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1.

Background

Clinical statement alone is not enough to predict the progression of disease. Instead, the gene expression profiles have been widely used to forecast clinical outcomes. Many genes related to survival have been identified, and recently miRNA expression signatures predicting patient survival have been also investigated for several cancers. However, miRNAs and their target genes associated with clinical outcomes have remained largely unexplored.

Methods

Here, we demonstrate a survival analysis based on the regulatory relationships of miRNAs and their target genes. The patient survivals for the two major cancers, ovarian cancer and glioblastoma multiforme (GBM), are investigated through the integrated analysis of miRNA-mRNA interaction pairs.

Results

We found that there is a larger survival difference between two patient groups with an inversely correlated expression profile of miRNA and mRNA. It supports the idea that signatures of miRNAs and their targets related to cancer progression can be detected via this approach.

Conclusions

This integrated analysis can help to discover coordinated expression signatures of miRNAs and their target mRNAs that can be employed for therapeutics in human cancers.
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2.

Background

Accumulation of amyloid β-peptide (Aβ) is implicated in the pathogenesis and development of Alzheimer’s disease (AD). Neuron-enriched miRNA was aberrantly regulated and may be associated with the pathogenesis of AD. However, regarding whether miRNA is involved in the accumulation of Aβ in AD, the underlying molecule mechanism remains unclear. Therefore, we conduct a systematic identification of the promising role of miRNAs in Aβ deposition, and shed light on the molecular mechanism of target miRNAs underlying SH-SY5Y cells treated with Aβ-induced cytotoxicity.

Results

Statistical analyses of microarray data revealed that 155 significantly upregulated and 50 significantly downregulated miRNAs were found on the basis of log2 | Fold Change |?≥?0.585 and P?< 0.05 filter condition through 2588 kinds of mature miRNA probe examined. PCR results show that the expression change trend of the selected six miRNAs (miR-6845-3p, miR-4487, miR-4534, miR-3622-3p, miR-1233-3p, miR-6760-5p) was consistent with the results of the gene chip. Notably, Aβ25–35 downregulated hsa-miR-4487 and upregulated hsa-miR-6845-3p in SH-SY5Y cell lines associated with Aβ-mediated pathophysiology. Increase of hsa-miR-4487 could inhibit cells apoptosis, and diminution of hsa-miR-6845-3p could attenuate axon damage mediated by Aβ25–35 in SH-SY5Y.

Conclusions

Together, these findings suggest that dysregulation of hsa-miR-4487 and hsa-miR-6845-3p contributed to the pathogenesis of AD associated with Aβ25–35 mediated by triggering cell apoptosis and synaptic dysfunction. It might be beneficial to understand the pathogenesis and development of clinical diagnosis and treatment of AD. Further, our well-designed validation studies will test the miRNAs signature as a prognostication tool associated with clinical outcomes in AD.
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3.

Background

MicroRNAs (miRNAs) have been shown to play important roles in regulating gene expression. Since miRNAs are often evolutionarily conserved and their precursors can be folded into stem-loop hairpins, many miRNAs have been predicted. Yet experimental confirmation is difficult since miRNA expression is often specific to particular tissues and developmental stages.

Results

Analysis of 29 human and 230 mouse longSAGE libraries revealed the expression of 22 known and 10 predicted mammalian miRNAs. Most were detected in embryonic tissues. Four SAGE tags detected in human embryonic stem cells specifically match a cluster of four human miRNAs (mir-302a, b, c&d) known to be expressed in embryonic stem cells. LongSAGE data also suggest the existence of a mouse homolog of human and rat mir-493.

Conclusion

The observation that some orphan longSAGE tags uniquely match miRNA precursors provides information about the expression of some known and predicted miRNAs.
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4.
5.

Background

MicroRNAs (miRNAs) are a large class of non-coding RNAs with important functions wide spread in animals, plants and viruses. Studies showed that an RNase III family member called Drosha recognizes most miRNAs, initiates their processing and determines the mature miRNAs. The Drosha processing sites identification will shed some light on both miRNA identification and understanding the mechanism of Drosha processing.

Methods

We developed a computational method for Drosha processing site predicting, named as DroshaPSP, which employs a two-layer mathematical model to integrate structure feature in the first layer and sequence features in the second layer. The performance of DroshaPSP was estimated by 5-fold cross-validation and measured by ACC (accuracy), Sn (sensitivity), Sp (specificity), P (precision) and MCC (Matthews correlation coefficient).

