MicroRNA signature in hepatocellular carcinoma patients: identification of potential markers

MicroRNAs (miRNAs) play important roles in liver pathologies and they are potential biomarkers for diagnosis of liver diseases progression. Changes in miRNA sera expression can be used as non-invasive biomarkers for hepatocellular carcinoma (HCC). The aim of the study was to identify the miRNome profiling of HCC and its diagnostic value in distinguishing HCC from healthy individuals. Expression profiles of miRNAs in serum samples of 20 HCC patients and 10 healthy controls were detected. Whole miRNome profiling was done using next generation sequencing. Receiver operating characteristic (ROC) analysis was performed to assess the diagnostic performance of the deregulated miRNAs for discriminating HCC cases from healthy controls. MiRNA 142 was highly expressed in HCC (P value?=?0.023) while miRNAs 191, 22, and 126 were higher in the controls (P value?=?0.005, 0.034, 0.010 respectively). We have identified 5 novel miRNAs and they were highly expressed in HCC than controls. Analysis of ROC curve demonstrated that these deregulated miRNAs can be used as a reliable biomarker for detection of HCC with high diagnostic accuracy (AUC?=?0.93). We have detected a panel of serum miRNAs that can be used as a reliable noninvasive screening biomarker of HCC. The study recommends further research to shed light on a possible role of the newly discovered novel miRNAs in HCC pathogenesis.

     

The human miRNA repertoire of different blood compounds

Background

MiRNAs from body fluids gain more and more attraction as biomarker candidates. Besides serum, patterns from whole blood are increasingly considered as markers for human pathologies. Usually, the contribution of different cell types to the respective signature remains however unknown. In this study we provide insights into the human miRNome of different compounds of the blood including CD3, CD14, CD15, CD19, CD56 positive cells as well as exosomes.

Methods

We measured the miRNA repertoire for each cell type and whole blood for two individuals at three time points over the course of one year in order to provide evidence that the cell type miRNomes can be reproducibly detected.

Results

For measurements repeated after 24 hours we found on average correlation of 0.97, even after one year profiles still correlated with 0.96, demonstrating the enormous stability of the cell type specific miRNomes. Highest correlation was found for CD15 positive cells, exceeding Pearson correlation of 0.99. For exosomes a significantly higher variability of miRNA expression was detected. In order to estimate the complexity and variability of the cell type specific miRNomes, we generated profiles for all considered cell types in a total of seven unaffected individuals. While CD15 positive cells showed the most complex miRNome consisting of 328 miRNAs, we detected significantly less miRNAs (186, p = 1.5*10^-5) in CD19 positive cells. Moreover, our analysis showed functional enrichment in many relevant categories such as onco-miRNAs and tumor miRNA suppressors. Interestingly, exosomes were enriched just for onco-miRNAs but not for miRNA tumor suppressors.

Conclusion

In sum, our results provide evidence that blood cell type specific miRNomes are very consistent between individuals and over time.     

癌症相关microRNA与靶基因的生物信息学分析

MicroRNAs(miRNAs)是一类长度约为22nt的内源性非编码RNA,通过与靶基因转录本互补结合调控基因的表达。近年来,研究发现miRNA与癌症发生密切相关,miRNA可以直接充当癌基因或者抑癌基因而影响肿瘤的发生和生长。为更进一步揭示癌症相关miRNA的特征及靶基因的功能,文章通过数据库搜索及文献检索,在人类基因组中发现了475个癌症相关miRNA,系统地比较了癌症相关miRNA与非癌症miRNA以及基因内和基因间区癌症相关miRNA在保守性、SNP位点分布、癌谱及转录调控等特性。研究发现,癌症相关miRNA比非癌症miRNA保守性要强,发生SNP概率比较低,同时发现miRNA所涉及癌症数目与保守性成正相关。基因组定位分析发现,癌症相关miRNA比非癌症miRNA更倾向于成簇存在。进一步对宿主基因、癌症相关miRNA及作用的靶基因与癌症发生进行关联分析,发现一些非癌症miRNA的宿主基因倾向于被癌症miRNA作用。本研究结果为深入理解miRNA与癌症之间的关系,以及进一步为miRNA作为癌症诊断指示物提供理论依据。     

Circulating micro-RNAs as potential blood-based markers for early stage breast cancer detection

Introduction

MicroRNAs (miRNAs, miRs) are a class of small, non-coding RNA molecules with relevance as regulators of gene expression thereby affecting crucial processes in cancer development. MiRNAs offer great potential as biomarkers for cancer detection due to their remarkable stability in blood and their characteristic expression in many different diseases. We investigated whether microarray-based miRNA profiling on whole blood could discriminate between early stage breast cancer patients and healthy controls.

