Differential expression and bioinformatics analysis of microRNAs in exosomes of sheep poxvirus-infected cells

Article information

Korean J Vet Res. 2024;64.e23
Publication date (electronic) : 2024 December 30
doi : https://doi.org/10.14405/kjvr.20240010
1College of Life Science and Technology, Xinjiang University, Urumqi 830017, China
2Xinjiang Key Laboratory of Biological Resources and Genetic Engineering, Urumqi 830017, China
3College of Textiles and Clothing, Xinjiang University, Urumqi 830017, China
*Corresponding author: Juntao Ding College of Life Science and Technology, Xinjiang University, No.777 Huarui Street, Shuimogou District, Urumqi 830017, China Tel: +86-991-18999161949 E-mail: dingjuntao2004@126.com
†These authors contributed equally to this work.
Received 2024 February 24; Revised 2024 June 27; Accepted 2024 July 1.

Abstract

Sheep pox is widespread worldwide and is the most severe animal pox virus infection. This study aimed to identify the key microRNAs (miRNAs) differentially expressed in the exosomes of sheep poxvirus-infected cells and their target genes and related pathways and provide a theoretical basis for an in-depth understanding of the molecular mechanisms of sheep poxvirus-infected cells. In this study, the differentially expressed miRNAs were verified by quantitative polymerase chain reaction (qPCR), and the target genes of miRNAs were predicted and analyzed by bioinformatics. The qPCR results showed that the expression trends of oar-miR-21, oar-miR-10b, oar-let-7f, oar-let-7b, and oar-miR-221 were consistent with the sequencing results. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes results showed that differentially expressed miRNAs were mainly involved in the immune system processes of the Arf6 downstream pathway. The target genes Reactome pathways were mainly enriched in the RAC1 GTPase cycle, CDC42 GTPase cycle, RHO GTPase cycle, RHOV GTPase cycle, and post-transcriptional silencing of small RNAs. The transcription factors SP4, NKX6-1, MEF2A, SP1, EGR1, and POU2F1 that may be connected to sheep pox virus (SPPV)-infected cells were discovered by transcription factor annotation screening. In conclusion, this study screened for differentially expressed miRNAs in SPPV-infected cells and performed a series of bioinformatic analyses of their target genes to provide a theoretical basis for the molecular mechanism of SPPV virus infections of cells. The data can be used as basic information in future studies on the defense mechanisms against poxvirus infections.

Introduction

The sheep pox virus (SPPV) is a member of the Poxviridae family, the subfamily Chordopoxvrinae, and the genus Caripoxvirus, and is the only double-stranded DNA virus with a vesicular membrane that replicates in the cytoplasm [13]. Sheep pox is an acute, febrile, contact infection of sheep caused by the SPPV or goat pox virus of the genus sheep pox. This virus is the most serious of all animal pox viruses and is distributed widely in Asia, Europe, North America, and Africa [4]. In recent years, the emergence of animal-derived poxvirus infections in humans has complicated the prevention and control of poxviruses [58]. Outbreaks of sheep pox have seriously jeopardized sheep production, causing severe economic losses and restricting trade in animals and animal products worldwide. Cases of sheep and goat pox virus infections in humans have continued to occur in India, Sweden, and China. On the other hand, there are still many gaps in research on the complex mechanisms of action and regulatory pathways between pox viruses and their hosts, and it is essential to strengthen research on the pathogenesis of pox viruses.

