Transcription factor and microRNA-regulated network motifs for cancer and signal transduction networks

Network subgraph-based approach for analyzing and comparing molecular networks

Molecular networks are built up from genetic elements that exhibit feedback interactions. Here, we studied the problem of measuring the similarity of directed networks by proposing a novel alignment-free approach: the network subgraph-based approach. Our approach does not make use of randomized networks to determine modular patterns embedded in a network, and this method differs from the network motif and graphlet methods. Network similarity was quantified by gauging the difference between the subgraph frequency distributions of two networks using Jensen-Shannon entropy. We applied the subgraph approach to study three types of molecular networks, i.e., cancer networks, signal transduction networks, and cellular process networks, which exhibit diverse molecular functions. We compared the performance of our subgraph detection algorithm with other algorithms, and the results were consistent, but other algorithms could not address the issue of subgraphs/motifs embedded within a subgraph/motif. To evaluate the effectiveness of the subgraph-based method, we applied the method along with the Jensen-Shannon entropy to classify six network models, and it achieves a 100% accuracy of classification. The proposed information-theoretic approach allows us to determine the structural similarity of two networks regardless of node identity and network size. We demonstrated the effectiveness of the subgraph approach to cluster molecular networks that exhibit similar regulatory interaction topologies. As an illustration, our method can identify (i) common subgraph-mediated signal transduction and/or cellular processes in AML and pancreatic cancer, and (ii) scaffold proteins in gastric cancer and hepatocellular carcinoma; thus, the results suggested that there are common regulation modules for cancer formation. We also found that the underlying substructures of the molecular networks are dominated by irreducible subgraphs; this feature is valid for the three classes of molecular networks we studied. The subgraph-based approach provides a systematic scenario for analyzing, compare and classifying molecular networks with diverse functionalities.

microRNA-Mediated Encoding and Decoding of Time-Dependent Signals in Tumorigenesis

microRNAs, pivotal post-transcriptional regulators of gene expression, in the past decades have caught the attention of researchers for their involvement in different biological processes, ranging from cell development to cancer. Although lots of effort has been devoted to elucidate the topological features and the equilibrium properties of microRNA-mediated motifs, little is known about how the information encoded in frequency, amplitude, duration, and other features of their regulatory signals can affect the resulting gene expression patterns. Here, we review the current knowledge about microRNA-mediated gene regulatory networks characterized by time-dependent input signals, such as pulses, transient inputs, and oscillations. First, we identify the general characteristic of the main motifs underlying temporal patterns. Then, we analyze their impact on two commonly studied oncogenic networks, showing how their dysfunction can lead to tumorigenesis.

nSARS-Cov-2, pulmonary edema and thrombosis: possible molecular insights using miRNA-gene circuits in regulatory networks

Background

Given the worldwide spread of the novel Severe Acute Respiratory Syndrome Coronavirus 2 (nSARS-CoV-2) infection pandemic situation, research to repurpose drugs, identify novel drug targets, vaccine candidates have created a new race to curb the disease. While the molecular signature of nSARS-CoV-2 is still under investigation, growing literature shows similarity among nSARS-CoV-2, pulmonary edema, and thromboembolic disorders due to common symptomatic features. A network medicine approach is used to to explore the molecular complexity of the disease and to uncover common molecular trajectories of edema and thrombosis with nSARS-CoV-2.

Results and conclusion

A comprehensive nSARS-CoV-2 responsive miRNA: Transcription Factor (TF): gene co-regulatory network was built using host-responsive miRNAs and it’s associated tripartite, Feed-Forward Loops (FFLs) regulatory circuits were identified. These regulatory circuits regulate signaling pathways like virus endocytosis, viral replication, inflammatory response, pulmonary vascularization, cell cycle control, virus spike protein stabilization, antigen presentation, etc. A unique miRNA-gene regulatory circuit containing a consortium of four hub FFL motifs is proposed to regulate the virus-endocytosis and antigen-presentation signaling pathways. These regulatory circuits also suggest potential correlations/similarity in the molecular mechanisms during nSARS-CoV-2 infection, pulmonary diseases and thromboembolic disorders and thus could pave way for repurposing of drugs. Some important miRNAs and genes have also been proposed as potential candidate markers. A detailed molecular snapshot of TGF signaling as the common pathway, that could play an important role in controlling common pathophysiologies among diseases, is also put forth.

Supplementary information

Supplementary information accompanies this paper at 10.1186/s41544-020-00057-y.

