MiRNA-miRNA synergistic network: construction via co-regulating functional modules and disease miRNA topological features

MGCNSS: miRNA-disease association prediction with multi-layer graph convolution and distance-based negative sample selection strategy

Identifying disease-associated microRNAs (miRNAs) could help understand the deep mechanism of diseases, which promotes the development of new medicine. Recently, network-based approaches have been widely proposed for inferring the potential associations between miRNAs and diseases. However, these approaches ignore the importance of different relations in meta-paths when learning the embeddings of miRNAs and diseases. Besides, they pay little attention to screening out reliable negative samples which is crucial for improving the prediction accuracy. In this study, we propose a novel approach named MGCNSS with the multi-layer graph convolution and high-quality negative sample selection strategy. Specifically, MGCNSS first constructs a comprehensive heterogeneous network by integrating miRNA and disease similarity networks coupled with their known association relationships. Then, we employ the multi-layer graph convolution to automatically capture the meta-path relations with different lengths in the heterogeneous network and learn the discriminative representations of miRNAs and diseases. After that, MGCNSS establishes a highly reliable negative sample set from the unlabeled sample set with the negative distance-based sample selection strategy. Finally, we train MGCNSS under an unsupervised learning manner and predict the potential associations between miRNAs and diseases. The experimental results fully demonstrate that MGCNSS outperforms all baseline methods on both balanced and imbalanced datasets. More importantly, we conduct case studies on colon neoplasms and esophageal neoplasms, further confirming the ability of MGCNSS to detect potential candidate miRNAs. The source code is publicly available on GitHub https://github.com/15136943622/MGCNSS/tree/master.

Plasma microRNA-195, -34c, and - 1246 as novel biomarkers for the diagnosis of trastuzumab-resistant HER2-positive breast cancer patients

Recently, miRNAs have been regarded as potential candidates for mediating therapeutic functions by targeting genes related to drug response. In this study, we suggested that plasma miRNAs may be correlated with response to trastuzumab in HER2-positive breast cancer patients. To determine whether miR-195, miR-23b-3p, miR-1246, and miR-34c-3p are involved in trastuzumab resistance, we screened their expressions in the BT-474 cell line, which was followed by plasma analysis from 20 trastuzumab-resistant HER2-positive breast cancer patients and 20 nonresistance subjects. Then, TargetScan, Pictar, and miRDB were applied to find the possible targets of the selected miRNAs. In addition, the expression status of admitted targets was evaluated. Our results showed that in resistant BT-474 cells, miR-1246, and miR-23b-3p were significantly upregulated, and miR-195-5p and miR-34c-3p were downregulated. In plasma analysis, we found miR-195-5p, miR-34c-3p, and miR-1246 meaningfully diminished in the resistant group, while the expression of miR-23b-3p was not statistically different. The expression levels of confirmed targets by qRT-PCR showed that the expression of RAF1, AKT3, c-MET, CCND1, PHLPP2, MYB, MAP2K1, and PTEN was significantly upregulated, while the expression of CCNG2 was significantly downregulated. The networks of miRNAs with their confirmed targets improved comprehension of miRNA-mediated therapeutic responses to trastuzumab and might be proposed for more characterization of miRNA functions. Moreover, these data indicated that miR-195-5p, miR-34c-3p, and miR-1246 could be possible biomarkers for prognosis and early detection of the trastuzumab-resistant group from the sensitive group of HER2-positive breast cancer patients.

Application of aptamer-drug delivery system in the therapy of breast cancer

Despite significant treatment advances, breast cancer remains the leading cause of cancer death in women. From the current treatment situation, in addition to developing chemoresistant tumours, distant organ metastasis, and recurrences, patients with breast cancer often have a poor prognosis. Aptamers as "chemical antibodies" may be a way to resolve this dilemma. Aptamers are single-stranded, non-coding oligonucleotides (DNA or RNA), resulting their many advantages, including stability for long-term storage, simplicity of synthesis and function, and low immunogenicity, a high degree of specificity and antidote. Aptamers have gained popularity as a method for diagnosing and treating specific tumors in recent years. This article introduces the application of ten different aptamer delivery systems in the treatment and diagnosis of breast cancer, and systematically reviews their latest research progress in breast cancer treatment and diagnosis. It provides a new direction for the clinical treatment of breast cancer.

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.

Stem Cells and Their Derivatives: An Implication for the Regeneration of Nonunion Fractures

Despite advances in biomedical research, fracture nonunion rates have remained stable throughout the years. Long-bone fractures have a high likelihood of nonunion, but the specific biological pathways involved in this severe consequence are unknown. Fractures often heal in an organized sequence, including the production of a hematoma and an early stage of inflammation, the development of a soft callus and hard callus, and eventually the stage of bone remodeling. Deficient healing can result in a persistent bone defect with instability, discomfort, and loss of function. In the treatment of nonunions, mesenchymal stem cells (MSCs) prove to be a promising and safe alternative to the standard therapeutic strategies. Moreover, novel scaffolds are being created in order to use a synergistic biomimetic technique to rapidly generate bone tissue. MSCs respond to acellular biomimetic matrices by regenerating bone. Extracellular vesicles (EVs) derived from MSCs have recently gained interest in the field of musculoskeletal regeneration. Although many of these techniques and technologies are still in the preclinical stage and have not yet been approved for use in humans, novel approaches to accelerate bone healing via MSCs and/or MSC derivatives have the potential to reduce the physical, economic, and social burdens associated with nonhealing fractures and bone defects. In this review, we focus on providing an up-to-date summary of recent scientific studies dealing with the treatment of nonunion fractures in clinical and preclinical settings employing MSC-based therapeutic techniques.

Surveying lncRNA-lncRNA cooperations reveals dominant effect on tumor immunity cross cancers

Long non-coding RNAs (lncRNAs) can crosstalk with each other by post-transcriptionally co-regulating genes involved in the same or similar functions; however, the regulatory principles and biological insights in tumor-immune are still unclear. Here, we show a multiple-step model to identify lncRNA-lncRNA immune cooperation based on co-regulating functional modules by integrating multi-omics data across 20 cancer types. Moreover, lncRNA immune cooperative networks (LICNs) are constructed, which are likely to modulate tumor-immune microenvironment by regulating immune-related functions. We highlight conserved and rewired network hubs which can regulate interactions between immune cells and tumor cells by targeting ligands and activating or inhibitory receptors such as PDCD1, CTLA4 and CD86. Immune cooperative lncRNAs (IC-lncRNAs) playing central roles in many cancers also tend to target known anticancer drug targets. In addition, these IC-lncRNAs tend to be highly expressed in immune cell populations and are significantly correlated with immune cell infiltration. The similar immune mechanisms cross cancers are revealed by the LICNs. Finally, we identify two subtypes of skin cutaneous melanoma with different immune context and prognosis based on IC-lncRNAs. In summary, this study contributes to a comprehensive understanding of the cooperative behaviours of lncRNAs and accelerating discovery of lncRNA-based biomarkers in cancer.