MicroRNAs (miRNAs) are endogenous single-stranded small molecule RNAs of approximately 22 nucleotides in length in eukaryotes and plant and animal cells located in the non-coding region of the genome. They were first discovered in nematodes. miRNAs can bind to the non-coding region of the mRNA of target genes in a complementary manner and regulate the functions of genes by preventing the translation or degradation of mRNAs [9,10]. Several studies showed that miRNAs are involved in various biological processes in almost all organisms, including cell differentiation, proliferation, apoptosis, viral replication, and regulation of the host antiviral immune response [1115]. Viruses can use miRNAs as expression-regulated “molecular switches” to regulate the expression of host genes directly or indirectly, reshaping the intracellular environment to facilitate their infection and proliferation. Exosomes, first discovered in sheep reticulocytes, are a class of biologically active vesicles with diameters ranging from 20 nm to 200 nm, which are strongly associated with cancer progression, immune response, neurological disorders, cardiovascular diseases, and viral pathogenicity [1619].

Nevertheless, many fine-grained regulatory mechanisms of the interaction between the vaccinia virus and the host are unclear. Rew reports on the mechanism of host miRNA and its related cellular signaling pathways in the exosomes of SPPV-infected cells have been published. Therefore, finding host miRNA and its related pathways that play a crucial role may become an essential breakthrough in the targeted treatment of sheep pox.

Materials and Methods

Experimental material

The ovine testicular cells and SPPV were kept in the laboratory. The Dulbecco's Modified Eagle Medium cell culture medium was purchased from Gibco, USA; Trizzol LS was acquired from Invitrogen, USA; total exosome isolation from cell culture media was obtained from Thermo Fisher Scientific, USA; 0.25% trypsin, double antibody (penicillin-streptomycin solution, 100 ×), and fetal bovine serum (FBS) were supplied by MRC, USA; an all-in-one miRNA cDNA synthesis kit and quantitative polymerase chain reaction (qPCR) quantification kit were procured from Gene Copoeia, China.

Cell culture and viral infections

Sheep testis primary cells were inoculated with 1.0 × 105 cells/mL in T25 culture flasks and cultured at 37℃ in a 5% CO2 incubator for 7 to 10 hours. After 7 to 10 hours, the cells adhered to the wall. The suspended cells were discarded, and the flasks were washed 3 times with PBS and supplemented with 5 mL of DMEM complete medium to continue the culture. When their density reached 80% to 90%, the cells were washed 3 times with PBS, inoculated with SPPV according to the number of infected replicates (10 multiplicity of infection), and incubated at 37°C for 2 hours. The supernatant was removed. Subsequently, 5 mL of fresh culture medium without FBS was added, and the cells were incubated for 4 hours. The uninfected cells were used as the control, and each group was carried out in quadruplicate.

Exosome isolation

The cells and cell culture supernatants from SPPV-infected sheep testis cells at 0 hour, 24 hours, and 72 hours were collected in 15 mL centrifuge tubes, centrifuged (3,200 × g for 5 minutes) at 4℃, and the precipitate was discarded. The supernatant was filtered through a 0.22 μm filter to remove the extracellular bodies in the supernatant. Half the volume of the Total Exosome Isolation (from cell culture media) reagent was added to the filtered supernatant so that it was well mixed and incubated overnight in a refrigerator at 4℃. The mixture was centrifuged at 10,000 × g for 1 hour at 4℃. The supernatant was discarded, and the precipitate was stored in a refrigerator at −80℃.

Detection of miRNA dynamic expression in exosomes during different infection periods by qPCR

The exosomal RNA was extracted using Trizol LS reagent and Primer 5.0 software for primer design according to the instruction manual (https://www.thermofisher.cn/, Item no.: 4478359).

Primers were synthesized by DynaProbiotics (see Table 1 for sequences). An all-in-one miRNA cDNA synthesis kit was used for exosomal RNA first-strand cDNA synthesis. The cDNA products were used for qPCR analysis using an ABI7500 thermocycler (Thermo Fisher Scientific) with the specific primers (Table 1) according to the two-step protocol: denaturation at 95℃ for 10 minutes, 40 cycles of 95℃ for 15 seconds, and 60℃ for 1 minute. The 2-ΔΔCt formula was used to calculate the relative expression of miRNAs, and t-tests were used for significance analysis.

