Investigating MicroRNA and transcription factor co-regulatory networks in colorectal cancer

Small non-coding RNAs and pancreatic ductal adenocarcinoma: Linking diagnosis, pathogenesis, drug resistance, and therapeutic potential

This review comprehensively investigates the intricate interplay between small non-coding RNAs (sncRNAs) and pancreatic ductal adenocarcinoma (PDAC), a devastating malignancy with limited therapeutic options. Our analysis reveals the pivotal roles of sncRNAs in various facets of PDAC biology, spanning diagnosis, pathogenesis, drug resistance, and therapeutic strategies. sncRNAs have emerged as promising biomarkers for PDAC, demonstrating distinct expression profiles in diseased tissues. sncRNA differential expression patterns, often detectable in bodily fluids, hold potential for early and minimally invasive diagnostic approaches. Furthermore, sncRNAs exhibit intricate involvement in PDAC pathogenesis, regulating critical cellular processes such as proliferation, apoptosis, and metastasis. Additionally, mechanistic insights into sncRNA-mediated pathogenic pathways illuminate novel therapeutic targets and interventions. A significant focus of this review is dedicated to unraveling sncRNA mechanisms underlying drug resistance in PDAC. Understanding these mechanisms at the molecular level is imperative for devising strategies to overcome drug resistance. Exploring the therapeutic landscape, we discuss the potential of sncRNAs as therapeutic agents themselves as their ability to modulate gene expression with high specificity renders them attractive candidates for targeted therapy. In summary, this review integrates current knowledge on sncRNAs in PDAC, offering a holistic perspective on their diagnostic, pathogenic, and therapeutic relevance. By elucidating the roles of sncRNAs in PDAC biology, this review provides valuable insights for the development of novel diagnostic tools and targeted therapeutic approaches, crucial for improving the prognosis of PDAC patients.

MicroRNA-Transcription factor regulatory networks in the early strobilar development of Echinococcus granulosus protoscoleces

BACKGROUND

Echinococcus granulosus sensu lato has a complex developmental biology with a variety of factors relating to both intermediate and final hosts. To achieve maximum parasite adaptability, the development of the cestode is dependent on essential changes in transcript regulation. Transcription factors (TFs) and miRNAs are known as master regulators that affect the expression of downstream genes through a wide range of metabolic and signaling pathways. In this study, we aimed to develop a regulatory miRNA-Transcription factor (miRNA-TF) network across early developmental stages of E. granulosus protoscoleces by performing in silico analysis, and to experimentally validate TFs expression in protoscoleces obtained from in vitro culture, and from in vivo experiments.

RESULTS

We obtained list of 394 unique E. granulosus TFs and matched them with 818 differentially expressed genes which identified 41 predicted TFs with differential expression. These TFs were used to predict the potential targets of 31 differentially expressed miRNAs. As a result, eight miRNAs and eight TFs were found, and the predicted network was constructed using Cytoscape. At least four miRNAs (egr-miR-124a, egr-miR-124b-3p, egr-miR-745-3p, and egr-miR-87-3p) and their corresponding differentially expressed TFs (Zinc finger protein 45, Early growth response protein 3, Ecdysone induced protein 78c and ETS transcription factor elf 2) were highlighted in this investigation. The expression of predicted differentially expressed TFs obtained from in vitro and in vivo experiments, were experimentally validated by quantitative polymerase chain reaction. This confirmed findings of RNA-seq data.

CONCLUSION

miRNA-TF networks presented in this study control some of the most important metabolic and signaling pathways in the development and life cycle of E. granulosus, providing a potential approach for disrupting the early hours of dog infection and preventing the development of the helminth in the final host.

Construction of novel lncRNA-miRNA-mRNA ceRNA networks associated with prognosis of hepatitis C virus related hepatocellular carcinoma

Background

Hepatitis C virus (HCV) infection contribute to liver fibrosis and cirrhosis, which significantly increases the risk of hepatocellular carcinoma (HCC) development. Previous studies have demonstrated the pivotal role of competitive endogenous RNA (ceRNA) networks in tumorigenesis and cancer progression. Consequently, we herein seek to identify and evaluate the prognostic relevance of a novel ceRNA network associated with HCV-related HCC.

Methods

Differentially expressed genes (DEGs) in GSE140846 dataset from GEO were identified using Network Analyst, and GO, KEGG and Reactome analyses were performed. Furthermore, a protein-protein interaction network was generated, and hub genes were detected. Hub gene expression levels, as well as those of their upstream lncRNAs and miRNAs and associated survival analyses were conducted using appropriate bioinformatics databases. Predicted target relationships were used to establish putative ceRNA networks for HCV-related HCC.

Results

A total of 372 and 360 up- and down-regulated DE-mRNA were identified, which were associated with nuclear division, cell cycle, and ATPase activity. A PPI network containing 704 DE-mRNAs was constructed, and the 6 hub gene with the highest degree of connectivity were selected for subsequent analysis. We discovered that 22 miRNAs and 4 lncRNAs upstream of 11 hub gene were significantly associated with poor prognosis of HCV-related HCC, and used them to constructe a prognostic ceRNA network. Further experiments confirmed the ceRNA-regulatory relationship of BUB1-hsa-miR-193a-3p-MALAT1.