Identification of potential microRNA diagnostic panels and uncovering regulatory mechanisms in breast cancer pathogenesis

Early diagnosis of breast cancer (BC), as the most common cancer among women, increases the survival rate and effectiveness of treatment. MicroRNAs (miRNAs) control various cell behaviors, and their dysregulation is widely involved in pathophysiological processes such as BC development and progress. In this study, we aimed to identify potential miRNA biomarkers for early diagnosis of BC. We also proposed a consensus-based strategy to analyze the miRNA expression data to gain a deeper insight into the regulatory roles of miRNAs in BC initiation. Two microarray datasets (GSE106817 and GSE113486) were analyzed to explore the differentially expressed miRNAs (DEMs) in serum of BC patients and healthy controls. Utilizing multiple bioinformatics tools, six serum-based miRNA biomarkers (miR-92a-3p, miR-23b-3p, miR-191-5p, miR-141-3p, miR-590-5p and miR-190a-5p) were identified for BC diagnosis. We applied our consensus and integration approach to construct a comprehensive BC-specific miRNA-TF co-regulatory network. Using different combination of these miRNA biomarkers, two novel diagnostic models, consisting of miR-92a-3p, miR-23b-3p, miR-191-5p (model 1) and miR-92a-3p, miR-23b-3p, miR-141-3p, and miR-590-5p (model 2), were obtained from bioinformatics analysis. Validation analysis was carried out for the considered models on two microarray datasets (GSE73002 and GSE41922). The model based on similar network topology features, comprising miR-92a-3p, miR-23b-3p and miR-191-5p was the most promising model in the diagnosis of BC patients from healthy controls with 0.89 sensitivity, 0.96 specificity and area under the curve (AUC) of 0.98. These findings elucidate the regulatory mechanisms underlying BC and represent novel biomarkers for early BC diagnosis.

miRNA-mRNA-protein dysregulated network in COPD in women

Rationale: Chronic obstructive pulmonary disease (COPD) is a complex disease caused by a multitude of underlying mechanisms, and molecular mechanistic modeling of COPD, especially at a multi-molecular level, is needed to facilitate the development of molecular diagnostic and prognostic tools and efficacious treatments. Objectives: To investigate the miRNA-mRNA-protein dysregulated network to facilitate prediction of biomarkers and disease subnetwork in COPD in women. Measurements and Results: Three omics data blocks (mRNA, miRNA, and protein) collected from BAL cells from female current-smoker COPD patients, smokers with normal lung function, and healthy never-smokers were integrated with miRNA-mRNA-protein regulatory networks to construct a COPD-specific dysregulated network. Furthermore, downstream network topology, literature annotation, and functional enrichment analysis identified both known and novel disease-related biomarkers and pathways. Both abnormal regulations in miRNA-induced mRNA transcription and protein translation repression play roles in COPD. Finally, the let-7-AIFM1-FKBP1A pathway is highlighted in COPD pathology. Conclusion: For the first time, a comprehensive miRNA-mRNA-protein dysregulated network of primary immune cells from the lung related to COPD in females was constructed to elucidate specific biomarkers and disease pathways. The multi-omics network provides a new molecular insight from a multi-molecular aspect and highlights dysregulated interactions. The highlighted let-7-AIFM1-FKBP1A pathway also indicates new hypotheses of COPD pathology.

MiRNA/mRNA network topology in hepatitis virus B-related liver cirrhosis reveals miR-20a-5p/340-5p as hubs initiating fibrosis

Background

The pathophysiology of hepatitis B-related liver cirrhosis (HBV-LC) remains unclear. This study aimed to explore the disease mechanisms using topological analysis of the miRNA/mRNA network.

Methods

Paired miRNA/mRNA sequencing was performed with thirty-three peripheral blood mononuclear cell samples (LC, n = 9; chronic hepatitis B, n = 12; normal controls, n = 12) collected from a prospective cohort to identify the miRNA/mRNA network. Topological features and functional implications of the network were analyzed to capture pathophysiologically important miRNAs/mRNAs, whose expression patterns were confirmed in the validation group (LC, n = 15; chronic hepatitis B, n = 15; normal controls, n = 10), and functional potentials initiating fibrogenesis were demonstrated in vitro.

Results

The miRNA/mRNA network contained 3121 interactions between 158 differentially expressed (DE) miRNAs and 442 DE-mRNAs. The topological analysis identified a core module containing 99 miRNA/mRNA interactions and two hub nodes (miR-20a-5p/miR-340-5p), which connected to 75 DE-mRNAs. The expression pattern along the disease progression of the core module was found associated with a continuous increase in wound healing, inflammation, and leukocyte migration but an inflection of immune response and lipid metabolic regulation, consistent with the pathophysiology of HBV-LC. MiR-20a-5p/miR-340-5p were found involved in macrophage polarization and hepatic stellate cell (HSC) activation in vitro (THP-1, LX-2 cell lines), and their expression levels were confirmed in the validation group independently.

Conclusion

Topological analysis of the miRNA/mRNA network in HBV-LC revealed the association between fibrosis and miR-20a-5p/miR-340-5p involving initiating activations of macrophage and HSC. Further validations should be performed to confirm the HSC/macrophage activations and the interactions between miR-20a-5p/miR-340-5p and their potential targets, which may help to develop non-invasive prognostic markers or intervention targets for HBV-LC.

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.

Common gene expression patterns are observed in rice roots during associations with plant growth-promoting bacteria, Herbaspirillum seropedicae and Azospirillum brasilense

Non-legume plants such as rice and maize can form beneficial associations with plant growth-promoting bacteria (PGPB) such as Herbaspirillum seropedicae and Azospirillum brasilense. Several studies have shown that these PGPB promote plant growth via multiple mechanisms. Our current understanding of the molecular aspects and signaling between plants like rice and PGPB like Herbaspirillum seropedicae is limited. In this study, we used an experimental system where H. seropedicae could colonize the plant roots and promote growth in wild-type rice. Using this experimental setup, we identified 1688 differentially expressed genes (DEGs) in rice roots, 1 day post-inoculation (dpi) with H. seropedicae. Several of these DEGs encode proteins involved in the flavonoid biosynthetic pathway, defense, hormone signaling pathways, and nitrate and sugar transport. We validated the expression pattern of some genes via RT-PCR. Next, we compared the DEGs identified in this study to those we previously identified in rice roots during associations with another PGPB, Azospirillum brasilense. We identified 628 genes that were differentially expressed during both associations. The expression pattern of these genes suggests that some of these are likely to play a significant role(s) during associations with both H. seropedicae and A. brasilense and are excellent targets for future studies.

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.

miRCom: Tensor Completion Integrating Multi-View Information to Deduce the Potential Disease-Related miRNA-miRNA Pairs

MicroRNAs (miRNAs) are consistently capable of regulating gene expression synergistically in a combination mode and play a key role in various biological processes associated with the initiation and development of human diseases, which indicate that comprehending the synergistic molecular mechanism of miRNAs may facilitate understanding the pathogenesis of diseases or even overcome it. However, most existing computational methods had an incomprehensive acknowledge of the miRNA synergistic effect on the pathogenesis of complex diseases, or were hard to be extended to a large-scale prediction task of miRNA synergistic combinations for different diseases. In this article, we propose a novel tensor completion framework integrating multi-view miRNAs and diseases information, called miRCom, for the discovery of potential disease-associated miRNA-miRNA pairs. We first construct an incomplete three-order association tensor and several types of similarity matrices based on existing biological knowledge. Then, we formulate an objective function via performing the factorizations of coupled tensor and matrices simultaneously. Finally, we build an optimization schema by adopting the ADMM algorithm. After that, we obtain the prediction of miRNA-miRNA pairs for different diseases from the full tensor. The contrastive experimental results with other approaches verified that miRCom effectively identify the potential disease-related miRNA-miRNA pairs. Moreover, case study results further illustrated that miRNA-miRNA pairs have more biologically significance and prognostic value than single miRNAs.

