Exploration of Positive and Negative Schizophrenia Symptom Heterogeneity and Establishment of Symptom-Related miRNA-mRNA Regulatory Network: Based on Transcriptome Sequencing Data

Schizophrenia (SCZ) symptoms can be classified as positive and negative ones, each of which has distinct traits and possibly differences in gene expression and regulation. The co-expression networks linked to PANSS (Positive and Negative Syndrome Scale) scores were identified by weighted gene co-expression network analysis (WGCNA) using the expression profiles of miRNA and mRNA in the peripheral blood of first-episode SCZ patients. The heterogeneity between positive and negative symptoms was demonstrated using gene functional enrichment, gene-medication interaction, and immune cell composition analysis. Then, target gene prediction and correlation analysis of miRNA and mRNA constructed a symptom-related miRNA-mRNA regulatory network, screened regulatory pairs, and predicted binding sites. A total of six mRNA co-expression modules, two miRNA co-expression modules, and ten hub genes were screened to be significantly associated with positive symptoms; five mRNA co-expression modules and eight hub genes were correlated with negative symptoms. Positive symptom-related modules were significantly enriched in axon guidance, actin skeleton regulation, and sphingolipid signaling pathway, while negative symptom-related modules were significantly enriched in adaptive immune response, leukocyte migration, dopaminergic synapses, etc. The development of positive symptoms may have been influenced by potential regulatory pairings such as miR-98-5p-EIF3J, miR-98-5p-SOCS4, let-7b-5p-CLUH, miR-454-3p-GTF2H1, and let-7b-5p-SNX17. Additionally, immune cells were substantially connected with several hub genes for symptoms. Positive and negative symptoms in SCZ individuals were heterogeneous to some extent. miRNAs such as let-7b-5p and miR-98-5p might contribute to the incidence of positive symptoms by targeting mRNAs, while the immune system's role in developing negative symptoms may be more nuanced.

Molecular mechanism of Shengyang Yiwei Decoction in treating chronic kidney disease based on network pharmacology

There is a serious worldwide health problem caused by chronic kidney disease (CKD), yet there are few viable therapies. Therapeutic promise in the treatment of chronic kidney disease (CKD) has been shown by the use of the traditional Chinese herbal compound Shengyang Yiwei Decoction (SYD). However, the chemical processes through which SYD exerts its effects are still unknown. The purpose of this network pharmacology research is to better understand the molecular mechanism of action of Shengyang Yiwei Decoction (SYD) in the treatment of chronic kidney disease (CKD). Traditional Chinese Medicine Systems Pharmacology (TCMSP) was first searched for information on the chemical components of Shengyang Yiwei Decoction. The molecular targets of SYD were then predicted using the Pharm Mapper service. After that, we used databases like DIG-SEE, TTD, and OMIM to zero down on the targets most closely linked to CKD. Cytoscape 3.2.1 was used to generate the component-target network representing SYD's therapy of CKD. In addition, KEGG signal pathways and GO biological processes were analyzed using the DAVID database, and the findings were displayed via OmicShare Tools. Twenty-two active components were isolated from Shengyang Yiwei Decoction, and they were linked to 36 therapeutic targets for CKD in the current investigation. According to the results of the network pharmacology study, 41 signaling pathways are involved in mediating the therapeutic effects of SYD. In addition, SYD's broad therapeutic impact in CKD therapy was shown to include 29 molecular activities, 14 cell components, and 91 biological processes. This research utilizes a multivariate analysis to provide light on the strategies and outcomes of treating CKD using Shengyang Yiwei Decoction. Clinical therapeutic methods for CKD management may benefit greatly from a thorough knowledge of the underlying processes and material foundation of this disease.

Construction of miRNA-mRNA regulatory network indicates potential biomarkers for primary open-angle glaucoma

BACKGROUND

Trabecular meshwork (TM) dysfunction-induced elevation of intraocular pressure has been identified as the main risk factor of irreversible optic nerve injury in Primary open‑angle glaucoma (POAG). Increasing evidences suggest that microRNA (miRNA) plays a vital role in the pathogenesis of POAG. This study aims to construct a miRNA-mRNA regulatory network and identify biomarkers for POAG.

