miRNA Data Research Articles

PRB inhibited cell proliferation through let-7b-E2F1 in breast cancer.

The presence of progesterone receptor (PR) and PR isoform B (PRB) in breast cancer is generally correlated with better clinical outcomes. Additionally, the significance of hormone-independent effects of PR/PRB correlated with better prognosis have been reported in non-small lung cancer (NSCLC). However, the detailed mechanism of that still remains unclear. In this study, we examined how microRNAs (miRNAs) could contribute to tumor inhibition via PR/PRB expression, in order to find miRNAs that have tumor-agnostic effects between breast cancer and NSCLC. We obtained miRNAs data using human tissues of breast cancer and NSCLC from The Cancer Genome Atlas database and PCR array from NSCLC patients of our cohort. Subsequently, we examined the function of the miRNA through in vitro study using breast cancer cell lines. As a result, only let-7b expression was significantly correlated with PR expression in both cancers. Additionally, the expression of let-7b significantly inhibited cell proliferation by inducing PR and PRB expression in breast cancer cell lines. However, the positive correlation of let-7b and PRB required a mediated factor, E2F1, obtained from TGCA databases analysis. In vitro experiments showed that let-7b significantly inhibited E2F1, and E2F1 significantly inhibited PRB. This study revealed that PRB inhibits the proliferation of breast cancer cells by the let-7b-E2F1 interaction. In addition, the immunohistochemical analysis in NSCLC was also consistent with these in vitro data. Our results could contribute to developing novel therapeutic strategies for patients with PR/PRB-positive cancer by targeting let7b or PRB expression in breast cancer and possibly NSCLC.

71P MicroRNA (miRNA) a putative biomarker to better define the molecular apocrine breast cancer (MABC) subtype

Breast cancer (BC), is a heterogeneous disease, divided into molecular subtypes based on gene expression and clinical outcomes. MABC is a poorly diagnosed subtype, characterized by estrogen (ER), progesterone receptor (PR) negativity, and HER-2-amplification in most cases; yet it overexpresses androgen receptor (AR) and activates its pathway. Its improper diagnosis demands the adoption of complementary tools to refine classification; miRNA, key players in regulating cell behavior, AR, and tumorigenic processes of BC hold promise in defining and studying the behavior of MABC. 539 breast cancer microarray data were downloaded from The Cancer Genome Atlas (TCGA-BRCA). Cases with available miRNA data were retained and classified using citbcmst R package (PMID: 30289602). Differential expression analysis identified deregulated miRNAs using DEseq2. A validation set of 131 ER-neg samples was constituted and MABC tumors were characterized apart of triple-negative (TN)BC by the previously described molecular signature (AR, FOXA1 and AR-related genes, PMID: 23663520) on fresh tissue sections. Using miRCURY LNATM miRNA PCR assay, miRNA profiling was done for a panel of 6 differentially expressed miRNAs. Finally, expression of in silico predicted target genes of these miRNAs was assessed by RT-qPCR in MABC and TNBC cell lines after transfection with miRNA mimics. TCGA data analysis indicated MABC as a separate entity based on gene signature. MiRNA-seq data analysis depicted a set of 6 significantly deregulated miRNA with absolute value of log2 fold change> 1 and P-adjusted value <0.05 between MABC and TNBC. We validated on 78 MABC (27 HER2-/ 51 HER2+), and 53 TN samples, by miRNA profiling, significant upregulation of miR-2115-3p and miR-187-3p in MABC compared to TNBC. Preliminary data, showed that the overexpression of these miRNAs significantly downregulates in silico predicted target genes (FGF2, HMGCS1, and ADAM12) implicated in carcinogenesis differently in each of the models used. MABC has a unique signature of miRNA compared to TNBC. The identified miRNAs regulate a set of genes implicated in tumorigenic processes and can potentially serve as biomarkers to effectively diagnose, prognose and treat MABC

Stage Analysis of Breast Cancer Metabolomics: A System Biology Approach.