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.

Network Approaches for Charting the Transcriptomic and Epigenetic Landscape of the Developmental Origins of Health and Disease

The early developmental phase is of critical importance for human health and disease later in life. To decipher the molecular mechanisms at play, current biomedical research is increasingly relying on large quantities of diverse omics data. The integration and interpretation of the different datasets pose a critical challenge towards the holistic understanding of the complex biological processes that are involved in early development. In this review, we outline the major transcriptomic and epigenetic processes and the respective datasets that are most relevant for studying the periconceptional period. We cover both basic data processing and analysis steps, as well as more advanced data integration methods. A particular focus is given to network-based methods. Finally, we review the medical applications of such integrative analyses.

A Multi-Level Iterative Bi-Clustering Method for Discovering miRNA Co-regulation Network of Abiotic Stress Tolerance in Soybeans

Although growing evidence shows that microRNA (miRNA) regulates plant growth and development, miRNA regulatory networks in plants are not well understood. Current experimental studies cannot characterize miRNA regulatory networks on a large scale. This information gap provides an excellent opportunity to employ computational methods for global analysis and generate valuable models and hypotheses. To address this opportunity, we collected miRNA-target interactions (MTIs) and used MTIs from Arabidopsis thaliana and Medicago truncatula to predict homologous MTIs in soybeans, resulting in 80,235 soybean MTIs in total. A multi-level iterative bi-clustering method was developed to identify 483 soybean miRNA-target regulatory modules (MTRMs). Furthermore, we collected soybean miRNA expression data and corresponding gene expression data in response to abiotic stresses. By clustering these data, 37 MTRMs related to abiotic stresses were identified, including stress-specific MTRMs and shared MTRMs. These MTRMs have gene ontology (GO) enrichment in resistance response, iron transport, positive growth regulation, etc. Our study predicts soybean MTRMs and miRNA-GO networks under different stresses, and provides miRNA targeting hypotheses for experimental analyses. The method can be applied to other biological processes and other plants to elucidate miRNA co-regulation mechanisms.

Transcriptome expression profiles reveal response mechanisms to drought and drought-stress mitigation mechanisms by exogenous glycine betaine in maize

Drought stress is one of the major abiotic stresses that limit growth, development and yield of maize crops. To better understand the responses of maize inbred lines with different levels of drought resistance and the molecular mechanism of exogenous glycine betaine (GB) in alleviating drought stress, the responses of two maize inbred lines to drought stress and to the stress-mitigating effects of exogenous GB were investigated. Seedling morphology, physiological and biochemical indexes, root cell morphology and root transcriptome expression profiles were compared between a drought-tolerant inbred line Chang 7-2 and drought-sensitive inbred line TS141. Plants of both lines were subjected to treatments of drought stress alone and drought stress with application of exogenous GB. The results showed that with the increase of drought treatment time, the growth and development of TS141 were inhibited, while those of Chang 7-2 were not significantly different from those of the control (no drought stress and GB). Compared with the corresponding data of the drought-stress group, every index measured from the two inbred lines indicated mitigating effects from exogenous GB, and TS141 produced stronger mitigating responses due to the GB. Transcriptome analysis showed that 562 differentially expressed genes (DEGs) were up-regulated and 824 DEGs were down-regulated in both inbred lines under drought stress. Due to the exogenous GB, 1061 DEGs were up-regulated and 424 DEGs were down-regulated in both lines. In addition, quantitative real-time polymerase chain reaction (qRT-PCR) was used to verify 10 DEGs screened from the different treatments. These results showed that the expression of 9 DEGs were basically consistent with their respective transcriptome expression profiles. The results of this study provide models of potential mechanisms of drought tolerance in maize as well as potential mechanisms of how exogenous GB may regulate drought tolerance.

Shedding light on the hidden human proteome expands immunopeptidome in cancer

Unrestrained cellular growth and immune escape of a tumor are associated with the incidental errors of the genome and transcriptome. Advances in next-generation sequencing have identified thousands of genomic and transcriptomic aberrations that generate variant peptides that assemble the hidden proteome, further expanding the immunopeptidome. Emerging next-generation sequencing technologies and a number of computational methods estimated the abundance of immune infiltration from bulk transcriptome have advanced our understanding of tumor microenvironments. Here, we will characterize several major types of tumor-specific antigens arising from single-nucleotide variants, insertions and deletions, gene fusion, alternative splicing, RNA editing and non-coding RNAs. Finally, we summarize the current state-of-the-art computational and experimental approaches or resources and provide an integrative pipeline for the identification of candidate tumor antigens. Together, the systematic investigation of the hidden proteome in cancer will help facilitate the development of effective and durable immunotherapy targets for cancer.

MicroRNA Alterations Induced in Human Skin by Diesel Fumes, Ozone, and UV Radiation

Epigenetic alterations are a driving force of the carcinogenesis process. MicroRNAs play a role in silencing mutated oncogenes, thus defending the cell against the adverse consequences of genotoxic damages induced by environmental pollutants. These processes have been well investigated in lungs; however, although skin is directly exposed to a great variety of environmental pollutants, more research is needed to better understand the effect on cutaneous tissue. Therefore, we investigated microRNA alteration in human skin biopsies exposed to diesel fumes, ozone, and UV light for over 24 h of exposure. UV and ozone-induced microRNA alteration right after exposure, while the peak of their deregulations induced by diesel fumes was reached only at the end of the 24 h. Diesel fumes mainly altered microRNAs involved in the carcinogenesis process, ozone in apoptosis, and UV in DNA repair. Accordingly, each tested pollutant induced a specific pattern of microRNA alteration in skin related to the intrinsic mechanisms activated by the specific pollutant. These alterations, over a short time basis, reflect adaptive events aimed at defending the tissue against damages. Conversely, whenever environmental exposure lasts for a long time, the irreversible alteration of the microRNA machinery results in epigenetic damage contributing to the pathogenesis of inflammation, dysplasia, and cancer induced by environmental pollutants.

Transcriptomics of the depressed and PTSD brain

Stress is the response of an organism to demands for change, yet excessive or chronic stress contributes to nearly all psychiatric disorders. The advent of high-throughput transcriptomic methods such as single cell RNA sequencing poses new opportunities to understand the neurobiology of stress, yet substantial barriers to understanding stress remain. Stress adaptation is an organismal survival mechanism conserved across all organisms, yet there is an infinity of potential stressful experiences. Unraveling shared and separate transcriptional programs for adapting to stressful experience remains a challenge, despite methodological and analytic advances. Here we review the state of the field focusing on the technologies used to study the transcriptome for the stress neurobiologist, and also attempt to identify central questions about the heterogeneity of stress for those applying transcriptomic approaches. We further explore how postmortem transcriptome studies aided by preclinical animal models are converging on common molecular pathways for adaptation to aversive experience. Finally, we discuss approaches to integrate large genomic datasets with human neuroimaging and other datasets.