Primers used in this study

Prediction of differentially expressed miRNA target genes and their Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Reactome enrichment analyses

A previous study identified the differentially expressed miRNA in the exosome of SPPV-infected cells, and these data were used for the succeeding bioinformatics analysis in the present study [20] First, target genes for differentially expressed miRNAs were predicted using websites, such as TargetScan 8.0 (https://www.targetscan.org/vert_80/), and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to assess the potential function of differential miRNA target genes. Furthermore, Reactome was used to perform pathway analysis of the target genes involved in the intermediate metabolism, signaling, transcriptional regulation, and the pathway analysis of classical biological pathways, such as apoptosis and disease.

Transcription factor annotation of differential miRNA target genes

The potential upstream transcription factors of differential miRNA target genes were analyzed using FunRich (https://www.funrich.org/), and transcription-factor-enrichment bar graphs were drawn.

Differential miRNA target gene–protein interaction network establishment and analysis

Using the String (https://string-db.org/) database, the target gene–protein-interaction network was established under a composite score ≥ 0.4, and the protein interaction network (PPI) map was further adjusted using Cyto-scape_3.8.1 software. The top 10 Hub genes were screened by the “Cyto-hubba.” The Top 10 Hub genes were screened by the maximum cluster centrality MCC algorithm using the “Cyto-hubba” plugin, and the PPI network map of target genes was obtained.

miRNA-mRNA molecular network construction

Experimental errors were reduced by selecting the 34 most abundant miRNAs among the differentially expressed cellular exosomal miRNAs during a sheep poxvirus infection to construct a miRNA-mRNA interaction network map. Different software, such as TargetScan and miRDB (https://mirdb.org/miRDB/), were used to predict the target genes of miRNAs. Cyto-scape software was used to analyze the data and construct the miRNA-mRNA molecular network. The analysis results are presented in a table.

Statistical analysis

All experiments were performed at least 3 times independently. The data are presented as mean ± standard error of the mean. Statistical analysis was performed using a Student t-test or one-way analysis of variance (ANOVA). The statistical values of p < 0.05 were considered significant, and p < 0.001 was highly significant.

Results

Analysis of differentially expressed miRNAs in exosomes

The authors’ group found many miRNAs differentially expressed in the exosomes of SPPV-infected sheep testicular cells by high-throughput sequencing in the previous period [20]. In this study, the high-throughput sequencing results were validated by in vitro experiments. Consistent with the sequencing data were oar-miR-21, oar-miR-10b, oar-let-7f, oar-let-7b, and oar-miR-221. Compared to the uninfected group (0 hour), oar-miR-21 and oar-miR-10b were significantly up-regulated at 24 hours of the SPPV infection (p < 0.001), and oar-let-7f was significantly up-regulated at 72 hours of infection (p < 0.05). In contrast, the levels of oar-let-7b and oar-miR-221 expression were significantly down-regulated (p < 0.05) at 24 hours and 72 hours of SPPV infection compared to the control (Fig. 1), which may be linked to SPPV DNA synthesis.

Fig. 1.

Validation of microRNA (miRNA) expression by a quantitative polymerase chain reaction (qPCR) assay. (A-E) Relative expression of miRNAs was analyzed by qPCR in sheep pox virus-infected sheep testicular cell exosomes at 0 hour, 24 hours, and 72 hours. U6 was used as an internal reference gene, and 3 independent replicates of the experiment were performed. ns, not significant. *p < 0.05, **p < 0.01,***p < 0.001.

GO and KEGG analysis of differentially expressed miRNA target genes

GO enrichment analysis showed that these differentially expressed miRNAs were mainly involved in growth, immune system process, signaling, transcription regulator activity, translation regulator activity, transporter activity, protein-containing complex, and stimulatory responses (Fig. 2AC). The KEGG pathway results showed that the corresponding target genes were mainly associated with the IFN-γ signaling pathway, TRAIL signaling pathway, PI3K-AKT signaling pathway, and Arf6 downstream pathway (Fig. 2D). Enrichment analysis showed that the target genes of differentially expressed miRNAs in the exosomes of SPPV-infected cells were mainly involved in biological functions, such as cell growth and immune regulation, which helps provide ideas for designing experiments to investigate the role mechanism of miRNAs in the process of SPPV infection at a later stage.

