Identification of candidate microRNA biomarkers in renal fibrosis: a meta-analysis of profiling studies

Abstract

The prognostic, diagnostic and therapeutic value of microRNA (miRNA) expression aberrations in renal fibrosis has been studied in recent years. However, the miRNA expression profiling efforts have led to inconsistent results between the studies. The aim of this study was to perform a meta-analysis on the renal fibrosis miRNA expression profiling studies to identify candidate diagnostic biomarkers. We performed comprehensive literature searches in several databases to identify miRNA expression studies of renal fibrosis in animal models and humans. The miRNAs expression data were extracted from 20 included studies, and both miRNA vote-counting strategy and Robust Rank Aggregation method were utilized to identify significant miRNA meta-signatures. The predicted and validated targets of miRNA meta-signature were obtained by using MultiMiR package in 11 databases. Then a gene set enrichment analysis (KEGG, PANTHER pathways and GO processes) were carried out with GeneCodis web tool to recognize pathways that are most strongly influenced by modified expressions of these miRNAs. We recognized in both meta-analysis approaches a significant miRNA meta-signature of five up-regulated (miR-142-3p, miR-223-3p, miR-21-5p, miR-142-5p and miR-214-3p) and two down-regulated (miR-29c-3p and miR-200a-3p) miRNAs. Enrichment analysis confirmed that miRNA meta-signature cooperatively target functionally related genes in signalling and developmental pathways in renal fibrosis. This meta-analysis identified seven highly significant and consistently dysregulated miRNAs from 20 datasets, as the focus of future investigations to discover their potential influence to renal fibrosis and their clinical utility as biomarkers and/or as therapeutic mediators against chronic kidney disease..     

Clinical significance of blood-based miRNAs as diagnostic and prognostic nucleic acid markers in breast cancer: Comparative to conventional tumor markers

microRNAs (miRNAs) are implicated in carcinogenesis and their expression in biological fluids offer great potential as nucleic acid markers for cancer detection and progression. Authors investigated the expression level of miRNAs (miRNA-21, miRNA-126, and miRNA-155) to evaluate their role as diagnostic and prognostic markers for breast cancer compared with other commonly used protein-based markers (CEA and CA15-3). Serum samples from patients with breast cancer (n = 96), patients with benign breast lesion (n = 47), and healthy individuals (n = 39) were enrolled for detection of miRNA expression levels and protein-based tumor markers using fluorescent real-time quantitative polymerase chain reaction and enzyme-linked immunosorbent assay, respectively. Correlation among investigated markers with clinicopathological factors and clinical outcomes were determined. Expression of miRNA-21 and miRNA-155 revealed significant increases in patients with breast cancer compared with both benign and control groups, the same result was reported for tumor markers; on the other hand, miRNA-126 was significantly decreased in breast cancer group as compared with the other two groups. miRNA frequencies were significantly related to clinical staging and histological grading as compared with tumor markers. Patients with breast cancer with increased miRNA-21 and miRNA-155 and decreased miRNA-126 expressions had significantly worse disease-free survival, while only miRNA-21 and miRNA-126 showed poor OS (P< 0.005). In conclusion, investigated miRNAs were superior over tumor markers for the early stage of breast cancer especially those with high-risk factor and their assessment in blood facilitates their role as a potential prognostic molecular marker.     

Global microRNA expression profiling identifies MiR-210 associated with tumor proliferation, invasion and poor clinical outcome in breast cancer

Purpose

Aberrant microRNA (miRNA) expression is associated with cancer and has potential diagnostic and prognostic value in various malignancies. In this study, we investigated miRNA profiling as a complementary tool to improve our understanding of breast cancer (BC) biology and to assess whether miRNA expression could predict clinical outcome of BC patients.

Experimental Design

Global miRNA expression profiling using microarray technology was conducted in 56 systemically untreated BC patients who had corresponding mRNA expression profiles available. Results were further confirmed using qRT-PCR in an independent dataset of 89 ER-positive BC patients homogeneously treated with tamoxifen only. MiR-210 functional analyses were performed in MCF7 and MDA-MB-231 BC cell lines using lentiviral transduction.

Results

Estrogen receptor (ER) status, tumor grade and our previously developed gene expression grade index (GGI) were associated with distinct miRNA profiles. Several miRNAs were found to be clinically relevant, including miR-210, its expression being associated with tumor proliferation and differentiation. Furthermore, miR-210 was associated with poor clinical outcome in ER-positive, tamoxifen-treated BC patients. Interestingly, the prognostic performance of miR-210 was similar to several reported multi-gene signatures, highlighting its important role in BC differentiation and tumor progression. Functional analyses in BC cell lines revealed that miR-210 is involved in cell proliferation, migration and invasion.