Human microRNA similarity in breast cancer

MicroRNAs (miRNAs) play important roles in a variety of human diseases, including breast cancer. A number of miRNAs are up- and down-regulated in breast cancer. However, little is known about miRNA similarity and similarity network in breast cancer. Here, a collection of 272 breast cancer-associated miRNA precursors (pre-miRNAs) were utilized to calculate similarities of sequences, target genes, pathways and functions and construct a combined similarity network. Well-characterized miRNAs and their similarity network were highlighted. Interestingly, miRNA sequence-dependent similarity networks were not identified in spite of sequence–target gene association. Similarity networks with minimum and maximum number of miRNAs originate from pathway and mature sequence, respectively. The breast cancer-associated miRNAs were divided into seven functional classes (classes I–VII) followed by disease enrichment analysis and novel miRNA-based disease similarities were found. The finding would provide insight into miRNA similarity, similarity network and disease heterogeneity in breast cancer.

Single-cell Transcriptomes Reveal Characteristics of MicroRNA in Gene Expression Noise Reduction

Isogenic cells growing in identical environments show cell-to-cell variations because of the stochasticity in gene expression. High levels of variation or noise can disrupt robust gene expression and result in tremendous consequences for cell behaviors. In this work, we showed evidence from single-cell RNA sequencing data analysis that microRNAs (miRNAs) can reduce gene expression noise at the mRNA level in mouse cells. We identified that the miRNA expression level, number of targets, target pool abundance, and miRNA–target interaction strength are the key features contributing to noise repression. miRNAs tend to work together in cooperative subnetworks to repress target noise synergistically in a cell type-specific manner. By building a physical model of post-transcriptional regulation and observing in synthetic gene circuits, we demonstrated that accelerated degradation with elevated transcriptional activation of the miRNA target provides resistance to extrinsic fluctuations. Together, through the integrated analysis of single-cell RNA and miRNA expression profiles, we demonstrated that miRNAs are important post-transcriptional regulators for reducing gene expression noise and conferring robustness to biological processes.

MicroRNAs and nervous system diseases: network insights and computational challenges

The nervous system is one of the most complex biological systems, and nervous system disease (NSD) is a major cause of disability and mortality. Extensive evidence indicates that numerous dysregulated microRNAs (miRNAs) are involved in a broad spectrum of NSDs. A comprehensive review of miRNA-mediated regulatory will facilitate our understanding of miRNA dysregulation mechanisms in NSDs. In this work, we summarized currently available databases on miRNAs and NSDs, star NSD miRNAs, NSD spectrum width, miRNA spectrum width and the distribution of miRNAs in NSD sub-categories by reviewing approximately 1000 studies. In addition, we characterized miRNA-miRNA and NSD-NSD interactions from a network perspective based on miRNA-NSD benchmarking data sets. Furthermore, we summarized the regulatory principles of miRNAs in NSDs, including miRNA synergistic regulation in NSDs, miRNA modules and NSD modules. We also discussed computational challenges for identifying novel miRNAs in NSDs. Elucidating the roles of miRNAs in NSDs from a network perspective would not only improve our understanding of the precise mechanism underlying these complex diseases, but also provide novel insight into the development, diagnosis and treatment of NSDs.

Establishment of Repertoire of Placentome-Associated MicroRNAs and Their Appearance in Blood Plasma Could Identify Early Establishment of Pregnancy in Buffalo (Bubalus bubalis)

Precise early pregnancy diagnosis in dairy animals is of utmost importance for an efficient dairy production system. Not detecting a dairy animal pregnant sufficiently early after the breeding results to extending the unproductive time of their milk production cycle and causes substantial economic loss for a dairy producer. At present, the most conventional and authentic pregnancy confirmation practice in cows and buffaloes is rectal palpation of the reproductive organs at Days 35–40 after insemination, which sometime leads to considering an animal as false pregnant. Other alternative methods available for early pregnancy diagnosis lack either accuracy or reproducibility or require elaborate instrumentation and laboratory setup not feasible to practice at farmers’ doorstep. The present study was aimed at establishment of the microRNA (miRNA) repertoire of the placentome in buffaloes, which could capture the event of the cross talk between a growing embryo and a dam, through fetal cotyledons and maternal caruncles, and thus could hint at the early pregnancy establishment event in ruminants. Total RNA was isolated from buffalo placentome tissues during early stages of pregnancy (at Day < 25 and Days 30–35), and global small RNA analysis was performed by using Illumina single-end read chemistry and Bubalus bubalis genome. A total of 2,199 miRNAs comprising 1,620 conserved and 579 non-conserved miRNAs were identified. Stringent functional miRNA selection criteria could predict 20 miRNAs worth evaluating for their abundance in the plasma of pregnant, non-pregnant, cyclic non-bred, and non-cyclic prepubertal animals. Eight of them (viz., miR-195-5p, miR-708-3p, miR-379-5p, miR-XX1, miR-XX2, miR-130a-3p, miR-200a-3p, and miR-27) displayed typical abundance patterns in the plasma samples of the animals on Day 19 as well as Day 25 post-insemination, thus making them ambiguous candidates for early pregnancy detection. Similarly, higher abundance of miR-200a-3p and miR130a-3p in non-pregnant animals was indicative of their utility for detecting the animals as not pregnant. Most interestingly, miR-XX1 and miR-XX2 were very characteristically abundant only in pregnant animals. In silico target prediction analysis confirmed that these two miRNAs are important regulators of cyclooxygenase-2 (COX-2) and cell adhesion molecule-2 (CADM-2), both of which play a significant role in the implantation process during feto-maternal cross talk. We interpret that circulatory miR-XX1 and miR-XX2 in blood plasma could be the potential biomarkers for early pregnancy detection in buffaloes.

CDX2 inducible microRNAs sustain colon cancer by targeting multiple DNA damage response pathway factors

Meta-analysis of transcripts in colon adenocarcinoma patient tissues led to the identification of a DNA damage responsive miR signature called DNA damage sensitive miRs (DDSMs). DDSMs were experimentally validated in the cancerous colon tissues obtained from an independent cohort of colon cancer patients and in multiple cellular systems with high levels of endogenous DNA damage. All the tested DDSMs were transcriptionally upregulated by a common intestine-specific transcription factor, CDX2. Reciprocally, DDSMs were repressed via the recruitment of HDAC1/2-containing complexes onto the CDX2 promoter. These miRs downregulated multiple key targets in the DNA damage response (DDR) pathway, namely BRCA1, ATM, Chk1 (also known as CHEK1) and RNF8. CDX2 directly regulated the DDSMs, which led to increased tumor volume and metastasis in multiple preclinical models. In colon cancer patient tissues, the DDSMs negatively correlated with BRCA1 levels, were associated with decreased probability of survival and thereby could be used as a prognostic biomarker. This article has an associated First Person interview with the first author of the paper.