Fig. 2.

Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. (A–C) GO analysis of the differentially expressed microRNA (miRNA) target genes; (D) KEGG analysis of differentially expressed miRNA target genes.

Target gene Reactome pathway enrichment

The potential mechanisms of differentially expressed miRNAs in viral infection were examined by selecting the 34 most abundant miRNAs for target gene prediction; 5614 target genes were predicted and subjected to Reactome pathway enrichment analysis. Table 2 lists the 25 relevant pathways in which the target genes were mainly involved, including the RAC1 GTPase cycle, CDC42 GTPase cycle, RHO GTPase cycle, RHOV GTPase cycle, and post-transcriptional silencing of small RNAs. Fig. 3 lists the genome-wide results of pathway analysis. The above analyses make the miRNA function analysis more complete from the classical biological pathways involved in the target genes of differentially expressed miRNAs during the SPPV infection process. Their biological functions will be the target of further research on the SPPV infection mechanism.

Enrichment of target gene Reactome pathway

Fig. 3.

Target gene Reactome enrichment analysis.

Target gene transcription factor annotation

Using Funrich software, the predicted target genes were annotated with transcription factors, and the top 6 transcription factors were screened out, i.e., SP4, NKX6-1, MEF2A, SP1, EGR1, and POU2F1, as shown in Fig. 4. The annotation of transcription factors helps explore the influence of the miRNA upstream transcription factors on SPPV infection during an SPPV infection at a later stage so that the screening of critical molecules can be more precise and efficient, and the screening of upstream and downstream key genes can make the molecular mechanism of SPPV infection more complete.

Fig. 4.

Annotation of the target gene transcription factors. The top 6 transcription factors screened were SP4, NKX6-1, MEF2A, SP1, EGR1, and POU2F1.

Target gene PPI network construction and hub gene prediction

The PPI networks for the target genes were produced from the String database. The above PPI network was then uploaded to Cyto-scape software, and Hub genes were screened using the Cyto-hubba plugin. The top 10 Hub genes were PTEN, KRAS, STAT3, MTOR, C-JUN, IGF1, CCND1, MAPK8, AKT3, and CASP3, as shown in Fig. 5. The above Hub genes can be used as the critical target genes for developing small molecule drugs for treating sheep pox, but further design of in vivo and in vitro experiments is needed to validate them.

Fig. 5.

Target gene hub gene screening. The top 10 Hub genes were PTEN, KRAS, STAT3, MTOR, C-JUN, IGF1, CCND1, MAPK8, AKT3, and CASP3.

DEM-hub genetic network

The DEM-hub gene network was constructed using Cyto-scape software. The results showed that miR-Let-7b interacted with SMAD2, IRS2, SOCS7, CHRD, FBXO32, and TSC1; miR-21 interacted with STAT3, CADM2, RBMS3, PRKCE, JAG1, and PIK3R1; miR-10b interacted with PIK3CA, CRK, LOC443340, ITSN1, BDNF, and CREB1; miR-Let-7f interacted with LIN28B, TRIM71, IGF2BP1, YOD1, TGFBR1, and HMGA2. Table 3 lists the specific results. The miRNA-mRNA molecular network screens for potential target molecules that differentially express key miRNAs during SPPV infection, which will help elucidate the pathogenesis of sheep pox as soon as possible through experiments at a later stage. The ultimate aim was to develop medicines to treat sheep pox with few side effects.