METHODS

miRNAs and mRNAs expression profiling of TM samples from controls and POAG patients were assessed through microarray analysis. Target genes of differentially expressed miRNAs (DEmiRNAs) were predicted by miEAA and miRNet. Then GO and KEGG pathway analysis of differentially expressed mRNAs (DEmRNAs) were performed. PPI of top 30 hub genes was identified and miRNA-mRNA network was established by STRING database and Cytoscape software. GSE27276 and GSE105269 datasets were used to verify the expression of hub genes and to predict potential biomarkers in TM and aqueous humor (AH) for POAG, respectively. Finally, GSEA analysis was conducted to estimate the main signaling pathway of POAG pathogenesis.

RESULTS

A total of 29 up-regulated and 7 down-regulated miRNAs, 923 up-regulated and 887 down-regulated mRNAs were identified in TM of POAG compared with controls. Target genes and DEmRNAs were mainly enriched in nitric oxide biosynthetic process, vasopressin-regulated water reabsorption, and so on. Through miRNA-mRNA network construction, top 30 hub genes were regulated by 24 DEmiRNAs. 8 genes were aberrantly expressed in dataset GSE27276. 3 genes (CREB1, CAPZA2, SLC2A3) and 2 miRNAs (miR-106b-5p, miR-15a-5p) were identified as potential biomarkers for POAG in TM and AH, respectively. GSEA analysis revealed that these 3 genes modulated POAG through different pathways.

CONCLUSION

In this study, construction of miRNA-mRNA network and identification of biomarkers provide a novel insight into the pathogenesis, early diagnosis and treatment for POAG.

Integrative miRNA-mRNA network analysis to identify crucial pathways of salinity adaptation in brain transcriptome of Labeo rohita

Introduction: Brain being the master regulator of the physiology of animal, the current study focuses on the gene expression pattern of the brain tissue with special emphasis on regulation of growth, developmental process of an organism and cellular adaptation of Labeo rohita against unfavourable environmental conditions. Methods: RNA-seq study was performed on collected brain samples at 8ppt salt concentration and analyzed for differential gene expression, functional annotation and miRNA-mRNA regulatory network. Results: We found that 2450 genes were having significant differential up and down regulation. The study identified 20 hub genes based on maximal clique centrality algorithm. These hub genes were mainly involved in various signaling pathways, energy metabolism and ion transportation. Further, 326 up and 1214 down regulated genes were found to be targeted by 7 differentially expressed miRNAs i.e., oni-miR-10712, oni-miR-10736, ssa-miR-221-3p, ssa-miR-130d-1-5p, ssa-miR-144-5p and oni-miR-10628. Gene ontology analysis of these differentially expressed genes led to the finding that these genes were involved in signal transduction i.e., calcium, FOXO, PI3K-AKT, TGF-β, Wnt and p53 signalling pathways. Differentially expressed genes were also involved in regulation of immune response, environmental adaptation i.e., neuroactive ligand-receptor interaction, ECM-receptor interaction, cell adhesion molecules and circadian entrainment, osmoregulation and energy metabolism, which are critical for salinity adaptation. Discussion: The findings of whole transcriptomic study on brain deciphered the miRNA-mRNA interaction patterns and pathways associated with salinity adaptation of L. rohita.

