Identifying miRNA synergism using multiple-intervention causal inference

The deleted in oral cancer (DOC1 aka CDK2AP1) tumor suppressor gene is downregulated in oral squamous cell carcinoma by multiple microRNAs

Cyclin-dependent kinase 2-associated protein 1 (CDK2AP1; also known as deleted in oral cancer or DOC1) is a tumor suppressor gene known to play functional roles in both cell cycle regulation and in the epigenetic control of embryonic stem cell differentiation, the latter as a core subunit of the nucleosome remodeling and histone deacetylation (NuRD) complex. In the vast majority of oral squamous cell carcinomas (OSCC), expression of the CDK2AP1 protein is reduced or lost. Notwithstanding the latter (and the DOC1 acronym), mutations or deletions in its coding sequence are extremely rare. Accordingly, CDK2AP1 protein-deficient oral cancer cell lines express as much CDK2AP1 mRNA as proficient cell lines. Here, by combining in silico and in vitro approaches, and by taking advantage of patient-derived data and tumor material in the analysis of loss of CDK2AP1 expression, we identified a set of microRNAs, namely miR-21-5p, miR-23b-3p, miR-26b-5p, miR-93-5p, and miR-155-5p, which inhibit its translation in both cell lines and patient-derived OSCCs. Of note, no synergistic effects were observed of the different miRs on the CDK2AP1-3-UTR common target. We also developed a novel approach to the combined ISH/IF tissue microarray analysis to study the expression patterns of miRs and their target genes in the context of tumor architecture. Last, we show that CDK2AP1 loss, as the result of miRNA expression, correlates with overall survival, thus highlighting the clinical relevance of these processes for carcinomas of the oral cavity.

Defining disease-related modules based on weighted miRNA synergistic network

MicroRNAs (miRNAs) play an important role in the biological process. Their expression and functional changes have been observed in most cancers. Meanwhile, there exists cooperative regulation among miRNAs which is important for studying the mechanisms of complex post-transcriptional regulations. Hence, studying miRNA synergy and identifying miRNA synergistic modules can help understand the development and progression of complex diseases, such as cancers. This work studies miRNA synergy and proposes a new method for defining disease-related modules (DDRM) by combining the knowledge databases and miRNA data. DDRM measures the miRNA synergy not only by the co-regulating target subset but also by the non-common target set to construct the weighted miRNA synergistic network (WMSN). The experiments on twelve the cancer genome atlas (TCGA) datasets showed that the important modules identified by DDRM can well distinguish the cancer samples from the normal samples, and DDRM performed better than the previous method in most cases. An external dataset of prostate cancer was applied to validate the module biomarkers determined by DDRM on the prostate cancer data of TCGA. The area under the receiver operating characteristic curve (AUC) value is 0.92 and the performance is superior. Hence, combining the miRNA synergy networks from the knowledge databases and the miRNA data can determine the important functional modules related to diseases, which is of great significance to the study of disease mechanism.

A microRNA-microRNA crosstalk network inferred from genome-wide single nucleotide polymorphism variants in natural populations of Arabidopsis thaliana

To adapt to variable natural conditions, plants have evolved several strategies to respond to different environmental stresses. MicroRNA (miRNA)-mediated gene regulation is one of such strategies. Variants, e.g., single nucleotide polymorphisms (SNPs) within the mature miRNAs or their target sites may cause the alteration of regulatory networks and serious phenotype changes. In this study, we proposed a novel approach to construct a miRNA-miRNA crosstalk network in Arabidopsis thaliana based on the notion that two cooperative miRNAs toward common targets are under a strong pressure to be inherited together across ecotypes. By performing a genome-wide scan of the SNPs within the mature miRNAs and their target sites, we defined a "regulation fate profile" to describe a miRNA-target regulation being static (kept) or dynamic (gained or lost) across 1,135 ecotypes compared with the reference genome of Col-0. The cooperative miRNA pairs were identified by estimating the similarity of their regulation fate profiles toward the common targets. The reliability of the cooperative miRNA pairs was supported by solid expressional correlation, high PPImiRFS scores, and similar stress responses. Different combinations of static and dynamic miRNA-target regulations account for the cooperative miRNA pairs acting on various biological characteristics of miRNA conservation, expression, homology, and stress response. Interestingly, the targets that are co-regulated dynamically by both cooperative miRNAs are more likely to be responsive to stress. Hence, stress-related genes probably bear selective pressures in a certain group of ecotypes, in which miRNA regulations on the stress genes reprogram. Finally, three case studies showed that reprogramming miRNA-miRNA crosstalk toward the targets in specific ecotypes was associated with these ecotypes' climatic variables and geographical locations. Our study highlights the potential of miRNA-miRNA crosstalk as a genetic basis underlying environmental adaptation in natural populations.

