Independent component and pathway-based analysis of miRNA-regulated gene expression in a model of type 1 diabetes

Machine learning integrated ensemble of feature selection methods followed by survival analysis for predicting breast cancer subtype specific miRNA biomarkers

Breast cancer is the second leading cancer type among females. In this regard, it is found that microRNAs play an important role by regulating the gene expressions at the post-transcriptional phase. However, identification of the most influencing miRNAs in breast cancer subtypes is a challenging task, while the recent advancement in Next Generation Sequencing techniques allows analyzing high throughput expression data of miRNAs. Thus, we have conducted this research with the help of NGS data of breast cancer in order to identify the most significant miRNA biomarkers. The selected miRNA biomarkers are highly associated with the multiple breast cancer subtypes. For this purpose, a two-phase technique, called Machine Learning Integrated Ensemble of Feature Selection Methods, followed by survival analysis, is proposed. In the first phase, we have selected the best among seven machine learning techniques based on classification accuracy using the entire set of features (in this case miRNAs). Subsequently, eight different feature selection methods are used separately in order to rank the features and validate each set of top features using the selected machine learning technique by considering a multi-class classification task of the breast cancer subtypes. In the second phase, based on the classification accuracy values, the top features from each feature selection method are considered to make an ensemble to provide further categorization of the miRNAs as 8*, 7* up to 1*. The 8* miRNAs provide the highest average classification accuracy of 86% after 10-fold cross-validation. Thereafter, 27 miRNAs are identified from the list that is confined within 8* to 4* miRNAs based on their importance in survival for breast cancer subtypes using Cox regression based survival analysis. Moreover, expression analysis, regulatory network analysis, protein-protein interaction analysis, KEGG pathway and gene ontology enrichment analysis are performed in order to validate biological significance of the proposed solution. Additionally, we have prepared a miRNA-protein-drug interaction network to identify possible drug for the selected miRNAs. Thus, our findings may be considered during a clinical trial for the treatment of breast cancer patients.

MicroRNA-296-5p promotes healing of diabetic wound by targeting sodium-glucose transporter 2 (SGLT2)

BACKGROUND

Diabetic wounds are refractory and very difficult to heal. We aimed to use miRNA to identify novel and specific molecular markers for diabetes mellitus (DM) diagnosis and treatment.

METHODS

The expression level of miR-296-5p was determined in tissue samples of 12 DM patients. The effect of miR-296-5p on proliferation of β-cells was examined using Cell Counting Kit-8 (CCK-8) and colony formation assay. The effect of miR-296-5p on cell cycle progression was analysed using flow cytometry. The target gene was verified using luciferase reporter assay. A rat diabetes model was used to assess the effect of miR-296-5p in vivo.

RESULTS

Overexpression of miR-296-5p suppressed cell proliferation, arrested cell cycle progression, and increased the healing rate of diabetic wounds both in vivo and in vitro. TargetScan analysis results showed that miR-296-5p is a direct regulator of SGLT2.

CONCLUSIONS

miR-296-5p can increase the healing rate of diabetic wounds and may be an effective molecular tool in DM diagnosis and therapy.

Serum microRNA Profiles Serve as Novel Biomarkers for Autoimmune Diseases

Autoimmune diseases involve a complex dysregulation of immunity. Autoimmune diseases include many members [e.g., rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE)], and most of them are classified according to what organs and tissues are targeted by the damaging immune response. Many studies have focused on finding specific biomarkers for single autoimmune diseases, but so far, there are no universal biomarkers for detecting almost all autoimmune diseases. Serum miRNAs have served as potential biomarkers for detecting various diseases. The purpose of this study was to find a universal biomarker for diagnosing autoimmune diseases. Regulatory T cells (Tregs) play a crucial role in protecting an individual from autoimmunity, and depletion of Tregs in mice is considered a representative animal model of autoimmune disease. Two mouse models for Treg depletion, in which Treg was depleted by CD25mAb (in C57 mice) or by diphtheria toxin (DT) (in Foxp3^DTR mice), were investigated, and 381 miRNAs were identified in the serum of mice with Treg depletion. A distinctive circulating miRNA profile was identified in Treg-depleted mice and in patients with autoimmune disease. QRT-PCR confirmation and ROC curve analysis determined that six miRNAs (miR-551b, miR-448, miR-9, miR-124, miR-148, and miR-34c) in the Treg-depleted mouse models and three miRNAs [miR-551b (specificity 73.5%, sensitivity 88.4%), miR-448 (specificity 82.4%, sensitivity 91.3%), and miR-124 (specificity 76.5%, sensitivity 91.3%)] in patients with RA, SLE, Sjogren's syndrome (SS), and ulcerative colitis (UC) could serve as valuable specific biomarkers. These circulating miRNAs may represent potential universal biomarkers for autoimmune diseases diagnosis and prognosis.

