scholarly journals Screening and Analysis of Key Genes in miRNA-mRNA Regulatory Network of Membranous Nephropathy

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Yawei Hou ◽  
Yameng Li ◽  
Yichuan Wang ◽  
Wenpu Li ◽  
Zhenwei Xiao
Keyword(s):  
Membranous Nephropathy ◽  
Regulatory Network ◽  
Target Genes ◽  
Differentially Expressed ◽  
Ppi Network ◽  
Data Set ◽  
Downstream Target ◽  
Differentially Expressed Mirnas ◽  
Candidate Target ◽  
Geo Database

Background. MicroRNAs (miRNAs) are confirmed to participate in occurrence, development, and prevention of membranous nephropathy (MN), but their mechanism of action is unclear. Objective. With the GEO database and the use of bioinformatics, miRNA-mRNA regulatory network genes relevant to MN were explored and their potential mechanism of action was explained. Methods. The MN-related miRNA chip data set (GSE51674) and mRNA chip data set (GSE108109) were downloaded from the GEO database. Differential analysis was performed using the GEO2R online tool. TargetScan, miRTarBase, and StarBase databases were used to predict potential downstream target genes regulated by differentially expressed miRNAs, and the intersection with differential genes were taken to obtain candidate target genes. According to the regulatory relationship between miRNA and mRNA, the miRNA-mRNA relationship pair was clarified and Cytoscape was used to construct a miRNA-mRNA regulatory network. WebGestalt was used to conduct enrichment analysis of the biological process of differential mRNAs in the regulatory network; FunRich analyzes the differential mRNA pathways in the miRNA-mRNA regulatory network. And the STRING database was used to construct a PPI network for candidate target genes, and Cytoscape visually analyzes the PPI network. Results. Experiments were conducted to screen differentially expressed miRNAs and mRNAs. There were 30 differentially expressed miRNAs, including 22 upregulated and 8 downregulated; and 1267 differentially expressed mRNAs, including 536 upregulated and 731 downregulated. Using TargetScan, miRTarBase, and StarBase databases to predict the downstream targets of differentially expressed miRNAs, 2957 downstream target genes coexisting in the 3 databases were predicted to intersect with differentially expressed mRNAs to obtain 175 candidate target genes. Finally, 36 miRNA-mRNA relationship pairs comprising 10 differentially expressed miRNAs and 27 differentially expressed mRNAs were screened out, and the regulatory network was constructed. Further analysis revealed that the miRNA regulatory network genes may be involved in the development of membranous nephropathy by mTOR, PDGFR-β, LKB1, and VEGF/VEGFR signaling pathways. Conclusion. The miRNA regulatory network genes may participate in the regulation of podocyte autophagy, lipid metabolism, and renal fibrosis through mTOR, PDGFR-β, LKB1, and VEGF/VEGFR signaling pathways, thereby affecting the occurrence and development of membranous nephropathy.

scholarly journals Construction and Bioinformatics Analysis of the miRNA-mRNA Regulatory Network in Diabetic Nephropathy

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yameng Li ◽  
Yukun Xu ◽  
Yawei Hou ◽  
Rui Li
Keyword(s):  
Diabetic Nephropathy ◽  
Regulatory Network ◽  
Target Genes ◽  
Differentially Expressed ◽  
Ras Signaling ◽  
Regulatory Relationship ◽  
Downstream Target ◽  
Differentially Expressed Mirnas ◽  
Candidate Target ◽  
Geo Database

Background. MicroRNA (miRNA) has been confirmed to be involved in the occurrence, development, and prevention of diabetic nephropathy (DN), but its mechanism of action is still unclear. Objective. With the help of the GEO database, bioinformatics methods are used to explore the miRNA-mRNA regulatory relationship pairs related to diabetic nephropathy and explain their potential mechanisms of action. Methods. The DN-related miRNA microarray dataset (GSE51674) and mRNA expression dataset (GSE30122) are downloaded through the GEO database, online analysis tool GEO2R is used for data differential expression analysis, TargetScan, miRTarBase, and miRDB databases are used to predict potential downstream target genes regulated by differentially expressed miRNAs, and intersection with differential genes is used to obtain candidate target genes. According to the regulatory relationship between miRNA and mRNA, the miRNA-mRNA relationship pair is clarified, and the miRNA-mRNA regulatory network is constructed using Cytoscape. DAVID is used to perform GO function enrichment analysis and KEGG pathway analysis of candidate target genes. By GeneMANIA prediction of miRNA target genes and coexpressed genes, the protein interaction network is constructed. Results and Conclusions. A total of 67 differentially expressed miRNAs were screened in the experiment, of which 42 were upregulated and 25 were downregulated; a total of 448 differentially expressed mRNAs were screened, of which 93 were upregulated and 355 were downregulated. Using TargetScan, miRTarBase, and miRDB databases to predict downstream targets of differentially expressed miRNAs, 2283 downstream target genes coexisting in 3 databases were predicted to intersect with differentially expressed mRNAs to obtain 96 candidate target genes. Finally, 44 miRNA-mRNA relationship pairs consisting of 12 differentially expressed miRNAs and 27 differentially expressed mRNAs were screened out; further analysis showed that miRNA regulatory network genes may participate in the occurrence and development of diabetic nephropathy through PI3K/Akt, ECM-receptor interaction pathway, and RAS signaling pathway.