The comparison of miRNAs that respond to anti-breast cancer drugs and usnic acid for the treatment of breast cancer

This study was designed to compare usnic acid with anti-breast cancer drug molecules (A-BCDM) routinely used in the treatment of breast cancer. The miRNA information of 17 anti-breast cancer drug used in breast cancer treatment was obtained from the Small Molecule-miRNA Network-Based Inferance (SMIR-NBI) tool. We had been determined common and different expressed miRNAs between 17 A-BCDM & usnic acid and were classified according to the common miRNAs to reveal molecular similarity. As a result of the bioinformatic analyzes, 20 common miRNAs were determined between 17 A-BCDM and usnic acid. The common miRNAs were analyzed with bioinformatic tolls for determining pathways and targets. The most common miRNAs for 6 of 17 A-BCDM and usnic acid were determined as miR-374a-5p and miR-26a-5p. We compared the anti-proliferative effect of usnic acid and one of the 17 A-BCDM that tamoxifen on MDA-MB-231 triple negative breast cancer cell with real-time cell analysis system. The real time PCR assay was carried out with miR-26a-5p for evaluate to expression level of MDA-MB-231 breast cancer cell and MCF-12A non-cancerous epithelial breast cell. As a result of study, usnic acid as novel candidate drug molecule showed high similarity ratio with 5-Fluorouracil, Sulindac Sulfide, Curcumin and Cisplatin A-BCDM used in treatment of breast cancer. miR-26a-5p as common response miRNA of usnic acid and tamoxifen was showed a decreased level of expression by validated qRT-PCR assay. The obtained from study, in addition to 17 A-BCDM, usnic acid has also the potential to be used as a candidate molecule in the treatment of breast cancer. Moreover, miR-26a-5p might be used as a biomarker in the treatment of breast cancer but further analysis is required.

Dissecting molecular network structures using a network subgraph approach

Biological processes are based on molecular networks, which exhibit biological functions through interactions of genetic elements or proteins. This study presents a graph-based method to characterize molecular networks by decomposing the networks into directed multigraphs: network subgraphs. Spectral graph theory, reciprocity and complexity measures were used to quantify the network subgraphs. Graph energy, reciprocity and cyclomatic complexity can optimally specify network subgraphs with some degree of degeneracy. Seventy-one molecular networks were analyzed from three network types: cancer networks, signal transduction networks, and cellular processes. Molecular networks are built from a finite number of subgraph patterns and subgraphs with large graph energies are not present, which implies a graph energy cutoff. In addition, certain subgraph patterns are absent from the three network types. Thus, the Shannon entropy of the subgraph frequency distribution is not maximal. Furthermore, frequently-observed subgraphs are irreducible graphs. These novel findings warrant further investigation and may lead to important applications. Finally, we observed that cancer-related cellular processes are enriched with subgraph-associated driver genes. Our study provides a systematic approach for dissecting biological networks and supports the conclusion that there are organizational principles underlying molecular networks.

MyomirDB: A unified database and server platform for muscle atrophy myomiRs, coregulatory networks and regulons

Muscular atrophy or muscle loss is a multifactorial clinical condition during many critical illnesses like cancer, cardiovascular diseases, diabetes, pulmonary diseases etc. leading to fatigue and weakness and contributes towards a decreased quality of life. The proportion of older adults (>65 y) in the overall population is also growing and aging is another important factor causing muscle loss. Some muscle miRNAs (myomiRs) and their target genes have even been proposed as potential diagnostic, therapeutic and predictive markers for muscular atrophy. MyomirDB (http://www.myomirdb.in/) is a unique resource that provides a comprehensive, curated, user- friendly and detailed compilation of various miRNA bio-molecular interactions; miRNA-Transcription Factor-Target Gene co-regulatory networks and ~8000 tripartite regulons associated with 247 myomiRs which have been experimentally validated to be associated with various muscular atrophy conditions. For each database entry, MyomirDB compiles source organism, muscle atrophic condition, experiment duration, its level of expression, fold change, tissue of expression, experimental validation, disease and drug association, tissue-specific expression level, Gene Ontology and KEGG pathway associations. The web resource is a unique server platform which uses in-house scripts to construct miRNA-Transcription Factor-Target Gene co-regulatory networks and extract tri-partite regulons also called Feed Forward Loops. These unique features helps to offer mechanistic insights in disease pathology. Hence, MyomirDB is a unique platform for researchers working in this area to explore, fetch, compare and analyse atrophy associated miRNAs, their co-regulatory networks and FFL regulons.