Conclusion

This study provides novel insights into the lncRNA-miRNA-mRNA ceRNA network, and reveals potential lncRNA biomarkers in HCV related HCC.

Structural and Functional Analyses of Hub MicroRNAs in An Integrated Gene Regulatory Network of Arabidopsis

MicroRNAs (miRNAs) are trans-acting small regulatory RNAs that work coordinately with transcription factors (TFs) to shape the repertoire of cellular mRNAs available for translation. Despite our growing knowledge of individual plant miRNAs, their global roles in gene regulatory networks remain mostly unassessed. Based on interactions obtained from public databases and curated from the literature, we reconstructed an integrated miRNA network in Arabidopsis that includes 66 core TFs, 318 miRNAs, and 1712 downstream genes. We found that miRNAs occupy distinct niches and enrich miRNA-containing feed-forward loops (FFLs), particularly those with miRNAs as intermediate nodes. Further analyses revealed that miRNA-containing FFLs coordinate TFs located in different hierarchical layers and that intertwined miRNA-containing FFLs are associated with party and date miRNA hubs. Using the date hub MIR858A as an example, we performed detailed molecular and genetic analyses of three interconnected miRNA-containing FFLs. These analyses revealed individual functions of the selected miRNA-containing FFLs and elucidated how the date hub miRNA fulfills multiple regulatory roles. Collectively, our findings highlight the prevalence and importance of miRNA-containing FFLs, and provide new insights into the design principles and control logics of miRNA regulatory networks governing gene expression programs in plants.

Integrative global co-expression analysis identifies Key MicroRNA-target gene networks as key blood biomarkers for obesity

Obesity is associated with the quantitative changes in miRNAs and their target genes. However, the molecular basis of their dysregulation and expression status correlations is incompletely understood. Therefore, this study aims to examine the shared differentially expressed miRNAs and their target genes between blood and adipose tissues of obese individuals to identify potential blood-based biomarkers. In this study, 3 gene expression datasets (two mRNA and one miRNA), generated from blood and adipose tissues of 68 obese and 39 lean individuals, were analyzed by a series of robust computational concepts, like protein interactome mapping, functional enrichment of biological pathways and construction of miRNA-mRNA and transcription factor gene networks. The comparison of blood versus tissue datasets has revealed the shared differential expression of 210 genes (59.5% upregulated) involved in lipid metabolism and inflammatory reactions. The blood miRNA (GSE25470) analysis has identified 79 differentially expressed miRNAs (71% downregulated). The miRNA-target gene scan identified regulation of 30 shared genes by 22miRNAs. The gene network analysis has identified the inverse expression correlation between 8 target genes (TP53, DYSF, GAB2, GFRA2, NACC2, FAM53C, JNK and GAB2) and 3 key miRNAs (hsa-mir-940, hsa-mir-765, hsa-mir-612), which are further regulated by 24 key transcription factors. This study identifies potential obesity related blood biomarkers from largescale gene expression data by computational miRNA-target gene interactome and transcription factor network construction methods.

An integrated network analysis approach to identify potential key genes, transcription factors, and microRNAs regulating human hematopoietic stem cell aging

Hematopoietic stem cells (HSCs) undergo functional deterioration with increasing age that causes loss of their self-renewal and regenerative potential. Despite various efforts, significant success in identifying molecular regulators of HSC aging has not been achieved, one prime reason being the non-availability of appropriate human HSC samples. To demonstrate the scope of integrating and re-analyzing the HSC transcriptomics data available, we used existing tools and databases to structure a sequential data analysis pipeline to predict potential candidate genes, transcription factors, and microRNAs simultaneously. This sequential approach comprises (i) collecting matched young and aged mice HSC sample datasets, (ii) identifying differentially expressed genes, (iii) identifying human homologs of differentially expressed genes, (iv) inferring gene co-expression network modules, and (v) inferring the microRNA-transcription factor-gene regulatory network. Systems-level analyses of HSC interaction networks provided various insights based on which several candidates were predicted. For example, 16 HSC aging-related candidate genes were predicted (e.g., CD38, BRCA1, AGTR1, GSTM1, etc.) from GCN analysis. Following this, the shortest path distance-based analyses of the regulatory network predicted several novel candidate miRNAs and TFs. Among these, miR-124-3p was a common regulator in candidate gene modules, while TFs MYC and SP1 were identified to regulate various candidate genes. Based on the regulatory interactions among candidate genes, TFs, and miRNAs, a potential regulation model of biological processes in each of the candidate modules was predicted, which provided systems-level insights into the molecular complexity of each module to regulate HSC aging.

Identification of novel prognostic biomarkers by integrating multi-omics data in gastric cancer

BACKGROUND

Gastric cancer is a fatal gastrointestinal cancer with high morbidity and poor prognosis. The dismal 5-year survival rate warrants reliable biomarkers to assess and improve the prognosis of gastric cancer. Distinguishing driver mutations that are required for the cancer phenotype from passenger mutations poses a formidable challenge for cancer genomics.