Methods

We performed microarray-based miRNA profiling on whole blood of 48 early stage breast cancer patients at diagnosis along with 57 healthy individuals as controls. This was followed by a real-time semi-quantitative Polymerase Chain Reaction (RT-qPCR) validation in a separate cohort of 24 early stage breast cancer patients from a breast cancer screening unit and 24 age matched controls using two differentially expressed miRNAs (miR-202, miR-718).

Results

Using the significance level of p<0.05, we found that 59 miRNAs were differentially expressed in whole blood of early stage breast cancer patients compared to healthy controls. 13 significantly up-regulated miRNAs and 46 significantly down-regulated miRNAs in our microarray panel of 1100 miRNAs and miRNA star sequences could be detected. A set of 240 miRNAs that was evaluated by radial basis function kernel support vector machines and 10-fold cross validation yielded a specificity of 78.8%, and a sensitivity of 92.5%, as well as an accuracy of 85.6%. Two miRNAs were validated by RT-qPCR in an independent cohort. The relative fold changes of the RT-qPCR validation were in line with the microarray data for both miRNAs, and statistically significant differences in miRNA-expression were found for miR-202.

Conclusions

MiRNA profiling in whole blood has potential as a novel method for early stage breast cancer detection, but there are still challenges that need to be addressed to establish these new biomarkers in clinical use.     

Comprehensive miRNA sequence analysis reveals survival differences in diffuse large B-cell lymphoma patients

BackgroundDiffuse large B-cell lymphoma (DLBCL) is an aggressive disease, with 30% to 40% of patients failing to be cured with available primary therapy. microRNAs (miRNAs) are RNA molecules that attenuate expression of their mRNA targets. To characterize the DLBCL miRNome, we sequenced miRNAs from 92 DLBCL and 15 benign centroblast fresh frozen samples and from 140 DLBCL formalin-fixed, paraffin-embedded tissue samples for validation.ResultsWe identify known and candidate novel miRNAs, 25 of which are associated with survival independently of cell-of-origin and International Prognostic Index scores, which are established indicators of outcome. Of these 25 miRNAs, six miRNAs are significantly associated with survival in our validation cohort. Abundant expression of miR-28-5p, miR-214-5p, miR-339-3p, and miR-5586-5p is associated with superior outcome, while abundant expression of miR-324-5p and NOVELM00203M is associated with inferior outcome. Comparison of DLBCL miRNA-seq expression profiles with those from other cancer types identifies miRNAs that were more abundant in B-cell contexts. Unsupervised clustering of miRNAs identifies two clusters of patients that have distinct differences in their outcomes. Our integrative miRNA and mRNA expression analyses reveal that miRNAs increased in abundance in DLBCL appear to regulate the expression of genes involved in metabolism, cell cycle, and protein modification. Additionally, these miRNAs, including one candidate novel miRNA, miR-10393-3p, appear to target chromatin modification genes that are frequent targets of somatic mutation in non-Hodgkin lymphomas.ConclusionsOur comprehensive sequence analysis of the DLBCL miRNome identifies candidate novel miRNAs and miRNAs associated with survival, reinforces results from previous mutational analyses, and reveals regulatory networks of significance for lymphomagenesis.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-014-0568-y) contains supplementary material, which is available to authorized users.     

Dissection of Regulatory Networks that Are Altered in Disease via Differential Co-expression

Comparing the gene-expression profiles of sick and healthy individuals can help in understanding disease. Such differential expression analysis is a well-established way to find gene sets whose expression is altered in the disease. Recent approaches to gene-expression analysis go a step further and seek differential co-expression patterns, wherein the level of co-expression of a set of genes differs markedly between disease and control samples. Such patterns can arise from a disease-related change in the regulatory mechanism governing that set of genes, and pinpoint dysfunctional regulatory networks.Here we present DICER, a new method for detecting differentially co-expressed gene sets using a novel probabilistic score for differential correlation. DICER goes beyond standard differential co-expression and detects pairs of modules showing differential co-expression. The expression profiles of genes within each module of the pair are correlated across all samples. The correlation between the two modules, however, differs markedly between the disease and normal samples.We show that DICER outperforms the state of the art in terms of significance and interpretability of the detected gene sets. Moreover, the gene sets discovered by DICER manifest regulation by disease-specific microRNA families. In a case study on Alzheimer''s disease, DICER dissected biological processes and protein complexes into functional subunits that are differentially co-expressed, thereby revealing inner structures in disease regulatory networks.     