miR-214-3p Protects and Restores the Myocardial Tissue of Rat Myocardial Infarction Model by Targeting PTEN

Myocardial infarction (MI), which results in myocardial cell dysfunction and irreversible loss, is one of the most serious health threats today. This study was started with rats, by which the consequence of miRNA expression dysregulation to the occurrence and progression of cardiovascular diseases was explored. We first conducted miRNA sequencing on the myocardial tissues separately from myocardial infarction treatment and sham operation treatment to clarify those differently expressed miRNAs; then, our experiment of functional verification of those key miRNAs was initiated so as to dig out the molecular mechanism behind the miRNA's regulation in myocardial infarction. And it turned out that there were 32 upregulated miRNAs and 16 downregulated miRNAs according to our comparison from the myocardial infarction model group to the sham operation group; of all those upregulated, alteration in miR-214-3p expression was the most conspicuous. Overexpression of miR-214-3p greatly alleviated myocardial infarct area and ameliorated myocardial tissue structure, even reducing myocardial fibrosis and the devastation in the tissues. On the molecular level, miR-214-3p overexpression brought down both the apoptosis rate and cleaved caspase 3 expression. Besides that, we verified that PTEN is the target gene of miR-214-3p through a dual-luciferase assay. A cotransfection of miR-214-3p and PTEN brought about an obvious elevation in the myocardial infarct area, tissue damage, and fibrosis, even in the aspect of cellular apoptosis than a mere transfection of miR-214-3p. All the results above verified miR-214-3p′s effects in protecting myocardial tissues and reducing the infarct area, and it was reasonable to assume that those functions of miR-214-3p came into effect by targeting PTEN, which was then justified by the inversion to miR-214-3p′s protection via PTEN overexpression.

Immunomodulatory Properties of Human Breast Milk: MicroRNA Contents and Potential Epigenetic Effects

Infants who are exclusively breastfed in the first six months of age receive adequate nutrients, achieving optimal immune protection and growth. In addition to the known nutritional components of human breast milk (HBM), i.e., water, carbohydrates, fats and proteins, it is also a rich source of microRNAs, which impact epigenetic mechanisms. This comprehensive work presents an up-to-date overview of the immunomodulatory constituents of HBM, highlighting its content of circulating microRNAs. The epigenetic effects of HBM are discussed, especially those regulated by miRNAs. HBM contains more than 1400 microRNAs. The majority of these microRNAs originate from the lactating gland and are based on the remodeling of cells in the gland during breastfeeding. These miRNAs can affect epigenetic patterns by several mechanisms, including DNA methylation, histone modifications and RNA regulation, which could ultimately result in alterations in gene expressions. Therefore, the unique microRNA profile of HBM, including exosomal microRNAs, is implicated in the regulation of the genes responsible for a variety of immunological and physiological functions, such as FTO, INS, IGF1, NRF2, GLUT1 and FOXP3 genes. Hence, studying the HBM miRNA composition is important for improving the nutritional approaches for pregnancy and infant's early life and preventing diseases that could occur in the future. Interestingly, the composition of miRNAs in HBM is affected by multiple factors, including diet, environmental and genetic factors.