Breast cancer (BC) is the most common malignancy in women worldwide. Altered miRNA profile can disturb the metabolic homeostatic via regulation of gene expression in BC. In the present study to evaluate which miRNA, regulate metabolic pathways according to their stage, we performed comprehensive analysis of BC expression (mRNA and miRNA) of a set of patients by comparing samples of solid tumor tissue and adjacent tissue. The mRNA and miRNA data of breast cancer were downloaded from the cancer genome database (TCGA) using TCGAbiolinks package. Differentially expressed (mRNAs and miRNAs) was determined by DESeq2 package and predict valid miRNA-mRNA pairs using multiMiR package. All analyses were performed using the R software. Compound-reaction-enzyme-gene network was constructed using the Metscape a plugin for Cytoscape software. Then, core subnetwork computed by CentiScaPe, another plugin for Cytoscape. In Stage I, hsa-miR-592, hsa-miR-449a and hsa-miR-1269a targeted HS3ST4, ACSL1 and USP9Y genes respectively. In stage II, hsa-miR-3662, Hsa-miR-429, and hsa-miR-1269a targeted GYS2, HAS3, ASPA, TRHDE, USP44, GDA, DGAT2, and USP9Y genes. In stage III, hsa-miR-3662 targeted TRHDE, GYS2, DPYS, HAS3, NMNAT2, ASPA genes. In stage IV, hsa-miR-429, has-miR-23c, and hsa-miR-449a targeted genes GDA, DGAT2, PDK4, ALDH1A2, ENPP2, and KL. Those miRNAs and their targets were identified as the discriminative elements for the four stages of breast cancer. The most notable differences between BC and normal tissue in four stages involved multiple pathways and metabolites include: carbohydrate metabolism (e.g., Amylose, N-acetyl-D-glucosamin, beta-D-Glucuronoside, ""g""-CEHC-glucuronide, ""a""-CEHC-glucuronide, Heparan-glucosamine, 5,6-Dihydrouracil, 5,6-Dihydrothymine), branch-chain amino acid metabolism (e.g., N-Acetyl-L-aspartate, N-Formyl-L-aspartate, N`-acetyl-L-asparagine), Retinal metabolism (e.g., Retinal, 9-`cis`-retinal, 13-`cis`-retinal) and (FAD, NAD) as central coenzymes of metabolism. Set of crucial microRNAs and targeted genes plus the related metabolites were introduced for four stages of BC that can be consider for therapeutic and diagnostic purposes in the different stages of disease.

Characterization of microRNAs and Target Genes in Musa acuminata subsp. burmannicoides, var. Calcutta 4 during Interaction with Pseudocercospora musae

Endogenous microRNAs (miRNAs) are small non-coding RNAs that perform post-transcriptional regulatory roles across diverse cellular processes, including defence responses to biotic stresses. Pseudocercospora musae, the causal agent of Sigatoka leaf spot disease in banana (Musa spp.), is an important fungal pathogen of the plant. Illumina HiSeq 2500 sequencing of small RNA libraries derived from leaf material in Musa acuminata subsp. burmannicoides, var. Calcutta 4 (resistant) after inoculation with fungal conidiospores and equivalent non-inoculated controls revealed 202 conserved miRNAs from 30 miR-families together with 24 predicted novel miRNAs. Conserved members included those from families miRNA156, miRNA166, miRNA171, miRNA396, miRNA167, miRNA172, miRNA160, miRNA164, miRNA168, miRNA159, miRNA169, miRNA393, miRNA535, miRNA482, miRNA2118, and miRNA397, all known to be involved in plant immune responses. Gene ontology (GO) analysis of gene targets indicated molecular activity terms related to defence responses that included nucleotide binding, oxidoreductase activity, and protein kinase activity. Biological process terms associated with defence included response to hormone and response to oxidative stress. DNA binding and transcription factor activity also indicated the involvement of miRNA target genes in the regulation of gene expression during defence responses. sRNA-seq expression data for miRNAs and RNAseq data for target genes were validated using stem-loop quantitative real-time PCR (qRT-PCR). For the 11 conserved miRNAs selected based on family abundance and known involvement in plant defence responses, the data revealed a frequent negative correlation of expression between miRNAs and target host genes. This examination provides novel information on miRNA-mediated host defence responses, applicable in genetic engineering for the control of Sigatoka leaf spot disease.