scholarly journals Identification of Potential Biomarkers and Biological Pathways in Juvenile Dermatomyositis Based on miRNA-mRNA Network

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Cheng-Cheng Qiu ◽  
Qi-Sheng Su ◽  
Shang-Yong Zhu ◽  
Ruo-Chuan Liu
Keyword(s):  
Regulatory Network ◽  
Messenger Rna ◽  
Target Genes ◽  
Juvenile Dermatomyositis ◽  
Type I Diabetes ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Type I ◽  
Ppi Network ◽  
Potential Biomarkers

Objective. The aim of this study is to explore the potential pathogenesis of juvenile dermatomyositis by bioinformatics analysis of gene chips, which would screen the hub genes, identify potential biomarkers, and reveal the development mechanism of juvenile dermatomyositis. Material and Methods. We retrieved juvenile dermatomyositis’s original expression microarray data of message RNAs (mRNAs) and microRNAs (miRNAs) from NCBI’s Gene Expression Omnibus database (GEO, http://www.ncbi.nlm.nih.gov/geo/); through the R package of limma in Bioconductor, we can screen the differentially expressed miRNAs and mRNAs, and then we further analyzed the predicted target genes by the methods such as Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and miRNA-mRNA regulatory network construction and protein-protein interaction (PPI) network using Cytoscape 3.6.1. Results. Compared with normal juvenile skin tissues, 6 upregulated microRNAs and 5 downregulated microRNAs were identified from 166 downregulated microRNAs and 58 upregulated microRNAs in juvenile dermatomyositis tissues. The enrichment pathways of differentially expressed microRNAs include cell adhesion molecules (CAMs), autoimmune thyroid disease, Type I diabetes mellitus, antigen and presentation, viral myocardium, graft-versus-host disease, and Kaposi sarcoma-associated herpes virus infection. By screening of microRNA-messenger RNA regulatory network and construction of PPI network map, three target miRNAs were identified, namely, miR-193b, miR-199b-5p, and miR-665. Conclusion. We identified mir-193b, mir-199b-5p, and mir-6653 target miRNAs by exploring the miRNA-mRNA regulation network mechanism related to the pathogenesis of juvenile dermatomyositis, which will be of great significance for further study on the pathogenesis and targeted therapy of juvenile dermatomyositis.

scholarly journals A Potential ceRNA Network for Neurological Damage in Preterm Infants

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Jin Huang ◽  
Xuejing Liang ◽  
Zhenyu Cai
Keyword(s):  
Brain Injury ◽  
Preterm Infants ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Neurological Injury ◽  
Ppi Network ◽  
Neurological Damage ◽  
Injury Group ◽  
Differentially Expressed Mirnas ◽  
Geo Database

Objective. This study is aimed at identifying key genes involved in neurological damage in preterm infants and at determining their potential circRNA-miRNA-mRNA regulatory mechanisms. Methods. Differentially expressed miRNAs, mRNAs, and circRNAs were downloaded from the GEO database. GO and KEGG enrichment analyses were used to determine possible relevant functions of differentially expressed mRNAs. The TTRUST database was used to predict differential TF-mRNA regulatory relationships. Then, CircMIR, miRDB, TargetScan and miRTarBase were then used to map circRNA/miRNA-TF/mRNA interaction networks. Finally, GSEA enrichment analysis was performed on the core transcription factors. Results. A total of 640 mRNAs, 139 circRNAs, and 206 differentially expressed miRNAs associated with neurological injury in preterm infants were obtained. Based on the findings of Cytoscape and PPI network analysis, the hsa_circ_0008439-hsa-mir-3665-STAT3-MMP3 regulatory axis was established. GSEA analysis revealed that suppressed expression levels of STAT3 were associated with upregulated oxidative phosphorylation pathways in the neurological injury group of preterm infants. Conclusions. The circRNA-miRNA-TF-mRNA regulatory network of neurological injury in preterm infants can be used to elucidate on the pathogenesis of brain injury and help us with the early detection of brain injury in preterm infants.