DEM-hub gene network prediction

Discussion

Viruses are intracellular organisms that are dependent on the host environment for reproduction, and they have evolved several mechanisms to survive stably within the host aimed at evading the host's immune system, such as inducing the up- or down-regulation of a variety of miRNAs to evade the host's immune system [21]. Poxviruses are important as pathogens, vaccine vectors, and models of host-virus interactions. They are large double-stranded DNA viruses that encode the mechanisms of DNA replication, transcription, and mRNA biogenesis, which underlie their ability to replicate exclusively in the cytoplasm. The study showed that poxviruses have a replication cycle of approximately 20 hours and usually accomplish a persistent and stable infection by interfering with the transcription and translation while causing a decrease in the RNA content of the host cell. This study found that oar-miR-let-7b and oar-miR-221 were down-regulated in SPPV-infected sheep testicular cell exosomes for 24 hours compared with the uninfected group, which is consistent with a previous study [22,23]. On the other hand, oar-miR-21, oar-miR-10b, and oar-miR-let-7f were up-regulated at 24 hours infection, which may be the antiviral mechanism of the host cell.

In this paper, the target genes were predicted for the top 34 miRNAs in abundance and enriched for the Reactome pathway. The corresponding target genes were mainly involved in the RAC1 GTPase cycle, CDC42 GTPase cycle, RHO GTPase cycle, RHOV GTPase cycle, and post-transcriptional silencing of small RNAs. This study confirmed that Rho GTPases, including Rho A and Rho C, are strongly expressed in many tumor types and that Rho proteins play an important role in various aspects of the tumor malignant transformation, aberrant proliferation, apoptosis, invasion and metastasis, and tumor angiogenesis [24,25]. These results suggest that the role of GTPase in viral infection deserves further exploration. Whether SPPV infection leads to changes in GTPase will also be a focus of future studies.

Transcription factors can regulate the expression of miRNAs, and miRNAs can, in turn, influence the function of transcription factors, both of which are involved in mRNA transcription and translation [26,27], regulating the transcriptional expression of genes and are important components of cellular metabolism [28]. The results of transcription factor annotation in this study showed that SP1, SP4, NKX6-1, MEF2A, EGR1, and POU2F1 were the transcription factors significantly regulating miRNAs. Zhao et al. [29] reported that the upregulation of miR-31-5p expression inhibited the proliferation, migration, and invasion of HepG2 hepatocellular carcinoma cells by regulating Sp1 transcription factor. Silencing of miR-190b accelerates pancreatic β-cell proliferation and insulin secretion by targeting NKX6-1 [30]. Vaccinia virus infections induce MAPK pathway activation, which in turn activates EGR1 [31]. An increasing number of findings confirmed that transcription factors are closely associated with viral infection. This study screened for significant transcription factors, such as SP1 and EGR1, among the target genes of differentially expressed miRNAs in SPPV-infected cells. In addition, they may play a regulatory role in SPPV-infected cells. The role of this transcription factor in SPPV replication can be detected later by overexpressing or repressing the transcription factor to explore the main factors affecting SPPV infections and provide a theoretical basis for elucidating the mechanism of SPPV infection.