Identification of novel miRNAs potentially involved in the pathogenesis of adult T-cell leukemia/lymphoma using WGCNA followed by RT-qPCR test of hub genes

BackgroundAdult T-cell Lymphoma/Leukemia (ATLL) is characterized by the malignant proliferation of T-cells in Human T-Lymphotropic Virus Type 1 and a high mortality rate. Considering the emerging roles of microRNAs (miRNAs) in various malignancies, the analysis of high-throughput miRNA data employing computational algorithms helps to identify potential biomarkers.MethodsWeighted gene co-expression network analysis was utilized to analyze miRNA microarray data from ATLL and healthy uninfected samples. To identify miRNAs involved in the progression of ATLL, module preservation analysis was used. Subsequently, based on the target genes of the identified miRNAs, the STRING database was employed to construct protein–protein interaction networks (PPIN). Real-time quantitative PCR was also performed to validate the expression of identified hub genes in the PPIN network.ResultsAfter constructing co-expression modules and then performing module preservation analysis, four out of 15 modules were determined as ATLL-specific modules. Next, the hub miRNA including hsa-miR-18a-3p, has-miR-187-5p, hsa-miR-196a-3p, and hsa-miR-346 were found as hub miRNAs. The protein–protein interaction networks were constructed for the target genes of each hub miRNA and hub genes were identified. Among them, UBB, RPS15A, and KMT2D were validated by Reverse-transcriptase PCR in ATLL patients.ConclusionThe results of the network analysis of miRNAs and their target genes revealed the major players in the pathogenesis of ATLL. Further studies are required to confirm the role of these molecular factors and to discover their potential benefits as treatment targets and diagnostic biomarkers.

A miRNA screening identifies miR-192-5p as associated with response to azacitidine and lenalidomide therapy in myelodysplastic syndromes

BackgroundmiRNAs are small non-coding RNAs that regulate gene expression and are linked to cancer development and progression. miRNA profiles are currently studied as new prognostic factors or therapeutic perspectives. Among hematological cancers, myelodysplastic syndromes at higher risk of evolution into acute myeloid leukemia are treated with hypomethylating agents, like azacitidine, alone or in combination with other drugs, such as lenalidomide. Recent data showed that, during azacitidine and lenalidomide therapy, the concurrent acquisition of specific point mutations affecting inositide signalling pathways is associated with lack or loss of response to therapy. As these molecules are implicated in epigenetic processes, possibly involving miRNA regulation, and in leukemic progression, through the regulation of proliferation, differentiation and apoptosis, here we performed a new miRNA expression analysis of 26 high-risk patients with myelodysplastic syndromes treated with azacitidine and lenalidomide at baseline and during therapy. miRNA array data were processed, and bioinformatic results were correlated with clinical outcome to investigate the translational relevance of selected miRNAs, while the relationship between selected miRNAs and specific molecules was experimentally tested and proven.ResultsPatients’ overall response rate was 76.9% (20/26 cases): complete remission (5/26, 19.2%), partial remission (1/26, 3.8%), marrow complete remission (2/26, 7.7%), hematologic improvement (6/26, 23.1%), hematologic improvement with marrow complete remission (6/26, 23.1%), whereas 6/26 patients (23.1%) had a stable disease. miRNA paired analysis showed a statistically significant up-regulation of miR-192-5p after 4 cycles of therapy (vs baseline), that was confirmed by real-time PCR analyses, along with an involvement of BCL2, that was proven to be a miR-192-5p target in hematopoietic cells by luciferase assays. Furthermore, Kaplan–Meier analyses showed a significant correlation between high levels of miR-192-5p after 4 cycles of therapy and overall survival or leukemia-free survival, that was stronger in responders, as compared with patients early losing response and non-responders.ConclusionsThis study shows that high levels of miR-192-5p are associated with higher overall survival and leukemia-free survival in myelodysplastic syndromes responding to azacitidine and lenalidomide. Moreover, miR-192-5p specifically targets and inhibits BCL2, possibly regulating proliferation and apoptosis and leading to the identification of new therapeutic targets.