Prediction and Boolean logical modelling of synergistic microRNA regulatory networks during reprogramming of male germline pluripotent stem cells

Unipotent male germline stem (GS) cells can undergo spontaneous reprogramming to germline pluripotent stem (GPS) cells during in vitro culture. In our previous study, we proposed a Boolean logical model of gene regulatory network (GRN) during reprogramming of GS cells to GPS cells. This study was designed to predict and model synergistic microRNA (miRNA) regulatory network during reprogramming of GS cells into GPS cells. The miRNAs targeting differentially expressed genes (DEGs) among GS and GPS cells were predicted by a novel Gene Ontology (GO) enrichment analysis to construct miRNA synergistic networks (MSN) and identify regulatory miRNA modules. Qualitative Boolean logical model of synergistic miRNAs and its regulated genes was then constructed by considering discrete, asynchronous, multivalued logical formalism using the GINsim modeling and simulation tools. Topology, functional and community overlap studies revealed that mmu-miR-200b-3p, mmu-miR-429-3p and mmu-miR-141-3p, mmu-miR-200a-3p and mmu-miR-200c-3p in MSN belongs to the family of miR-200/429/141 and conjectured to control the pluripotency and reprogramming by promoting Mesenchymal to Epithelial Transition (MET). Synergistic network involving mmu-miR-20b-5p, mmu-miR-20a-5p, mmu-miR-106a-5p, mmu-miR-106b-5p, and mmu-miR-17-5p were found to be essential for the maintenance of GS cells. Logical miRNA regulatory network modelling showed that synergistic miRNAs regulates the gene dynamics of MET during GS-GPS reprogramming, as confirmed by perturbation analysis. Taken together, our study predicted novel synergistic miRNAs involved in the regulation of reprogramming and pluripotency in GPS cells. The Boolean logical model of synergistic miRNAs regulatory network further confirms our previous study that gene dynamics of MET regulates GS-GPS reprogramming.

Role of microRNA-335 carried by bone marrow mesenchymal stem cells-derived extracellular vesicles in bone fracture recovery

Mesenchymal stem cells (MSCs) have the potential to reduce healing time and treat nonunion in fracture patients. In this study, bone marrow MSCs-derived extracellular vesicles (B-EVs) were firstly extracted and identified. CD9-/- and normal mice were enrolled for the establishment of fracture models and then injected with B-EVs. Osteoblast differentiation and fracture recovery were estimated. The levels of osteoblast-related genes were detected, and differentially expressed microRNAs (miRs) in B-EVs-treated normal fracture mice were screened and verified. The downstream mechanisms of miR were predicted and assessed. The loss-of functions of miR-335 in B-EV and gain-of-functions of VapB were performed in animal and cell experiments to evaluate their roles in bone fracture. Collectively, B-EVs promoted bone fracture recovery and osteoblast differentiation by releasing miR-335. miR-335 downregulation in B-EVs impaired B-EV functions in fracture recovery and osteoblast differentiation. miR-335 could target VapB, and VapB overexpression reversed the effects of B-EVs on osteoblast differentiation. B-EV treatment activated the Wnt/β-catenin pathway in fracture mice and osteoblasts-like cells. Taken together, the study suggested that B-EVs carry miR-335 to promote bone fracture recovery via VapB and the Wnt/β-catenin pathway. This study may offer insights into bone fracture treatment.

Construction of a TF-miRNA-gene feed-forward loop network predicts biomarkers and potential drugs for myasthenia gravis

Myasthenia gravis (MG) is an autoimmune disease and the most common type of neuromuscular disease. Genes and miRNAs associated with MG have been widely studied; however, the molecular mechanisms of transcription factors (TFs) and the relationship among them remain unclear. A TF–miRNA–gene network (TMGN) of MG was constructed by extracting six regulatory pairs (TF–miRNA, miRNA–gene, TF–gene, miRNA–TF, gene–gene and miRNA–miRNA). Then, 3/4/5-node regulatory motifs were detected in the TMGN. Then, the motifs with the highest Z-score, occurring as 3/4/5-node composite feed-forward loops (FFLs), were selected as statistically significant motifs. By merging these motifs together, we constructed a 3/4/5-node composite FFL motif-specific subnetwork (CFMSN). Then, pathway and GO enrichment analyses were performed to further elucidate the mechanism of MG. In addition, the genes, TFs and miRNAs in the CFMSN were also utilized to identify potential drugs. Five related genes, 3 TFs and 13 miRNAs, were extracted from the CFMSN. As the most important TF in the CFMSN, MYC was inferred to play a critical role in MG. Pathway enrichment analysis showed that the genes and miRNAs in the CFMSN were mainly enriched in pathways related to cancer and infections. Furthermore, 21 drugs were identified through the CFMSN, of which estradiol, estramustine, raloxifene and tamoxifen have the potential to be novel drugs to treat MG. The present study provides MG-related TFs by constructing the CFMSN for further experimental studies and provides a novel perspective for new biomarkers and potential drugs for MG.

Dynamic Expression of m6A Regulators During Multiple Human Tissue Development and Cancers

N6-methyladenosine (m⁶A) plays critical roles in human development and cancer progression. However, our knowledge regarding the dynamic expression of m⁶A regulators during human tissue development is still lacking. Here, we comprehensively analyzed the dynamic expression alterations of m⁶A regulators during seven tissue development and eight cancer types. We found that m⁶A regulators globally exhibited decreased expression during development. In addition, IGF2BP1/2/3 (insulinlike growth factor 2 MRNA-binding protein 1/2/3) exhibited reverse expression pattern in cancer progression, suggesting an oncofetal reprogramming in cancer. The expressions of IGF2BP1/2/3 were regulated by genome alterations, particularly copy number amplification in cancer. Clinical association analysis revealed that higher expressions of IGF2BP1/2/3 were associated with worse survival of cancer patients. Finally, we found that genes significantly correlated with IGF2BP1/2/3 were significantly enriched in cancer hallmark-related pathways. In summary, dynamic expression analysis will guide both mechanistic and therapeutic roles of m⁶A regulators during tissue development and cancer progression.

Network and Pathway-Based Integrated Analysis Identified a Novel "rs28457673-miR-15/16/195/424/497 Family-IGF1R-MAPK Signaling Pathway" Axis Associated With Post-stroke Depression

Single-nucleotide polymorphisms (SNPs) of microRNA (miRNA) (miRSNP) are SNPs located on miRNA genes or miRNA target sites, which have been supposed to be involved in the development of central nervous system diseases by interfering with miRNA-mediated regulatory functions. However, the association of miRSNP with post-stroke depression (PSD) has not been well-investigated. In this study, we collected 54 PSD risk genes via manual literature-mining and integrated PSD-related risk pathways based on multiple public databases. Furthermore, we systematically screened candidate functional miRSNPs for PSD and integrated a miRSNP-based PSD-associated pathway network, which included 99 miRNAs that target 12 PSD risk pathways. We also reviewed the association between three risk pathways and PSD pathogenetic mechanism thoroughly. Combining literature mining and network analysis, our results proposed an underlying mechanism of "miRSNP → miRNA → risk gene → pathway" axis effects on PSD pathogenesis, especially for rs28457673 (miR-15/16/195/424/497 family) → IGF1R → hsa04010 (MAPK signaling pathway). Our studies revealed a functional role in genetic modifier at the system level in the pathogenesis of PSD, which might provide further information for the miRSNP studies in PSD.

Long noncoding RNA SNHG14 promotes hepatocellular carcinoma progression by regulating miR-876-5p/SSR2 axis

Background

Aberrant expressions of long noncoding RNAs (lncRNAs) have been demonstrated to be related to the progress of HCC. The mechanisms that SNHG14 has participated in the development of HCC are obscure.

Methods

Quantitative real-time PCR (qRT-PCR) was used to measure the lncRNA, microRNA and mRNA expression level. Cell migration, invasion and proliferation ability were evaluated by transwell and CCK8 assays. The ceRNA regulatory mechanism of SNHG14 was evaluated by RNA immunoprecipitation (RIP) and dual luciferase reporter assay. Tumorigenesis mouse model was used to explore the roles of miR-876-5p in vivo. The protein levels of SSR2 were measured by western blot assay.