MicroRNAs and histone deacetylase inhibition-mediated protection against inflammatory β-cell damage

Inflammatory β-cell failure contributes to type 1 and type 2 diabetes pathogenesis. Pro-inflammatory cytokines cause β-cell dysfunction and apoptosis, and lysine deacetylase inhibitors (KDACi) prevent β-cell failure in vitro and in vivo, in part by reducing NF-κB transcriptional activity. We investigated the hypothesis that the protective effect of KDACi involves transcriptional regulation of microRNAs (miRs), potential new targets in diabetes treatment. Insulin-producing INS1 cells were cultured with or without the broad-spectrum KDACi Givinostat, prior to exposure to the pro-inflammatory cytokines IL-1β and IFN-γ for 6 h or 24 h, and miR expression was profiled with miR array. Thirteen miRs (miR-7a-2-3p, miR-29c-3p, miR-96-5p, miR-101a-3p, miR-140-5p, miR-146a-5p, miR-146b-5p, miR-340-5p, miR-384-5p, miR-455-5p, miR-466b-2-3p, miR-652-5p, and miR-3584-5p) were regulated by both cytokines and Givinostat, and nine were examined by qRT-PCR. miR-146a-5p was strongly regulated by cytokines and KDACi and was analyzed further. miR-146a-5p expression was induced by cytokines in rat and human islets. Cytokine-induced miR-146a-5p expression was specific for INS1 and β-TC3 cells, whereas α-TC1 cells exhibited a higher basal expression. Transfection of INS1 cells with miR-146a-5p reduced cytokine signaling, including the activity of NF-κB and iNOS promoters, as well as NO production and protein levels of iNOS and its own direct targets TNF receptor associated factor 6 (TRAF6) and interleukin-1 receptor-associated kinase 1 (IRAK1). miR-146a-5p was elevated in the pancreas of diabetes-prone BB-DP rats at diabetes onset, suggesting that miR-146a-5p could play a role in type 1 diabetes development. The miR array of cytokine-exposed INS1 cells rescued by KDACi revealed several other miRs potentially involved in cytokine-induced β-cell apoptosis, demonstrating the strength of this approach.

Determining the optimal number of independent components for reproducible transcriptomic data analysis

BACKGROUND

Independent Component Analysis (ICA) is a method that models gene expression data as an action of a set of statistically independent hidden factors. The output of ICA depends on a fundamental parameter: the number of components (factors) to compute. The optimal choice of this parameter, related to determining the effective data dimension, remains an open question in the application of blind source separation techniques to transcriptomic data.

RESULTS

Here we address the question of optimizing the number of statistically independent components in the analysis of transcriptomic data for reproducibility of the components in multiple runs of ICA (within the same or within varying effective dimensions) and in multiple independent datasets. To this end, we introduce ranking of independent components based on their stability in multiple ICA computation runs and define a distinguished number of components (Most Stable Transcriptome Dimension, MSTD) corresponding to the point of the qualitative change of the stability profile. Based on a large body of data, we demonstrate that a sufficient number of dimensions is required for biological interpretability of the ICA decomposition and that the most stable components with ranks below MSTD have more chances to be reproduced in independent studies compared to the less stable ones. At the same time, we show that a transcriptomics dataset can be reduced to a relatively high number of dimensions without losing the interpretability of ICA, even though higher dimensions give rise to components driven by small gene sets.

CONCLUSIONS

We suggest a protocol of ICA application to transcriptomics data with a possibility of prioritizing components with respect to their reproducibility that strengthens the biological interpretation. Computing too few components (much less than MSTD) is not optimal for interpretability of the results. The components ranked within MSTD range have more chances to be reproduced in independent studies.