Comprehensive Analysis of the miRNA-mRNA Pathological Regulatory Network of Intestinal CD4 + T Cells in Parkinson's Disease

Infiltration of CD4 + T cells was found in brain tissue samples from PD patients, suggesting their involvement in developing central nervous system (CNS) disease. The idea of the gut-brain axis further corroborates intestinal T cells' activation as the central immune response initiation. However, the specific factors and molecular pathways regulating intestinal T-cell activation are unclear. We used the GSE156287 and GSE145814 datasets from the GEO database to analyze and obtain the miRNAs, which are aberrantly expressed in intestinal CD4 + T cells in PD patients and predict their regulatory target mRNAs. Further, combined with the GSE174473 dataset of CD4 + T cells sequencing in PD patients, we finally clarified the aberrant genes expressed in CD4 + T cells from the intestine of PD patients and constructed a miRNA-mRNA regulatory network. The highlight of our findings showed pathways, networks, biological functions, and key molecules potentially involved in the miRNA-mediated functional effects in CD4 + T cell from the intestine of PD patients. The hsa-miR-3180-3p mediated CBX8, etc. were determined as most effective in enhancing T cell survival. PEG10, etc. regulated by hsa-miR-20a-3p targets were possibly involved in T cell differentiation. The JPT2 regulated by hsa-miR-1281 were involved in influencing T cell infiltration. The discovery of this interaction between miRNA and mRNA in CD4 + T cell has important implications for understanding the intestinal initial of PD pathological molecular and anti-inflammation of T cell activation.

Identification of the miRNA-mRNA regulatory network associated with radiosensitivity in esophageal cancer based on integrative analysis of the TCGA and GEO data

BACKGROUND

The current study set out to identify the miRNA-mRNA regulatory networks that influence the radiosensitivity in esophageal cancer based on the The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases.

METHODS

Firstly, esophageal cancer-related miRNA-seq and mRNA-seq data were retrieved from the TCGA database, and the mRNA dataset of esophageal cancer radiotherapy was downloaded from the GEO database to analyze the differential expressed miRNAs (DEmiRNAs) and mRNAs (DEmRNAs) in radiosensitive and radioresistant samples, followed by the construction of the miRNA-mRNA regulatory network and Gene Ontology and KEGG enrichment analysis. Additionally, a prognostic risk model was constructed, and its accuracy was evaluated by means of receiver operating characteristic analysis.

RESULTS

A total of 125 DEmiRNAs and 42 DEmRNAs were closely related to the radiosensitivity in patients with esophageal cancer. Based on 47 miRNA-mRNA interactions, including 21 miRNAs and 21 mRNAs, the miRNA-mRNA regulatory network was constructed. The prognostic risk model based on 2 miRNAs (miR-132-3p and miR-576-5p) and 4 mRNAs (CAND1, ZDHHC23, AHR, and MTMR4) could accurately predict the prognosis of esophageal cancer patients. Finally, it was verified that miR-132-3p/CAND1/ZDHHC23 and miR-576-5p/AHR could affect the radiosensitivity in esophageal cancer.

CONCLUSION

Our study demonstrated that miR-132-3p/CAND1/ZDHHC23 and miR-576-5p/AHR were critical molecular pathways related to the radiosensitivity of esophageal cancer.

Integrated Microarray for Identifying the Hub mRNAs and Constructed MiRNA-mRNA Network in Coronary In-stent Restenosis

As a major complication after percutaneous coronary intervention (PCI) in patients who suffer from coronary artery disease, in-stent restenosis (ISR) poses a significant challenge for clinical management. A miRNA-mRNA regulatory network of ISR can be constructed to better reveal the occurrence of ISR. The relevant dataset from the Gene Expression Omnibus (GEO) database was downloaded, and 284 differentially expressed miRNAs (DE-miRNAs) and 849 differentially expressed mRNAs (DE-mRNAs) were identified. As predicted by online tools, 65 final functional genes (FmRNAs) were overlapping DE-mRNAs and DE-miRNAs target genes. In the biological process (BP) terms of Gene Ontology (GO) functional analysis, the FmRNAs were mainly enriched in cellular response to peptide, epithelial cell proliferation and response to peptide hormone. In the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, the FmRNAs were mainly enriched in breast cancer, endocrine resistance and cushing syndrome. Jun Proto-Oncogene, AP-1 Transcription Factor Subunit (JUN), Insulin Like Growth Factor 1 Receptor (IGF1R), Member RAS Oncogene Family (RAB14), Specificity Protein 1 (SP1), Protein Tyrosine Phosphatase Non-Receptor Type1(PTPN1), DDB1 And CUL4 Associated Factor 10 (DCAF10), Retinoblastoma-Binding Protein 5 (RBBP5) and Eukaryotic Initiation Factor 4A-I (EIF4A1) were hub genes in the protein-protein interaction network (PPI network). The miRNA-mRNA network containing DE-miRNA and hub genes was built. Hsa-miR-139-5p-JUN, hsa-miR-324-5p-SP1 axis pairs were found in the miRNA-mRNA network, which could promote ISR development. The above results indicate that the miRNA-mRNA network constructed in ISR has a regulatory role in the development of ISR, and may provide new approaches for clinical treatment and experimental development.