Results

In this study, we demonstrated that SNHG14 was highly expressed in HCC tissues, meanwhile, the elevated expression of SNHG14 predicted poor prognosis in patients with HCC. SNHG14 promoted proliferation and metastasis of HCC cells. We further revealed that SNHG14 functioned as a competing endogenous RNA (ceRNA) for miR-876-5p and that SSR2 was a downstream target of miR-876-5p in HCC. Transwell, CCK8 and animal experiments exhibited miR-876-5p inhibited HCC progression in vitro and in vivo. By conducting rescue experiments, we found the overexpression of SSR2 or knocking down the level of miR-876-5p could reverse the suppressive roles of SNHG14 depletion in HCC.

Conclusion

SNHG14 promotes HCC progress by acting as a sponge of miR-876-5p to regulate the expression of SSR2 in HCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13046-021-01838-5.

Triple negative breast cancer in the era of miRNA

The objective of this review is to elucidate the role of miRNAs in triple negative breast cancer (TNBC). To achieve our goal, we searched databases such as PubMed, ScienceDirect, Springer, Web of Science and Scopus. We retrieved up to 1233 articles, based a rigorous selection criterion, only 197 articles were extensively reviewed. We selected articles only addressing TNBC, but not other types of breast cancer, with the employed approach being miRNA analysis and/or profiling. Our extensive review resulted in grouping of miRNAs into categories in which specific members of miRNAs have roles in specific mechanism in TNBC i.e., carcinogenesis, invasion, metastasis, apoptosis, diagnosis, prognosis, and treatment. TNBC is an aggressive subtype of breast cancer; therefore, different approaches for accurate diagnosis, prognosis and treatment are needed. In this review we summarize the up-to-date miRNA profiling, prognostic, and therapeutic findings that add to the route of controlling TNBC.

Identifying Key MicroRNAs Targeted by Narenmandula in a Rodent Nephropathy Model

Background

Untreated nephropathy can progress to renal failure. The traditional Mongolian remedy Narenmandula regulates the kidney “yang.” This study aimed to identify key microRNAs (miRNAs) targeted by Narenmandula in a rat model of nephropathy.

Methods

Fifteen rats exhibiting normal renal function were randomized to three study arms. Nephropathy was induced in n = 10 rats using doxorubicin hydrochloride, followed by either Narenmandula treatment (treatment group) or no treatment (control group). In n = 5 rats, no doxorubicin was given and renal function remained unchanged (healthy group). Microarray analysis identified miRNAs which were differentially expressed (DE-miRNAs) between groups. Target genes of DE-miRNAs were predicted using miRWalk version 2.0, followed by enrichment analysis using DAVID, and construction of the miRNA coregulatory network using Cytoscape.

Results

Nephropathy was successfully induced, with doxorubicin resulting in differential expression of 3645 miRNAs (1324 upregulated and 2321 downregulated). Narenmandula treatment induced differential expression of a total of 159 miRNAs (102 upregulated and 57 downregulated). Upregulated DE-miRNAs (e.g., miR-497-5p, miR-195-5p, miR-181a-5p, miR-181c-5p, and miR-30e-5p) and downregulated DE-miRNAs (e.g., miR-330-3p and miR-214-3p) regulated a high number of target genes. Moreover, the miRNA pairs (e.g., miR-195-5p—miR-497-5p, miR-181a-5p—miR-181c-5p, and miR-30e-5p—miR-30a-5p) coregulated a high number of genes. Enrichment analysis indicated functional synergy between miR-30e-5p—miR-30a-3p, miR-34a-5p—miR-30e-5p, miR-30e-5p—miR-195-3p, and miR-30a-3p—miR-195-3p pairs.

Conclusion

Narenmandula may modulate doxorubicin-induced nephropathy via targeting miR-497-5p, miR-195-5p, miR-181a-5p, miR-181c-5p, miR-30e-5p, miR-330-3p, miR-214-3p, miR-34a-5p, miR-30a-3p, and miR-30a-5p.

Underpinning miRNA-miRNA co-functional interaction patterns in the metabolism of Oryza sativa by genome-scale network analysis

MicroRNA (miRNA) is a class of non-coding small RNAs, which post-transcriptionally regulate a large number of genes and are now known to be important regulators in a wide variety of biological processes including metabolism. Thus, for better understanding these complex biological networks, and to derive their significance and inter-dependency, a systems biology approach enables us to explore and draw vital insights into these molecular network architectures. In this study, we aimed to understand the significance of synergistic miRNA-miRNA interactions in rice by constructing and analysing metabolic networks. The construction of the network involves target gene prediction of experimentally verified miRNAs of rice and then appending associated metabolic pathways to the network. A genome-scale miRNA-miRNA co-functional network (MFSN) is constructed based on co-regulatory interactions among the miRNAs and common target genes by applying transformational procedures. The analysis of the extracted MFSN modules identifies co-regulated target genes that are associated with corresponding interconnected metabolic pathways such as VALDEG-PWY (L-valine degradation I pathway was found to be targeted by multiple miRNA families, such as osa-miR812, osa-miR818, osa-miR821, and osa-miR5799 families while another pathway that was found to be associated with multiple miRNA families was PWY-6952 (glycerophosphodiester degradation pathway), PWY-6952 was found to be targeted by osa-miR812, osa-miR11344 and osa-miR5801 families. Such extensive study will help in systematically elucidating the regulatory networks in metabolism of rice, which in turn can be utilised to devise strategies for crop improvement and novel cultivar development.

Non-Coding RNAs, a Novel Paradigm for the Management of Gastrointestinal Stromal Tumors

Gastrointestinal stromal tumors (GISTs) are the most common mesenchymal malignancies found in the gastrointestinal tract. At a molecular level, most GISTs are characterized by gain-of-function mutations in V-Kit Hardy-Zuckerman 4 Feline Sarcoma Viral Oncogene Homolog (KIT) and Platelet Derived Growth Factor Receptor Alpha (PDGFRA), leading to constitutive activated signaling through these receptor tyrosine kinases, which drive GIST pathogenesis. In addition to surgery, treatment with the tyrosine kinase inhibitor imatinib forms the mainstay of GIST treatment, particularly in the advanced setting. Nevertheless, the majority of GISTs develop imatinib resistance. Biomarkers that indicate metastasis, drug resistance and disease progression early on could be of great clinical value. Likewise, novel treatment strategies that overcome resistance mechanisms are equally needed. Non-coding RNAs, particularly microRNAs, can be employed as diagnostic, prognostic or predictive biomarkers and have therapeutic potential. Here we review which non-coding RNAs are deregulated in GISTs, whether they can be linked to specific clinicopathological features and discuss how they can be used to improve the clinical management of GISTs.