miRCoop: Identifying Cooperating miRNAs via Kernel Based Interaction Tests

Although miRNAs can cause widespread changes in expression programs, single miRNAs typically induce mild repression on their targets. Cooperativity among miRNAs is reported as one strategy to overcome this constraint. Expanding the catalog of synergistic miRNAs is critical for understanding gene regulation and for developing miRNA-based therapeutics. In this study, we develop miRCoop to identify synergistic miRNA pairs that have weak or no repression on the target mRNA individually, but when act together, induce strong repression. miRCoop uses kernel-based statistical interaction tests, together with miRNA and mRNA target information. We apply our approach to patient data of two different cancer types. In kidney cancer, we identify 66 putative triplets. For 64 of these triplets, there is at least one common transcription factor that potentially regulates all participating RNAs of the triplet, supporting a functional association among them. Furthermore, we find that identified triplets are enriched for certain biological processes that are relevant to kidney cancer. Some of the synergistic miRNAs are very closely encoded in the genome, hinting a functional association among them. In applying the method on tumor data with the primary liver site, we find 3105 potential triplet interactions. We believe miRCoop can aid our understanding of the complex regulatory interactions in different health and disease states of the cell and can help in designing miRNA-based therapies. Matlab code for the methodology is provided in https://github.com/guldenolgun/miRCoop.

Effective tools for RNA-derived therapeutics: siRNA interference or miRNA mimicry

The approval of the first small interfering RNA (siRNA) drug Patisiran by FDA in 2018 marks a new era of RNA interference (RNAi) therapeutics. MicroRNAs (miRNA), an important post-transcriptional gene regulator, are also the subject of both basic research and clinical trials. Both siRNA and miRNA mimics are ~21 nucleotides RNA duplexes inducing mRNA silencing. Given the well performance of siRNA, researchers ask whether miRNA mimics are unnecessary or developed siRNA technology can pave the way for the emergence of miRNA mimic drugs. Through comprehensive comparison of siRNA and miRNA, we focus on (1) the common features and lessons learnt from the success of siRNAs; (2) the unique characteristics of miRNA that potentially offer additional therapeutic advantages and opportunities; (3) key areas of ongoing research that will contribute to clinical application of miRNA mimics. In conclusion, miRNA mimics have unique properties and advantages which cannot be fully matched by siRNA in clinical applications. MiRNAs are endogenous molecules and the gene silencing effects of miRNA mimics can be regulated or buffered to ameliorate or eliminate off-target effects. An in-depth understanding of the differences between siRNA and miRNA mimics will facilitate the development of miRNA mimic drugs.

Combinatorial targeting of microRNA-26b and microRNA-101 exerts a synergistic inhibition on cyclooxygenase-2 in brain metastatic triple-negative breast cancer cells

PURPOSE

Extravasation of triple-negative (TN) metastatic breast cancer (BC) cells through the brain endothelium (BE) is a critical step in brain metastasis (BM). During extravasation, metastatic cells induce alteration in the inter-endothelial junctions and transmigrate through the endothelial barrier. Transmigration of metastatic cells is mediated by the upregulation of cyclooxygenase-2 (COX-2) that induces matrix metalloproteinase-1 (MMP-1) capable of degrading inter-endothelial junctional proteins. Despite their important role in BM, the molecular mechanisms upregulating COX-2 and MMP-1 in TNBC cells remain poorly understood. In this study, we unraveled a synergistic effect of a pair of micro-RNAs (miR-26b-5p and miR-101-3p) on COX-2 expression and the brain transmigration ability of BC cells.

METHODS

Using a gain-and-loss of function approach, we modulated levels of miR-26b-5p and miR-101-3p in two TNBC cell lines (the parental MDA-MB-231 and its brain metastatic variant MDA-MB-231-BrM2), and examined the resultant effect on COX-2/MMP-1 expression and the transmigration of cancer cells through the BE.

RESULTS

We observed that the dual inhibition of miR-26b-5p and miR-101-3p in BC cells results in higher increase of COX-2/MMP-1 expression and a higher trans-endothelial migration compared to either micro-RNA alone. The dual restoration of both micro-RNAs exerted a synergistic inhibition on COX-2/MMP-1 by targeting COX-2 and potentiated the suppression of trans-endothelial migration compared to single micro-RNA.

CONCLUSION

These findings provide new insights on a synergism between miR-26-5p and miR-101-3p in regulating COX-2 in metastatic TNBC cells and shed light on miR-26-5p and miR-101-3p as prognostic and therapeutic targets that can be exploited to predict or prevent BM.