Further analysis of the miRNA-mRNA molecular regulatory network showed that miR-let-7b interacted with SMAD2, IRS2, SOCS7, CHRD, FBXO32, and TSC1. miR-let-7b has a dual role in IFN expression and signal transduction, which simultaneously targets the NS5B and 5'UTR coding sequences of the HCV genome and limits the accumulation of HCV RNA in the early stage of HCV infection [32]. Zeng et al. [33] reported that SOCS7 protein inhibits the IFN response and promotes HCV replication, suggesting that miR-let-7b is associated with SOCS7. Nevertheless, more study is needed to determine if miR-let-7b regulates HCV infection through the SOCS7 protein. miR-21 interacts with STAT3, CADM2, RBMS3, PRKCE, JAG1, and PIK3R1. The overexpression of miR-21 promotes the expression of STAT3 proteins, such as matrix metalloproteinase 2/9 (MMP-2/9), in a HPV infection and accelerates tumor invasion [34]. miR-21 promotes hepatocellular carcinoma transformation in HBV infection by targeting IL6-STAT3 [35]. Several studies showed that miR-21 plays a regulatory role in HCV, HPV, and EBV infections. Abnormal miR-21 expression is closely related to viral infection and tumorigenesis and plays a regulatory role in viral replication by targeting TGF-β1, PTEN, STAT3, and other target genes [36]. miR-10b interacts with PIK3CA, CRK, LOC443340, ITSN1, BDNF, and CREB1. The role of miR-10b in other diseases has also attracted increasing interest. Pinchas Tsukerman reported that MICB is targeted by the metastamir miR-10b and that such targeting leads to tumor escape from NK cell attack. Geekiyanage and Galanis [37] found that PVRL4 is regulated post-transcriptionally by miR-128, suggesting that miR-128 may regulate measles virus infections [38]. miRNAs play a role in viral infection or the host antiviral immune response primarily through differential base complementation with target mRNA sequences, negatively regulating the expression of the downstream target genes. Backes et al. [39] reported that vaccinia viruses exploit the miRNA pathway in cells. The present study screened for differentially expressed miRNAs and their target genes in SPPV-infected cell exosomes and analyzed their possible involvement in signaling pathways, which could contribute to the proposed anti-SPPV viral strategy.

In summary, a viral infection of host cells induces miRNA aberrant expression through multiple mechanisms to achieve immune evasion, and an excavation of the mechanisms remains to be experimentally verified. In the present study, a series of analyses of differentially expressed miRNAs in the exosomes of SPPV-infected cells were performed by bioinformatics. The target genes of differentially expressed miRNAs with high abundance were predicted and functionally annotated. The key targeting factors that might be related to miRNAs were screened out to construct a potential miRNA-mRNA regulatory network, which provides some theoretical support for refining the sheep poxvirus-infected cells and some theoretical support for refining the molecular mechanism of sheep poxvirus infections. Future studies will screen out potential target genes and the key signaling pathways closely related to SPPV infections through preliminary bioinformatics analyses to elucidate the infection mechanism of SPPV and develop small molecule drugs for sheep pox that have little side effects and significant antiviral effects.

Nevertheless, this study still had some limitations. Only the differentially expressed miRNAs, their targets, and possible signaling pathways were predicted. This study did not verify their potential mechanisms through in vivo and in vitro experiments, and the functions of differential miRNAs during viral infection were verified at the transcriptional and translational levels. Therefore, more study will be needed to determine if miRNAs affect viral replication through synergistic effects.

Some miRNAs were differentially expressed in the exosomes of SPPV-infected cells, and bioinformatics preliminarily predicted the key target molecules and signaling pathways in the process of SPPV infection, which can be used as the object of research for the subsequent experiments. In summary, these results can provide a theoretical basis for the molecular mechanism of SPPV infection and provide data support for the verification of subsequent experiments, which can help to elucidate the infection mechanism of SPPV.

Notes

The authors declare no conflict of interest.

Author’s Contributions

Conceptualization: Wang H, Gao Y, Wang L, He M; Data curation: Ma X, Zhang B; Formal analysis: Ma X; Funding acquisition: Ding J; Investigation: Ma X, Zhu Z, Chao X; Methodology: Ma X; Supervision: Wang Y; Writing–original draft: Ma X; Supervision: Wang Y; Writing–review & editing: Ding J.

Funding

This research was supported by the Xinjiang Uygur Autonomous Region Natural Science Foundation (2021D01C058).

Acknowledgments

The authors express their sincere gratitude to all the teachers and students who worked hard on this study.

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Fig. 1.

Validation of microRNA (miRNA) expression by a quantitative polymerase chain reaction (qPCR) assay. (A-E) Relative expression of miRNAs was analyzed by qPCR in sheep pox virus-infected sheep testicular cell exosomes at 0 hour, 24 hours, and 72 hours. U6 was used as an internal reference gene, and 3 independent replicates of the experiment were performed. ns, not significant. *p < 0.05, **p < 0.01,***p < 0.001.