Results

The results of testing DroshaPSP on the miRNA data of Drosophila melanogaster indicated that the Sn, Sp, and MCC thereof reach to 0.86, 0.99 and 0.86 respectively.

Conclusions

We found the Shannon entropy, a chemical kinetics feature, is a significant feature in telling the true sites among the nearby sites and improving the performance.
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6.

Background

MicroRNAs (miRNAs) regulate many biological processes by post-translational gene silencing. Analysis of miRNA expression profiles is a reliable method for investigating particular biological processes due to the stability of miRNA and the development of advanced sequencing methods. However, this approach is limited by the broad specificity of miRNAs, which may target several mRNAs.

Result

In this study, we developed a method for comprehensive annotation of miRNA array or deep sequencing data for investigation of cellular biological effects. Using this method, the specific pathways and biological processes involved in Alzheimer’s disease were predicted with high correlation in four independent samples. Furthermore, this method was validated for evaluation of cadmium telluride (CdTe) nanomaterial cytotoxicity. As a result, apoptosis pathways were selected as the top pathways associated with CdTe nanoparticle exposure, which is consistent with previous studies.

Conclusions

Our findings contribute to the validation of miRNA microarray or deep sequencing results for early diagnosis of disease and evaluation of the biological safety of new materials and drugs.
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7.

Background

Individuals at risk of rheumatoid arthritis (RA) demonstrate systemic autoimmunity in the form of anti-citrullinated peptide antibodies (ACPA). MicroRNAs (miRNAs) are implicated in established RA. This study aimed to (1) compare miRNA expression between healthy individuals and those at risk of and those that develop RA, (2) evaluate the change in expression of miRNA from “at-risk” to early RA and (3) explore whether these miRNAs could inform a signature predictive of progression from “at-risk” to RA.

Methods

We performed global profiling of 754 miRNAs per patient on a matched serum sample cohort of 12 anti-cyclic citrullinated peptide (CCP)?+?“at-risk” individuals that progressed to RA. Each individual had a serum sample from baseline and at time of detection of synovitis, forming the matched element. Healthy controls were also studied. miRNAs with a fold difference/fold change of four in expression level met our primary criterion for selection as candidate miRNAs. Validation of the miRNAs of interest was conducted using custom miRNA array cards on matched samples (baseline and follow up) in 24 CCP+ individuals; 12 RA progressors and 12 RA non-progressors.

Results

We report on the first study to use matched serum samples and a comprehensive miRNA array approach to identify in particular, three miRNAs (miR-22, miR-486-3p, and miR-382) associated with progression from systemic autoimmunity to RA inflammation. MiR-22 demonstrated significant fold difference between progressors and non-progressors indicating a potential biomarker role for at-risk individuals.

Conclusions

This first study using a cohort with matched serum samples provides important mechanistic insights in the transition from systemic autoimmunity to inflammatory disease for future investigation, and with further evaluation, might also serve as a predictive biomarker.
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8.

Background

Although, substantial experimental evidence related to diagnosis and treatment of pediatric central nervous system (CNS) neoplasms have been demonstrated, the understanding of the etiology and pathogenesis of the disease remains scarce. Recent microRNA (miRNA)-based research reveals the involvement of miRNAs in various aspects of CNS development and proposes that they might compose key molecules underlying oncogenesis. The current study evaluated miRNA differential expression detected between pediatric embryonal brain tumors and normal controls to characterize candidate biomarkers related to diagnosis, prognosis and therapy.

Methods

Overall, 19 embryonal brain tumors; 15 Medulloblastomas (MBs) and 4 Atypical Teratoid/Rabdoid Tumors (AT/RTs) were studied. As controls, 13 samples were used; The First-Choice Human Brain Reference RNA and 12 samples from deceased children who underwent autopsy and were not present with any brain malignancy. RNA extraction was carried out using the Trizol method, whilst miRNA extraction was performed with the mirVANA miRNA isolation kit. The experimental approach included miRNA microarrays covering 1211 miRNAs. Quantitative Real-Time Polymerase Chain Reaction was performed to validate the expression profiles of miR-34a and miR-601 in all 32 samples initially screened with miRNA microarrays and in an additional independent cohort of 30 patients (21MBs and 9 AT/RTs). Moreover, meta-analyses was performed in total 27 embryonal tumor samples; 19 MBs, 8 ATRTs and 121 control samples. Twelve germinomas were also used as an independent validation cohort. All deregulated miRNAs were correlated to patients’ clinical characteristics and pathological measures.