Identification of key regulatory genes and their working mechanisms in type 1 diabetes

BackgroundType 1 diabetes (T1D) is an autoimmune disease characterized by the destruction of beta cells in pancreatic islets. Identification of the key genes involved in T1D progression and their mechanisms of action may contribute to a better understanding of T1D.MethodsThe microarray profile of T1D-related gene expression was searched using the Gene Expression Omnibus (GEO) database. Then, the expression data of two messenger RNAs (mRNAs) were integrated for Weighted Gene Co-Expression Network Analysis (WGCNA) to generate candidate genes related to T1D. In parallel, T1D microRNA (miRNA) data were analyzed to screen for possible regulatory miRNAs and their target genes. An miRNA–mRNA regulatory network was then established to predict the key regulatory genes and their mechanisms.ResultsA total of 24 modules (i.e., clusters/communities) were selected using WGCNA analysis, in which three modules were significantly associated with T1D. Further correlation analysis of the gene module revealed 926 differentially expressed genes (DEGs), of which 327 genes were correlated with T1D. Analysis of the miRNA microarray showed that 13 miRNAs had significant expression differences in T1D. An miRNA–mRNA network was established based on the prediction of miRNA target genes and the combined analysis of mRNA, in which the target genes of two miRNAs were found in T1D correlated genes.ConclusionAn miRNA–mRNA network for T1D was established, based on which 2 miRNAs and 12 mRNAs were screened, suggesting that they may play key regulatory roles in the initiation and development of T1D.

Uncovering potential diagnostic biomarkers of acute myocardial infarction based on machine learning and analyzing its relationship with immune cells

BackgroundAcute myocardial infarction (AMI) is a common cardiovascular disease. This study aimed to mine biomarkers associated with AMI to aid in clinical diagnosis and management.MethodsAll mRNA and miRNA data were downloaded from public database. Differentially expressed mRNAs (DEmRNAs) and differentially expressed miRNAs (DEmiRNAs) were identified using the metaMA and limma packages, respectively. Functional analysis of the DEmRNAs was performed. In order to explore the relationship between miRNA and mRNA, we construct miRNA-mRNA negative regulatory network. Potential biomarkers were identified based on machine learning. Subsequently, ROC and immune correlation analysis were performed on the identified key DEmRNA biomarkers.ResultsAccording to the false discovery rate < 0.05, 92 DEmRNAs and 272 DEmiRNAs were identified. GSEA analysis found that kegg_peroxisome was up-regulated in AMI and kegg_steroid_hormone_biosynthesis was down-regulated in AMI compared to normal controls. 5 key DEmRNA biomarkers were identified based on machine learning, and classification diagnostic models were constructed. The random forests (RF) model has the highest accuracy. This indicates that RF model has high diagnostic value and may contribute to the early diagnosis of AMI. ROC analysis found that the area under curve of 5 key DEmRNA biomarkers were all greater than 0.7. Pearson correlation analysis showed that 5 key DEmRNA biomarkers were correlated with most of the differential infiltrating immune cells.ConclusionThe identification of new molecular biomarkers provides potential research directions for exploring the molecular mechanism of AMI. Furthermore, it is important to explore new diagnostic genetic biomarkers for the diagnosis and treatment of AMI.

Identifying miRNA-Gene Common and Specific Regulatory Modules for Cancer Subtyping by a High-Order Graph Matching Model.

Identifying regulatory modules between miRNAs and genes is crucial in cancer research. It promotes a comprehensive understanding of the molecular mechanisms of cancer. The genomic data collected from subjects usually relate to different cancer statuses, such as different TNM Classifications of Malignant Tumors (TNM) or histological subtypes. Simple integrated analyses generally identify the core of the tumorigenesis (common modules) but miss the subtype-specific regulatory mechanisms (specific modules). In contrast, separate analyses can only report the differences and ignore important common modules. Therefore, there is an urgent need to develop a novel method to jointly analyze miRNA and gene data of different cancer statuses to identify common and specific modules. To that end, we developed a High-Order Graph Matching model to identify Common and Specific modules (HOGMCS) between miRNA and gene data of different cancer statuses. We first demonstrate the superiority of HOGMCS through a comparison with four state-of-the-art techniques using a set of simulated data. Then, we apply HOGMCS on stomach adenocarcinoma data with four TNM stages and two histological types, and breast invasive carcinoma data with four PAM50 subtypes. The experimental results demonstrate that HOGMCS can accurately extract common and subtype-specific miRNA-gene regulatory modules, where many identified miRNA-gene interactions have been confirmed in several public databases.