T2DiACoD: A Gene Atlas of Type 2 Diabetes Mellitus Associated Complex Disorders

We performed integrative analysis of genes associated with type 2 Diabetes Mellitus (T2DM) associated complications by automated text mining with manual curation and also gene expression analysis from Gene Expression Omnibus. They were analysed for pathogenic or protective role, trends, interaction with risk factors, Gene Ontology enrichment and tissue wise differential expression. The database T2DiACoD houses 650 genes, and 34 microRNAs associated with T2DM complications. Seven genes AGER, TNFRSF11B, CRK, PON1, ADIPOQ, CRP and NOS3 are associated with all 5 complications. Several genes are studied in multiple years in all complications with high proportion in cardiovascular (75.8%) and atherosclerosis (51.3%). T2DM Patients' skeletal muscle tissues showed high fold change in differentially expressed genes. Among the differentially expressed genes, VEGFA is associated with several complications of T2DM. A few genes ACE2, ADCYAP1, HDAC4, NCF1, NFE2L2, OSM, SMAD1, TGFB1, BDNF, SYVN1, TXNIP, CD36, CYP2J2, NLRP3 with details of protective role are catalogued. Obesity is clearly a dominant risk factor interacting with the genes of T2DM complications followed by inflammation, diet and stress to variable extents. This information emerging from the integrative approach used in this work could benefit further therapeutic approaches. The T2DiACoD is available at www.http://t2diacod.igib.res.in/ .

Quantification of MicroRNAs in human aqueous humor by miRFLP assay

MiRNAs are expressed in a tissue-specific fashion in the eyes and changes in miRNAs levels in aqueous humor (AH) may reflect the function of the eye and eye disease. Due to the low concentration of total miRNA in human aqueous humor, high volume of sample is required for RNA extraction prior to routine quantification such as RT-qPCR. However, limited volume of AH could be collected through surgery because of the characteristic of the eye. In addition, inefficiency of RNA-extraction kits could affect target miRNA quantification dramatically. AH-direct miRFLP assay was developed for quantification of target miRNAs in human aqueous humor samples. For the first time, accurate miRNA quantification in human AH was achieved with microliter scale sample loading. Higher copy numbers of target miRNAs were obtained in direct detection than in RNA-extraction solution. It indicates that AH-direct miRFLP assay was able to quantify target miRNAs more accurately with no requirement for RNA-extraction to avoid sampling variability.

An independent component analysis confounding factor correction framework for identifying broad impact expression quantitative trait loci

Genome-wide expression Quantitative Trait Loci (eQTL) studies in humans have provided numerous insights into the genetics of both gene expression and complex diseases. While the majority of eQTL identified in genome-wide analyses impact a single gene, eQTL that impact many genes are particularly valuable for network modeling and disease analysis. To enable the identification of such broad impact eQTL, we introduce CONFETI: Confounding Factor Estimation Through Independent component analysis. CONFETI is designed to address two conflicting issues when searching for broad impact eQTL: the need to account for non-genetic confounding factors that can lower the power of the analysis or produce broad impact eQTL false positives, and the tendency of methods that account for confounding factors to model broad impact eQTL as non-genetic variation. The key advance of the CONFETI framework is the use of Independent Component Analysis (ICA) to identify variation likely caused by broad impact eQTL when constructing the sample covariance matrix used for the random effect in a mixed model. We show that CONFETI has better performance than other mixed model confounding factor methods when considering broad impact eQTL recovery from synthetic data. We also used the CONFETI framework and these same confounding factor methods to identify eQTL that replicate between matched twin pair datasets in the Multiple Tissue Human Expression Resource (MuTHER), the Depression Genes Networks study (DGN), the Netherlands Study of Depression and Anxiety (NESDA), and multiple tissue types in the Genotype-Tissue Expression (GTEx) consortium. These analyses identified both cis-eQTL and trans-eQTL impacting individual genes, and CONFETI had better or comparable performance to other mixed model confounding factor analysis methods when identifying such eQTL. In these analyses, we were able to identify and replicate a few broad impact eQTL although the overall number was small even when applying CONFETI. In light of these results, we discuss the broad impact eQTL that have been previously reported from the analysis of human data and suggest that considerable caution should be exercised when making biological inferences based on these reported eQTL.

MicroRNAs Involvement in Renal Pathophysiology: A Bird's Eye View

MicroRNAs (miRNAs) are known to suppress gene expression by binding to messenger RNAs and in turn regulate different pathophysiological processes. Transforming growth factor-β, mitogen-activated protein kinase signaling, and Wnt signaling-like major pathways associated with miRNAs are involved with kidney diseases. The discovery of miRNAs has provided new insights into kidney pathologies and may provide effective therapeutic strategies. Research has demonstrated the role of miRNAs in a variety of kidney diseases including diabetic nephropathy, lupus nephritis, hypertension, nephritic syndrome, acute kidney injury, renal cell carcinoma, and renal fibrosis. miRNAs are implicated as playing a role in these diseases due to their role in apoptosis, cell proliferation, differentiation, and development. As miRNAs have been detected in a stable condition in different biological fluids, they have the potential to be tools to study the pathogenesis of human diseases with a great potential to be used in disease diagnosis and prognosis. The purpose of this review is to examine the role of miRNA in kidney disease.