Results

In several cases, there was a positive correlation between individual miRNA expression levels and laboratory or clinical characteristics. Based on that, miR-601 could serve as a putative tumor suppressor gene, whilst miR-34a as an oncogene. In general, miR-34a demonstrated oncogenic roles in all pediatric embryonal CNS neoplasms studied.

Conclusions

Deeper understanding of the aberrant miRNA expression in pediatric embryonal brain tumors might aid in the development of tumor-specific miRNA signatures, which could potentially afford promising biomarkers related to diagnosis, prognosis and patient targeted therapy.
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9.

Background

High-grade serous ovarian carcinoma (HG-SOC) is the dominant tumor histologic type in epithelial ovarian cancers, exhibiting highly aberrant microRNA expression profiles and diverse pathways that collectively determine the disease aggressiveness and clinical outcomes. However, the functional relationships between microRNAs, the common pathways controlled by the microRNAs and their prognostic and therapeutic significance remain poorly understood.

Methods

We investigated the gene expression patterns of microRNAs in the tumors of 582 HG-SOC patients to identify prognosis signatures and pathways controlled by tumor miRNAs. We developed a variable selection and prognostic method, which performs a robust selection of small-sized subsets of the predictive features (e.g., expressed microRNAs) that collectively serves as the biomarkers of cancer risk and progression stratification system, interconnecting these features with common cancer-related pathways.

Results

Across different cohorts, our meta-analysis revealed two robust and unbiased miRNA-based prognostic classifiers. Each classifier reproducibly discriminates HG-SOC patients into high-confidence low-, intermediate- or high-prognostic risk subgroups with essentially different 5-year overall survival rates of 51.6-85%, 20-38.1%, and 0-10%, respectively. Significant correlations of the risk subgroup’s stratification with chemotherapy treatment response were observed. We predicted specific target genes involved in nine cancer-related and two oocyte maturation pathways (neurotrophin and progesterone-mediated oocyte maturation), where each gene can be controlled by more than one miRNA species of the distinct miRNA HG-SOC prognostic classifiers.

Conclusions

We identified robust and reproducible miRNA-based prognostic subsets of the of HG-SOC classifiers. The miRNAs of these classifiers could control nine oncogenic and two developmental pathways, highlighting common underlying pathologic mechanisms and perspective targets for the further development of a personalized prognosis assay(s) and the development of miRNA-interconnected pathway-centric and multi-agent therapeutic intervention.
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10.

Background

Schwannoma arising from peripheral nervous sheaths is a benign tumor.

Methods

To evaluate cell cytotoxicity, (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) tetrazolium reduction and terminal deoxynucleotidyltransferase UTP nick-end labeling (TUNEL) assays were used. A microRNA (miRNA) array was used to identify the miRNAs involved in curcumin-induced apoptosis. To examine miRNA expression, quantitative RT-PCR was used.

Results

In this study, curcumin exerted cellular cytotoxicity against RT4 schwannoma cells, with an increase in TUNEL-positive cells. Curcumin also activated the expression of apoptotic proteins, such as polyADP ribose polymerase, caspase-3, and caspase-9. The miRNA array revealed that seven miRNAs (miRNA 350, miRNA 17-2-3p, let 7e-3p, miRNA1224, miRNA 466b-1-3p, miRNA 18a-5p, and miRNA 322-5p) were downregulated following treatment with both 10 and 20 μM curcumin in RT4 cells, while four miRNAs (miRNA122-5p, miRNA 3473, miRNA182, and miRNA344a-3p) were upregulated. Interestingly, transfection with a miRNA 344a-3p mimic downregulated the mRNA expression of Bcl2 and upregulated that of Bax, Curcumin treatment in RT 4 cells also reduced the mRNA expression of Bcl2 and enhanced expression of Bax, Overexpression of miRNA344a-3p mimic combined with curcumin treatment activated the expression of apoptotic proteins, including procaspase-9 and cleaved caspase-3 while inhibition of miRNA 344a-3p using miR344a-3p inhibitor repressed cleaved caspase-3 and -9 in curcumin treated RT-4 cells compared to control.

Conclusions

Our findings demonstrate that curcumin induces apoptosis in schwannoma cells via miRNA 344a-3p. Thus, curcumin may serve as a potent therapeutic agent for the treatment of schwannoma.
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11.
12.