METHODS

We integrated the multi-omics data of 293 primary gastric cancer patients from The Cancer Genome Atlas (TCGA) to identify key driver genes by establishing a prognostic model of the patients. Analyzing both copy number alteration and somatic mutation data helped us to comprehensively reveal molecular markers of genomic variation. Integrating the transcription level of genes provided a unique perspective for us to discover dysregulated factors in transcriptional regulation.

RESULTS

We comprehensively identified 31 molecular markers of genomic variation. For instance, the copy number alteration of WASHC5 (also known as KIAA0196) frequently occurred in gastric cancer patients, which cannot be discovered using traditional methods based on significant mutations. Furthermore, we revealed that several dysregulation factors played a hub regulatory role in the process of biological metabolism based on dysregulation networks. Cancer hallmark and functional enrichment analysis showed that these key driver (KD) genes played a vital role in regulating programmed cell death. The drug response patterns and transcriptional signatures of KD genes reflected their clinical application value.

CONCLUSIONS

These findings indicated that KD genes could serve as novel prognostic biomarkers for further research on the pathogenesis of gastric cancers. Our study elucidated a multidimensional and comprehensive genomic landscape and highlighted the molecular complexity of GC.

Investigating potential molecular mechanisms of serum exosomal miRNAs in colorectal cancer based on bioinformatics analysis

Colorectal cancer (CRC) is the most common malignant gastrointestinal tumor worldwide. Serum exosomal microRNAs (miRNAs) play a critical role in tumor progression and metastasis. However, the underlying molecular mechanisms are poorly understood.The miRNAs expression profile (GSE39833) was downloaded from Gene Expression Omnibus (GEO) database. GEO2R was applied to screen the differentially expressed miRNAs (DEmiRNAs) between healthy and CRC serum exosome samples. The target genes of DEmiRNAs were predicted by starBase v3.0 online tool. The gene ontology (GO) and Kyoto Encyclopedia of Genomes pathway (KEGG) enrichment analysis were performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID) online tool. The protein-protein interaction (PPI) network was established by the Search Tool for the Retrieval of Interacting Genes (STRING) visualized using Cytoscape software. Molecular Complex Detection (MCODE) and cytohubba plug-in were used to screen hub genes and gene modules.In total, 102 DEmiRNAs were identified including 67 upregulated and 35 downregulated DEmiRNAs, and 1437 target genes were predicted. GO analysis showed target genes of upregulated DEmiRNAs were significantly enriched in transcription regulation, protein binding, and ubiquitin protein ligase activity. While the target genes of downregulated DEmiRNAs were mainly involved in transcription from RNA polymerase II promoter, SMAD binding, and DNA binding. The KEGG pathway enrichment analyses showed target genes of upregulated DEmiRNAs were significantly enriched in proteoglycans in cancer, microRNAs in cancer, and phosphatidylinositol-3 kinases/Akt (PI3K-Akt) signaling pathway, while target genes of downregulated DEmiRNAs were mainly enriched in transforming growth factor-beta (TGF-beta) signaling pathway and proteoglycans in cancer. The genes of the top 3 modules were mainly enriched in ubiquitin mediated proteolysis, spliceosome, and mRNA surveillance pathway. According to the cytohubba plugin, 37 hub genes were selected, and 4 hub genes including phosphoinositide-3-kinase regulatory subunit 1 (PIK3R1), SRC, cell division cycle 42 (CDC42), E1A binding protein p300 (EP300) were identified by combining 8 ranked methods of cytohubba.The study provides a comprehensive analysis of exosomal DEmiRNAs and target genes regulatory network in CRC, which can better understand the roles of exosomal miRNAs in the development of CRC. However, these findings require further experimental validation in future studies.

Construction of a potential microRNA, transcription factor and mRNA regulatory network in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the most common malignancies worldwide and the third leading cause of cancer-related death. MicroRNAs and transcription factors (TFs) cooperate to regulate the same target gene, thus affecting the progression of HCC.

Methods

Differentially expressed miRNAs and mRNAs were screened. Functional enrichment analysis of these HCC-related mRNAs was performed, and a protein-protein interaction network was constructed. TFs that regulate these miRNAs and hub genes were also screened.

Results

Ten differentially upregulated miRNAs and 5 differentially downregulated miRNAs were screened. Additionally, 183 downregulated mRNAs and 303 upregulated mRNAs that are potentially bound to these differentially expressed miRNAs were identified. The Kyoto Encyclopedia of Genes and Genomes (KEGG) results showed that the differentially expressed mRNAs were significantly enriched in pathways in cancer, the Wnt signaling pathway, and the Rap1 signaling pathway. Then, 220 TFs were identified for 5 candidate genes of the downregulated mRNAs, and 258 TFs were identified for 9 candidate genes of the upregulated mRNAs. Finally, the 9 upregulated hub genes were related to higher overall survival (OS) in the low-expression group, and 4/5 downregulated hub genes were related to higher OS in the high-expression group.

Conclusions

This study constructed a potential regulatory network between candidate molecules and that need to be further verified. These regulatory relationships are expected to clarify the new molecular mechanisms of the occurrence and development of HCC.