Conclusions

This integrated analysis combining miRNA and mRNA expression demonstrates that miRNA expression provides additional biological information beyond mRNA expression. Expression of miR-210 is linked to tumor proliferation and appears to be a strong potential biomarker of clinical outcome in BC.     

MicroRNA expression in abdominal and gluteal adipose tissue is associated with mRNA expression levels and partly genetically driven

To understand how miRNAs contribute to the molecular phenotype of adipose tissues and related traits, we performed global miRNA expression profiling in subcutaneous abdominal and gluteal adipose tissue of 70 human subjects and characterised which miRNAs were differentially expressed between these tissues. We found that 12% of the miRNAs were significantly differentially expressed between abdominal and gluteal adipose tissue (FDR adjusted p<0.05) in the primary study, of which 59 replicated in a follow-up study of 40 additional subjects. Further, 14 miRNAs were found to be associated with metabolic syndrome case-control status in abdominal tissue and three of these replicated (primary study: FDR adjusted p<0.05, replication: p<0.05 and directionally consistent effect). Genome-wide genotyping was performed in the 70 subjects to enable miRNA expression quantitative trait loci (eQTL) analysis. Candidate miRNA eQTLs were followed-up in the additional 40 subjects and six significant, independent cis-located miRNA eQTLs (primary study: p<0.001; replication: p<0.05 and directionally consistent effect) were identified. Finally, global mRNA expression profiling was performed in both tissues to enable association analysis between miRNA and target mRNA expression levels. We find 22% miRNAs in abdominal and 9% miRNAs in gluteal adipose tissue with expression levels significantly associated with the expression of corresponding target mRNAs (FDR adjusted p<0.05). Taken together, our results indicate a clear difference in the miRNA molecular phenotypic profile of abdominal and gluteal adipose tissue, that the expressions of some miRNAs are influenced by cis-located genetic variants and that miRNAs are associated with expression levels of their predicted mRNA targets.     

Integrated analysis of co‐expression and ceRNA network identifies five lncRNAs as prognostic markers for breast cancer

Long non‐coding RNAs (lncRNAs), which competitively bind miRNAs to regulate target mRNA expression in the competing endogenous RNAs (ceRNAs) network, have attracted increasing attention in breast cancer research. We aim to find more effective therapeutic targets and prognostic markers for breast cancer. LncRNA, mRNA and miRNA expression profiles of breast cancer were downloaded from TCGA database. We screened the top 5000 lncRNAs, top 5000 mRNAs and all miRNAs to perform weighted gene co‐expression network analysis. The correlation between modules and clinical information of breast cancer was identified by Pearson's correlation coefficient. Based on the most relevant modules, we constructed a ceRNA network of breast cancer. Additionally, the standard Kaplan‐Meier univariate curve analysis was adopted to identify the prognosis of lncRNAs. Ultimately, a total of 23 and 5 modules were generated in the lncRNAs/mRNAs and miRNAs co‐expression network, respectively. According to the Green module of lncRNAs/mRNAs and Blue module of miRNAs, our constructed ceRNA network consisted of 52 lncRNAs, 17miRNAs and 79 mRNAs. Through survival analysis, 5 lncRNAs (AL117190.1, COL4A2‐AS1, LINC00184, MEG3 and MIR22HG) were identified as crucial prognostic factors for patients with breast cancer. Taken together, we have identified five novel lncRNAs related to prognosis of breast cancer. Our study has contributed to the deeper understanding of the molecular mechanism of breast cancer and provided novel insights into the use of breast cancer drugs and prognosis.     