Computational methods for cancer driver discovery: A survey

Identifying the genes responsible for driving cancer is of critical importance for directing treatment. Accordingly, multiple computational tools have been developed to facilitate this task. Due to the different methods employed by these tools, different data considered by the tools, and the rapidly evolving nature of the field, the selection of an appropriate tool for cancer driver discovery is not straightforward. This survey seeks to provide a comprehensive review of the different computational methods for discovering cancer drivers. We categorise the methods into three groups; methods for single driver identification, methods for driver module identification, and methods for identifying personalised cancer drivers. In addition to providing a “one-stop” reference of these methods, by evaluating and comparing their performance, we also provide readers the information about the different capabilities of the methods in identifying biologically significant cancer drivers. The biologically relevant information identified by these tools can be seen through the enrichment of discovered cancer drivers in GO biological processes and KEGG pathways and through our identification of a small cancer-driver cohort that is capable of stratifying patient survival.

DriverGroup: a novel method for identifying driver gene groups

MOTIVATION

Identifying cancer driver genes is a key task in cancer informatics. Most existing methods are focused on individual cancer drivers which regulate biological processes leading to cancer. However, the effect of a single gene may not be sufficient to drive cancer progression. Here, we hypothesize that there are driver gene groups that work in concert to regulate cancer, and we develop a novel computational method to detect those driver gene groups.

RESULTS

We develop a novel method named DriverGroup to detect driver gene groups by using gene expression and gene interaction data. The proposed method has three stages: (i) constructing the gene network, (ii) discovering critical nodes of the constructed network and (iii) identifying driver gene groups based on the discovered critical nodes. Before evaluating the performance of DriverGroup in detecting cancer driver groups, we firstly assess its performance in detecting the influence of gene groups, a key step of DriverGroup. The application of DriverGroup to DREAM4 data demonstrates that it is more effective than other methods in detecting the regulation of gene groups. We then apply DriverGroup to the BRCA dataset to identify driver groups for breast cancer. The identified driver groups are promising as several group members are confirmed to be related to cancer in literature. We further use the predicted driver groups in survival analysis and the results show that the survival curves of patient subpopulations classified using the predicted driver groups are significantly differentiated, indicating the usefulness of DriverGroup.

AVAILABILITY AND IMPLEMENTATION

DriverGroup is available at https://github.com/pvvhoang/DriverGroup.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Synergism of Proneurogenic miRNAs Provides a More Effective Strategy to Target Glioma Stem Cells

Simple Summary

miRNAs function as critical regulators of gene expression and have been defined as contributors of cancer phenotypes by acting as oncogenes or tumor suppressors. Based on these findings, miRNA-based therapies have been explored in the treatment of many different malignancies. The use of single miRNAs has faced some challenges and showed limited success. miRNAs cooperate to regulate distinct biological processes and pathways and, therefore, combination of related miRNAs could amplify the repression of oncogenic factors and the effect on cancer relevant pathways. We established that the combination of tumor suppressor miRNAs miR-124, miR-128, and miR-137 is much more effective than single miRNAs in disrupting proliferation and survival of glioma stem cells and neuroblastoma lines and promoting differentiation and response to radiation. Subsequent genomic analyses showed that other combinations of tumor suppressor miRNAs could be equally effective, and its use could provide new routes to target in special cancer-initiating cell populations.

Abstract

Tumor suppressor microRNAs (miRNAs) have been explored as agents to target cancer stem cells. Most strategies use a single miRNA mimic and present many disadvantages, such as the amount of reagent required and the diluted effect on target genes. miRNAs work in a cooperative fashion to regulate distinct biological processes and pathways. Therefore, we propose that miRNA combinations could provide more efficient ways to target cancer stem cells. We have previously shown that miR-124, miR-128, and miR-137 function synergistically to regulate neurogenesis. We used a combination of these three miRNAs to treat glioma stem cells and showed that this treatment was much more effective than single miRNAs in disrupting cell proliferation and survival and promoting differentiation and response to radiation. Transcriptomic analyses indicated that transcription regulation, angiogenesis, metabolism, and neuronal differentiation are among the main biological processes affected by transfection of this miRNA combination. In conclusion, we demonstrated the value of using combinations of neurogenic miRNAs to disrupt cancer phenotypes and glioma stem cell growth. The synergistic effect of these three miRNA amplified the repression of oncogenic factors and the effect on cancer relevant pathways. Future therapeutic approaches would benefit from utilizing miRNA combinations, especially when targeting cancer-initiating cell populations.