Critical microRNAs and regulatory motifs in cleft palate identified by a conserved miRNA-TF-gene network approach in humans and mice

Cleft palate (CP) is the second most common congenital birth defect. The etiology of CP is complicated, with involvement of various genetic and environmental factors. To investigate the gene regulatory mechanisms, we designed a powerful regulatory analytical approach to identify the conserved regulatory networks in humans and mice, from which we identified critical microRNAs (miRNAs), target genes and regulatory motifs (miRNA-TF-gene) related to CP. Using our manually curated genes and miRNAs with evidence in CP in humans and mice, we constructed miRNA and transcription factor (TF) co-regulation networks for both humans and mice. A consensus regulatory loop (miR17/miR20a-FOXE1-PDGFRA) and eight miRNAs (miR-140, miR-17, miR-18a, miR-19a, miR-19b, miR-20a, miR-451a and miR-92a) were discovered in both humans and mice. The role of miR-140, which had the strongest association with CP, was investigated in both human and mouse palate cells. The overexpression of miR-140-5p, but not miR-140-3p, significantly inhibited cell proliferation. We further examined whether miR-140 overexpression could suppress the expression of its predicted target genes (BMP2, FGF9, PAX9 and PDGFRA). Our results indicated that miR-140-5p overexpression suppressed the expression of BMP2 and FGF9 in cultured human palate cells and Fgf9 and Pdgfra in cultured mouse palate cells. In summary, our conserved miRNA-TF-gene regulatory network approach is effective in detecting consensus miRNAs, motifs, and regulatory mechanisms in human and mouse CP.

KRAS Mutation-Responsive miR-139-5p inhibits Colorectal Cancer Progression and is repressed by Wnt Signaling

Introduction: Colorectal cancer (CRC) frequently harbors KRAS mutations that result in chemoresistance and metastasis. MicroRNAs (miRNAs) are usually dysregulated and play important regulatory roles in tumor progression. However, the KRAS mutation-responsive miRNA profile in CRC remains uninvestigated. Methods: miR-139-5p was identified and evaluated by small RNA sequencing, qRT-PCR and in situ hybridization. The roles of miR-139-5p in CRC cells with and without KRAS mutation were determined by Cell Counting Kit-8 (CCK-8), colony formation, flow cytometry and transwell assays in vitro and by tumorigenesis and metastasis assays in vivo. Microarrays followed by bioinformatic analyses, luciferase reporter assays and Western blotting were applied for mechanistic studies. Results: miR-139-5p was significantly downregulated in KRAS-mutated CRC cells and tissues compared with their wild-type counterparts. Low miR-139-5p expression was associated with aggressive phenotypes and poor prognosis in CRC patients. miR-139-5p overexpression inhibited CRC cell proliferation, migration and invasion in vitro, sensitized tumors to chemotherapy, and impaired tumor growth and metastasis in vivo. Transcriptomic profiling identified multiple modulators in the Ras (JUN and FOS) and Wnt (CTNNB1 and DVL1) signaling pathways and the epithelial-to-mesenchymal transition (EMT) process (ZEB1) as direct targets of miR-139-5p, and inverse correlations were confirmed in CRC clinical tissues. Aberrantly activated Wnt signaling in KRAS-mutant cells was demonstrated to transcriptionally repress miR-139-5p through TCF4, forming a miR-139-5p/Wnt signaling double-negative feedback loop. Conclusions: We identified miR-139-5p as a KRAS-responsive miRNA and demonstrated its involvement in CRC progression. KRAS mutation disrupted the miR-139-5p/Wnt signaling reciprocal negative feedback mechanism, which might cause miR-139-5p downregulation and derepression of oncogenic signaling pathways and EMT. These results reveal a transcriptional regulatory mode of KRAS-driven malignant transformation and highlight miR-139-5p as a novel regulator of crosstalk between the Ras and Wnt signaling pathways in CRC.

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.

Identification of key miRNAs in the progression of hepatocellular carcinoma using an integrated bioinformatics approach

Backgroud

It has been shown that aberrant expression of microRNAs (miRNAs) and transcriptional factors (TFs) is tightly associated with the development of HCC. Therefore, in order to further understand the pathogenesis of HCC, it is necessary to systematically study the relationship between the expression of miRNAs, TF and genes. In this study, we aim to identify the potential transcriptomic markers of HCC through analyzing common microarray datasets, and further establish the differential co-expression network of miRNAs-TF-mRNA to screen for key miRNAs as candidate diagnostic markers for HCC.

Method

We first downloaded the mRNA and miRNA expression profiles of liver cancer from the GEO database. After pretreatment, we used a linear model to screen for differentially expressed genes (DEGs) and miRNAs. Further, we used weighed gene co-expression network analysis (WGCNA) to construct the differential gene co-expression network for these DEGs. Next, we identified mRNA modules significantly related to tumorigenesis in this network, and evaluated the relationship between mRNAs and TFs by TFBtools. Finally, the key miRNA was screened out in the mRNA-TF-miRNA ternary network constructed based on the target TF of differentially expressed miRNAs, and was further verified with external data set.

Results

A total of 465 DEGs and 215 differentially expressed miRNAs were identified through differential genes expression analysis, and WGCNA was used to establish a co-expression network of DEGs. One module that closely related to tumorigenesis was obtained, including 33 genes. Next, a ternary network was constructed by selecting 256 pairs of mRNA-TF pairs and 100 pairs of miRNA-TF pairs. Network mining revealed that there were significant interactions between 18 mRNAs and 25 miRNAs. Finally, we used another independent data set to verify that miRNA hsa-mir-106b and hsa-mir-195 are good classifiers of HCC and might play key roles in the progression of HCC.