scholarly journals Identification of the TF-miRNA-mRNA Co-regulatory Networks Involved in Sepsis

2021 ◽  
Author(s):  
Xiaoqian Luo ◽  
Weina Lu ◽  
Jianfeng Zhao ◽  
Jun Hu ◽  
Enjiang Chen ◽  
...  
Keyword(s):  
Expression Analysis ◽  
Regulatory Network ◽  
Regulatory Networks ◽  
Mirna Target ◽  
Target Genes ◽  
Medical Condition ◽  
Differentially Expressed ◽  
Biological Targets ◽  
Differentially Expressed Mirnas

Abstract BackgroundSepsis is a life-threatening medical condition caused by a dysregulated host response to infection. Recent studies have found that the expression of miRNAs is associated with the pathogenesis of sepsis and septic shock. Our study aimed to reveal which miRNAs may be involved in the dysregulated immune response in sepsis and how these miRNAs interact with transcription factors (TFs) using a computational approach with in vitro validation studies. MethodsTo determine the network of TFs, miRNAs and target genes involved in sepsis, GEO datasets GSE94717 and GSE131761 were used to identify differentially expressed miRNAs and DEGs. TargetScan and miRWalk databases were used to predict biological targets that overlap with the identified DEGs of differentially expressed miRNAs. The TransmiR database was used to predict the differential miRNA TFs that overlap with the identified DEGs. The TF-miRNA-mRNA network was constructed and visualized. Finally, qRT-PCR was used to verify the expression of TFs and miRNA in HUVECs. ResultBetween the healthy and sepsis groups, there were 146 upregulated and 98 downregulated DEGs in the GSE131761 dataset, and there were 1 upregulated and 183 downregulated DEMs in the GSE94717 dataset. A regulatory network of the TF-miRNA-target genes was established. According to the experimental results, RUNX3 was found to be downregulated while MAPK14 was upregulated, which corroborates the result of the computational expression analysis. In a HUVECs model, miR-19b-1-5p and miR-5009-5p were found to be significantly downregulated. Other TFs and miRNAs did not correlate with our bioinformatics expression analysis. ConclusionWe constructed a TF-miRNA-target gene regulatory network and identified potential treatment targets RUNX3, MAPK14, miR-19b-1-5p and miR-5009-5p. This information provides an initial basis for understanding the complex sepsis regulatory mechanisms.

scholarly journals A Comprehensive Genomic Analysis Constructs miRNA–mRNA Interaction Network in Hepatoblastoma

2021 ◽  
Vol 9 ◽  
Author(s):  
Tong Chen ◽  
Linlin Tian ◽  
Jianglong Chen ◽  
Xiuhao Zhao ◽  
Jing Zhou ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Target Genes ◽  
Pediatric Population ◽  
Genomic Analysis ◽  
Interaction Network ◽  
Normal Liver ◽  
Differentially Expressed ◽  
Ppi Network ◽  
Hub Genes ◽  
Downstream Target

Hepatoblastoma (HB) is a rare disease but nevertheless the most common hepatic tumor in the pediatric population. For patients with advanced HB, the prognosis is dismal and there are limited therapeutic options. Multiple microRNAs (miRNAs) were reported to be involved in HB development, but the miRNA–mRNA interaction network in HB remains elusive. Through a comparison between HB and normal liver samples in the GSE131329 dataset, we detected 580 upregulated differentially expressed mRNAs (DE-mRNAs) and 790 downregulated DE-mRNAs. As for the GSE153089 dataset, the first cluster of differentially expressed miRNAs (DE-miRNAs) were detected between fetal-type tumor and normal liver groups, while the second cluster of DE-miRNAs were detected between embryonal-type tumor and normal liver groups. Through the intersection of these two clusters of DE-miRNAs, 33 upregulated hub miRNAs, and 12 downregulated hub miRNAs were obtained. Based on the respective hub miRNAs, the upstream transcription factors (TFs) were detected via TransmiR v2.0, while the downstream target genes were predicted via miRNet database. The intersection of target genes of respective hub miRNAs and corresponding DE-mRNAs contributed to 250 downregulated candidate genes and 202 upregulated candidate genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses demonstrated the upregulated candidate genes mainly enriched in the terms and pathways relating to the cell cycle. We constructed protein–protein interaction (PPI) network, and obtained 211 node pairs for the downregulated candidate genes and 157 node pairs for the upregulated candidate genes. Cytoscape software was applied for visualizing the PPI network and respective top 10 hub genes were identified using CytoHubba. The expression values of hub genes in the PPI network were subsequently validated through Oncopression database followed by quantitative real-time polymerase chain reaction (qRT-PCR) in HB and matched normal liver tissues, resulting in six significant downregulated genes and seven significant upregulated genes. The miRNA–mRNA interaction network was finally constructed. In conclusion, we uncover various miRNAs, TFs, and hub genes as potential regulators in HB pathogenesis. Additionally, the miRNA–mRNA interaction network, PPI modules, and pathways may provide potential biomarkers for future HB theranostics.