Fig. 2.

Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. (A–C) GO analysis of the differentially expressed microRNA (miRNA) target genes; (D) KEGG analysis of differentially expressed miRNA target genes.

Fig. 3.

Target gene Reactome enrichment analysis.

Fig. 4.

Annotation of the target gene transcription factors. The top 6 transcription factors screened were SP4, NKX6-1, MEF2A, SP1, EGR1, and POU2F1.

Fig. 5.

Target gene hub gene screening. The top 10 Hub genes were PTEN, KRAS, STAT3, MTOR, C-JUN, IGF1, CCND1, MAPK8, AKT3, and CASP3.

Table 1.

Primers used in this study

Primer Sequence (5’-3’)
RT primer GCGAGCACAGAATTAATACGACTCACTATAGG(T)12VN
universal primer GCGAGCACAGAATTAATACGAC
oar-let-7f TGAGGTAGTAGATTGTATAGT
oar-let-7b TGAGGTAGTAGGTTGTGTGGT
oar-miR-221 AGCTACATTGTCTGCTGGGTTT
oar-miR-21 TAGCTTATCAGACTGATGTTGAC
oar-miR-10b ACCCTGTAGAACCGAATTTGTG
oar-miR-27a TTCACAGTGGCTAAGTTCCG
oar-miR-23a ATCACATTGCCAGGGATTTCC
oar-miR-26a TTCAAGTAATCCAGGATAGGCT
U6 Forward Primer GCTTCGGCAGCACATATACTAAAAT
U6 Reverse Primer CGCTTCACGAATTTGCGTGTCAT

‘V’ stands for A, G or C; ‘N’ stands for A, T, G or C.

Table 2.

Enrichment of target gene Reactome pathway

Pathway name Entities
Reactions
Found Ratio p-value FDR Found Ratio
RAC1 GTPase cycle 67 (191) 0.008 2.84e-05 0.036 4/6 4.24e-04
CDC42 GTPase cycle 58 (159) 0.007 3.35e-05 0.036 6/6 4.24e-04
RHO GTPase cycle 184 (557) 0.025 4.46e-05 0.036 63/91 0.006
RHOV GTPase cycle 20 (39) 0.002 2.42e-04 0.145 1/2 1.41e-04
Post-transcriptional silencing by small RNAs 7 (7) 3.11e-04 7.09e-04 0.289 3/3 2.12e-04
RHOJ GTPase cycle 25 (59) 0.003 7.34e-04 0.289 3/3 2.12e
Aberrant regulation of mitotic G1/S transition in cancer due to RB1 defects 11 (17) 7.56e-04 9.67e-04 0.289 2/2 1.14e-04
Defective binding of RB1 mutants to E2F1, (E2F2, E2F3) 11 (17) 7.56e-04 9.67e-04 0.289 1/1 7.07e-05
Anchoring fibril formation 10 (15) 6.67e-04 0.001 0.33 4/4 2.83e-04
RHOA GTPase cycle 50 (154) 0.007 0.001 0.33 4/6 4.24e-04
Collagen chain trimerization 19 (44) 0.002 0.002 0.524 15/28 0.002
Signaling by BRAF and RAF1 fusions 27 (73) 0.003 0.003 0.571 5/5 3.53e-04
RHOQ GTPase cycle 24 (63) 0.003 0.004 0.571 3/5 3.53e-04
Loss of Function of TGFBR1 in Cancer 6 (7) 3.11e-04 0.004 0.571 2/2 1.41e-04
Constitutive Signaling by Aberrant PI3K in Cancer 33 (96) 0.004 0.004 0.571 2/2 1.41e-04
RHOG GTPase cycle 28 (78) 0.003 0.004 0.575 4/6 4.24e-04
Interaction between L1 and Ankyrins 15 (33) 0.001 0.004 0.575 4/4 2.83e-04
RHOD GTPase cycle 22 (57) 0.003 0.004 0.575 4/9 6.36e-04
GRB2 events in ERBB2 signaling 11 (21) 9.34e-04 0.005 0.575 4/4 2.83e-04
RAC2 GTPase cycle 34 (98) 0.004 0.005 0.575 5/10 7.07e-04
Antigen processing: Ubiquitination &Proteasome degradation 88 (320) 0.014 0.006 0.64 9/9 6.36e-04
PI3K events in ERBB2 signaling 11 (22) 9.78e-04 0.007 0.64 7/7 4.95e-04
Signaling by PDGFRA transmembrane, juxtamembrane and kinase domain mutants 10 (19) 8.45e-04 0.007 0.64 7/7 4.95e-04
Signaling by PDGFRA extracellular domain mutants 10 (19) 8.45e-04 0.007 0.64 7/74 4.95e-04
Signaling by PDGFRA extracellular domain mutants 10 (19) 8.45e-04 0.007 0.64 4.95e-04

