Hub miRNAs Research Articles

Integrative Analysis of MicroRNA and Gene Interactions for Revealing Candidate Signatures in Prostate Cancer.

MicroRNA (miRNA)–gene interactions are well-recognized as involved in the progression of almost all cancer types including prostate cancer, which is one of the most common cancers in men. This study explored the significantly dysregulated genes and miRNAs and elucidated the potential miRNA–gene regulatory network in prostate cancer. Integrative analysis of prostate cancer and normal prostate transcriptomic data in The Cancer Genome Atlas dataset was conducted using both differential expression analysis and weighted correlation network analysis (WGCNA). Thirteen genes (RRM2, ORC6, CDC45, CDKN2A, E2F2, MYBL2, CCNB2, PLK1, FOXM1, CDC25C, PKMYT1, GTSE1, and CDC20) were potentially correlated with prostate cancer based on functional enrichment analyses. MiRNAs targeting these genes were predicted and eight miRNAs were intersections between those miRNAs and the hub miRNAs obtained from miRNA WGCNA analysis. Three genes (E2F2, RRM2, and PKMYT1) and four miRNAs (hsa-mir-17-5p, hsa-mir-20a-5p, hsa-mir-92a-3p, and hsa-mir-93-5p) were key factors according to the interaction network. RRM2 and PKMYT1 were significantly related to survival. These findings partially elucidated the dysregulation of gene expressions in prostate cancer. Efficient manipulations of the miRNA–gene interactions in prostate cancer may be exploited as promising therapeutics.

Molecule mechanisms of Ganoderma lucidum treated hepatocellular carcinoma based on the transcriptional profiles and miRNA-target network

Ganoderma lucidum has salutary effects on tumor treatment, including pancreatic cancer and hepatocellular carcinoma. However, the molecular mechanisms underlying Ganoderma lucidum therapy is obscure. In this study, the Hepa1-6-bearing C57 BL/6 mouse model was utilized to explore the therapeutic efficacy of Ganoderma lucidum extract (GLE), documenting that it could effectively inhibit tumor growth. The microRNA (miRNA) profiles of GLE-treated and untreated mice were detected, and 25 differentially expressed (DE) miRNAs were determined, including 24 up-expressed and one down-expressed miRNAs. Using the ClusterOne algorithm, 8 hub miRNAs were isolated from the established miRNA-target network. The qRT-PCR assay demonstrated that these 8 miRNAs were up-expressed in the GLE treated tumor mice. Furthermore, the mRNA profiles showed that there are 76 DE mRNAs between GLE treated and model groups. The protein-protein interaction (PPI) network shows that Cntn1, Irs1, Nfkbia, Rybp and Ywhaz playing important roles, and qRT-PCR further revealed they were down-expressed in GLE treated Hepa1-6-bearing C57 BL/6 mice. The rebuilt miRNA-target network was shown that these 5 mRNAs were regulated by mmu-mir-23a-5p, -3102-3p, -337-3p, and -467a-3p, respectively. This study suggested that these 4 interesting miRNAs were potential biomarkers for evaluation of GLE efficacy, which may down-regulate the expression of Cntn1, Irs1, Nfkbia, Rybp and Ywhaz, and mediate many signaling pathways occurring in tumor treatment.

MiR-3940-5p promotes granulosa cell proliferation through targeting KCNA5 in polycystic ovarian syndrome

Increased granulosa cell (GC) proliferation may contribute to abnormal folliculogenesis in patients with polycystic ovary syndrome (PCOS), which affects approximately 10% reproductive aged women. However, the mechanisms underlying increased GC proliferation in PCOS remain incompletely understood. In this study, we identified miR-3940-5p as a hub miRNA in GC from PCOS using weighted gene co-expression network analysis (WGCNA), and real-time polymerase chain reaction (RT-PCR) analysis confirmed that miR-3940-5p was significantly increased in GC from PCOS. Enrichment analysis of predicted target genes of miR-3940-5p indicated potential roles of miR-3940-5p in follicular development and cell proliferation regulation. Consistently, functional study confirmed that miR-3940-5p overexpression promoted granulosa cell proliferation. Integrated analysis of mRNA expression profiling data and predicted target genes of miR-3940-5p identified potassium voltage-gated channel subfamily A member 5 (KCNA5) as a potential target of miR-3940-5p, and was validated by luciferase reporter assay. Finally, functional analysis suggested that miR-3940-5p promoted GC proliferation in a KCNA5 dependent manner. In conclusion, miR-3940-5p was a hub miRNA upregulated in GC from PCOS, and promoted GC proliferation by targeting KCNA5.