scholarly journals ARHGEF3 Associated with Invasion, Metastasis, and Proliferation in Human Osteosarcoma

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Jie Gong ◽  
Wei Tang ◽  
Bin Lv ◽  
Shushu Zhang ◽  
Tingjuan Fan ◽  
...  
Keyword(s):  
Target Genes ◽  
Gene Expression Omnibus ◽  
Differentially Expressed ◽  
Qrt Pcr ◽  
Human Osteosarcoma ◽  
Gene Profiles ◽  
Kaplan Meier ◽  
Differentially Expressed Mirnas ◽  
Kaplan Meier Plotter ◽  
Geo Database

Background. Osteosarcoma is a malignant bone tumor composed of mesenchymal cells producing osteoid and immature bone. This study is aimed at developing novel potential prognostic biomarkers and constructing a miRNA-mRNA network for progression in osteosarcoma. Method. GSE70367 and GSE70414 were obtained in the Gene Expression Omnibus (GEO) database. GEO software and the GEO2R calculation method were used to analyze two gene profiles. The coexpression of differentially expressed miRNAs (DEMs) and genes (DEGs) was identified and searched for in the FunRich database for pathway and ontology analysis. Cytoscape was utilized to construct the mRNA-miRNA network. Survival analysis of identified miRNAs and mRNAs was performed by utilizing the Kaplan-Meier Plotter. Besides, expression levels of DEMs and target mRNAs were verified by performing quantitative real-time PCR (qRT-PCR) and Western blot (WB). Results. Six differentially expressed microRNAs (DEMs) were identified, and 8 target genes were selected after screening. By using the KM Plotter software, miRNA-124 and ARHGEF3 were obviously associated with the overall survival of patients with osteosarcoma. Furthermore, ARHGEF3 was found downregulated in osteosarcoma cells by performing qRT-PCR and WB experiments. Results also showed that downregulated ARHGEF3 may associate with invasion, metastasis, and proliferation. Conclusions. By using microarray and bioinformatics analysis, DEMs were selected, and a complete miRNA-mRNA network was constructed. ARHGEF3 may act as a therapeutic and prognostic target of osteosarcoma.

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

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12075
Author(s):  
Jinhua Ma ◽  
Xiaodong Hu ◽  
Baoqiang Dai ◽  
Qiang Wang ◽  
Hongqin Wang
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Regulatory Network ◽  
Bioinformatics Analysis ◽  
Laryngeal Squamous Cell Carcinoma ◽  
Differentially Expressed ◽  
Cell Counting ◽  
Differentially Expressed Mirnas ◽  
Geo Database

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.

Bioinformatics Analysis Reveals Functions of MicroRNAs in Rice Under the Drought Stress

2021 ◽  
Vol 15 (8) ◽  
pp. 927-936 ◽  
Author(s):  
Yan Peng ◽  
Yuewu Liu ◽  
Xinbo Chen
Keyword(s):  
Drought Stress ◽  
Target Genes ◽  
Hot Spot ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Protein Protein Interaction ◽  
Promising Tool ◽  
Differentially Expressed Mirnas ◽  
Aba Biosynthesis

Background: Drought is one of the most damaging and widespread abiotic stresses that can severely limit the rice production. MicroRNAs (miRNAs) act as a promising tool for improving the drought tolerance of rice and have become a hot spot in recent years. Objective: In order to further extend the understanding of miRNAs, the functions of miRNAs in rice under drought stress are analyzed by bioinformatics. Method: In this study, we integrated miRNAs and genes transcriptome data of rice under the drought stress. Some bioinformatics methods were used to reveal the functions of miRNAs in rice under drought stress. These methods included target genes identification, differentially expressed miRNAs screening, enrichment analysis of DEGs, network constructions for miRNA-target and target-target proteins interaction. Results: (1) A total of 229 miRNAs with differential expression in rice under the drought stress, corresponding to 73 rice miRNAs families, were identified. (2) 1035 differentially expressed genes (DEGs) were identified, which included 357 up-regulated genes, 542 down-regulated genes and 136 up/down-regulated genes. (3) The network of regulatory relationships between 73 rice miRNAs families and 1035 DEGs was constructed. (4) 25 UP_KEYWORDS terms of DEGs, 125 GO terms and 7 pathways were obtained. (5) The protein-protein interaction network of 1035 DEGs was constructed. Conclusion: (1) MiRNA-regulated targets in rice might mainly involve in a series of basic biological processes and pathways under drought conditions. (2) MiRNAs in rice might play critical roles in Lignin degradation and ABA biosynthesis. (3) MiRNAs in rice might play an important role in drought signal perceiving and transduction.

