagnosing LN metastasis was evaluated both in silico and clinical validation methods. In silico validation was conducted using TCGA and Asian Cancer Research Group (ACRG) datasets. Clinical validation was performed on T1 and T2 patients, and the panel's efficacy was compared with that of traditional tumor markers and computed tomography (CT) scans.ResultsProfiling of genome-wide RNA expression identified a panel of lncRNA to predict LN metastasis in T1 stage gastric cancer (AUC = 0.961). A 10-lncRNA risk-prediction model was then constructed, which was validated successfully in T1 and T2 datasets (TCGA, AUC = 0.852; ACRG, AUC = 0.834). Thereafter, the clinical performance of the lncRNA panel was validated in clinical cohorts (T1, AUC = 0.812; T2, AUC = 0.805; T1 + T2, AUC = 0.764). Notably, the panel demonstrated significantly better performance compared with CT and traditional tumor markers.ConclusionsThe novel 10-lncRNA could diagnose LN metastasis robustly in relatively early gastric cancer (T1-T2), with promising clinical potential.
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