Significance of a tumor microenvironment-mediated P65-miR-30a-5p-BCL2L11 amplification loop in multiple myeloma

Despite significant progress in the treatment of myeloma, multiple myeloma (MM) remains an incurable hematological malignancy due to cell adhesion-mediated drug resistance (CAM-DR) phenotype. However, data on the molecular mechanisms underlying the CAM-DR remains scanty. Here, we identified a miRNA-mRNA regulatory network in myeloma cells that are directly adherent to bone marrow stromal cells (BMSCs). Our data showed that the BMSCs up-regulated miR-30a-5p and down-regulated BCL2L11 at both mRNA and protein level in the myeloma cells. Besides, luciferase reporter genes demonstrated direct interaction between miR-30a-5p and BCL2L11 gene. Moreover, the BMSCs activated NF-ΚB signaling pathway in myeloma cells and the NF-κB P65 was shown to directly bind the miR-30a-5p promoter region. Moreover, suppression of the miR-30a-5p or upregulation of the BCL2L11 promoted apoptosis of the myeloma cells independent of the BMSCs, thus suggesting clinical significance of miR-30a-5p inhibitor and PLBCL2L11 plasmid in CAM-DR. Together, our data demonstrated the role of P65-miR-30a-5p-BCL2L11 loop in CAM-DR myeloma cells. These findings give new insights into the role of tumor microenvironment in the treatment of patients with myeloma.

Using biological information to analyze potential miRNA-mRNA regulatory networks in the plasma of patients with non-small cell lung cancer

Background

Lung cancer is the most common malignant tumor, and it has a high mortality rate. However, the study of miRNA-mRNA regulatory networks in the plasma of patients with non-small cell lung cancer (NSCLC) is insufficient. Therefore, this study explored the differential expression of mRNA and miRNA in the plasma of NSCLC patients.

Methods

The Gene Expression Omnibus (GEO) database was used to download microarray datasets, and the differentially expressed miRNAs (DEMs) were analyzed. We predicted transcription factors and target genes of the DEMs by using FunRich software and the TargetScanHuman database, respectively. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was used for GO annotation and KEGG enrichment analysis of downstream target genes. We constructed protein-protein interaction (PPI) and DEM-hub gene networks using the STRING database and Cytoscape software. The GSE20189 dataset was used to screen out the key hub gene. Using The Cancer Genome Atlas (TCGA) and UALCAN databases to analyze the expression and prognosis of the key hub gene and DEMs. Then, GSE17681 and GSE137140 datasets were used to validate DEMs expression. Finally, the receiver operating characteristic (ROC) curve was used to verify the ability of the DEMs to distinguish lung cancer patients from healthy patients.

Results

Four upregulated candidate DEMs (hsa-miR199a-5p, hsa-miR-186-5p, hsa-miR-328-3p, and hsa-let-7d-3p) were screened from 3 databases, and 6 upstream transcription factors and 2253 downstream target genes were predicted. These genes were mainly enriched in cancer pathways and PI3k-Akt pathways. Among the top 30 hub genes, the expression of KLHL3 was consistent with the GSE20189 dataset. Except for let-7d-3p, the expression of other DEMs and KLHL3 in tissues were consistent with those in plasma. LUSC patients with high let-7d-3p expression had poor overall survival rates (OS). External validation demonstrated that the expression of hsa-miR-199a-5p and hsa-miR-186-5p in peripheral blood of NSCLC patients was higher than the healthy controls. The ROC curve confirmed that the DEMs could better distinguish lung cancer patients from healthy people.