MicroRNAs as regulators of beta-cell function and dysfunction

In the last decade, there has been an explosion in both the number of and knowledge about miRNAs associated with both type 1 and type 2 diabetes. Even though we are presently in the initial stages of understanding how this novel class of posttranscriptional regulators are involved in diabetes, recent studies have demonstrated that miRNAs are important regulators of the islet transcriptome, controlling apoptosis, differentiation and proliferation, as well as regulating unique islet and beta-cell functions and pathways such as insulin expression, processing and secretion. Furthermore, a large number of miRNAs have been linked to diabetogenic processes induced by elevated levels of glucose, free fatty acids and inflammatory cytokines. Thus, miRNAs are novel therapeutic targets with the potential of protecting the beta-cell, and there is proof of principle that miRNA antagonists, so-called antagomirs, are effective in vivo for other disorders. miRNAs are exported out of cells in exosomes, raising the intriguing possibility of cell-to-cell communication between distant tissues via miRNAs and that miRNAs can be used as biomarkers of beta-cell function, mass and survival. The purpose of this review is to provide a status on how miRNAs control beta-cell function and viability in health and disease.

Alteration in Inflammation-related miR-146a Expression in NF-KB Signaling Pathway in Diabetic Rat Hippocampus

PURPOSE

The purpose of the present study is to evaluate the expression of miR-146a gene, its adaptor genes (TRAF6, NF-KB, and IRAK1), and possible changes in the cellular signaling pathway in diabetic hippocampus tissue.

METHODS

Male Sprague-Dawley rats are randomly selected and divided into control and diabetic (n=6) groups. Diabetes induced by the single-dose injection of nicotinamide [110 mg/kg, (i.p.)], 15 min before streptozotocin (50 mg/kg; i.p.) in 12-h fasted rats. The rats are kept at the laboratory for two months. After anaesthetization, hippocampus of the rats was removed in order to measure the expression of miR-146a, NFK-B, IRAK1, and TRAF6 genes using real-time PCR and activity of NF-KB as well as amount of apoptosis rate using ELISA.

RESULTS

The results indicated a reduction in expression of miR-146a and an increase in expression of IRAK1, NF-KB, and TRAF6 genes in the hippocampus of diabetic rats compared to control. Also it reveals an increase in the activity of NF-KB and apoptosis rate in the hippocampus of diabetic rats.

CONCLUSION

Our results report the probability that reduction of miR-146a expression in the negative feedback loop between miR-146a and NF-KB increases NF-kB expression and thus intensifies inflammation and apoptosis in hippocampus.

MicroRNAs: Novel Players in the Dialogue between Pancreatic Islets and Immune System in Autoimmune Diabetes

MicroRNAs are small noncoding RNA molecules that regulate gene expression in all cell types. Therefore, these tiny noncoding RNA molecules are involved in a wide range of biological processes, exerting functional effects at cellular, tissue, and organ level. In pancreatic islets of Langerhans, including beta-cells, microRNAs are involved in cell differentiation as well as in insulin secretion, while in immune cells they have been shown to play pivotal roles in development, activation, and response to antigens. Indeed, it is not surprising that microRNA alterations can lead to the development of several diseases, including type 1 diabetes (T1D). Type 1 diabetes is the result of a selective autoimmune destruction of insulin-producing beta-cells, characterized by islet inflammation (insulitis), which leads to chronic hyperglycemia. Given the growing importance of microRNA in the pathophysiology of T1D, the aim of this review is to summarize the most recent data on the potential involvement of microRNAs in autoimmune diabetes. Specifically, we will focus on three different aspects: (i) microRNAs as regulators of immune homeostasis in autoimmune diabetes; (ii) microRNA expression in pancreatic islet inflammation; (iii) microRNAs as players in the dialogue between the immune system and pancreatic endocrine cells.