Conclusion

Our data indicated that two miRNAs-hsa-mir-106b and hsa-mir-195-are identified as good classifiers of HCC.

MicroRNA and transcription factor co-regulatory networks and subtype classification of seminoma and non-seminoma in testicular germ cell tumors

Recent studies have revealed that feed-forward loops (FFLs) as regulatory motifs have synergistic roles in cellular systems and their disruption may cause diseases including cancer. FFLs may include two regulators such as transcription factors (TFs) and microRNAs (miRNAs). In this study, we extensively investigated TF and miRNA regulation pairs, their FFLs, and TF-miRNA mediated regulatory networks in two major types of testicular germ cell tumors (TGCT): seminoma (SE) and non-seminoma (NSE). Specifically, we identified differentially expressed mRNA genes and miRNAs in 103 tumors using the transcriptomic data from The Cancer Genome Atlas. Next, we determined significantly correlated TF-gene/miRNA and miRNA-gene/TF pairs with regulation direction. Subsequently, we determined 288 and 664 dysregulated TF-miRNA-gene FFLs in SE and NSE, respectively. By constructing dysregulated FFL networks, we found that many hub nodes (12 out of 30 for SE and 8 out of 32 for NSE) in the top ranked FFLs could predict subtype-classification (Random Forest classifier, average accuracy ≥90%). These hub molecules were validated by an independent dataset. Our network analysis pinpointed several SE-specific dysregulated miRNAs (miR-200c-3p, miR-25-3p, and miR-302a-3p) and genes (EPHA2, JUN, KLF4, PLXDC2, RND3, SPI1, and TIMP3) and NSE-specific dysregulated miRNAs (miR-367-3p, miR-519d-3p, and miR-96-5p) and genes (NR2F1 and NR2F2). This study is the first systematic investigation of TF and miRNA regulation and their co-regulation in two major TGCT subtypes.

MicroRNA-Based Combinatorial Cancer Therapy: Effects of MicroRNAs on the Efficacy of Anti-Cancer Therapies

The susceptibility of cancer cells to different types of treatments can be restricted by intrinsic and acquired therapeutic resistance, leading to the failure of cancer regression and remission. To overcome this problem, a combination therapy has been proposed as a fundamental strategy to improve therapeutic responses; however, resistance is still unavoidable. MicroRNA (miRNAs) are associated with cancer therapeutic resistance. The modulation of dysregulated miRNA levels through miRNA-based therapy comprising a replacement or inhibition approach has been proposed to sensitize cancer cells to other anti-cancer therapies. The combination of miRNA-based therapy with other anti-cancer therapies (miRNA-based combinatorial cancer therapy) is attractive, due to the ability of miRNAs to target multiple genes associated with the signaling pathways controlling therapeutic resistance. In this article, we present an overview of recent findings on the role of therapeutic resistance-related miRNAs in different types of cancer. We review the feasibility of utilizing dysregulated miRNAs in cancer cells and extracellular vesicles as potential candidates for miRNA-based combinatorial cancer therapy. We also discuss innate properties of miRNAs that need to be considered for more effective combinatorial cancer therapy.

Identifying prognostic biomarkers in endometrial carcinoma based on ceRNA network

PURPOSE

Endometrial carcinoma (EC), a common gynecological malignancy with high incidence, affects the mental and physical health of women. Mounting evidence shows that long noncoding RNAs (lncRNAs), messenger RNAs (mRNAs), and microRNAs (miRNAs) have instrumental roles in various biological processes associated with the pathogenesis of EC. In this research, we intend to further study the mechanism of EC and the potential predictive markers of EC.

METHODS

First, we obtained original data of EC RNA transcripts from The Cancer Genome Atlas database and performed differential analysis. Subsequently, according to the miRcode online software, relationship pairs of lncRNA-miRNA were constructed, and miRNA-mRNA pairs were established based on miRDB, TargetScan, and miRTarBase. Then, we constructed the competing endogenous RNA (ceRNA) network based on lncRNA-miRNA and miRNA-mRNA pairs. To further explain the function of the ceRNA network and explore the potential prognostic markers, functional enrichment analysis, and survival analysis were carried out.

RESULTS

The research showed that there were 744 differential expression lncRNAs (DElncRNAs), 164 differential expression miRNAs (DEmiRNAs), and 2447 differential expression mRNAs (DEmRNAs) between EC tissues and normal tissues. Subsequently, we built 103 DEmiRNA-DEmRNA interaction pairs and 369 DElncRNA-DEmiRNA pairs. Then, we established the ceRNA network of EC, including 62 DElncRNAs, 26 DEmiRNAs, and 70 DEmRNAs. Moreover, 10 of 62 lncRNAs, 19 of 70 mRNAs, and 4 of 26 miRNAs that closely related to the survival of EC with P < .05 were obtained. Notably, based on this network, it was found that LINC00261-hsa-mir-31 pair and LINC00261-hsa-mir-211 target pairs could be used as the potential prognostic markers of EC.