Conclusion

The results showed that miR-199a-5p and miR-186-5p may be noninvasive diagnostic biomarkers for NSCLC patients. MiR-199a-5p-KLHL3 may be involved in the occurrence and development of NSCLC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09281-1.

Developing metabolic gene signatures to predict intrahepatic cholangiocarcinoma prognosis and mining a miRNA regulatory network

Background

Metabolic disturbance is closely correlated with intrahepatic cholangiocarcinoma (IHCC), and we aimed to identify metabolic gene marker for the prognosis of IHCC.

Methods

We obtained expression and clinical data from 141 patients with IHCC from public databases. Prognostic metabolic genes were selected using univariate Cox regression analysis. Unsupervised cluster analysis was applied to identify IHCC subtypes, and CIBERSORT was used for immune infiltration analysis of different subtypes. Then, the metabolic gene signature was screened using multivariate Cox regression analysis and the LASSO algorithm. The prognostic potential and regulatory network of the metabolic gene signature were further investigated.

Results

We screened 228 prognosis‐related metabolic genes. Based on their expression levels, IHCC samples were divided into two subtypes, which showed significant differences in survival and immune cell infiltration. After LASSO analysis, eight metabolic genes including CYP19A1, SCD5, ACOT8, SRD5A3, MOGAT2, PFKFB3, PPARGC1B, and RPL17 were identified as the optimal genes for the prognosis signature. The prognostic model had excellent predictive abilities, with areas under the receiver‐operating characteristic curves over 0.8. A nomogram model was also established based on two independent prognostic clinical factors (pathologic stage and prognostic model), and the generated calibration curves and c‐indexes determined its excellent accuracy and discriminative ability to predict 1‐ and 5‐year survival status (c‐indexes>0.7). Finally, we found that miR‐26a‐5p, miR‐27a‐3p, and miR‐27b‐3p were the upstream regulators that mediate the involvement of gene signatures in metabolic pathways.

Conclusion

We developed eight metabolic gene signatures to predict IHCC prognosis and proposed potential upstream regulatory axes of gene signatures.

Integrating microRNA expression, miRNA-mRNA regulation network and signal pathway: a novel strategy for lung cancer biomarker discovery

Background

Since there are inextricably connections among molecules in the biological networks, it would be a more efficient and accurate research strategy to screen microRNA (miRNA) markers combining with miRNA-mRNA regulatory networks. The independent regulation mode is more “fragile” and “influential” than the co-regulation mode. miRNAs can be used as biomarkers if they can independently regulate hub genes with important roles in the PPI network, simultaneously the expression products of the regulated hub genes play important roles in the signaling pathways of related tissue diseases.

Methods

We collected miRNA expression of non-small cell lung cancer (NSCLC) from The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database. Volcano plot and signal-to-noise ratio (SNR) methods were used to obtain significant differentially expressed (SDE) miRNAs from the TCGA database and GEO database, respectively. A human miRNA-mRNA regulatory network was constructed and the number of genes uniquely targeted (NOG) by a certain miRNA was calculated. The area under the curve (AUC) values were used to screen for clinical sensitivity and specificity. The candidate markers were obtained using the criteria of the top five maximum AUC values and NOG ≥ 3. The protein–protein interaction (PPI) network was constructed and independently regulated hub genes were obtained. Gene Ontology (GO) analysis and KEGG pathway analysis were used to identify genes involved in cancer-related pathways. Finally, the miRNA which can independently regulate a hub gene and the hub gene can participate in an important cancer-related pathway was considered as a biomarker. The AUC values and gene expression profile analysis from two external GEO datasets as well as literature validation were used to verify the screening capability and reliability of this marker.