Comparative analysis of CEA and SCC serum markers with IAP in human lung cancer

Serum levels of carcinoembryonic antigen (CEA), squamous cell carcinoma antigen (SCC) and immunosuppressive acidic protein (IAP) were measured in 37 patients with lung cancers, in 24 with non-cancer pulmonary diseases and in 24 normal controls We evaluated the sensitivity, specificity and accuracy of these three markers alone and combined. The highest specificity was observed for SCC (83.3%) and the highest sensitivity for IAP (94.6%). The best accuracy was obtained with the combined determination of CEA and SCC. In cancer and non-cancer pulmonary diseases the best correlation was observed between CEA and SCC (r = 0.30 in cancer and r = 0.45 in non-cancer pulmonary diseases). Although the IAP test is not specific in the detection of lung cancer, its use may be helpful in monitoring the acute phase reactions that occur very frequently in this malignancy.     

High-resolution analysis of the human retina miRNome reveals isomiR variations and novel microRNAs

MicroRNAs play a fundamental role in retinal development and function. To characterise the miRNome of the human retina, we carried out deep sequencing analysis on sixteen individuals. We established the catalogue of retina-expressed miRNAs, determined their relative abundance and found that a small number of miRNAs accounts for almost 90% of the retina miRNome. We discovered more than 3000 miRNA variants (isomiRs), encompassing a wide range of sequence variations, which include seed modifications that are predicted to have an impact on miRNA action. We demonstrated that a seed-modifying isomiR of the retina-enriched miR-124-3p was endowed with different targeting properties with respect to the corresponding canonical form. Moreover, we identified 51 putative novel, retina-specific miRNAs and experimentally validated the expression for nine of them. Finally, a parallel analysis of the human Retinal Pigment Epithelium (RPE)/choroid, two tissues that are known to be crucial for retina homeostasis, yielded notably distinct miRNA enrichment patterns compared to the retina. The generated data are accessible through an ad hoc database. This study is the first to reveal the complexity of the human retina miRNome at nucleotide resolution and constitutes a unique resource to assess the contribution of miRNAs to the pathophysiology of the human retina.     

MicroRNA-5p and -3p co-expression and cross-targeting in colon cancer cells

Background

Two mature miRNA species may be generated from the 5’ and 3’ arms of a pre-miRNA precursor. In most cases, only one species remains while the complementary species is degraded. However, co-existence of miRNA-5p and -3p species is increasingly being reported. In this work, we aimed to systematically investigate co-expression of miRNA-5p/3p in colon cancer cells in a genome-wide analysis, and to examine cross-targeting of the dysregulated miRNAs and 5p/3p species.

Results

Four colon cancer cell lines were examined relative to two normal colon tissues. Of the 1,190 miRNAs analyzed, 92 and 36 were found to be up- or down-regulated, respectively, in cancer cells. Nineteen co-expressed miRNA-5p/3p pairs were further identified suggesting frequent 5p/3p co-accumulation in colon cancer cells. Of these, 14 pairs were co-up-regulated and 3 pairs were co-down-regulated indicating concerted 5p/3p dysregulation. Nine dysregulated miRNA pairs fell into three miRNA gene families, namely let-7, mir-8/200 and mir-17, which showed frequent cross-targeting in the metastasis process. Focusing on the let-7d-5p/3p pair, the respectively targeted IGF1R and KRAS were shown to be in a reverse relationship with expression of the respective miRNA, which was confirmed in transient transfection assays using let-7d mimic or inhibitor. Targeting of KRAS by let-7d was previous reported; targeting of IGF1R by let-7d-5p was confirmed in luciferase assays in this study. The findings of let-7d-5p/3p and multiple other miRNAs targeting IGF1R, KRAS and other metastasis-related factors suggest that 5p/3p miRNAs contribute to cross-targeting of multiple cancer-associated factors and processes possibly to evade functional abolishment when any one of the crucial factors are inactivated.