Screening and Functional Analysis of Hub MicroRNAs Related to Tumor Development in Colon Cancer

Various microRNAs (miRNAs) are of importance in the development of colon cancer, but most of the mechanisms of the miRNAs are still unclear. In order to clarify the hub miRNAs and their roles in colon cancer development, GSE98406 was used to screen hub miRNAs by bioinformatics analysis. 46 DE-miRNAs (14 were upregulated and 32 were downregulated) and 1738 target genes of DE-miRNAs were ascertained. miRNAs-gene-networks and miRNAs-GO-networks were built to get more knowledge about the function of candidate miRNAs. After validation, three miRNAs (miR-17-5p, miR-182-5p and miR-200a-3p) were recognized to be hub miRNAs associated with the progression of colon cancer. More importantly, the hub miRNAs and the putative targets genes might be new diagnostic and therapeutic targets for colon cancer in the future.

Comprehensive Analysis of Competitive Endogenous RNAs Network, Being Associated With Esophageal Squamous Cell Carcinoma and Its Emerging Role in Head and Neck Squamous Cell Carcinoma.

Esophageal squamous cell carcinoma (ESCC) is a common malignancy with poor prognosis and survival rate. To identify meaningful long non-coding RNA (lncRNA), microRNA (miRNA), and messenger RNA (mRNA) modules related to the ESCC prognosis, The Cancer Genome Atlas-ESCC was downloaded and processed, and then, a weighted gene co-expression network analysis was applied to construct lncRNA co-expression networks, miRNA co-expression networks, and mRNA co-expression networks. Twenty-one hub lncRNAs, seven hub miRNAs, and eight hub mRNAs were clarified. Additionally, a competitive endogenous RNAs network was constructed, and the emerging role of the network involved in head and neck squamous cell carcinoma (HNSCC) was also analyzed using several webtools. The expression levels of eight hub genes (TBC1D2, ATP6V0E1, SPI1, RNASE6, C1QB, C1QC, CSF1R, and C1QA) were different between normal esophageal tissues and HNSCC tissues. The expression levels of TBC1D2 and ATP6V0E1 were related to the survival time of HNSCC. The competitive endogenous RNAs network might provide common mechanisms involving in ESCC and HNSCC. More importantly, useful clues were provided for clinical treatments of both diseases based on novel molecular advances.

Related Network and Differential Expression Analyses Identify Nuclear Genes and Pathways in the Hippocampus of Alzheimer Disease.

BackgroundAlzheimer disease (AD) is a typical progressive and destructive neurodegenerative disease that has been studied extensively. However, genetic features and molecular mechanisms underlying AD remain unclear. Here we used bioinformatics to investigate the candidate nuclear genes involved in the molecular mechanisms of AD.Material/MethodsFirst, we used Gene Expression Omnibus (GEO) database to obtain the expression profiles of the mRNAs from hippocampus microarray and identify differentially expressed genes (DEGs) the plier algorithm. Second, functional annotation and visualization of the DEGs were conducted by the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Finally, BioGRID, IntAct, STRING, and Cytoscape were utilized to construct a protein-protein interaction (PPI) network. Hub genes were analytically obtained from the PPI network and the microRNA (miRNA)-target network.ResultsTwo hippocampus microarrays (GSE5281 and GSE48350) were obtained from the GEO database, comprising 161 and 253 cases separately. Among these, 118 upregulated genes and 694 downregulated genes were identified. The upregulated DEGs were mainly involved in positive regulation of transcription from RNA polymerase II promoter, positive regulation of cartilage development, and response to wounding. The downregulated DEGs were enriched in chemical synaptic transmission, neurotransmitter secretion, and learning. By combining the results of PPI and miRNA-target network, 8 genes and 2 hub miRNAs were identified, including YWHAZ, DLG4, AGAP2, EGFR, TGFBR3, PSD3, RDX, BRWD1, and hsa-miR-106b-5p and hsa-miR-93-5p. These target genes are highly enriched in various key pathways, such as amyloid-beta formation, regulation of cardiocyte differentiation, and actin cytoskeleton reorganization.ConclusionsIn this study, YWHAZ, DLG4, AGAP2, EGFR, TGFBR3, PSD3, RDX, and BRWD1 were identified as candidate genes for future molecular studies in AD, which is expected to improve our understanding of its cause and potential molecular mechanisms. Nuclear genes, DEGs, and related networks identified by integrated bioinformatics analysis may serve as diagnostic and therapeutic targets for AD.