MicroRNA‑143‑3p levels are reduced in the peripheral blood of patients with gestational diabetes mellitus and influences pancreatic β‑cell function and viability.

Pancreatic β-cell dysfunction has been demonstrated to mediate key roles in the pathogenesis of gestational diabetes mellitus (GDM). Accumulating evidence has supported the functional involvement of microRNAs (miRNAs) in various types of diabetes, including GDM. However, the detailed biological effect of miRNAs in pancreatic β-cell dysfunction remains poorly understood. In the present study, microarray data of miRNAs in the blood plasma of patients with GDM were retrieved from the Gene Expression Omnibus dataset under the accession number GSE98043. Reverse transcription-quantitative PCR (RT-qPCR) was performed to measure the expression levels of miR-143-3p in the blood plasma isolated from 30 female patients with GDM women and 30 healthy female individuals. Subsequently, murine pancreatic β-cell line, MIN6 cells were treated with high glucose (HG) to construct in vitro cell models of GDM. miR-143-3p in HG-treated MIN6 cells was overexpressed or knocked down using miR-143-3p mimics and miR-143-3p inhibitor. Cell viability, insulin secretion and proinflammatory cytokine production were examined using CCK-8 and ELISA, respectively Cell apoptosis was measured by flow cytometry assay. The protein expression levels of proteins involved in the TAK1/NF-κB pathway were also assessed using western blot. The levels of miR-143-3p were found to be markedly lower in samples from patients with GDM, which were in turn negatively correlated with blood glucose levels. Overexpression of miR-143-3p in MIN6 cells significantly reversed HG-induced cell apoptosis and impairments in cell viability and insulin secretion. In addition, miR-143-3p overexpression attenuated HG-induced proinflammatory cytokine production by MIN6 cells. Subsequently, TGFβ-activated kinase 1 (TAK1), an upstream regulator of the NF-κB pathway, was found to be a direct target of miR-143-3p in pancreatic β cells through luciferase assays and western blot. Overexpression of TAK1 was revealed to abolish the curative effects of miR-143-3p on insulin secretion, cell viability and inflammatory response in HG-treated MIN6 cells. In addition, miR-143-3p could inactivate the NF-κB pathway by inhibiting TAK1 expression. Collectively, these results suggest that miR-143-3p levels are downregulated in the peripheral blood of patients with GDM. Therefore, miR-143-3p overexpression may serve as a method for preventing pancreatic β cell dysfunction by inhibiting the TAK1/NF-κB pathway.

The immune-related circRNA-miRNA-mRNA ceRNA regulatory network in the liver of turbot (Scophthalmus maximus L.) induced by Vibrio anguillarum

Recently, Vibrio anguillarum, a Gram-negative pathogenic bacterium, has been becoming a major constraint on the development of the turbot aquaculture industry because of its characteristics of worldwide distribution, broad host range and potentially devastating impacts. Although the functions of protein-coding mRNAs in the immune response against bacterial infection have been reported, as well as several non-coding RNAs (ncRNAs), such as circular RNAs (circRNAs) and microRNAs (miRNAs), the relationships between mRNAs and ncRNAs in the immune system of turbot liver are still limited during bacterial infection. In present study, the comprehensive analyses of whole-transcriptome sequencing were conducted in turbot liver infected by V. anguillarum. The differential expression was analyzed in the data of circRNAs, miRNAs, and mRNAs. The interactions of miRNA-circRNA pairs and miRNA-mRNA pairs were predicted basing on the negative regulatory relationships between miRNAs and their target circRNAs\\mRNAs. The circRNA-related ceRNA regulatory networks were constructed for the analyses of regulated mechanism in turbot immune system. Subsequently, the RT-qPCR was carried out to verify the results of sequencing. Finally, we identified 31 circRNAs, 53 miRNAs and 948 mRNAs with differential expression. Gene set enrichment analyses using Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways showed that innate immunity was principally activated at the early stages of infection, while adaptive immunity was activated after 24 h. Finally, 65 circRNA-miRNA-mRNA pathways were constructed, based on the hypothesis of ceRNA regulatory networks. In conclusion, our findings provide new insights on the underlying immune response to bacterial infection and identify novel target genes for the prevention and control of disease in turbot.