Pathway analysis from lists of microRNAs: common pitfalls and alternative strategy

MicroRNAs (miRNAs) are involved in the regulation of gene expression at a post-transcriptional level. As such, monitoring miRNA expression has been increasingly used to assess their role in regulatory mechanisms of biological processes. In large scale studies, once miRNAs of interest have been identified, the target genes they regulate are often inferred using algorithms or databases. A pathway analysis is then often performed in order to generate hypotheses about the relevant biological functions controlled by the miRNA signature. Here we show that the method widely used in scientific literature to identify these pathways is biased and leads to inaccurate results. In addition to describing the bias and its origin we present an alternative strategy to identify potential biological functions specifically impacted by a miRNA signature. More generally, our study exemplifies the crucial need of relevant negative controls when developing, and using, bioinformatics methods.

Downregulation of TrkA protein expression by miRNA‑92a promotes the proliferation and migration of human neuroblastoma cells

The aims of this study were to investigate the regulation of TrkA protein by micro (mi)RNA‑92a and its effect on the proliferation and migration of human neuroblastoma cells. The BE(2)‑M17 human neuroblastoma cell line was cultured and transfected with either miRNA‑92a mimics or miRNA‑92a inhibitors. The expression levels of miRNA‑92a and TrkA mRNA were detected by quantitative polymerase chain reaction prior and subsequent to transfection. TrkA protein was quantitatively detected by flow cytometry. The proliferation and migration of neuroblastoma cells were examined in vitro by Cell Counting Kit‑8 and Transwell assays. Transfection of BE(2)‑M17 cells with miRNA‑92a mimics produced significantly higher expression levels of miRNA‑92a compared with those in the same cells transfected with negative controls (NCs). Increased proliferation and migration of the cells was also observed. Transfection of BE(2)‑M17 cells with miRNA‑92a inhibitors resulted in significantly lower expression levels of miRNA‑92a when compared with those of the same cells transfected with NCs (P<0.01). This reduction in the miRNA‑92a expression levels was accompanied by reduced proliferation and migration of the cells. The expression levels of TrkA mRNA and protein after 24 h transfection with the miRNA‑92a mimics were significantly reduced when compared with the control (P<0.01). However, the expression levels of TrkA were significantly higher (P<0.01) after 48 h transfection with miRNA‑92a inhibitors when compared with the control. In conclusion, miRNA‑92a promoted the proliferation and migration of human neuroblastoma cells through downregulation of TrkA, which suggested that miRNA‑92a may be a potential target for human neuroblastoma treatment in the future.

Identifying common and specific microRNAs expressed in peripheral blood mononuclear cell of type 1, type 2, and gestational diabetes mellitus patients

Background

Regardless the regulatory function of microRNAs (miRNA), their differential expression pattern has been used to define miRNA signatures and to disclose disease biomarkers. To address the question of whether patients presenting the different types of diabetes mellitus could be distinguished on the basis of their miRNA and mRNA expression profiling, we obtained peripheral blood mononuclear cell (PBMC) RNAs from 7 type 1 (T1D), 7 type 2 (T2D), and 6 gestational diabetes (GDM) patients, which were hybridized to Agilent miRNA and mRNA microarrays. Data quantification and quality control were obtained using the Feature Extraction software, and data distribution was normalized using quantile function implemented in the Aroma light package. Differentially expressed miRNAs/mRNAs were identified using Rank products, comparing T1DxGDM, T2DxGDM and T1DxT2D. Hierarchical clustering was performed using the average linkage criterion with Pearson uncentered distance as metrics.

Results

The use of the same microarrays platform permitted the identification of sets of shared or specific miRNAs/mRNA interaction for each type of diabetes. Nine miRNAs (hsa-miR-126, hsa-miR-1307, hsa-miR-142-3p, hsa-miR-142-5p, hsa-miR-144, hsa-miR-199a-5p, hsa-miR-27a, hsa-miR-29b, and hsa-miR-342-3p) were shared among T1D, T2D and GDM, and additional specific miRNAs were identified for T1D (20 miRNAs), T2D (14) and GDM (19) patients. ROC curves allowed the identification of specific and relevant (greater AUC values) miRNAs for each type of diabetes, including: i) hsa-miR-1274a, hsa-miR-1274b and hsa-let-7f for T1D; ii) hsa-miR-222, hsa-miR-30e and hsa-miR-140-3p for T2D, and iii) hsa-miR-181a and hsa-miR-1268 for GDM. Many of these miRNAs targeted mRNAs associated with diabetes pathogenesis.