Identification of Potential Biomarkers for Intervertebral Disc Degeneration Using the Genome-Wide Expression Analysis.

Intervertebral disc degeneration (IDD) is the major cause of low back pain. The current study was aimed to further elucidate the mechanisms underlying it. Microarray data sets GSE70362 containing Thompson degeneration grades I-V were divided into the control and the degenerative group and were analyzed. Differentially expressed genes (DEGs) were screened and clustered, followed by functional enrichment analysis. Then the protein-protein interaction (PPI) network and the microRNA (miRNA) regulatory network were constructed and integratedly analyzed. Finally, modules from the integrated network were mined, and gene ontology and pathway enrichment analysis were performed. DEGs in three clusters had the overall expression trend with the Thompson grades. The upregulated DEGs were associated with protein transport and localization, while the downregulated DEGs were enriched in membrane lipid metabolic process and endocytosis. After the integrated analysis of PPI and miRNA-target interactions, some hub genes such as HSP90B1, RPS4Y1, RPL15, and UTY, as well as hub miRNAs, including miR-124a and miR-506, were screened. Finally, modules in the integrated network were functionally associated with protein targeting, peptide processing, and metabolic process, as well as protein folding. Taken together, our data showed that the protein synthesis, targeting, and localization can be greatly changed to contribute to the progress of IDD. Besides, the related genes such as RPS4Y1 and HSP90B1 would be used as diagnostic and therapeutic targets for IDD.

Investigation of key miRNAs and potential mechanisms in non-small cell lung cancer development from chronic obstructive pulmonary disease.

Lung cancer (LC) is the prominent cause of cancer-related death worldwide, and non-small cell lung cancer (NSCLC) represents approximately 85% of all diagnosed LC cases. It is stated that LC and chronic obstructive pulmonary disease (COPD) are directly linked at a molecular genetics level. Early diagnosis of LC is important for individuals affected by COPD. This study aims to construct a molecular network to discover molecules in NSCLC development from COPD. We downloaded the expression profiles of COPD patients from Gene Expression Omnibus database. The Database Annotation for Visualization and Integrated Discovery tool was utilized for enrichment analysis; STRING and Cytoscape were used for network construction. 15 hub genes were detected among 1517 differentially expressed genes (DEGs). Additionally, 20 differentially expressed miRNAswere identified from five datasets. We constructed miRNA-mRNA regulatory network between the groups of overlapping predicted target genes/DEGs and miRNAs that contained miRNA-mRNA pairs. UALCAN and OncomiR web-portals were used to validate hub genes and miRNAs in NSCLC. JUN, IL6, CD4 and hsa-miR-497-5p, hsa-miR-130b-5p were verified in both lung adenocarcinomas and lung squamous cell carcinomas. This study presents potential biomarkers and mechanisms underlying NSCLC development from COPD that would be targeted for early intervention.

Global Analysis of miRNA Signature Differentially Expressed in Insulin-resistant Human Hepatocellular Carcinoma Cell Line.