The Novel Transcription Factor CREB3L4 Contributes to the Progression of Human Breast Carcinoma

Breast carcinoma(BC)is the most common cancer type among females globally. Understanding the molecular pathways that trigger the development of BC is crucial for both prevention and treatment. As such, the role of transcription factors (TFs) in the development of BC is a focal point in this field. CREB3s play a critical role in initiating the unfolded protein response (UPR); however, the role of CREB3 family members in breast cancer development remains largely unknown. Here, we mined the ONCOMINE database for the transcriptional data of CREB3s in patients with BC. Then, the regulatory functions of a novel TF, CREB3L4, were investigated. CREB3L4 knockdown in MDA-MB-231 and MCF-7 cells suppressed proliferation and promoted apoptosis and cell cycle arrest. ChIP assays confirmed that CREB3L4 can directly bind to the PCNA promoter region, suggesting that the PCNA protein may be functionally downstream of CREB3L4. Additionally, the expression level of CREB3L4 was assessed using our cohort. CREB3L4 is upregulated in breast cancer tissues and is significantly associated with histological grade and tumour size (P = 0.001 and P < 0.001, respectively). Furthermore, PCNA expression was upregulated in breast cancer tissues and positively correlated with CREB3L4. In summary, CREB3L4 may play an important role in the progression of human BC and may serve as a therapeutic target.

From Endogenous to Synthetic microRNA-Mediated Regulatory Circuits: An Overview

MicroRNAs are short non-coding RNAs that are evolutionarily conserved and are pivotal post-transcriptional mediators of gene regulation. Together with transcription factors and epigenetic regulators, they form a highly interconnected network whose building blocks can be classified depending on the number of molecular species involved and the type of interactions amongst them. Depending on their topology, these molecular circuits may carry out specific functions that years of studies have related to the processing of gene expression noise. In this review, we first present the different over-represented network motifs involving microRNAs and their specific role in implementing relevant biological functions, reviewing both theoretical and experimental studies. We then illustrate the recent advances in synthetic biology, such as the construction of artificially synthesised circuits, which provide a controlled tool to test experimentally the possible microRNA regulatory tasks and constitute a starting point for clinical applications.

rSNPBase 3.0: an updated database of SNP-related regulatory elements, element-gene pairs and SNP-based gene regulatory networks

Here, we present the updated rSNPBase 3.0 database (http://rsnp3.psych.ac.cn), which provides human SNP-related regulatory elements, element-gene pairs and SNP-based regulatory networks. This database is the updated version of the SNP regulatory annotation database rSNPBase and rVarBase. In comparison to the last two versions, there are both structural and data adjustments in rSNPBase 3.0: (i) The most significant new feature is the expansion of analysis scope from SNP-related regulatory elements to include regulatory element–target gene pairs (E–G pairs), therefore it can provide SNP-based gene regulatory networks. (ii) Web function was modified according to data content and a new network search module is provided in the rSNPBase 3.0 in addition to the previous regulatory SNP (rSNP) search module. The two search modules support data query for detailed information (related-elements, element-gene pairs, and other extended annotations) on specific SNPs and SNP-related graphic networks constructed by interacting transcription factors (TFs), miRNAs and genes. (3) The type of regulatory elements was modified and enriched. To our best knowledge, the updated rSNPBase 3.0 is the first data tool supports SNP functional analysis from a regulatory network prospective, it will provide both a comprehensive understanding and concrete guidance for SNP-related regulatory studies.

Burkitt lymphoma-associated network construction and important network motif analysis

Biological and medical researchers have discovered numerous transcription factors (TFs), microRNAs (miRNAs) and genes associated with Burkitt lymphoma (BL) through individual experiments; however, their regulatory mechanisms remain unclear. In the present study, BL-dysregulated and BL-associated networks were constructed to investigate these mechanisms. All data and regulatory associations were from known data resources and literature. The dysregulated network consisted of dysregulated TFs, miRNAs and genes, and partially determined the pathogenesis mechanisms underlying BL. The BL-associated network consisted of BL-associated TFs, miRNAs and genes. It has been indicated that the network motif consisted of TFs, miRNAs and genes serve potential functions in numerous biological processes within cancer. Two of the most studied network motifs are feedback loop (FBL) and feed-forward loop (FFL). The important network motifs were extracted, including the FBL motif, 3-nodes FFL motif and 4-nodes motif, from BL-dysregulated and BL-associated networks, and 10 types of motifs were identified from BL-associated network. Finally, 26/31 FBL motifs, 45/75 3-nodes FFL motifs and 54/94 4-nodes motifs were obtained from the dysregulated/associated networks. A total of four TFs (E2F1, NFKB1, E2F4 and TCF3) exhibit complicated regulation associations in BL-associated networks. The biological network does not demonstrate the dysregulated status for healthy people. When the individual becomes unwell, their biological network exhibits a dysregulated status. If the dysregulated status is regulated to a normal status by a number of medical methods, the diseases may be treated successfully. BL-dysregulated networks serve important roles in pathogenesis mechanisms underlying BL regulation of the dysregulated network, which may be an effective strategy that contributes to gene therapy for BL.