Reconstruction and analysis of circRNA-miRNA-mRNA network in the pathology of lung cancer.

The presented study aimed to gain insights into the pathogenesis of lung cancer (LC) and provide novel bio-markers for LC by building a regulatory circular (circ) RNAmicro (mi) RNAmRNA network. High-throughput sequencing data of circRNAs, miRNAs and mRNAs related to LC originated from GEO (Gene Expression Omnibus) database, and the differential expressions of circRNAs, miRNAs and mRNAs were screened with R language Limma. The circRNA-miRNA and miRNA-mRNA pairs were used to build the ceRNA network. The functions of differential expression circRNAs were elucidated by performing the functional enrichment analysis on GO and KEGG. Furthermore, the selected LC prognostic genes were verified by tissue chips and immunohistochemistry (IHC). On the whole, 20 downregulated circRNAs, 55 upregulated miRNAs and 243 downregulated mRNAs were identified in LC. Lastly, a circRNA-miRNA-mRNA ceRNA network was built, which was composed of 2 circRNAs, 2 miRNAs, and 2 mRNAs. As indicated from the analysis based on public databases and IHC, the differential genes (i.e., FXYD1 and SEMA5A) in this network acted as LC prognostic factors. As confirmed by performing IHC and survival analyses, FXYD1 and SEMA5A expressions in LC were downregulated, and their expressions displayed a relationship to the overall survival (OS) of LC cases. This study presents novel insights into the role of circRNAs in the development of LC via the ceRNA mechanism. The identified FXYD1 and SEMA5A gene could act as novel and vital LC prognostic indicators.

Integrated miRNA and mRNA omics reveal dioscin suppresses migration and invasion via MEK/ERK and JNK signaling pathways in human endometrial carcinoma in vivo and in vitro

Ethnopharmacological relevancePolygonatum sibiricum Redouté (PS, also called Huangjing in traditional Chinese medicine), is a perennial herb as homology of medicine and food. According to the traditional Chinese medicine theory “Special Records of Famous Doctors”, its functions include invigorating qi and nourishing yin, tonifying spleen and kidney. Traditionally, qi and blood therapy has been believed as most applicable to the treatment of uterine disease. The current research has focused on the effect and mechanism of dioscin, the main active component of PS, on Endometrial carcinoma (EC). Aim of the studyTo study the efficacy of dioscin on proliferation and migration of Endometrial carcinoma cell line, we conducted experiments by using xenograft model and Ishikawa cells, and explored the potential molecular mechanism. Materials and methodsmRNA and miRNA omics techniques were employed to investigate the regulatory mechanism of dioscin on EC Ishikawa cells. Based on in vivo and in vitro experiments, cell clone formation, cell scratching, Transwell, H&E staining, immunohistochemistry, q-PCR, and Western blot techniques were used to determine the molecular effects and mechanisms of dioscin on cell migration. ResultsIntegrated miRNA and mRNA omics data showed that 513 significantly different genes marked enrichment in MAPK signaling pathway. The in vivo data showed that dioscin (24 mg/kg) significantly inhibited tumor growth. The in vitro proliferation and invasiveness of dioscin on Ishikawa cells showed that dioscin could significantly decrease the colony numbers, and suppress the Ishikawa cell wound healing, migration and invasion. Molecular data revealed that dioscin decreased the MMP2 and MMP9 expression in vitro and in vivo. The p-MEK, p-ERK, and p-JNK expression levels were also confirmed to be significantly reduced. Key regulators in the MAPK signaling pathway were further validated in xenograft tumors. ConclusionOur data indicated that dioscin inhibited Ishikawa cell migration and invasion mediated through MEK/ERK and JNK signaling. More importantly, screened hub miRNAs and genes can be regarded as potential molecular targets for future EC treatment.

SGAEMDA: Predicting miRNA-Disease Associations Based on Stacked Graph Autoencoder.