Detecting microRNAs of high influence on protein functional interaction networks: a prostate cancer case study

ABSTRACT: BACKGROUND: The use of biological molecular network information for diagnostic and prognostic purposes and elucidation of molecular disease mechanism is a key objective in systems biomedicine. The network of regulatory miRNA-target and functional protein interactions is a rich source of information to elucidate the function and the prognostic value of miRNAs in cancer. The objective of this study is to identify miRNAs that have high influence on target protein complexes in prostate cancer as a case study. This could provide biomarkers or therapeutic targets relevant for prostate cancer treatment. RESULTS: Our findings demonstrate that a miRNA's functional role can be explained by its target protein connectivity within a physical and functional interaction network. To detect miRNAs with high influence on target protein modules, we integrated miRNA and mRNA expression profiles with a sequence based miRNA-target network and human functional and physical protein interactions (FPI). miRNAs with high influence on target protein complexes play a role in prostate cancer progression and are promising diagnostic or prognostic biomarkers. We uncovered several miRNA-regulated protein modules which were enriched in focal adhesion and prostate cancer genes. Several miRNAs such as miR-96, miR-182, and miR-143 demonstrated high influence on their target protein complexes and could explain most of the gene expression changes in our analyzed prostate cancer data set. CONCLUSIONS: We describe a novel method to identify active miRNA-target modules relevant to prostate cancer progression and outcome. miRNAs with high influence on protein networks are valuable biomarkers that can be used in clinical investigations for prostate cancer treatment.     

MicroRNA signature predicts survival in papillary thyroid carcinoma

Papillary thyroid cancer (PTC) accounts for the majority of malignant thyroid tumors. Recently, several microRNA (miRNA) expression profiling studies have used bioinformatics to suggest miRNA signatures as potential prognostic biomarkers in various malignancies. However, a prognostic miRNA biomarker has not yet been established for PTC. The aim of the present study was to identify miRNAs with prognostic value for the overall survival (OS) of patients with PTC by analyzing high-throughput miRNA data and their associated clinical characteristics downloaded from The Cancer Genome Atlas database. From our dataset, 150 differentially expressed miRNAs were identified between tumor and nontumor samples; of these miRNAs, 118 were upregulated and 32 were downregulated. Among the 150 differentially expressed miRNAs, a four miRNA signature was identified that reliably predicts OS in patients with PTC. This miRNA signature was able to classify patients into a high-risk group and a low-risk group with a significant difference in OS (P < .01). The prognostic value of the signature was validated in a testing set ( P < .01). The four miRNA signature was an independent prognostic predictor according to the multivariate analysis and demonstrated good performance in predicting 5-year disease survival with an area under the receiver operating characteristic curve area under the curve (AUC) score of 0.886. Thus, this signature may serve as a novel biomarker for predicting the survival of patients with PTC.     

The mRNA–miRNA–lncRNA Regulatory Network and Factors Associated with Prognosis Prediction of Hepatocellular Carcinoma

The aim of this study was to identify novel prognostic mRNA and microRNA (miRNA) biomarkers for hepatocellular carcinoma (HCC) using methods in systems biology. Differentially expressed mRNAs, miRNAs, and long non-coding RNAs (lncRNAs) were compared between HCC tumor tissues and normal liver tissues in The Cancer Genome Atlas (TCGA) database. Subsequently, a prognosis-associated mRNA co-expression network, an mRNA–miRNA regulatory network, and an mRNA–miRNA–lncRNA regulatory network were constructed to identify prognostic biomarkers for HCC through Cox survival analysis. Seven prognosis-associated mRNA co-expression modules were obtained by analyzing these differentially expressed mRNAs. An expression module including 120 mRNAs was significantly correlated with HCC patient survival. Combined with patient survival data, several mRNAs and miRNAs, including CHST4, SLC22A8, STC2, hsa-miR-326, and hsa-miR-21 were identified from the network to predict HCC patient prognosis. Clinical significance was investigated using tissue microarray analysis of samples from 258 patients with HCC. Functional annotation of hsa-miR-326 and hsa-miR-21-5p indicated specific associations with several cancer-related pathways. The present study provides a bioinformatics method for biomarker screening, leading to the identification of an integrated mRNA–miRNA–lncRNA regulatory network and their co-expression patterns in relation to predicting HCC patient survival.     

Discovery of shear- and side-specific mRNAs and miRNAs in human aortic valvular endothelial cells