A causal mediation model of ischemia reperfusion injury in the retina

The goal of this study is to develop a model that explains the relationship between microRNAs, transcription factors, and their co-target genes. This relationship was previously reported in gene regulatory loops associated with 24 hour (24h) and 7 day (7d) time periods following ischemia-reperfusion injury in a rat's retina. Using a model system of retinal ischemia-reperfusion injury, we propose that microRNAs first influence transcription factors, which in turn act as mediators to influence transcription of genes via triadic regulatory loops. Analysis of the relative contributions of direct and indirect regulatory influences on genes revealed that a substantial fraction of the regulatory loops (69% for 24 hours and 77% for 7 days) could be explained by causal mediation. Over 40% of the mediated loops in both time points were regulated by transcription factors only, while about 20% of the loops were regulated entirely by microRNAs. The remaining fractions of the mediated regulatory loops were cooperatively mediated by both microRNAs and transcription factors. The results from these analyses were supported by the patterns of expression of the genes, transcription factors, and microRNAs involved in the mediated loops in both post-ischemic time points. Additionally, network motif detection for the mediated loops showed a handful of time specific motifs related to ischemia-reperfusion injury in a rat's retina. In summary, the effects of microRNAs on genes are mediated, in large part, via transcription factors.

Systems biology study of transcriptional and post-transcriptional co-regulatory network sheds light on key regulators involved in important biological processes in Citrus sinensis

Transcriptional and post-transcriptional regulators including transcription regulator, transcription factor and miRNA are the main endogenous molecular elements which control complex cellular mechanisms such as development, growth and response to biotic and abiotic stresses in a coordinated manner in plants. Utilizing the most recent information on such relationships in a plant species, obtained from high-throughput experimental technologies and advanced computational tools, we can reconstruct its co-regulatory network which consequently sheds light on key regulators involved in its important biological processes. In this article, combined systems biology approaches such as mining the literatures, various databases and network reconstruction, analysis, and visualization tools were employed to infer and visualize the coregulatory relationships between miRNAs and transcriptional regulators in Citrus sinensis. Using computationally and experimentally verified miRNA-target interactions and constructed co-expression networks on array-based data, 10 coregulatory networks and 10 corresponding subgraphs include FFL motifs were obtained for 10 distinct tissues/conditions. Then PPI subnetworks were extracted for transcripts/genes included in mentioned subgraphs in order to the functional analysis of extracted coregulatory circuits. These proposed coregulatory connections shed light on precisely identifying C. sinensis metabolic pathways key switches, which are demanded for ultimate goals such as genome editing.

miR-2478 inhibits TGFβ1 expression by targeting the transcriptional activation region downstream of the TGFβ1 promoter in dairy goats

In a previous study, miR-2478 was demonstrated to be up-regulated in dairy goat mammary glands during peak lactation compared with the dry period. However, the detailed mechanisms by which miR-2478 regulates physiological lactation and mammary gland development in dairy goats remain unclear. In this study, we used bioinformatics analysis and homologous cloning to predict the target genes of miR-2478 and selected INSR, FBXO11, TGFβ1 and ING4 as candidate target genes of miR-2478. Subsequently, by targeting the 5′UTR of the TGFβ1 gene, we verified that miR-2478 significantly inhibited TGFβ1 transcription and the Pearson’s correlation coefficient between miR-2478 expression and TGFβ1 expression was −0.98. Furthermore, we identified the potential promoter and transcription factor binding regions of TGFβ1 and analyzed the potential mechanisms of interaction between miR-2478 and TGFβ1. Dual-luciferase reporter assays revealed that two regions, spanning from −904 to −690 bp and from −79 to +197 bp, were transcription factor binding regions of TGFβ1. Interesting, the miR-2478 binding sequence was determined to span from +123 to +142 bp in the TGFβ1 gene promoter. Thus, our results have demonstrated that miR-2478 binds to the core region of the TGFβ1 promoter and that it affects goat mammary gland development by inhibiting TGFβ1 transcription.