Chemoresistance mediated by insulin resistance (IR) in HCC has already been validated. However, the underlying mechanism, especially the involvement of microRNAs (miRNAs) was unelucidated. In this study, miRNA microarrays and bioinformatics methods were employed to determine the dysregulation of miRNA by IR in HCC cells, and quantitative RT-PCR (qRT-PCR) was applied to valid the miRNA array data. Of all the 2006 miRNAs screened, 32 miRNAs were found up or down regulated between the HepG2/IR cells and its parental cells. Further literature mining revealed that some of these miRNAs may function as oncogenes or tumor suppressors that contribute to tumor progression, recurrence, and metastasis which eventually lead to chemotherapeutic resistance. Interestingly, bioinformatics analysis by Gene Ontology (GO) enrichment pathway indicating that function of the predicted target genes of these dysregulated miRNAs were significantly enriched in the processes related with biosynthesis, catabolism, modification etc., and Kyoto Encyclopedia of Genes and Genomes (KEGG) mapping showed that the biological regulatory mechanisms were integrated in cancer-related pathways. Moreover, we also constructed a network which connected the differentially expressed miRNAs to target genes, GO enrichments and KEGG pathways to reveal the hub miRNAs, genes and pathways. Collectively, our present study demonstrated the possible miRNAs and predicted target genes involving in the pathophysiology of insulin resistant HCC, providing novel insights into the molecular mechanisms of multidrug resistance in the insulin resistant HepG2 cells.

PSVI-15 Transcriptome analysis of ileal lymph nodes identifies key microRNAs affecting disease progression in Holstein cows with subclinical Johne’s disease

Abstract Johne’s disease (JD) is a chronic enteric disease of ruminants caused by Mycobacterium avium subsp. Paratuberculosis (MAP) but immune and metabolic mechanisms affecting JD progression have not been clearly elucidated. MicroRNAs (miRNA) have been reported to play important roles in numerous biological processes by regulating gene expression. In this study, miRNA expression in ileal lymph nodes (ILLN) from MAP positive (JD subclinical stage) Holstein cows (n = 5) and MAP negative cows (n = 5) were characterized by high throughput sequencing. MiRNA-sequence data was processed using a standard pipeline followed by functional enrichment with ClueGo app in Cytoscape. Among 324 expressed miRNAs, 37 were differently expressed (DE) (18 up-regulated and 19 down-regulated) in MAP infected cows relative to MAP negative cows. Bta-miR-100 (fold change = -2.29), a down-regulated miRNA, has previously been associated with Streptococcus uberis and MAP infections in cows, while bta-miR-330 (fold change = 63.42), the most up-regulated miRNA, was previously reported to be present in the sera of MAP infected calves. Predicted target genes of 37 DE miRNAs were enriched (P < 0.05) in gene ontology terms related to metabolic, cellular and developmental processes, and immune system development, as well as pathways related to cancer and Th17 cell differentiation, and lysosome compartmentalization. This suggests that miRNAs DE following MAP infection may be involved in regulating a wide variety of processes. In addition, 5 DE miRNAs were negatively correlated (P < 0.05) with 39 DE mRNAs (mRNAs expressed in the same tissue), comprising 42 negatively correlated DE miRNA-mRNA pairs. Bta-miR-2447 was negatively correlated with 29 DE mRNAs, suggesting it may be an important hub miRNA in the regulation of MAP infection in ILLN tissue. Our data thus suggest that bta-miR-100, bta-miR-330 and bta-miR-2447, which are implicated in the Th17 cell differentiation pathway, may be key regulators of the host response during MAP infection in ILLN.

Analysis of whole genome-wide microRNA transcriptome profiling in invasive pituitary adenomas and non-invasive pituitary adenomas

BackgroundDysregulation of microRNAs (miRNAs) plays a critical role during the occurrence and progress of pituitary adenomas (PAs). However, the roles of miRNAs in the invasiveness of PA are poorly understood. This study aims to more comprehensively and specific define the relationship between altered miRNA and PA invasion.MethodsThe differential expression of miRNAs (DEMs) between invasive PAs (IPAs) and non-invasive PAs (NPAs) was explored by RNA sequencing and which functions were analyzed by gene ontology (GO) as well as Kyoto Encyclopedia of Genes and Genomes (KEGG). The miRNA-mRNA network was predicted with bioinformatics.ResultsWe identified 31 upregulated miRNAs and 24 downregulated miRNAs in IPAs compared with NPAs. GO analysis and KEGG pathway analysis showed the DEMs were mainly associated with cell proliferation and cell cycle pathway. In addition, on the count of predicted miRNA-mRNA network, two hub miRNAs were identified.ConclusionsOur results demonstrate the miRNA-mRNA network in detail, which suggest that miRNA may be a promising target in diagnosis and therapy for IPAs.