The role of endothelial cells (ECs) in aortic valve (AV) disease remains relatively unknown; however, disease preferentially occurs in the fibrosa. We hypothesized oscillatory shear (OS) present on the fibrosa stimulates ECs to modify mRNAs and microRNAs (miRNAs) inducing disease. Our goal was to identify mRNAs and miRNAs differentially regulated by OS and laminar shear (LS) in human AVECs (HAVECs) from the fibrosa (fHAVECs) and ventricularis (vHAVECs). HAVECs expressed EC markers as well as some smooth muscle cell markers and functionally aligned with the flow. HAVECs were exposed to OS and LS for 24 h, and total RNA was analyzed by mRNA and miRNA microarrays. We found over 700 and 300 mRNAs down- and upregulated, respectively, by OS; however, there was no side dependency. mRNA microarray results were validated for 26 of 28 tested genes. Ingenuity Pathway Analysis revealed thrombospondin 1 (Thbs1) and NF-κB inhibitor-α (Nfkbia) as highly connected, shear-sensitive genes. miRNA array analysis yielded 30 shear-sensitive miRNAs and 3 side-specific miRNAs. miRNA validation confirmed 4 of 17 shear-sensitive miRNAs and 1 of 3 side-dependent miRNAs. Using miRWalk and several filtering steps, we identified shear-sensitive mRNAs potentially targeted by shear-sensitive miRNAs. These genes and signaling pathways could act as therapeutic targets of AV disease.     

MicroRNAs in tomato plants

MicroRNAs (miRNAs) are a specialized class of small silencing RNAs that regulate gene expression in eukaryotes. In plants, miRNAs negatively regulate target mRNAs containing a highly complementary sequence by either mRNA cleavage or translational repression. As a model plant to study fleshy fruit ripening, miRNA studies in tomato have made great progress recently. MiRNAs were predicted to be involved in nearly all biological processes in tomato, particularly development, differentiation, and biotic and abiotic stress responses. Surprisingly, several miRNAs were verified to be involved in tomato fruit ripening and senescence. Recent studies suggest that miRNAs are related to host-virus interactions, which raises the possibility that miRNAs can be used as diagnostic markers for response to virus infection in tomato plants. In this review, we summarize our current knowledge systematically and advance future directions for miRNA research in tomato.     

MicroRNA expression profile in serum reveals novel diagnostic biomarkers for endometrial cancer

Purpose: Circulating microRNAs (miRNAs) prove to be promising diagnostic biomarkers for various cancers, including endometrial cancer (EC). The present study aims to identify serum microRNAs that can serve as potential biomarkers for EC diagnosis.Patients and methods: A total of 92 EC and 102 normal control (NC) serum samples were analyzed using quantitative real-time polymerase chain reaction (qRT-PCR) in this four-phase experiment. The logistic regression method was used to construct a diagnostic model based on the differentially expressed miRNAs in serum. The receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic value. To further validate the diagnostic capacity of the identified signature, the 6-miRNA marker was compared with previously reported biomarkers and verified in three public datasets. In addition, the expression characteristics of the identified miRNAs were further explored in tissue and serum exosomes samples.Results: Six miRNAs (miR-143-3p, miR-195-5p, miR-20b-5p, miR-204-5p, miR-423-3p, and miR-484) were significantly overexpressed in the serum of EC compared with NCs. Areas under the ROC of the 6-miRNA signatures were 0.748, 0.833, and 0.967 for the training, testing, and the external validation phases, respectively. The identified signature has a very stable diagnostic performance in the large cohorts of three public datasets. Compared with previously identified miRNA biomarkers, the 6-miRNA signature in the present study has superior performance in diagnosing EC. Moreover, the expression of miR-143-3p and miR-195-5p in tissues and the expression of miR-20b-5p in serum exosomes were consistent with those in serum.Conclusions: We established a 6-miRNA signature in serum and they could function as potential non-invasive biomarker for EC diagnosis.     

高通量测序技术分析急性髓系白血病血浆外泌体微RNA表达谱差异

急性髓系白血病（acute myeloid leukemia,AML）是一类造血干细胞的恶性克隆性疾病,目前的诊断方法不利于疾病的早期发现,且诊断结果重复性较差。已有大量研究显示,细胞外microRNA（miRNA或miR）富集在外泌体（exosome）中,且受其表面膜的保护而具有很好的稳定性,是理想的分子标志物。目前,多种实体肿瘤均已检测到肿瘤特异性外泌体miRNA(exosomal miRNA)。然而,在AML患者中未见此外泌体miRNA报道。本研究探讨急性髓系白血病血浆外泌体miRNA表达谱差异及新miRNA序列。采用solexa高通量测序技术对7例AML患者（AML组）及7例健康对照者（对照组）血浆外泌体miRNAs进行测序,利用Mireap预测软件进行新miRNAs分析,通过edger差异分析软件筛选组间差异miRNA,获得211个已知的差异表达miRNAs以及2个新miRNAs,选择4个差异表达的miRNAs：miR-155-5p、miR-335-5p、miR-451a及xxx-m0038 5p（新miRNA）,在两组（各23例）的血浆外泌体样本中,进行实时荧光定量PCR（qRT-PCR）验证,验证结果与测序结果一致。对差异表达的外泌体miRNA进行靶基因预测及其GO（Gene Ontology）和信号通路富集分析,发现靶基因聚集的生物学功能多数参与生物进展过程的调控。靶基因主要富集在FoxO、MAPK、Hippo信号通路以及HTLV-I感染等。结果显示,AML患者与健康对照者的血浆外泌体miRNA存在着差异性表达。差异性表达的miRNA特异性很高,对进一步阐明AML白血病发生与发展的分子机制、研发新的无创诊断方法、新的诊断标记物和有效治疗AML的方法具有十分重要和深远的意义。     