Table 3.

DEM-hub gene network prediction

miRNA Target genes
miR-Let-7b SMAD2 IRS2 SOCS7 CHRD FBXO32 TSC1
miR-27a GRB2 PIK3CA SHC4 SOS1 GAB1 PDPK1
miR-23a PPARGC1A PTEN UBE2D1 NCOA2 NCOA1 UBE2K
miR-221 ERBB4 PIK3R1 KIT KDR CDH2 ESR1
miR-21 STAT3 CADM2 RBMS3 PRKCE JAG1 PIK3R1
miR-26a EP300 PTEN KPNA2 KPNA6 TNRC6C PLCB1
miR-Let-7f LIN28B TRIM71 IGF2BP1 YOD1 TGFBR1 HMGA2
miR-143 MAPK7 KRAS ERBB3 FGF1 FRS2 SH3PXD2A
miR-22-3p EP300 TP53 ESR1 SIRT1 HDAC4 KDM6B
miR-29a LOC443512 COL3A1 COL11A1 COL4A1 COL5A2 COL2A1
miR-125b DAAM1 MAPRE2 ATXN1 RORA SLC25A15 BAK1
miR-199a-3p ITGA8 ITGA6 ITGA3 FN1 NID2 COL4A5
miR-25 PIK3CA PIK3CB PIK3R3 PTEN CDC42 IRS2
miR-200c C-JUN EP300 SOX2 NOTCH1 KLF4 VEGFA
miR-99a AGO2 CDYL2 MTOR TRIM71 TRIB2 BAZ2A
miR-23b CREBBP EPAS1 SMAD3 NCOA1 NCOA2 SMAD5
miR-10b PIK3CA CRK LOC443340 ITSN1 BDNF CREB1
miR-Let-7d COL4A1 COL5A2 COL3A1 COL4A6 CERCAM LOC443512
miR-181a KAT2B KMT2A KMT2C CHD1 RBBP7 ESR1
miR-26b USP9X USP3 USP25 USP15 CHFR EIF2S1
miR-148a ERBB3 PIK3CA PIK3R3 CBLB NRAS C-MET
miR-133 YES1 SYT1 CTBP2 SYT2 RIMS1 SACM1L
miR-152 ERBB3 PIK3R3 PIK3CA NRAS KIT PTEN
miR-30a-5p RAP1B ABL1 FOXG1 ELL2 SNX33 RARG
miR-103 PIK3R1 ESR1 LOC443340 MAPK8 NEDD9 KIF5C
miR-17-5p MAPK1 CCND1 KAT2B CREB1 ABL2 RUNX3
miR-10a LOC443340 PIK3CA BDNF NCOR2 UBE2I CRK

There are 27 data sets in the results because some miRNAs were not detected as key mRNAs.

miRNA, microRNA.