Conclusions

These results indicate that PBMC can be used as reporter cells to characterize the miRNA expression profiling disclosed by the different diabetes mellitus manifestations. Shared miRNAs may characterize diabetes as a metabolic and inflammatory disorder, whereas specific miRNAs may represent biological markers for each type of diabetes, deserving further attention.

Candidate genes for type 1 diabetes modulate pancreatic islet inflammation and β-cell apoptosis

Genome-wide association studies (GWAS) have identified more than 50 loci associated with genetic risk of type 1 diabetes (T1D). Several T1D candidate genes have been suggested or identified within these regions, but the molecular mechanisms by which they contribute to insulitis and β-cell destruction remain to be clarified. More than 60% of the T1D candidate genes are expressed in human pancreatic islets, suggesting that they contribute to T1D by regulating at least in part pathogenic mechanisms at the β-cell level. Recent studies by our group indicate that important genetically regulated pathways in β-cells include innate immunity and antiviral activity, involving RIG-like receptors (particularly MDA5) and regulators of type I IFNs (i.e. PTPN2 and USP18), and genes related to β-cell phenotype and susceptibility to pro-apoptotic stimuli (i.e. GLIS3). These observations reinforce the concept that the early pathogenesis of T1D is characterized by a dialogue between the immune system and pancreatic β-cells. This dialogue is probably influenced by polymorphisms in genes expressed at the β-cell and/or immune system level, leading to inadequate responses to environmental cues such as viral infections. Further studies are needed to clarify how these disease-associated variants affect pancreatic β-cell responses to inflammation and the subsequent triggering of autoimmune responses and progressive β-cell loss.

MicroRNAs: new insights into chronic childhood diseases

Chronic diseases are the major cause of morbidity and mortality worldwide and have shown increasing incidence rates among children in the last decades. Chronic illnesses in the pediatric population, even if well managed, affect social, psychological, and physical development and often limit education and active participation and increase the risk for health complications. The significant pediatric morbidity and mortality rates caused by chronic illnesses call for serious efforts toward better understanding of the pathogenesis of these disorders. Recent studies have shown the involvement of microRNAs (miRNAs) in various aspects of major pediatric chronic non-neoplastic diseases. This review focuses on the role of miRNAs in four major pediatric chronic diseases including bronchial asthma, diabetes mellitus, epilepsy and cystic fibrosis. We intend to emphasize the importance of miRNA-based research in combating these major disorders, as we believe this approach will result in novel therapies to aid securing normal development and to prevent disabilities in the pediatric population.

Context-specific microRNA function in developmental complexity

Since their discovery, microRNAs (miRNA) have been implicated in a vast array of biological processes in animals, from fundamental developmental functions including cellular proliferation and differentiation, to more complex and specialized roles such as long-term potentiation and synapse-specific modifications in neurons. This review recounts the history behind this paradigm shift, which has seen small non-coding RNA molecules coming to the forefront of molecular biology, and introduces their role in establishing developmental complexity in animals. The fundamental mechanisms of miRNA biogenesis and function are then considered, leading into a discussion of recent discoveries transforming our understanding of how these molecules regulate gene network behaviour throughout developmental and pathophysiological processes. The emerging complexity of this mechanism is also examined with respect to the influence of cellular context on miRNA function. This discussion highlights the absolute imperative for experimental designs to appreciate the significance of context-specific factors when determining what genes are regulated by a particular miRNA. Moreover, by establishing the timing, location, and mechanism of these regulatory events, we may ultimately understand the true biological function of a specific miRNA in a given cellular environment.

An integrative analysis of cellular contexts, miRNAs and mRNAs reveals network clusters associated with antiestrogen-resistant breast cancer cells

Background

A major goal of the field of systems biology is to translate genome-wide profiling data (e.g., mRNAs, miRNAs) into interpretable functional networks. However, employing a systems biology approach to better understand the complexities underlying drug resistance phenotypes in cancer continues to represent a significant challenge to the field. Previously, we derived two drug-resistant breast cancer sublines (tamoxifen- and fulvestrant-resistant cell lines) from the MCF7 breast cancer cell line and performed genome-wide mRNA and microRNA profiling to identify differential molecular pathways underlying acquired resistance to these important antiestrogens. In the current study, to further define molecular characteristics of acquired antiestrogen resistance we constructed an “integrative network”. We combined joint miRNA-mRNA expression profiles, cancer contexts, miRNA-target mRNA relationships, and miRNA upstream regulators. In particular, to reduce the probability of false positive connections in the network, experimentally validated, rather than prediction-oriented, databases were utilized to obtain connectivity. Also, to improve biological interpretation, cancer contexts were incorporated into the network connectivity.