CONCLUSION

This research recommended an available basis for the molecular mechanism of EC and prognosis prediction, which could help guide the subsequent treatments and predict the prognosis for patients with EC.

Identification of the lncRNA-miRNA-mRNA network associated with gastric cancer via integrated bioinformatics analysis

The aim of the present study was to investigate the long non-coding RNA (lncRNA)-microRNA (miRNA)-mRNA regulatory network in gastric cancer (GC) using bioinformatics analysis. Two mRNA gene expression profiles, GSE79973 and GSE54129, and two miRNA expression profiles, GSE93415 and GSE78091, were downloaded from the Gene Expression Omnibus database. The differentially expressed mRNAs (DEMs) and the differentially expressed miRNAs (DEMis) were merged separately. Gene ontology and pathway enrichment analysis were conducted using the Database for Annotation, Visualization and Integrated Discovery. A protein-protein interaction (PPI) network was then constructed and the 10 top hub genes in the network were analyzed using the Search Tool for the Retrieval of Interacting Genes. The lncRNA-miRNA-mRNA networks were visualized using Cytoscape software. As a result, 158 shared DEMs (40 upregulated and 118 downregulated) were identified from two mRNA datasets. A total of 30 upregulated miRNAs and 1 downregulated miRNA functioned as DEMis. The PPI network consisted of 129 nodes and 572 interactions. The 10 top hub genes were selected by degree using Cytohubba, including Jun proto-oncogene, mitogen-activated protein kinase (MAPK)3, transforming growth factor-β1, Fos proto-oncogene, AP-1 transcription factor subunit, interleukin (IL)-8, MAPK1, RELA proto-oncogene nuclear factor-κB subunit, interferon regulatory factor 7, ubiquitin like modifier and vascular endothelial growth factor A. In the lncRNA-miRNA-mRNA network, a total of 1,215 regulatory associations were constructed using Cytoscape. In conclusion, the present study provides a novel perspective of the molecular mechanisms underlying GC by identifying the lncRNA-miRNA-mRNA regulatory network via bioinformatics analysis.

Significance of miR-27a and miR-31 in early diagnosis and prognosis of colorectal cancer

Clinical significance of micro-ribonucleic acid (miR)-27a and miR-31 in the early diagnosis and prognosis of colorectal cancer were investigated. Forty patients with colorectal malignancy admitted to Xintai People's Hospital from February 2014 to April 2018 were enrolled as the observation group, of which 30 patients were diagnosed via pathological biopsy. Another 40 patients diagnosed with colorectal polyp and receiving surgical treatment were selected as the control group. The relative amount of miR-27a and miR-31 was measured. The relative expression levels of miR-27a and miR-31 in patients were analyzed. The diagnostic sensitivity, specificity and accordance rates of positive miR-27a and miR-31 expression in colorectal cancer were recorded. The correlation of the relative expression levels of miR-27a and miR-31 with the survival time of patients were analyzed. In the observation group, the relative expression levels of miR-27a and miR-31 in patients with lymph node metastasis and distant metastasis were higher than those in patients without lymph node metastasis and distant metastasis (P<0.05). Histological type of patients with non-mucinous carcinoma had increased relative expression levels of miR-27a and miR-31 in comparison with those with mucinous carcinoma (P<0.05). In terms of Duke's grade, the relative expression levels of miR-27a and miR-31 in patients with grade C and D were higher than those in patients with grade A and B (P<0.05). The diagnostic sensitivity, specificity and accordance rate of positive miR-27a expression were lower than those of positive miR-31 expression. The relative expression levels of miR-27a and miR-31 were positively correlated with the survival time of patients (P<0.05). The expression levels of miR-27a and miR-31 are related to distant metastasis and tumor grade of patients with colorectal cancer, and positively associated with the survival time of patients, having high diagnostic value.

Exploration of prognosis-related microRNA and transcription factor co-regulatory networks across cancer types

The study of cancer prognosis serves as an important part of cancer research. Large-scale cancer studies have identified numerous genes and microRNAs (miRNAs) associated with prognosis. These informative genes and miRNAs represent potential biomarkers to predict survival and to elucidate the molecular mechanism of tumour progression. MiRNAs and transcription factors (TFs) can work cooperatively as essential mediators of gene expression, and their dysregulation affects cancer prognosis. A panoramic view of cancer prognosis at the system level, considering the co-regulation roles of miRNA and TF, remains elusive. Here, we establish 12 prognosis-related miRNA-TF co-regulatory networks. The characteristics of prognostic target genes and their regulators in the network are depicted. Although the target genes and co-regulatory patterns exhibit cancer-specific properties, some miRNAs and TFs are highly conserved across cancers. We illustrate and interpret the roles of these conserved regulators by building a model associated with cancer hallmarks, functional enrichment analysis, network community detection, and exhaustive literature research. The elaborated system-level prognostic miRNA-TF co-regulation landscape, including the highlighted roles of conserved regulators, provides a novel and powerful insights into further biological and medical discoveries.

MicroRNA-related transcription factor regulatory networks in human colorectal cancer

OBJECTIVE

Colorectal cancer (CRC) is an extremely common gastrointestinal malignancy. The present study aimed to identify microRNAs (miRNAs) and transcription factors (TFs) associated with tumor development.