Investigation of a common gene expression signature in gastrointestinal cancers using systems biology approaches

According to GLOBOCAN 2012, the incidence and the mortality rate of colorectal, stomach and liver cancers are the highest among the total gastrointestinal (GI) cancers.

Identification of miRNAs Potentially Involved in Bronchiolitis Obliterans Syndrome: A Computational Study

The pathogenesis of Bronchiolitis Obliterans Syndrome (BOS), the main clinical phenotype of chronic lung allograft dysfunction, is poorly understood. Recent studies suggest that epigenetic regulation of microRNAs might play a role in its development. In this paper we present the application of a complex computational pipeline to perform enrichment analysis of miRNAs in pathways applied to the study of BOS. The analysis considered the full set of miRNAs annotated in miRBase (version 21), and applied a sequence of filtering approaches and statistical analyses to reduce this set and to score the candidate miRNAs according to their potential involvement in BOS development. Dysregulation of two of the selected candidate miRNAs–miR-34a and miR-21 –was clearly shown in in-situ hybridization (ISH) on five explanted human BOS lungs and on a rat model of acute and chronic lung rejection, thus definitely identifying miR-34a and miR-21 as pathogenic factors in BOS and confirming the effectiveness of the computational pipeline.

Understanding the CREB1-miRNA feedback loop in human malignancies

cAMP response element binding protein 1 (CREB1, CREB) is a key transcription factor that mediates transcriptional responses to a variety of growth factors and stress signals. CREB1 has been shown to play a critical role in development and progression of tumors. MicroRNAs (miRNAs) are a class of non-coding RNAs. They post-transcriptionally regulate gene expression through pairing with the 3'-UTR of their target mRNAs and thus regulate initiation and progression of various types of human cancers. Recent studies have demonstrated that a number of miRNAs can be transcriptionally regulated by CREB1. Interestingly, CREB1 expression can also be modulated by miRNAs, thus forming a feedback loop. This review outlines the functional roles of CREB1, miRNA, and their interactions in human malignancies. This will help to define a relationship between CREB1 and miRNA in human cancer and develop novel therapeutic strategies.

miR-146b-5p within BCR-ABL1-Positive Microvesicles Promotes Leukemic Transformation of Hematopoietic Cells

Evidence is accumulating that extracellular microvesicles (MV) facilitate progression and relapse in cancer. Using a model in which MVs derived from K562 chronic myelogenous leukemia (CML) cells transform normal hematopoietic transplants into leukemia-like cells, we defined the underlying mechanisms of this process through gene-expression studies and network analyses of transcription factors (TF) and miRNAs. We found that antitumor miRNAs were increased and several defense pathways were initiated during the early phases of oncogenic transformation. Later, oncomiRs and genes involved in cell cycle, DNA repair, and energy metabolism pathways were upregulated. Regulatory network analyses revealed that a number of TFs and miRNAs were responsible for the pathway dysregulation and the oncogenic transformation. In particular, we found that miR-146b-5p, which was highly expressed in MVs, coordinated the regulation of cancer-related genes to promote cell-transforming processes. Notably, treatment of recipient cells with MV derived from K562 cells expressing mimics of miR-146b-5p revealed that it accelerated the transformation process in large part by silencing the tumor-suppressor NUMB High levels of miR-146b-5p also enhanced reactive oxygen species levels and genome instability of recipient cells. Taken together, our finding showed how upregulation of oncogenic miRNAs in MVs promote hematopoetic cells to a leukemic state, as well as a demonstration for TF and miRNA coregulatory analysis in exploring the dysregulation of cancers and discovering key factors. Cancer Res; 76(10); 2901-11. ©2016 AACR.

Emerging role of transcription factor-microRNA-target gene feed-forward loops in cancer

Transcriptional regulatory networks are biological network motifs that act in accordance with each other to play decisive roles in the pathological processes of cancer. One of the most common types, the feed-forward loop (FFL), has recently attracted interest. Three connected deregulated nodes, a transcription factor (TF), its downstream microRNA (miRNA) and their shared target gene can make up a class of cancer-involved FFLs as ≥1 of the 3 can act individually as a bona fide oncogene or a tumor suppressor. Numerous notable elements, such as p53, miR-17-92 cluster and cyclins, are proven members of their respective FFLs. Databases of interaction prediction, verification of experimental methods and confirmation of loops have been continually emerging during recent years. Development of TF-miRNA-target loops may help understand the mechanism of tumorgenesis at a higher level and explain the discovery and screening of the therapeutic target for drug exploitation.