Results

Fifteen SDE miRNAs in lung cancer were obtained from the intersection of volcano plot and SNR based on the GEO database and the TCGA database. Five miRNAs with the top five maximum AUC values and NOG ≥ 3 were screened out. A total of 61 hub genes were obtained from the PPI network. It was found that the hub gene GTF2F2 was independently regulated by miR-708-5p. Further pathway analysis indicated that GTF2F2 participates in protein expression by binding with polymerase II, and it can regulate transcription and accelerate tumor growth. Hence, miR-708-5p could be used as a biomarker. The good screening capability and reliability of miR-708-5p as a lung cancer marker were confirmed by AUC values and gene expression profiling of external datasets, and experimental literature. The potential mechanism of miR-708-5p was proposed.

Conclusions

This study proposes a new idea for lung cancer marker screening by integrating microRNA expression, regulation network and signal pathway. miR-708-5p was identified as a biomarker using this novel strategy. This study may provide some help for cancer marker screening.

Construction of miRNA-mRNA network reveals crucial miRNAs and genes in acute myocardial infarction

Acute myocardial infarction (AMI) is a severe cardiovascular disease. This study aimed to identify crucial microRNAs (miRNAs) and mRNAs in AMI by establishing a miRNA-mRNA network. The microarray datasets GSE31568, GSE148153, and GSE66360 were downloaded from the Gene Expression Omnibus (GEO) database. We identified differentially expressed miRNAs (DE-miRNAs) and mRNAs (DE-mRNAs) in AMI samples compared with normal control samples. The consistently changing miRNAs in both GSE31568 and GSE148153 datasets were selected as candidate DE-miRNAs. The interactions between the candidate DE-miRNAs and DE-mRNAs were analyzed, and a miRNA-mRNA network and a protein-protein interaction network were constructed, along with functional enrichment and pathway analyses. A total of 209 DE-miRNAs in the GSE31568 dataset, 857 DE-miRNAs in the GSE148153 dataset, and 351 DE-mRNAs in the GSE66360 dataset were identified. Eighteen candidate DE-miRNAs were selected from both the GSE31568 and GSE148153 datasets. Furthermore, miR-646, miR-127-5p, miR-509-5p, miR-509-3-5p, and miR-767-5p were shown to have a higher degree in the miRNA-mRNA network.THBS-1 as well as FOS was a hub gene in the miRNA-mRNA network and the protein-protein interaction (PPI) network, respectively. CDKN1A was important in both miRNA-mRNA network and PPI network. We established a miRNA-mRNA network in AMI and identified five miRNAs and three genes, which might be used as biomarkers and potential therapeutic targets for patients with AMI.

Prediction of the mechanism of miRNAs in laryngeal squamous cell carcinoma based on the miRNA-mRNA regulatory network

In this study, a bioinformatics analysis is conducted to screen differentially expressed miRNAs and mRNAs in laryngeal squamous cell carcinoma (LSCC). Based on this information, we explored the possible roles of miRNAs in the pathogenesis of LSCC. The RNA-Seq data from 79 laryngeal cancer samples in the Gene Expression Omnibus (GEO) database were sorted. Differentially expressed miRNAs and mRNAs in LSCC are screened using the PERL programming language, and it was analysed by Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). The miRNA-mRNA regulatory network of LSCC is constructed using Cytoscape software. Then, quantitative real-time PCR (QRT- PCR), Cell Counting Kit-8 (CCK8) and flow cytometry analysis we are used to further validate key miRNAs. We identified 99 differentially expressed miRNAs and 2,758 differentially expressed mRNAs in LSCC tissues from the GEO database. Four more important miRNAs displaying a high degree of connectivity are selected, these results suggest that they play an important role in the pathogenesis of LSCC. As shown in the present study, we identified specific miRNA-mRNA networks associated with the occurrence and development of LSCC through bioinformatics analysis. We found a miRNA molecule closely related to LSCC based on miRNA-mRNA network: miR-140-3p was down-regulated in LSCC. In addition, the potential antitumor effect of miR-140-3p in LSCC was verified in the experiment, and it was proved that overexpression of miR-140-3p could inhibit the proliferation of LSCC cells and promote cell apoptosis, suggesting that miR-140-3p may be a potential tumor marker in LSCC.