METHODS

Three miRNA profile datasets were integrated and analyzed to elucidate the potential key candidate miRNAs in CRC. The starBase database was used to identify the potential targets of common differentially expressed miRNAs (DEMs). Transcriptional Regulatory Element Database and Transcriptional Regulatory Relationships Unraveled by Sentence-based Text databases were used to identify cancer-related TFs and the TF-regulated target genes. Functional and pathway enrichment analyses were performed using the Database for Annotation, Visualization and Integration Discovery (DAVID) database, and the miRNA-TF-gene networks were constructed by Cytoscape. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to detect the expression of genes and miRNAs.

RESULTS

In total, 14 DEMs were found in CRC. By bioinformatics analysis, 5 DEMs (miR-145, miR-497, miR-30a, miR-31, and miR-20a) and 8 TFs (ELK4 (ETS-family transcription factor), myeloblastosis proto-oncogene like (MYBL)1, MYBL2, CEBPA, PPARA, PPARD, PPARG, and endothelial PAS domain protein (EPAS1)) appeared to be associated with CRC and were therefore used to construct miRNA-TF-gene networks. From the networks, we found that miR-20a might play the most important role as an miRNA in the networks. By qRT-PCR, we demonstrated that miR-20a was significantly upregulated in CRC tissues. We also performed qRT-PCR to identify the expression of miR-20a-related TFs (PPARA, PPARD, PPARG, EPAS1). Three of them, PPARA, PPARG, and EPAS1, were downregulated in CRC tissues, with statistically significant differences, while the downregulation of PPARD in CRC tissues was not significantly different. Pathway enrichment analyses indicated that the phosphoinositide 3-kinase (PI3K)-Akt signaling pathway was the most significantly enriched pathway. Two main elements of the PI3K-Akt signaling pathway, phosphatase and tensin homolog deleted on chromosome 10 and B-cell lymphoma 2-associated agonist of cell death, were demonstrated to be downregulated in CRC.

CONCLUSION

The present study identified hub miRNAs and miRNA-related TF regulatory networks in CRC, which might be potential targets for the diagnosis and treatment of CRC.

Network-based identification of critical regulators as putative drivers of human cleft lip

BACKGROUND

Cleft lip (CL) is one of the most common congenital birth defects with complex etiology. While genome-wide association studies (GWAS) have made significant advances in our understanding of mutations and their related genes with potential involvement in the etiology of CL, it remains unknown how these genes are functionally regulated and interact with each other in lip development. Currently, identifying the disease-causing genes in human CL is urgently needed. So far, the causative CL genes have been largely undiscovered, making it challenging to design experiments to validate the functional influence of the mutations identified from large genomic studies such as CL GWAS.

RESULTS

Transcription factors (TFs) and microRNAs (miRNAs) are two important regulators in cellular system. In this study, we aimed to investigate the genetic interactions among TFs, miRNAs and the CL genes curated from the previous studies. We constructed miRNA-TF co-regulatory networks, from which the critical regulators as putative drivers in CL were examined. Based on the constructed networks, we identified ten critical hub genes with prior evidence in CL. Furthermore, the analysis of partitioned regulatory modules highlighted a number of biological processes involved in the pathology of CL, including a novel pathway "Signaling pathway regulating pluripotency of stem cells". Our subnetwork analysis pinpointed two candidate miRNAs, hsa-mir-27b and hsa-mir-497, activating the Wnt pathway that was associated with CL. Our results were supported by an independent gene expression dataset in CL.

CONCLUSIONS

This study represents the first regulatory network analysis of CL genes. Our work presents a global view of the CL regulatory network and a novel approach on investigating critical miRNAs, TFs and genes via combinatory regulatory networks in craniofacial development. The top genes and miRNAs will be important candidates for future experimental validation of their functions in CL.

Regulatory network analysis reveals the oncogenesis roles of feed-forward loops and therapeutic target in T-cell acute lymphoblastic leukemia

BACKGROUND

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematological malignancy. Aberrant expressed genes contribute to the development and progression of T-ALL. However, the regulation underlying their aberrant expression remains elusive. Dysregulated expression of transcription factors and miRNAs played important regulatory roles in the pathogenesis of T-ALL.

METHODS

In this study, we analyzed the alteration of transcriptome profiling and regulatory networks between T-ALL sample and normal T cell samples at transcriptional and post-transcriptional levels.

RESULTS

Our results demonstrated that genes related to cell cycle and cell proliferation processes were significantly upregulated in T-ALL comparing to normal samples. Meanwhile, regulatory network analyses revealed that FOXM1, MYB, SOX4 and miR-21/19b as core regulators played vital roles in the development of T-ALL. FOXM1-miR-21-5p-CDC25A and MYB/SOX4-miR-19b-3p-RBBP8 were identified as important feed-forward loops involved in the oncogenesis of T-ALL. Drug-specific analyses showed that GSK-J4 may be an effective drug, and CDC25A/CAPN2/MCM2 could serve as potential therapeutic targets for T-ALL.

CONCLUSIONS

This study may provide novel insights for the regulatory mechanisms underlying the development of T-ALL and potential therapeutic targets.