A novel circRNA-miRNA-mRNA network identifies circ-YOD1 as a biomarker for coronary artery disease

Circular RNAs (circRNAs) are involved in many physiological functions. Whether circulating circRNAs serve as markers for coronary artery disease (CAD) is unknown. Seven CAD-related microarray datasets were downloaded from the Gene Expression Omnibus (GEO) database and were analyzed using clustering and functional enrichment to identify hub mRNAs and miRNAs. StarBase V3.0 and circinteractome databases were used to predict interactions between circRNAs and miRNAs whereas miRwalk and DIANA TOOLS were used to predict interactions between miRNAs and mRNAs. Altogether, this helped establish a circRNA-miRNA-mRNA triple network for diagnosis of CAD. Five non-coding RNAs (ncRNAs) were identified in our study population with the use of quantitative real-time PCR (RT-PCR). The prognostic values of circYOD1, hsa-miR-21-3p and hsa-miR-296-3p were evaluated using a receiver operating characteristic (ROC) curve. A CAD circRNA-miRNA-mRNA network was established from our analyses containing one circRNA, four miRNAs and thirteen mRNAs. After performing RT-PCR validation between CAD and non-CAD samples, only three ncRNAs of five ncRNAs showed significance for further analysis. The area under ROC curve (AUC) of circ-YOD1 was 0.824, the AUC of hsa-miR-21-3p was 0.731 and hsa-miR-296-3p was 0.776. The pairwise comparison results showed that circ-YOD1 had statistical significance (PYOD1-21 < 0.01 and PYOD1-296 < 0.05). The results of functional enrichment analysis of interacting genes and microRNAs showed that the shared circ-YOD1 may act as a new biomarker for CAD. Our investigation of the triple regulatory networks of circRNA-miRNA-mRNA in CAD revealed circ-YOD1 as a potential biomarker for CAD.

A Circulating miRNA-Based Scoring System Established by WGCNA to Predict Colon Cancer.

Introduction Circulation microRNAs (miRNAs) perform as potential diagnostic biomarkers of many kinds of cancers. This study is aimed at identifying circulation miRNAs as diagnostic biomarkers in colon cancer. Methods We conducted a weighted gene coexpression network analysis (WGCNA) in miRNAs to find out the expression pattern among circulation miRNAs by using a “WGCNA” package in R. Correlation analysis was performed to find cancer-related modules. Differentially expressed miRNAs (DEmiRs) in colon cancer were identified by a “limma” package in R. Hub gene analysis was conducted for these DEmiRs in the cancer-related modules by the “closeness” method in cytoscape software. Then, logistic regression was performed to identify the independent risk factors, and a scoring system was constructed based on these independent risk factors. Then, we use data from the GEO database to confirm the reliability of this scoring system. Results A total of 9 independent coexpression modules were constructed based on the expression levels of 848 miRNAs by WGCNA. After correlation analysis, green (cor = 0.77, p = 3 × 10‐25) and yellow (cor = 0.65, p = 6 × 10‐16) modules were strongly correlated with cancer development. 20 hub genes were found after hub gene analysis in these DEmiRs by cytoscape. Among all these hub genes, hsa-miR-23a-3p (OR = 2.6391, p = 6.23 × 10‐5) and hsa-miR-663a (OR = 1.4220, p = 0.0069) were identified as an independent risk factor of colon cancer by multivariate regression. Furthermore, a scoring system was built to predict the probability of colon cancer based on both of these miRNAs, the area under the curve (AUC) of which was 0.828. Data from GSE106817 and GSE112264 was used to confirm this scoring system. And the AUC of them was 0.980 and 0.917, respectively. Conclusion We built a scoring system based on circulation hub miRNAs found by WGCNA to predict the development of colon cancer.

MiR-30a-GNG2 and miR-15b-ACSS2 Interaction Pairs May Be Potentially Crucial for Development of Abdominal Aortic Aneurysm by Influencing Inflammation.