scholarly journals MicroRNA sequence analysis identifies microRNAs associated with peri-implantitis in dogs

2017 ◽  
Vol 37 (5) ◽  
Author(s):  
Xiaolin Wu ◽  
Xipeng Chen ◽  
Wenxiang Mi ◽  
Tingting Wu ◽  
Qinhua Gu ◽  
...  
Keyword(s):  
Sequence Analysis ◽  
Target Genes ◽  
Alveolar Bone ◽  
Biological Effects ◽  
Bone Destruction ◽  
Mapk Signaling ◽  
Differentially Expressed ◽  
Mitogen Activated Protein Kinase ◽  
Mirna Sequence ◽  
Differentially Expressed Mirnas

Peri-implantitis, which is characterized by dense inflammatory infiltrates and increased osteoclast activity, can lead to alveolar bone destruction and implantation failure. miRNAs participate in the regulation of various inflammatory diseases, such as periodontitis and osteoporosis. Therefore, the present study aimed to investigate the differential expression of miRNAs in canine peri-implantitis and to explore the functions of their target genes. An miRNA sequence analysis was used to identify differentially expressed miRNAs in peri-implantitis. Under the criteria of a fold-change >1.5 and P<0.01, 8 up-regulated and 30 down-regulated miRNAs were selected for predictions of target genes and their biological functions. Based on the results of Gene Ontology (GO) and KEGG pathway analyses, these miRNAs may fine-tune the inflammatory process in peri-implantitis through an intricate mechanism. The results of quantitative real-time PCR (qRT-PCR) revealed that let-7g, miR-27a, and miR-145 may play important roles in peri-implantitis and are worth further investigation. The results of the present study provide insights into the potential biological effects of the differentially expressed miRNAs, and specific enrichment of target genes involved in the mitogen-activated protein kinase (MAPK) signaling pathway was observed. These findings highlight the intricate and specific roles of miRNAs in inflammation and osteoclastogenesis, both of which are key aspects of peri-implantitis, and thus may contribute to future investigations of the etiology, underlying mechanism, and treatment of peri-implantitis.

scholarly journals Identification of New miRNA-mRNA Networks in the Development of Non-syndromic Cleft Lip With or Without Cleft Palate

2021 ◽  
Vol 9 ◽  
Author(s):  
Chengyi Fu ◽  
Shu Lou ◽  
Guirong Zhu ◽  
Liwen Fan ◽  
Xin Yu ◽  
...  
Keyword(s):  
Cell Proliferation ◽  
Cleft Palate ◽  
Negative Correlation ◽  
Cell Apoptosis ◽  
Cleft Lip ◽  
Target Genes ◽  
Craniofacial Development ◽  
Differentially Expressed ◽  
Differentially Expressed Mirnas

Objective: To identify new microRNA (miRNA)-mRNA networks in non-syndromic cleft lip with or without cleft palate (NSCL/P).Materials and Methods: Overlapping differentially expressed miRNAs (DEMs) were selected from cleft palate patients (GSE47939) and murine embryonic orofacial tissues (GSE20880). Next, the target genes of DEMs were predicted by Targetscan, miRDB, and FUNRICH, and further filtered through differentially expressed genes (DEGs) from NSCL/P patients and controls (GSE42589), MGI, MalaCards, and DECIPHER databases. The results were then confirmed by in vitro experiments. NSCL/P lip tissues were obtained to explore the expression of miRNAs and their target genes.Results: Let-7c-5p and miR-193a-3p were identified as DEMs, and their overexpression inhibited cell proliferation and promoted cell apoptosis. PIGA and TGFB2 were confirmed as targets of let-7c-5p and miR-193a-3p, respectively, and were involved in craniofacial development in mice. Negative correlation between miRNA and mRNA expression was detected in the NSCL/P lip tissues. They were also associated with the occurrence of NSCL/P based on the MGI, MalaCards, and DECIPHER databases.Conclusions: Let-7c-5p-PIGA and miR-193a-3p-TGFB2 networks may be involved in the development of NSCL/P.

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