Conclusions

miRNA-5p/3p species are frequently co-expressed and are coordinately regulated in colon cancer cells. In cancer cells, multiple cross-targeting by the miRNAs, including the co-existing 5p/3p species, frequently occurs in an apparent safe-proof scheme of miRNA regulation of important tumorigenesis processes. Further systematic analysis of co-existing miRNA-5p/3p pairs in clinical tissues is important in elucidating 5p/3p contributions to cancer pathogenesis.

Electronic supplementary material

The online version of this article (doi:10.1186/s12929-014-0095-x) contains supplementary material, which is available to authorized users.     

Epigenetics, miRNAs, and human cancer: a new chapter in human gene regulation

Cancer is a genetic and epigenetic disease. MicroRNAs (miRNAs), a class of small noncoding RNAs, have been shown to be deregulated in many diseases including cancer. An intertwined connection between epigenetics and miRNAs has been supported by the recent identification of a specific subgroup of miRNAs called “epi-miRNAs” that can directly and indirectly modulate the activity of the epigenetic machinery. The complexity of this connection is enhanced by the epigenetic regulation of miRNA expression that generates a fine regulatory feedback loop. This review focuses on how epigenetics affects the miRNome and how the recently identified epi-miRNAs regulate the epigenome in human cancers, ultimately contributing to human carcinogenesis.     

Multiscale Embedded Gene Co-expression Network Analysis

Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG) has been applied to many real-world data sets such as financial stock prices and gene expression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|³), the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA) by: i) introducing quality control of co-expression similarities, ii) parallelizing embedded network construction, and iii) developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs). We applied MEGENA to a series of simulated data and the gene expression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA). MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressed gene clusters but also novel targets in breast carcinoma and lung adenocarcinoma.     

Global microRNA level regulation of EGFR‐driven cell‐cycle protein network in breast cancer

The EGFR‐driven cell‐cycle pathway has been extensively studied due to its pivotal role in breast cancer proliferation and pathogenesis. Although several studies reported regulation of individual pathway components by microRNAs (miRNAs), little is known about how miRNAs coordinate the EGFR protein network on a global miRNA (miRNome) level. Here, we combined a large‐scale miRNA screening approach with a high‐throughput proteomic readout and network‐based data analysis to identify which miRNAs are involved, and to uncover potential regulatory patterns. Our results indicated that the regulation of proteins by miRNAs is dominated by the nucleotide matching mechanism between seed sequences of the miRNAs and 3′‐UTR of target genes. Furthermore, the novel network‐analysis methodology we developed implied the existence of consistent intrinsic regulatory patterns where miRNAs simultaneously co‐regulate several proteins acting in the same functional module. Finally, our approach led us to identify and validate three miRNAs (miR‐124, miR‐147 and miR‐193a‐3p) as novel tumor suppressors that co‐target EGFR‐driven cell‐cycle network proteins and inhibit cell‐cycle progression and proliferation in breast cancer.     

Genome-wide miRNA signatures of human longevity

Little is known about the functions of miRNAs in human longevity. Here, we present the first genome-wide miRNA study in long-lived individuals (LLI) who are considered a model for healthy aging. Using a microarray with 863 miRNAs, we compared the expression profiles obtained from blood samples of 15 centenarians and nonagenarians (mean age 96.4 years) with those of 55 younger individuals (mean age 45.9 years). Eighty miRNAs showed aging-associated expression changes, with 16 miRNAs being up-regulated and 64 down-regulated in the LLI relative to the younger probands. Seven of the eight selected aging-related biomarkers were technically validated using quantitative RT-PCR, confirming the microarray data. Three of the eight miRNAs were further investigated in independent samples of 15 LLI and 17 younger participants (mean age 101.5 and 36.9 years, respectively). Our screening confirmed previously published miRNAs of human aging, thus reflecting the utility of the applied approach. The hierarchical clustering analysis of the miRNA microarray expression data revealed a distinct separation between the LLI and the younger controls (P-value < 10(-5) ). The down-regulated miRNAs appeared as a cluster and were more often reported in the context of diseases than the up-regulated miRNAs. Moreover, many of the differentially regulated miRNAs are known to exhibit contrasting expression patterns in major age-related diseases. Further in silico analyses showed enrichment of potential targets of the down-regulated miRNAs in p53 and other cancer pathways. Altogether, synchronized miRNA-p53 activities could be involved in the prevention of tumorigenesis and the maintenance of genomic integrity during aging.