MiRACLe: an individual-specific approach to improve microRNA-target prediction based on a random contact model

Deciphering microRNA (miRNA) targets is important for understanding the function of miRNAs as well as miRNA-based diagnostics and therapeutics. Given the highly cell-specific nature of miRNA regulation, recent computational approaches typically exploit expression data to identify the most physiologically relevant target messenger RNAs (mRNAs). Although effective, those methods usually require a large sample size to infer miRNA-mRNA interactions, thus limiting their applications in personalized medicine. In this study, we developed a novel miRNA target prediction algorithm called miRACLe (miRNA Analysis by a Contact modeL). It integrates sequence characteristics and RNA expression profiles into a random contact model, and determines the target preferences by relative probability of effective contacts in an individual-specific manner. Evaluation by a variety of measures shows that fitting TargetScan, a frequently used prediction tool, into the framework of miRACLe can improve its predictive power with a significant margin and consistently outperform other state-of-the-art methods in prediction accuracy, regulatory potential and biological relevance. Notably, the superiority of miRACLe is robust to various biological contexts, types of expression data and validation datasets, and the computation process is fast and efficient. Additionally, we show that the model can be readily applied to other sequence-based algorithms to improve their predictive power, such as DIANA-microT-CDS, miRanda-mirSVR and MirTarget4. MiRACLe is publicly available at https://github.com/PANWANG2014/miRACLe.

Construction and Analysis of Human Diseases and Metabolites Network

The relationship between aberrant metabolism and the initiation and progression of diseases has gained considerable attention in recent years. To gain insights into the global relationship between diseases and metabolites, here we constructed a human diseases-metabolites network (HDMN). Through analyses based on network biology, the metabolites associated with the same disorder tend to participate in the same metabolic pathway or cascade. In addition, the shortest distance between disease-related metabolites was shorter than that of all metabolites in the Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic network. Both disease and metabolite nodes in the HDMN displayed slight clustering phenomenon, resulting in functional modules. Furthermore, a significant positive correlation was observed between the degree of metabolites and the proportion of disease-related metabolites in the KEGG metabolic network. We also found that the average degree of disease metabolites is larger than that of all metabolites. Depicting a comprehensive characteristic of HDMN could provide great insights into understanding the global relationship between disease and metabolites.

Pathway perturbations in signaling networks: Linking genotype to phenotype

Genes and gene products interact with each other to form signal transduction networks in the cell. The interactome networks are under intricate regulation in physiological conditions, but could go awry upon genome instability caused by genetic mutations. In the past decade with next-generation sequencing technologies, an increasing number of genomic mutations have been identified in a variety of disease patients and healthy individuals. As functional and systematic studies on these mutations leap forward, they begin to reveal insights into cellular homeostasis and disease mechanisms. In this review, we discuss recent advances in the field of network biology and signaling pathway perturbations upon genomic changes, and highlight the success of various omics datasets in unraveling genotype-to-phenotype relationships.

Identifying miRNA synergism using multiple-intervention causal inference

BACKGROUND

Studying multiple microRNAs (miRNAs) synergism in gene regulation could help to understand the regulatory mechanisms of complicated human diseases caused by miRNAs. Several existing methods have been presented to infer miRNA synergism. Most of the current methods assume that miRNAs with shared targets at the sequence level are working synergistically. However, it is unclear if miRNAs with shared targets are working in concert to regulate the targets or they individually regulate the targets at different time points or different biological processes. A standard method to test the synergistic activities is to knock-down multiple miRNAs at the same time and measure the changes in the target genes. However, this approach may not be practical as we would have too many sets of miRNAs to test.

RESULTS

n this paper, we present a novel framework called miRsyn for inferring miRNA synergism by using a causal inference method that mimics the multiple-intervention experiments, e.g. knocking-down multiple miRNAs, with observational data. Our results show that several miRNA-miRNA pairs that have shared targets at the sequence level are not working synergistically at the expression level. Moreover, the identified miRNA synergistic network is small-world and biologically meaningful, and a number of miRNA synergistic modules are significantly enriched in breast cancer. Our further analyses also reveal that most of synergistic miRNA-miRNA pairs show the same expression patterns. The comparison results indicate that the proposed multiple-intervention causal inference method performs better than the single-intervention causal inference method in identifying miRNA synergistic network.

CONCLUSIONS

Taken together, the results imply that miRsyn is a promising framework for identifying miRNA synergism, and it could enhance the understanding of miRNA synergism in breast cancer.

System level characterization of small molecule drugs and their affected long noncoding RNAs

Long noncoding RNAs (lncRNAs) have multiple regulatory roles and are involved in many human diseases. A potential therapeutic strategy based on targeting lncRNAs was recently developed. To gain insight into the global relationship between small molecule drugs and their affected lncRNAs, we constructed a small molecule lncRNA network consisting of 1206 nodes (1033 drugs and 173 lncRNAs) and 4770 drug-lncRNA associations using LNCmap, which reannotated the microarray data from the Connectivity Map (CMap) database. Based on network biology, we found that the connected drug pairs tended to share the same targets, indications, and side effects. In addition, the connected drug pairs tended to have a similar structure. By inferring the functions of lncRNAs through their co-expressing mRNAs, we found that lncRNA functions related to the modular interface were associated with the mode of action or side effects of the corresponding connected drugs, suggesting that lncRNAs may directly/indirectly participate in specific biological processes after drug administration. Finally, we investigated the tissue-specificity of drug-affected lncRNAs and found that some kinds of drugs tended to have a broader influence (e.g. antineoplastic and immunomodulating drugs), whereas some tissue-specific lncRNAs (nervous system) tended to be affected by multiple types of drugs.

Identification of microRNA clusters cooperatively acting on epithelial to mesenchymal transition in triple negative breast cancer

MicroRNAs play important roles in many biological processes. Their aberrant expression can have oncogenic or tumor suppressor function directly participating to carcinogenesis, malignant transformation, invasiveness and metastasis. Indeed, miRNA profiles can distinguish not only between normal and cancerous tissue but they can also successfully classify different subtypes of a particular cancer. Here, we focus on a particular class of transcripts encoding polycistronic miRNA genes that yields multiple miRNA components. We describe 'clustered MiRNA Master Regulator Analysis (ClustMMRA)', a fully redesigned release of the MMRA computational pipeline (MiRNA Master Regulator Analysis), developed to search for clustered miRNAs potentially driving cancer molecular subtyping. Genomically clustered miRNAs are frequently co-expressed to target different components of pro-tumorigenic signaling pathways. By applying ClustMMRA to breast cancer patient data, we identified key miRNA clusters driving the phenotype of different tumor subgroups. The pipeline was applied to two independent breast cancer datasets, providing statistically concordant results between the two analyses. We validated in cell lines the miR-199/miR-214 as a novel cluster of miRNAs promoting the triple negative breast cancer (TNBC) phenotype through its control of proliferation and EMT.

Challenges in microRNAs' targetome prediction and validation

MicroRNAs (miRNAs) are small RNA molecules with important roles in post-transcriptional regulation of gene expression. In recent years, the predicted number of miRNAs has skyrocketed, largely as a consequence of high-throughput sequencing technologies becoming ubiquitous. This dramatic increase in miRNA candidates poses multiple challenges in terms of data deposition, curation, and validation. Although multiple databases containing miRNA annotations and targets have been developed, ensuring data quality by validating miRNA-target interactions requires the efforts of the research community. In order to generate databases containing biologically active miRNAs, it is imperative to overcome a multitude of hurdles, including restricted miRNA expression patterns, distinct miRNA biogenesis machineries, and divergent miRNA-mRNA interaction dynamics. In the present review, we discuss recent advances and limitations in miRNA prediction, identification, and validation. Lastly, we focus on the most enriched neuronal miRNA, miR-124, and its gene regulatory network in human neurons, which has been revealed using a combined computational and experimental approach.