Results

Based on the integrative network, we extracted “substructures” (network clusters) representing the drug resistant states (tamoxifen- or fulvestrant-resistance cells) compared to drug sensitive state (parental MCF7 cells). We identified un-described network clusters that contribute to antiestrogen resistance consisting of miR-146a, -27a, -145, -21, -155, -15a, -125b, and let-7s, in addition to the previously described miR-221/222.

Conclusions

By integrating miRNA-related network, gene/miRNA expression and text-mining, the current study provides a computational-based systems biology approach for further investigating the molecular mechanism underlying antiestrogen resistance in breast cancer cells. In addition, new miRNA clusters that contribute to antiestrogen resistance were identified, and they warrant further investigation.

Study on Genetic Variance of miR-541 in Type 1 Diabetes

Genetic susceptibility plays a key role in type 1 diabetes development. Because miR-541 gene was located within the associated chromosome loci and its target genes include the diabetes-associated gene neurogenin3, this study aimed to investigate whether miR-541 had type 1 diabetes-associated genetic variations. Type 1 diabetes children and healthy volunteers were recruited; direct sequencing was performed in initial 69 patients and 46 volunteers. We identified 1 reported SNP (rs12893725) and 3 novel genetic variations, for the candidate -404 G→T variation, restriction fragment length polymorphism (RFLP) was performed in total 247 diabetes children and 212 healthy volunteers, a different distribution trait of allele frequencies was found between the two groups, and further clinical analysis found no significant correlation between clinical parameter and genotypes among patients. In addition, by luciferase reporter assay, -404 was found to be within putative promoter region of pre-miR-541; although mutation of G→T has no effect on promoter activity, a significant secondary structure alteration may possibly influence its processing and transcription. In conclusion, we identified 3 novel genetic variations in putative promoter of miR-541 in type 1 diabetes patients; -404 G→T of miR-541 is a potential T1D-associated genetic variation.

MicroRNA in aqueous humor from patients with cataract

MicroRNAs (miRNAs) are small non-coding RNA molecules with regulatory function and marked tissue specificity that can modulate multiple gene targets. They have been detected in body fluids and are associated with various physiologic and pathologic processes. We analyzed aqueous humor (AH) from human subjects undergoing cataract surgery to establish the presence and relative quantities of known miRNAs. AH was collected from patients without known ocular diseases other than cataract and a normal systemic history. Quantitative real-time PCR in an array platform was used to detect known miRNAs present in the AH. Among the 264 miRNAs tested, 110 were present in the AH. The top 5 abundant miRNAs identified were miR-202, miR-193b, miR-135a, miR-365, and miR-376a. The presence of miRNAs in AH suggests that they may have functional roles in regulating target genes in tissues lining the anterior chamber. Further analysis of the AH miRNA population may identify potential gene targets and provide insights regarding their roles in AH regulation, glaucoma and anterior segment disease processes.

Gene network analysis of small molecules with autoimmune disease associated genes predicts a novel strategy for drug efficacy

Numerous genes/SNPs in autoimmune diseases (ADs) are identified through genome-wide association studies (GWAS) and likely to contribute in developing autoimmune phenotypes. Constructions of biologically meaningful pathways are necessary to determine how these genes interact with each other and with other small molecules to develop various complex AD phenotypes prior to beginning time-consuming rigorous experimentation. We have constructed biological pathways with genetically identified genes leading to shared AD phenotypes. Various environmental and endogenous factors interact with these AD associated genes suggesting their critical role in developing diseases and further association studies could be designed for assessing the role of these factors with risk allele in a specific gene. Additionally, existing drugs that have been used long before the identification of these genetically associated genes also interact with these newly associated genes. Thus advanced therapeutic strategies could be designed by grouping patients with risk allele(s) in particular genes that directly or closely interact with the specified drugs. This drug-susceptible gene network will not only increase our understanding about the additional molecular basis for effectiveness against these diseases but also indicate which drug could be more effective for those patients carrying risk allele(s) in that gene. Additionally, we have also identified several interlinking genes in the pathways that could be used for designing future association studies.