Abdominal aortic aneurysm (AAA) is a lethal vascular degenerative disease for the elderly, but current therapeutic options are limited. This study was to explore the molecular mechanisms of AAA to screen underlying treatment targets for AAA. The gene and microRNA (miRNA) expression profiles of human AAA were downloaded from Gene Expression Omnibus database under accession number GSE57691, GSE62179, and GSE63541. Differentially expressed genes (DEGs) and microRNAs (miRNAs; DEMs) were identified using the Linear Models for Microarray data method. Protein-protein interaction (PPI) network, module analysis, and miRNA-mRNA regulatory network analyses were performed to screen hub genes and miRNAs that regulated the hub genes. The Database for Annotation, Visualization and Integrated Discovery was used to predict the functions of genes. GEPIA and Tumor-miRNA-Pathway online software were used to validate the expressions of crucial DEMs and DEGs in other cancers, respectively. As a result, in the GSE57691 dataset, a total of 584 DEGs were found to be specific for AAA, 521 of which were used for constructing the PPI network. ACSS2 (acyl-CoA synthetase short-chain family member 2), GNG2 (G protein subunit gamma 2), and CXCL1 (C-X-C motif chemokine ligand 1) and CCR7 (C-C motif chemokine receptor 7) were believed to be hub genes by calculating their topological features in the PPI network. Upregulated GNG2 could interact with CXCL1 and CCR7 to involve in chemokine signaling pathway, while downregulated ACSS2 was associated with lipid biosynthetic process. In the miRNA-mRNA regulatory network, ACSS2 was found to be regulated by hsa-miR-15b; hsa-miR-30a could modulate the expression of GNG2. In line with our analysis in AAA, GNG2, ACSS2, hsa-miR-30a, and hsa-miR-15b were also confirmed to be significantly upregulated or downregulated in several cancer types. In conclusion, hsa-miR-30a-GNG2 and hsa-miR-15b-ACSS2 interaction pairs may represent novel mechanisms for explaining the pathogenesis of AAA. Targeted regulation of them may be potential strategies for treatment of AAA.

Construction and analysis of circular RNA molecular regulatory networks in clear cell renal cell carcinoma.

Increasing evidence has indicated that circular (circ)RNAs participate in carcinogenesis; however, the specific regulatory mechanisms underlying the effects of circRNAs, microRNAs (miRNAs/miRs) and genes on the development of clear cell renal cell carcinoma (CCRCC) remain unclear. In the present study, RNA microarray data from CCRCC tissues and control samples were downloaded from the Gene Expression Omnibus and The Cancer Genome Atlas, in order to identify significantly dysregulated circRNAs, miRNAs and genes. The Cancer-Specific circRNA Database was used to explore the interactions between miRNAs and circRNAs, whereas TargetScan and miRDB were employed to predict the mRNA targets of miRNAs. Functional enrichment and prognostic analyses were conducted in R. The results revealed that 324 circRNAs were downregulated, whereas 218 circRNAs were upregulated in cancer. In addition, a circRNA-miRNA-mRNA interaction network was constructed. Gene Ontology analysis of the upregulated genes revealed that these genes were enriched in biological processes, including ‘flavonoid metabolic process’, ‘cellular glucuronidation’ and ‘T cell activation’. The downregulated genes were mainly enriched in biological processes, such as ‘nephron development’, ‘kidney development’ and ‘renal system development’. The hub genes, including membrane palmitoylated protein 7, aldehyde dehydrogenase 6 family member A1, transcription factor AP-2α, collagen type IV α 4 chain, nuclear receptor subfamily 3 group C member 2, plasminogen, Holliday junction recognition protein, claudin 10, kinesin family member 18B and thyroid hormone receptor β, and the hub miRNAs, including miR-21-3p, miR-155-3p, miR-144-3p, miR-142-5p, miR-875-3p, miR-885-3p, miR-3941, miR-224-3p, miR-584-3p and miR-138-1-3p, were significantly associated with CCRCC survival. In conclusion, these results suggested that the significantly dysregulated circRNAs, miRNAs and genes identified in this study may be considered potential biomarkers of the carcinogenesis of CCRCC and the survival of patients with this disease.

The four‑microRNA signature identified by bioinformatics analysis predicts the prognosis of nasopharyngeal carcinoma patients.