MicroRNA (miRNA)-disease association (MDA) prediction is critical for disease prevention, diagnosis, and treatment. Traditional MDA wet experiments, on the other hand, are inefficient and costly.Therefore, we proposed a multi-layer collaborative unsupervised training base model called SGAEMDA (Stacked Graph Autoencoder-Based Prediction of Potential miRNA-Disease Associations). First, from the original miRNA and disease data, we defined two types of initial features: similarity features and association features. Second, stacked graph autoencoder is then used to learn unsupervised low-dimensional representations of meaningful higher-order similarity features, and we concatenate the association features with the learned low-dimensional representations to obtain the final miRNA-disease pair features. Finally, we used a multilayer perceptron (MLP) to predict scores for unknown miRNA-disease associations. SGAEMDA achieved a mean area under the ROC curve of 0.9585 and 0.9516 in 5-fold and 10-fold cross-validation, which is significantly higher than the other baseline methods. Furthermore, case studies have shown that SGAEMDA can accurately predict candidate miRNAs for brain, breast, colon, and kidney neoplasms.

Let-7b-5p inhibits colon cancer progression by prohibiting APC ubiquitination degradation and the Wnt pathway by targeting NKD1.

Naked cuticle homolog 1 (NKD1), which is expressed at low levels in many tumors, is considered an inhibitor of the Wnt/β-catenin pathway, but it is highly expressed in colon cancer and can promote colon cancer cell proliferation. miRNAs are involved in the occurrence and progression of many tumors. However, miRNAs that can regulate NKD1 and the mechanisms by which NKD1 regulates tumor progression remain ambiguous. This research aims to reveal the potential regulatory network of NKD1 in colon cancer. miRNA data downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were analyzed by bioinformatics to screen for potential miRNAs targeting NKD1. Let-7b-5p was found to inhibit proliferation, migration, and invasion of colon cancer cells targeting NKD1. Further studies suggested that let-7b-5p can modulate Wnt signaling activity, and the nuclear accumulation of β-catenin was significantly restrained by let-7b-5p through targeting NKD1. Moreover, NKD1 could prohibit the expression of the APC protein. Further studies manifested that NKD1 bound to APC and promoted the ubiquitination degradation of APC through restraining the expression of the deubiquitinating enzyme USP15 and blocking the combination between USP15 and APC. Functionally, NKD1 enhanced the proliferation and migration of colon cancer cells by inhibiting APC expression. This research revealed a novel mechanism by which the let-7b-5p-NKD1-APC-β-catenin signaling pathway inhibited colon cancer cell progression.

Addressing the Clinical Feasibility of Adopting Circulating miRNA for Breast Cancer Detection, Monitoring and Management with Artificial Intelligence and Machine Learning Platforms

Detecting breast cancer (BC) at the initial stages of progression has always been regarded as a lifesaving intervention. With modern technology, extensive studies have unraveled the complexity of BC, but the current standard practice of early breast cancer screening and clinical management of cancer progression is still heavily dependent on tissue biopsies, which are invasive and limited in capturing definitive cancer signatures for more comprehensive applications to improve outcomes in BC care and treatments. In recent years, reviews and studies have shown that liquid biopsies in the form of blood, containing free circulating and exosomal microRNAs (miRNAs), have become increasingly evident as a potential minimally invasive alternative to tissue biopsy or as a complement to biomarkers in assessing and classifying BC. As such, in this review, the potential of miRNAs as the key BC signatures in liquid biopsy are addressed, including the role of artificial intelligence (AI) and machine learning platforms (ML), in capitalizing on the big data of miRNA for a more comprehensive assessment of the cancer, leading to practical clinical utility in BC management.

Optimal microRNA Sequencing Depth to Predict Cancer Patient Survival with Random Forest and Cox Models.