Context-specific microRNA analysis: identification of functional microRNAs and their mRNA targets

MicroRNAs (miRs) function primarily as post-transcriptional negative regulators of gene expression through binding to their mRNA targets. Reliable prediction of a miR's targets is a considerable bioinformatic challenge of great importance for inferring the miR's function. Sequence-based prediction algorithms have high false-positive rates, are not in agreement, and are not biological context specific. Here we introduce CoSMic (Context-Specific MicroRNA analysis), an algorithm that combines sequence-based prediction with miR and mRNA expression data. CoSMic differs from existing methods--it identifies miRs that play active roles in the specific biological system of interest and predicts with less false positives their functional targets. We applied CoSMic to search for miRs that regulate the migratory response of human mammary cells to epidermal growth factor (EGF) stimulation. Several such miRs, whose putative targets were significantly enriched by migration processes were identified. We tested three of these miRs experimentally, and showed that they indeed affected the migratory phenotype; we also tested three negative controls. In comparison to other algorithms CoSMic indeed filters out false positives and allows improved identification of context-specific targets. CoSMic can greatly facilitate miR research in general and, in particular, advance our understanding of individual miRs' function in a specific context.

miRSystem: an integrated system for characterizing enriched functions and pathways of microRNA targets

Background

Many prediction tools for microRNA (miRNA) targets have been developed, but inconsistent predictions were observed across multiple algorithms, which can make further analysis difficult. Moreover, the nomenclature of human miRNAs changes rapidly. To address these issues, we developed a web-based system, miRSystem, for converting queried miRNAs to the latest annotation and predicting the function of miRNA by integrating miRNA target gene prediction and function/pathway analyses.

Results

First, queried miRNA IDs were converted to the latest annotated version to prevent potential conflicts resulting from multiple aliases. Next, by combining seven algorithms and two validated databases, potential gene targets of miRNAs and their functions were predicted based on the consistency across independent algorithms and observed/expected ratios. Lastly, five pathway databases were included to characterize the enriched pathways of target genes through bootstrap approaches. Based on the enriched pathways of target genes, the functions of queried miRNAs could be predicted.

Conclusions

MiRSystem is a user-friendly tool for predicting the target genes and their associated pathways for many miRNAs simultaneously. The web server and the documentation are freely available at http://mirsystem.cgm.ntu.edu.tw/.

Synchronous detection of miRNAs, their targets and downstream proteins in transferred FFPE sections: applications in clinical and basic research

After discovering new miRNAs, it is often difficult to determine their targets and effects on downstream protein expression. In situ hybridization (ISH) and immunohistochemistry (IHC) are two commonly used methods for clinical diagnosis and basic research. We used an optimized technique that simultaneously detects miRNAs, their binding targets and corresponding proteins on transferred serial formalin fixed paraffin embedded (FFPE) sections from patients. Combined with bioinformatics, this method was used to validate the reciprocal expression of specific miRNAs and targets that were detected by ISH, as well as the expression of downstream proteins that were detected by IHC. A complete analysis was performed using a limited number of transferred serial FFPE sections that had been stored for 1-4 years at room temperature. Some sections had even been previously stained with H&E. We identified a miRNA that regulates epithelial ovarian cancer, along with its candidate target and related downstream protein. These findings were directly validated using sub-cellular components obtained from the same patient sample. In addition, the expression of Nephrin (a podocyte marker) and Stmn1 (a recently identified marker related to glomerular development) were confirmed in transferred FFPE sections of mouse kidney. This procedure may be adapted for clinical diagnosis and basic research, providing a qualitative and efficient method to dissect the detailed spatial expression patterns of miRNA pathways in FFPE tissue, especially in cases where only a small biopsy sample can be obtained.

Expression of microRNAs: potential molecular link between obesity, diabetes and cancer

Clinicians are routinely challenged in their management of cancer patients because of the complexities of obesity and diabetes that are often found as comorbid conditions. Although attention has been given to optimizing treatment planning for these patients, less attention has been given to manage their obesity and diabetes. This suggests that newer, comprehensive approaches must be developed for the treatment of cancer patients as a 'whole' rather than as a single disease. While the specific pathologies of each are unique, years of research have indicated intimate molecular links between these chronic diseases. The contribution of sedentary lifestyles and poor dietary habits is recognized; however, the precise molecular links are still not well-explored. In addition, emerging evidence suggests the important role of microRNAs (miRNAs) in the development and progression of several diseases, yet their roles in linking obesity, diabetes and cancer are only now beginning to be recognized. It is hoped that miRNAs will serve as novel biomarkers and molecular targets for cancer therapy in patients with comorbid conditions. In this review, we discuss the current understanding of the pathobiology of obesity, diabetes and cancer, and document molecular roles of miRNAs linking cancer with obesity and diabetes.