The aim of the present study was to identify microRNAs (miRNAs) that predict the prognosis of patients with nasopharyngeal carcinoma by integrated bioinformatics analysis. First, the original microarray dataset GSE32960, including 312 nasopharyngeal carcinomas and 18 normal samples, was downloaded from the Gene Expression Omnibus database. In addition, 46 differentially expressed miRNAs (DEMs) were screened. Then, four miRNAs, including hsa-miR-142-3p, hsa-miR-150, hsa-miR-29b, and hsa-miR-29c, were obtained as prognostic markers by combining univariate Cox regression analysis with weighted gene coexpression network analysis (WGCNA). Subsequently, the risk score of 312 NPC patients from the signature of miRNAs was calculated, and patients were divided into high-risk or low-risk groups. Notably, compared with patients with low-risk scores, high-risk groups had shorter disease-free survival (DFS), overall survival (OS), and distant metastasis-free survival (DMFS). Receiver operating characteristic curve (ROC) analysis indicated that the risk score was a very effective prognostic factor. Moreover, the Search Tool for the Database for Annotation, Visualization, and Integrated Discovery (DAVID), Cytoscape, starBase, and Retrieval of Interacting Genes database (STRING) were used to establish the miRNA-mRNA correlation network and the protein-protein interaction (PPI) network. In addition, the shared genes superimposing 888 protein-coding genes targeted by four hub miRNAs and 1,601 upregulated differentially expressed mRNAs accounted for 127 and were used for subsequent gene functional enrichment analysis. In particular, biological pathway analysis indicated that these genes mainly participate in some vital pathways related to cancer pathogenesis, such as the focal adhesion, PI3K/Akt, p53, and mTOR signalling pathways. In summary, the identification of NPC patients with a four-miRNA signature may increase the prognostic value and provide reference information for precision medicine.

Comparison of microRNAs in adipose and muscle tissue from seven indigenous Chinese breeds and Yorkshire pigs.

Elucidation of the pig microRNAome is essential for interpreting functional elements of the genome and understanding the genetic architecture of complex traits. Here, we extracted small RNAs from skeletal muscle and adipose tissue, and we compared their expression levels between one Western breed (Yorkshire) and seven indigenous Chinese breeds. We detected the expression of 172 known porcine microRNAs (miRNAs) and 181 novel miRNAs. Differential expression analysis found 92 and 12 differentially expressed miRNAs in adipose and muscle tissue respectively. We found that different Chinese breeds shared common directional miRNA expression changes compared to Yorkshire pigs. Some miRNAs differentially expressed across multiple Chinese breeds, including ssc-miR-129-5p, ssc-miR-30 and ssc-miR-150,are involved in adipose tissue function. Functional enrichment analysis revealed that the target genes of the differentially expressed miRNAs are associated mainly with signaling pathways rather than metabolic and biosynthetic processes. The miRNA-target gene and miRNA-phenotypic traits networks identified many hub miRNAs that regulate a large number of target genes or phenotypic traits. Specifically, we found that intramuscular fat content is regulated by the greatest number of miRNAs in muscle tissue. This study provides valuable new candidate miRNAs that will aid in the improvement of meat quality and production.

Abstract 1805: Integrative analysis of microRNAs in blastic plasmacytoid dendritic cell neoplasm