Background

Epstein-Barr virus (EBV) was the first virus identified to encode microRNAs (miRNAs). Both of viral and human cellular miRNAs are important in EBV infection. However, the dynamic expression profile of miRNAs during primary EBV infection was unknown. This study aimed to investigate the dynamic expression profile of viral and cellular miRNAs in infectious mononucleosis (IM) caused by primary EBV infection.

Methods

The levels of viral and cellular miRNAs were measured in fifteen pediatric IM patients at three different time-points. Fifteen healthy children who were seropositive for EBV were enrolled in the control group. Relative expression levels of miRNAs were detected by quantitative real-time PCR (qPCR) assay.

Results

EBV-miR-BHRF1-1, 1-2-3P, miR-BART13-1, 19-3p, 11-3P, 12–1, and 16–1 in IM patients of early phase were significantly higher than in healthy children. Most cellular miRNAs of B cells, such as hsa-miR-155-5p, ?34a-5p, ?18b-5p, ?181a-5p, and ?142-5p were up-regulated; while most of cellular miRNAs of CD8?+?T cells, such as hsa-miR-223, ?29c-3p, ?181a, ?200a-3p, miR-155-5p, ?146a, and ?142-5p were down-regulated in IM patients. With disease progression, nearly all of EBV-miRNAs decreased, especially miR-BHRF1, but at a slower rate than EBV DNA loads. Most of the cellular miRNAs of B cells, including hsa-miR-134-5p, ?18b-5p, ?34a-5p, and -196a-5p increased with time. However, most of the cellular miRNAs of CD8?+?T cells, including hsa-let-7a-5p, ?142-3p, ?142-5p, and ?155-5p decreased with time. Additionally, hsa-miR-155-5p of B cells and hsa-miR-18b-5p of CD8+ T cells exhibited a positive correlation with miR-BHRF1-2-5P and miR-BART2-5P (0.96?≤?r?≤?0.99, P?<?0.05). Finally, hsa-miR-181a-5p of B cells had positive correlation with miR-BART4-3p, 4-5P, 16–1, and 22 (0.97?≤?r?≤?0.99, P?<?0.05).

Conclusions

Our study is the first to describe the expression profile of viral and cellular miRNAs in IM caused by primary EBV infection. These results might be the basis of investigating the pathogenic mechanism of EBV-related diseases and bring new insights into their diagnosis and treatment.
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13.
14.

Background

Transgenic expression of small RNAs is a prevalent approach in agrobiotechnology for the global enhancement of plant foods. Meanwhile, emerging studies have, on the one hand, emphasized the potential of transgenic microRNAs (miRNAs) as novel dietary therapeutics and, on the other, suggested potential food safety issues if harmful miRNAs are absorbed and bioactive. For these reasons, it is necessary to evaluate the bioavailability of transgenic miRNAs in genetically modified crops.

Results

As a pilot study, two transgenic Arabidopsis lines ectopically expressing unique miRNAs were compared and contrasted with the plant bioavailable small RNA MIR2911 for digestive stability and serum bioavailability. The expression levels of these transgenic miRNAs in Arabidopsis were found to be comparable to that of MIR2911 in fresh tissues. Assays of digestive stability in vitro and in vivo suggested the transgenic miRNAs and MIR2911 had comparable resistance to degradation. Healthy mice consuming diets rich in Arabidopsis lines expressing these miRNAs displayed MIR2911 in the bloodstream but no detectable levels of the transgenic miRNAs.

Conclusions

These preliminary results imply digestive stability and high expression levels of miRNAs in plants do not readily equate to bioavailability. This initial work suggests novel engineering strategies be employed to enhance miRNA bioavailability when attempting to use transgenic foods as a delivery platform.
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15.

Background

Regulation mechanisms between miRNAs and genes are complicated. To accomplish a biological function, a miRNA may regulate multiple target genes, and similarly a target gene may be regulated by multiple miRNAs. Wet-lab knowledge of co-regulating miRNAs is limited. This work introduces a computational method to group miRNAs of similar functions to identify co-regulating miRNAsfrom a similarity matrix of miRNAs.

Results

We define a novel information content of gene ontology (GO) to measure similarity between two sets of GO graphs corresponding to the two sets of target genes of two miRNAs. This between-graph similarity is then transferred as a functional similarity between the two miRNAs. Our definition of the information content is based on the size of a GO term’s descendants, but adjusted by a weight derived from its depth level and the GO relationships at its path to the root node or to the most informative common ancestor (MICA). Further, a self-tuning technique and the eigenvalues of the normalized Laplacian matrix are applied to determine the optimal parameters for the spectral clustering of the similarity matrix of the miRNAs.