(1) Background: tumor profiling enables patient survival prediction. The two essential parameters to be calibrated when designing a study based on tumor profiles from a cohort are the sequencing depth of RNA-seq technology and the number of patients. This calibration is carried out under cost constraints, and a compromise has to be found. In the context of survival data, the goal of this work is to benchmark the impact of the number of patients and of the sequencing depth of miRNA-seq and mRNA-seq on the predictive capabilities for both the Cox model with elastic net penalty and random survival forest. (2) Results: we first show that the Cox model and random survival forest provide comparable prediction capabilities, with significant differences for some cancers. Second, we demonstrate that miRNA and/or mRNA data improve prediction over clinical data alone. mRNA-seq data leads to slightly better prediction than miRNA-seq, with the notable exception of lung adenocarcinoma for which the tumor miRNA profile shows higher predictive power. Third, we demonstrate that the sequencing depth of RNA-seq data can be reduced for most of the investigated cancers without degrading the prediction abilities, allowing the creation of independent validation sets at a lower cost. Finally, we show that the number of patients in the training dataset can be reduced for the Cox model and random survival forest, allowing the use of different models on different patient subgroups.

A novel approach for a joint analysis of isomiR and mRNA expression data reveals features of isomiR targeting in breast cancer.

A widely used procedure for selecting significant miRNA-mRNA or isomiR-mRNA pairs out of predicted interactions involves calculating the correlation between expression levels of miRNAs/isomiRs and mRNAs in a series of samples. In this manuscript, we aimed to assess the validity of this procedure by comparing isomiR-mRNA correlation profiles in sets of sequence-based predicted target mRNAs and non-target mRNAs (negative controls). Target prediction was carried out using RNA22 and TargetScan algorithms. Spearman's correlation analysis was conducted using miRNA and mRNA sequencing data of The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) project. Luminal A, luminal B, basal-like breast cancer subtypes, and adjacent normal tissue samples were analyzed separately. Using the sets of putative targets and non-targets, we introduced adjusted isomiR targeting activity (ITA)-the number of negatively correlated potential isomiR targets adjusted by the background (estimated using non-target mRNAs). We found that for most isomiRs a significant negative correlation between isomiR-mRNA expression levels appeared more often in a set of predicted targets compared to the non-targets. This trend was detected for both classical seed region binding types (8mer, 7mer-m8, 7mer-A1, 6mer) predicted by TargetScan and the non-classical ones (G:U wobbles and up to one mismatch or unpaired nucleotide within seed sequence) predicted by RNA22. Adjusted ITA distributions were similar for target sites located in 3'-UTRs and coding mRNA sequences, while 5'-UTRs had much lower scores. Finally, we observed strong cancer subtype-specific patterns of isomiR activity, highlighting the differences between breast cancer molecular subtypes and normal tissues. Surprisingly, our target prediction- and correlation-based estimates of isomiR activities were practically non-correlated with the average isomiR expression levels neither in cancerous nor in normal samples.

The effects of circulating MIR22-3p and MIR16-1-3p levels in different stages of subacute thyroiditis

Subacute thyroiditis (SAT) is an inflammatory thyroid disease with a frequency is 5% among all thyroid diseases. miRNAs are endogenous, non-coding RNAs ranging in length from 19 to 25 nucleotides. They play an important role in the posttranscriptional regulation of gene expression. In this study, we aimed to investigate whether the expression levels of two circulating miRNAs, MIR22 and MIR16-1, can be used as a parameter in the diagnosis and follow-up of SAT disease. Fifty patients diagnosed with SAT and 41 healthy controls were included in this study. Expression levels of miRNAs were determined by real time-PCR method. Expression data of miRNAs were calculated by fold change (2-ΔΔCt) method. The statistical significance of miRNA expression was evaluated by t-test. The expression levels of MIR22-3p and MIR16-1-3p were not found to be statistically different between SAT patients and controls and also between the patients in different stages (hyperthyroid, euthyroid, and hypothyroid) of the disease. According to correlation analyses, we observed a positive strong correlation between erythrocyte sedimentation rate (ESR) and the expression levels of MIR22-3p and MIR16-1-3p (r = 0.960, p = 0.000 and r = 0.865, p = 0.006, respectively), and a positive strong correlation between fT4 and the expression levels of MIR22-3p in SAT patients in euthyroid stage (r = 0.712, p = 0.047). In this study, we showed that the expression levels of MIR22-3p and MIR16-1-3p have correlation with clinical characteristics of SAT disease. Our results suggest that MIR22 and MIR16-1 may be effective in the pathogenesis of SAT.

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.