Understanding the Modus Operandi of MicroRNA Regulatory Clusters

MicroRNAs (miRNAs) are non-coding RNAs that regulate a wide range of biological pathways by post-transcriptionally modulating gene expression levels. Given that even a single miRNA may simultaneously control several genes enrolled in multiple biological functions, one would expect that these tiny RNAs have the ability to properly sort among distinctive cellular processes to drive protein production. To test this hypothesis, we scrutinized previously published microarray datasets and clustered protein-coding gene expression profiles according to the intensity of fold-change levels caused by the exogenous transfection of 10 miRNAs (miR-1, miR-7, miR-9, miR-124, miR-128a, miR-132, miR-133a, miR-142, miR-148b, miR-181a) in a human cell line. Through an in silico functional enrichment analysis, we discovered non-randomic regulatory patterns, proper of each cluster identified. We demonstrated that miRNAs are capable of equivalently modulate the expression signatures of target genes in regulatory clusters according to the biological function they are assigned to. Moreover, target prediction analysis applied to ten vertebrate species, suggest that such miRNA regulatory modus operandi is evolutionarily conserved within vertebrates. Overall, we discovered a complex regulatory cluster-module strategy driven by miRNAs, which relies on the controlled intensity of the repression over distinct targets under specific biological contexts. Our discovery helps to clarify the mechanisms underlying the functional activity of miRNAs and makes it easier to take the fastest and most accurate path in the search for the functions of miRNAs in any distinct biological process of interest.

CeRNA network analysis and functional enrichment of salt sensitivity of blood pressure by weighted-gene co-expression analysis

Background

Salt sensitivity of blood pressure (SSBP) is an independent risk factor for cardiovascular disease. The pathogenic mechanisms of SSBP are still uncertain. This study aimed to construct the co-regulatory network of SSBP and data mining strategy based on the competitive endogenous RNA (ceRNA) theory.

Methods

LncRNA and mRNA microarray was performed to screen for candidate RNAs. Four criteria were used to select the potential differently expressed RNAs. The weighted correlation network analysis (WGCNA) package of R software and target miRNA and mRNA prediction online databases were used to construct the ceRNA co-regulatory network and discover the pathways related to SSBP. Gene ontology enrichment, gene set enrichment analysis (GSEA) and KEGG pathway analysis were performed to explore the functions of hub genes in networks.

Results

There were 274 lncRNAs and 36 mRNAs that differently expressed between salt-sensitive and salt-resistant groups (P < 0.05). Using WGCNA analysis, two modules were identified (blue and turquoise). The blue module had a positive relationship with salt-sensitivity (R = 0.7, P < 0.01), high-density lipoprotein (HDL) (R = 0.53, P = 0.02), and total cholesterol (TC) (R = 0.55, P = 0.01). The turquoise module was positively related with triglyceride (TG) (R = 0.8, P < 0.01) and low-density lipoprotein (LDL) (R = 0.54, P = 0.01). Furthermore, 84 ceRNA loops were identified and one loop may be of great importance for involving in pathogenesis of SSBP. KEGG analysis showed that differently expressed mRNAs were mostly enriched in the SSBP-related pathways. However, the enrichment results of GSEA were mainly focused on basic physical metabolic processes.

Conclusion

The microarray data mining process based on WGCNA co-expression analysis had identified 84 ceRNA loops that closely related with known SSBP pathogenesis. The results of our study provide implications for further understanding of the pathogenesis of SSBP and facilitate the precise diagnosis and therapeutics.

Systems biology-based investigation of cooperating microRNAs as monotherapy or adjuvant therapy in cancer

MicroRNAs (miRNAs) are short, noncoding RNAs that regulate gene expression by suppressing mRNA translation and reducing mRNA stability. A miRNA can potentially bind many mRNAs, thereby affecting the expression of oncogenes and tumor suppressor genes as well as the activity of whole pathways. The promise of miRNA therapeutics in cancer is to harness this evolutionarily conserved mechanism for the coordinated regulation of gene expression, and thus restoring a normal cell phenotype. However, the promiscuous binding of miRNAs can provoke unwanted off-target effects, which are usually caused by high-dose single-miRNA treatments. Thus, it is desirable to develop miRNA therapeutics with increased specificity and efficacy. To achieve that, we propose the concept of miRNA cooperativity in order to exert synergistic repression on target genes, thus lowering the required total amount of miRNAs. We first review miRNA therapies in clinical application. Next, we summarize the knowledge on the molecular mechanism and biological function of miRNA cooperativity and discuss its application in cancer therapies. We then propose and discuss a systems biology approach to investigate miRNA cooperativity for the clinical setting. Altogether, we point out the potential of miRNA cooperativity to reduce off-target effects and to complement conventional, targeted, or immune-based therapies for cancer.

MERIT: Systematic Analysis and Characterization of Mutational Effect on RNA Interactome Topology

The interaction between RNA-binding proteins (RBPs) and RNA plays an important role in regulating cellular function. However, decoding genome-wide protein-RNA regulatory networks as well as how cancer-related mutations impair RNA regulatory activities in hepatocellular carcinoma (HCC) remains mostly undetermined. We explored the genetic alteration patterns of RBPs and found that deleterious mutations are likely to occur on the surface of RBPs. We then constructed protein-RNA interactome networks by integration of target binding screens and expression profiles. Network analysis highlights regulatory principles among interacting RBPs. In addition, somatic mutations selectively target functionally important genes (cancer genes, core fitness genes, or conserved genes) and perturb the RBP-gene regulatory networks in cancer. These regulatory patterns were further validated using independent data. A computational method (Mutational Effect on RNA Interactome Topology) and a web-based, user-friendly resource were further proposed to analyze the RBP-gene regulatory networks across cancer types. Pan-cancer analysis also suggests that cancer cells selectively target "vulnerability" genes to perturb protein-RNA interactome that is involved in cancer hallmark-related functions. Specifically, we experimentally validated four pairs of RBP-gene interactions perturbed by mutations in HCC, which play critical roles in cell proliferation. Based on the expression of perturbed RBP and target genes, we identified three subtypes of HCC with different survival rates. Conclusion: Our results provide a valuable resource for characterizing somatic mutation-perturbed protein-RNA regulatory networks in HCC, yielding valuable insights into the genotype-phenotype relationships underlying human cancer, and potential biomarkers for precision medicine.

Computationally Modeling ncRNA-ncRNA Crosstalk

Our understanding of complex gene regulatory networks have been improved by the discovery of ncRNA-ncRNA crosstalk in normal and disease-specific physiological conditions. Previous studies have proposed numerous approaches for constructing ncRNA-ncRNA networks via ncRNA-mRNA regulation, functional information, or phenomics alone, or by combining heterogeneous data. Furthermore, it has been shown that ncRNA-ncRNA crosstalk can be rewired in different tissues or specific diseases. Therefore, it is necessary to integrate transcriptome data to construct context-specific ncRNA-ncRNA networks. In this chapter, we elucidated the commonly used ncRNA-ncRNA network modeling methods, and highlighted the need to integrate heterogeneous multi-mics data. Finally, we suggest future directions for studies of ncRNAs crosstalk. This comprehensive description and discussion elucidated in this chapter will provide constructive insights into ncRNA-ncRNA crosstalk.