Differential Connectivity in Colorectal Cancer Gene Expression Network

BACKGROUND

Colorectal cancer (CRC) is one of the challenging types of cancers; thus, exploring effective biomarkers related to colorectal could lead to significant progresses toward the treatment of this disease.

METHODS

In the present study, CRC gene expression datasets have been reanalyzed. Mutual differentially expressed genes across 294 normal mucosa and adjacent tumoral samples were then utilized in order to build two independent transcriptional regulatory networks. By analyzing the networks topologically, genes with differential global connectivity related to cancer state were determined for which the potential transcriptional regulators including transcription factors were identified.

RESULTS

The majority of differentially connected genes (DCGs) were up-regulated in colorectal transcriptome experiments. Moreover, a number of these genes have been experimentally validated as cancer or CRC-associated genes. The DCGs, including GART, TGFB1, ITGA2, SLC16A5, SOX9, and MMP7, were investigated across 12 cancer types. Functional enrichment analysis followed by detailed data mining exhibited that these candidate genes could be related to CRC by mediating in metastatic cascade in addition to shared pathways with 12 cancer types by triggering the inflammatory events.

DISCUSSION

Our study uncovered correlated alterations in gene expression related to CRC susceptibility and progression that the potent candidate biomarkers could provide a link to disease.

Investigating the Role of MicroRNA and Transcription Factor Co-regulatory Networks in Multiple Sclerosis Pathogenesis

MicroRNAs (miRNAs) and transcription factors (TFs) play key roles in complex multifactorial diseases like multiple sclerosis (MS). Starting from the miRNomic profile previously associated with a cohort of pediatric MS (PedMS) patients, we applied a combined molecular and computational approach in order to verify published data in patients with adult-onset MS (AOMS). Six out of the 13 selected miRNAs (miR-320a, miR-125a-5p, miR-652-3p, miR-185-5p, miR-942-5p, miR-25-3p) were significantly upregulated in PedMS and AOMS patients, suggesting that they may be considered circulating biomarkers distinctive of the disease independently from age. A computational and unbiased miRNA-based screening of target genes not necessarily associated to MS was then performed in order to provide an extensive view of the genetic mechanisms underlying the disease. A comprehensive MS-specific miRNA-TF co-regulatory network was hypothesized; among others, SP1, RELA, NF-κB, TP53, AR, MYC, HDAC1, and STAT3 regulated the transcription of 61 targets. Interestingly, NF-κB and STAT3 cooperatively regulate the expression of immune response genes and control the cross-talk between inflammatory and immune cells. Further functional analysis will be performed on the identified critical hubs. Above all, in our view, this approach supports the need of multidisciplinary strategies for shedding light into the pathogenesis of MS.

CMTCN: a web tool for investigating cancer-specific microRNA and transcription factor co-regulatory networks

Transcription factors (TFs) and microRNAs (miRNAs) are well-characterized trans-acting essential players in gene expression regulation. Growing evidence indicates that TFs and miRNAs can work cooperatively, and their dysregulation has been associated with many diseases including cancer. A unified picture of regulatory interactions of these regulators and their joint target genes would shed light on cancer studies. Although online resources developed to support probing of TF-gene and miRNA-gene interactions are available, online applications for miRNA-TF co-regulatory analysis, especially with a focus on cancers, are lacking. In light of this, we developed a web tool, namely CMTCN (freely available at http://www.cbportal.org/CMTCN), which constructs miRNA-TF co-regulatory networks and conducts comprehensive analyses within the context of particular cancer types. With its user-friendly provision of topological and functional analyses, CMTCN promises to be a reliable and indispensable web tool for biomedical studies.

miR-24 inhibited the killing effect of natural killer cells to colorectal cancer cells by downregulating Paxillin

OBJECTIVE

To identify the molecular mechanism that modulates the killing effect of natural killer (NK) cells to colorectal cancer cells.

MATERIALS AND METHODS

Expressions of miR-24 and Paxillin were detected by qRT-PCR and Western blot. Secretions of IFN-γ and TNF-α were measured by ELISA. The killing effect of NK cells was detected by CytoTox 96 non-radioactive cytotoxicity assay. Luciferase reporter assay was conducted to confirm the regulation of miR-24 on Paxillin.

RESULTS

miR-24 was overexpressed in NK cells from patients with colorectal cancer than healthy volunteers. Secretions of IFN-γ and TNF-α in activated NK cells were significantly increased, indicating the enhancement of the killing effect of NK cells. Paxillin expression was overexpressed in activated NK cells. Interference of Paxillin significantly decreased Paxillin expression, secretions of IFN-γ and TNF-α, and the killing effect of NK cells to colorectal cancer cells. In addition, we confirmed that Paxillin was a direct target of miR-24, and miR-24 was negatively correlated with Paxillin. Moreover, overexpression of miR-24 inhibited secretions of IFN-γ and TNF-α, and decreased cytotoxicity by downregulating Paxillin expression. Finally, we observed that overexpression of Paxillin significantly decreased tumor volume of colorectal cancer.

CONCLUSION

Overexpression of miR-24 supressed the killing effect of NK cells to colorectal cancer cells by downregulating Paxillin expression.