MicroRNA‐guided gene expression in prostate cancer: Literature and database overview

Insight into the aberrant expression of microRNAs (miRNAs) and the genes that they regulate during the progression of cancer in general and prostate cancer (PCa) in particular is one of the most important issues in current molecular biomedicine and allows for the discovery of therapeutic or diagnostic miRNA targets. The present study aimed to analyze the available data regarding the direct or indirect effects of miRNAs on the expression of the mRNAs involved in carcinogenesis and to enable updating and optimizing the selection of the corresponding targets. The present review focuses on the data related to the genes with miRNA‐dependent expression during the development of PCa. The data used in this review have been extracted from research papers and the databases STRING, PANTHER and TargetScan, with a special focus on the genes directly associated with cell transformation and the maintenance of the transformed genotype, as well as tumor invasion and spread. The search for miRNA markers of PCa and therapeutically active molecules should rely on bioinformatics resources, such as data from recent experimental studies, as well as meta‐analysis and cross‐analysis of the data on the state of the tumor, patient status, histological/immunohistological data and data on mRNA–miRNA coexpression.     

Integrating high-throughput microRNA and mRNA expression data to identify risk mRNA signature for pancreatic cancer prognosis

Pancreatic cancer is a malignancy of the digestive system characterized by poor prognosis. A number of prognostic messenger RNA (mRNA) signatures have been identified by using the high-throughput expression profiles. MicroRNAs (miRNA) play a critical role in regulating multiple cellular functions. However, no such integrated analysis of miRNAs and mRNAs for studying the prognostic mechanisms of pancreatic cancer has been reported. In this study, we first identified prognostic mRNAs and miRNAs based on The Cancer Genome Atlas datasets, and then performed an enrichment analysis to explore the underlying biological mechanisms involved in pancreatic cancer prognosis at the mRNA level. Furthermore, we performed an integrated analysis of mRNAs and miRNAs to identify prognostic subpathways, which were closely associated with pancreatic cancer genes and tumor hallmarks and involved in hypoxia, oxidative phosphyorylation and xenobiotic metabolisms. Meanwhile, we performed a random walk algorithm based on global network, prognostic mRNAs and miRNAs, and identified top risk mRNAs as the prognostic signature. Finally, an independent testing set was used to confirm the predictive power of the top mRNA signature, and most of these genes involved were known oncogenes. In conclusion, we performed a series of integrated analyses by comprehensively exploring pancreatic cancer prognosis and systematically optimized the prognostic signature for clinical use.     

Using hippocampal microRNA expression differences between mouse inbred strains to characterise miRNA function

Micro-RNAs (miRNAs) are short, single-stranded, noncoding RNAs that are involved in the regulation of protein-coding genes at the level of messenger RNA (mRNA). They are involved in the regulation of numerous traits, including developmental timing, apoptosis, immune function, and neuronal development. To better understand how the expression of the miRNAs themselves is regulated, we looked for miRNA expression differences among four mouse inbred strains, A/J, BALB/cJ, C57BL/6J, and DBA/2J, in one tissue, the hippocampus. A total of 166 miRNA RT-PCR assays were used to screen RNA pools for each strain. Twenty miRNA species that were markedly different between strains were further investigated using eight individual samples per strain, and 11 miRNAs showed significant differences across strains (p < 0.05). This is the first observation of miRNA expression differences across inbred mice strains. We conducted an in silico correlation analysis of the expression of these differentially expressed miRNAs with phenotype data and mRNA expression to better characterise the effects of these miRNAs on both phenotype and the regulation of mRNA expression. This approach has allowed us to nominate miRNAs that have potential roles in anxiety, exploration, and learning and memory.