Conclusions

Experimental results demonstrate that our method has better clustering performance than the existing edge-based, node-based or hybrid methods. Our method has also demonstrated a novel usefulness for the function annotation of new miRNAs, as reported in the detailed case studies.
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16.

Background

Current knowledge and data on miRNA-lncRNA interactions is still limited and little effort has been made to predict target lncRNAs of miRNAs. Accumulating evidences suggest that the interaction patterns between lncRNAs and miRNAs are closely related to relative expression level, forming a titration mechanism. It could provide an effective approach for characteristic feature extraction. In addition, using the coding non-coding co-expression network and sequence data could also help to measure the similarities among miRNAs and lncRNAs. By mathematically analyzing these types of similarities, we come up with two findings that (i) lncRNAs/miRNAs tend to collaboratively interact with miRNAs/lncRNAs of similar expression profiles, and vice versa, and (ii) those miRNAs interacting with a cluster of common target genes tend to jointly target at the common lncRNAs.

Methods

In this work, we developed a novel group preference Bayesian collaborative filtering model called GBCF for picking up a top-k probability ranking list for an individual miRNA or lncRNA based on the known miRNA-lncRNA interaction network.

Results

To evaluate the effectiveness of GBCF, leave-one-out and k-fold cross validations as well as a series of comparison experiments were carried out. GBCF achieved the values of area under ROC curve of 0.9193, 0.8354+/??0.0079, 0.8615+/??0.0078, and 0.8928+/??0.0082 based on leave-one-out, 2-fold, 5-fold, and 10-fold cross validations respectively, demonstrating its reliability and robustness.

Conclusions

GBCF could be used to select potential lncRNA targets of specific miRNAs and offer great insights for further researches on ceRNA regulation network.
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17.
18.
19.

Background

MicroRNA (miRNA) plays a key role in regulation mechanism of human biological processes, including the development of disease and disorder. It is necessary to identify potential miRNA biomarkers for various human diseases. Computational prediction model is expected to accelerate the process of identification.

Results

Considering the limitations of previously proposed models, we present a novel computational model called FMSM. It infers latent miRNA biomarkers involved in the mechanism of various diseases based on the known miRNA-disease association network, miRNA expression similarity, disease semantic similarity and Gaussian interaction profile kernel similarity. FMSM achieves reliable prediction performance in 5-fold and leave-one-out cross validations with area under ROC curve (AUC) values of 0.9629+/??0.0127 and 0.9433, respectively, which outperforms the state-of-the-art competitors and classical algorithms. In addition, 19 of top 25 predicted miRNAs have been validated to have associations with Colonic Neoplasms in case study.

Conclusions

A factored miRNA similarity based model and miRNA expression similarity substantially contribute to the well-performing prediction. The list of the predicted most latent miRNA biomarkers of various human diseases is publicized. It is anticipated that FMSM could serve as a useful tool guiding the future experimental validation for those promising miRNA biomarker candidates.
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20.

Background

With the given diversity and abundance of several targets of miRNAs, they functionally appear to interact with several elements of the multiple cellular networks to maintain physiologic homeostasis. They can function as tumor suppressors or oncogenes, whose under or overexpression has both diagnostic and prognostic significance in various cancers while being implicated as prospective regulators of age-related disorders (ARD) as well. Establishing a concatenate between ARD and cancers by looking into the insights of the shared miRNAs may have a practical relevance.

Methods

In the present work, we performed network analysis of miRNA-disease association and miRNA-target gene interaction to prioritize miRNAs that play significant roles in the manifestation of cancer as well as ARD. Also, we developed a repository that stores miRNAs common to both ARD and cancers along with their target genes.

Results

We have comprehensively curated all miRNAs that we found to be shared in both the diseases in the human genome and established a database, miRACA (Database for microRNAs Associated with Cancers and ARD) that currently houses information of 1648 miRNAs that are significantly associated with 38 variants supported with pertinent data. It has been made available online at http://genomeinformatics.dtu.ac.in/miraca/ for easy retrieval and utilization of data by the scientific community.

Conclusion

To the best of our knowledge, our database is the first attempt at compilation of such data. We believe this work may serve as a significant resource and facilitate the analysis of miRNA regulatory mechanisms shared between cancers and ARD to apprehend disease etiology.
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