Abstract Background: Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is an extremely rare and aggressive hematological disease, deriving from the malignant transformation of plasmacytoid, alpha-interferon producing dendritic cells (pDCs). Recent studies shed new light on BPDCN genomic and trascriptomic alterations, but the microRNA (miRNA) profile is still largely unknown. We analyzed the miRNA expression profile of BPDCN patients to enhance our understanding of the molecular mechanisms driving this disease and to identify new potential diagnostic and therapeutic biomarkers. Methods: We performed the miRNA profiling (NanoString Technologies) of 26 BPDCN patients and 4 normal pDCs samples as controls. To better investigate the functional consequences of miRNAs dysregulation, 9 BPDCN patients, were also analyzed at the transcriptomic level. We applied a Moderated t-test to find genes and miRNAs differentially expressed between BPDCNs and pDCs. The most deregulated miRNAs and mRNAs were validated by qRT-PCR and immunohistochemistry and analyzed by miRNET, a bioinformatic tool for statistical analysis and functional interpretation of miRNA and mRNA data. Results: We found that, according to the supervised clustering analysis of miRNAs, tumor samples display a molecular signature well distinct from their normal counterpart. Indeed, BPDCN patients expressed a set of 175 miRNAs significantly deregulated and potentially involved in essential biological processes and therefore in malignant transformation. Thus, to evaluate the impact of these miRNAs on the BPDCN transcriptome, miRNAs and mRNAs expression profiles were analyzed by miRNET tool. Thanks to this integrative approach, we uncovered the most relevant miRNA-mRNA networks in BPDCN setting and in particular we identified 9 up-regulated hub miRNAs, targeting multiple genes and synergistically inter-connected: hsa-mir-93-5p, hsa-mir-106b-5p, hsa-mir-19b-3p, hsa-mir-19a-3p, hsa-mir-21-5p, hsa-mir-181a-5p, hsa-mir-25-3p, hsa-mir-155-5p, hsa-mir-17-3p (in order of relevance). These 9 hub miRNAs regulate the expression of genes already described as relevant in BPDCN patients (ex. TCF4, RHOA, EP300) and, according to functional enrichment analysis, that could aberrantly interfere with TLR signaling, protein translation and DNA transcription regulation. Of interest, most of these hub miRNAs are classified as oncomir (OncoMir Cancer Database) and, if validated in an extended number of cases, promising targets for anti-miRNA based therapy. In conclusion, we identified a panel of miRNAs that regulate relevant cancer-related pathways and can be also used as new potential biomarkers and therapeutic targets in BPDCN. Citation Format: Maria Rosaria Sapienza, Manuela Ferracin, Fabio Fuligni, Federica Melle, Giovanna Motta, Maria Antonella Laginestra, Maura Rossi, Luciano Cascione, Alessandro Laganà, Claudio Agostinelli, Elena Sabattini, Alessandro Pileri, Carlo Maria Croce, Stefano Aldo Pileri. Integrative analysis of microRNAs in blastic plasmacytoid dendritic cell neoplasm [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1805.

Exploration of the hub genes and miRNAs in lung adenocarcinoma.

In order to investigate the oncogenic mechanisms of lung adenocarcinoma (LUAD), hub genes can be identified by constructing co-expression networks, and the potential linkages between hub genes, transcription factors (TFs) and microRNAs (miRNAs/miRs) can be visualized and identified. In the present study, a total of 12 co-expressed modules were constructed, and 9 of these were significantly correlated with clinical traits in LUAD. The differentially expressed genes and differentially expressed miRNAs were determined, and the targets of differentially expressed miRNA were identified from the hub genes or TFs. The results of the present study demonstrated that 10 hub genes and 12 TFs are the predicted targets for the 5 and 8 differentially expressed miRNAs, respectively. Genes in pink and red modules, which have a high correlation with the clinical trait of days to death, are significantly enriched in ‘nucleosome assembly’ and ‘microtubule-based process’, respectively. These results indicated that miR-206, miR-137, miR-153, hub genes and enriched TFs in the pink and red modules exert a potentially pivotal function in the development of LUAD.

Integrative bioinformatics analysis of miRNA and mRNA expression profiles and identification of associated miRNA-mRNA network in aortic dissection.

Aortic dissection (AD) is one of the most lethal cardiovascular diseases. The aim of this study was to identify core genes and pathways revealing pathogenesis in AD. We screened differentially expressed mRNAs and miRNAs using mRNA and miRNA expression profile data of AD from Gene Expression Omnibus. Then functional and pathway enrichment analyses of differential expression genes (DEGs) was performed utilizing the database for annotation, visualization, and integrated discovery (DAVID). Target genes with differential expression miRNAs (DEMIs) were predicted using the miRWalk database, and the intersection between these predictions and DEGs was selected as differentially expressed miRNA-target genes. In addition, a protein-protein interaction (PPI) network and miRNA-mRNA regulatory network were constructed. In total, 130 DEGs and 47 DEMIs were identified from mRNA and miRNA microarray, respectively, and 45 DEGs were DEMI-target genes. The PPI and miRNA-mRNA network included 79 node genes and 74 node genes, respectively, while 23 hub genes and 2 hub miRNAs were identified. The DEGs, PPI and modules differential expression miRNA-target genes were all mainly enriched in cell cycle, cell proliferation and cell apoptosis signaling pathways. Taken above, the study reveals some candidate genes and pathways potentially involving molecular mechanisms of AD. These findings provide a new insight for research and treatment of AD.