Analysis of miRNA-mRNA Crosstalk in Radiation-Induced Mouse Thymic Lymphomas to Identify miR-486 as a Critical Regulator by Targeting IGF2BP3 mRNA

Ionizing radiation is one of the common environmental carcinogens. miRNAs play critical roles in the processes of tumor occurrence, development, metastasis. However, the relationship between radiation-induced carcinogenesis and miRNA rarely reported. This study is aimed to investigate the effect of miRNAs on radiation-induced carcinogenesis. In this study we established the radiation-induced thymic lymphoma mice model. By using miRNA array of RTL tissue and predicting for miRNAs target genes, a miRNA-mRNA crosstalk network was established. Based on this network, we identified a critical miRNA, miR-486, which was the most down-regulated in the radiation-induced carcinogenesis. Then the function of miR-486 was confirmed by using knockout mice and cellular experiments. As a result, miR-486 could inhibit proliferation of mouse lymphoma cells by targeting IGF2BP3 mRNA. The adenovirus over-expression miR-486 vector reduced tumorigenesis in vivo. MiR-486 knockout mice have a strong tendency of radiation-induced carcinogenesis. In conclusion, miR-486 inhibits the proliferation of lymphoma cells and tumorigenesis induced by radiation through targeting IGF2BP3.

Key microRNAs and hub genes associated with poor prognosis in lung adenocarcinoma

In the study, we obtained 36 pairs of lung adenocarcinoma (LUAD) tissues and adjacent non-tumorous tissues. Then, we chose a specific hub-target gene of miRNA and used qRT-PCR to evaluate the expression of PECAM1. We found that the expression level of PECAM1 mRNA in LUAD was significantly lower than that in adjacent nontumor tissues (P<0.0001). Univariate and multivariate analyses were conducted on 481 LUAD patients from The Cancer Genome Atlas (TCGA) according to the Cox proportional hazard regression model to evaluate the impact of PECAM1 expression and other clinicopathological factors on survival. The results showed that the low expression of PECAM1 was an important independent predictor of poor overall survival (HR, 0.704; 95% CI, 0.518-0.957; P = 0.025). Based on the Tumor Immune Estimation Resource (TIMER) database, the relationship between PECAM1 expression and B cell, CD8+ T cell, CD4+ T cell, macrophage, neutrophil, and dendritic cell infiltration was weak in LUAD (P<0.01). In particular, a more significant positive correlation between PECAM1 expression and HLA-complex members, CD1C, NRP1, and ITGAX expression in dendritic cell was detected in LUAD. The mechanism which PECAM1 involved in the development of LUAD may be closely related to changes in the immune microenvironment.

Identification of an MiRNA-mRNA Regulatory Network in Colorectal Cancer

BACKGROUND

Colorectal cancer (CRC) is the fourth most prevalent cancer in the world. However, the molecular mechanism underlying CRC is largely unknown.

OBJECTIVE

To explore the pathogenic mechanism of CRC and to facilitate better diagnosis and treatment of this disease.

METHODS

Differentially expressed miRNAs (DEMs) and genes (DEGs) in CRC vs. Control samples from the miRNA expression data in GSE115513 and the miRNA and mRNA expression data in the TCGA-COAD dataset were screened, followed by the construction of the miRNAmRNA regulatory network. Functional and pathway enrichment analysis, protein-protein interaction (PPI) analysis, and survival analysis were then performed for these DEGs and DEMs.

RESULTS

We identified 64 DEMs from the GSE115513 dataset and 265 DEMs and 2218 DEGs from the TCGA-COAD dataset. miR-27a-3p was a hub DEM with the highest degree in the miRNA-mRNA network, while GRIN2B and PCDH10 were hub DEGs targeted by multiple miRNAs, including miR-27a-3p. SNAP25 and GRIN2B were also hub DEGs with the highest degree of interactions in the PPI network. These DEMs and DEGs were significantly enriched in multiple KEGG pathways, including proteoglycans expression and cAMP signaling pathway in cancer. Finally, seven DEGs, including FJX1 Dsc2, and hsa-miR-375, were revealed to be correlated with CRC prognosis.

CONCLUSION

Aberrant expressions of genes and miRNAs were involved in the pathogenesis of CRC, probably by regulating proteoglycans expression and cAMP signaling. miR-27a-3p, PCDH10, GRIN2B, FJX1, Dsc2, and hsa-miR-375 were identified as potential targets for understanding the pathogenic mechanism of CRC. In addition, FJX1, Dsc2 and hsa-miR-375 were identified as potential predictive markers for CRC prognosis.

Network vulnerability-based and knowledge-guided identification of microRNA biomarkers indicating platinum resistance in high-grade serous ovarian cancer

Background

High-grade serous ovarian cancer (HGSC), the most common ovarian carcinoma type, is associated with the highest mortality rate among all gynecological malignancies. As chemoresistance has been demonstrated as the major challenge in improving the prognosis of HGSC patients, we here aimed to identify microRNA (miRNA) biomarkers for predicting platinum resistance and further explore their functions in HGSC.

Results

We developed and applied our network vulnerability-based and knowledge-guided bioinformatics model first time for the study of drug-resistance in cancer. Four miRNA biomarkers (miR-454-3p, miR-98-5p, miR-183-5p and miR-22-3p) were identified with potential in stratifying platinum-sensitive and platinum-resistant HGSC patients and predicting prognostic outcome. Among them, miR-454-3p and miR-183-5p were newly discovered to be closely implicated in platinum resistance in HGSC. Functional analyses highlighted crucial roles of the four miRNA biomarkers in platinum resistance through mediating transcriptional regulation, cell proliferation and apoptosis. Moreover, expression patterns of the miRNA biomarkers were validated in both platinum-sensitive and platinum-resistant ovarian cancer cells.

Conclusions

With bioinformatics modeling and analysis, we identified and confirmed four novel putative miRNA biomarkers, miR-454-3p, miR-98-5p, miR-183-5p and miR-22-3p that could serve as indicators of resistance to platinum-based chemotherapy, thereby contributing to the improvement of chemotherapeutic efficiency and optimization of personalized treatments in HGSC.

microRNA-messenger RNA regulatory network of esophageal squamous cell carcinoma and the identification of miR-1 as a biomarker of patient survival

Emerging evidence indicates that microRNAs (miRNAs) play an important role in tumor carcinogenesis and progression by targeting gene expression. The goal of this study was to comprehensively analyze the vital functional miRNAs and their target genes in esophageal squamous cell carcinoma (ESCC) and to explore the clinical significance and mechanisms of miR-1 in ESCC. First, the miRNA and messenger RNA (mRNA) expression profiles of ESCC were determined with microarray technology. Using an integrated analysis of miRNAs and their target genes with multistep bioinformatics methods, the miRNA-mRNA regulatory network in ESCC was constructed. Next, miR-1 expression in 292 ESCC patients and its relationship with clinicopathological features and prognosis were detected by in situ hybridization. Furthermore, the biological functions of miR-1 were determined with in vitro and in vivo functional experiments. Finally, real-time quantitative reverse transcription polymerase chain reaction, Western blot analysis, and luciferase reporter assays were performed to verify the target genes of miR-1. In this study, 67 miRNAs and 2992 genes were significantly differentially expressed in ESCC tissues compared with their expression in adjacent normal tissues, and an miRNA-mRNA regulatory network comprising 59 miRNAs and 162 target mRNAs was identified. Low miR-1 expression was correlated with pathological T stage, lymph node metastasis, vessel invasion, and poor clinical outcome. miR-1 suppressed ESCC cell proliferation and invasion and promoted ESCC cell apoptosis. Fibronectin 1 (FN1) was verified as a direct target of miR-1. Taken together, the present results suggest that miR-1 may be a valuable prognostic predictor for ESCC, and the miR-1/FN1 axis may be a therapeutic target.