The Identification of MiRNA and MRNA Expression Profiles Associated with Pediatric Atypical Teratoid/rhabdoid Tumor

The Identification of MiRNA and MRNA Expression Profiles Associated with Pediatric Atypical Teratoid/rhabdoid Tumor | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Identification of MiRNA and MRNA Expression Profiles Associated with Pediatric Atypical Teratoid/rhabdoid Tumor Xinke Xu, Hongyao Yuan, Junping Pan, Wei Chen, Cheng Chen, Yang Li, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-986121/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Background: Atypical teratoid/rhabdoid tumor (AT/RT) is a malignant pediatric tumor of the central nervous system (CNS) with high recurrence and low survival rates that is often misdiagnosed. MicroRNAs (miRNAs) are involved in the tumorigenesis of numerous pediatric cancers, but their roles in AT/RT remain unclear. Methods: In this study, we used miRNA sequencing and gene expression microarrays from patient tissue to study both the miRNAome and transcriptome traits of AT/RT. Results: Our findings demonstrate that 5 miRNAs were up-regulated, 16 miRNAs were down-regulated, 179 mRNAs were up-regulated and 402 mRNAs were down-regulated in AT/RT. The expressions of hsa-miR-17-5p and MAP7 mRNA showed the most significant differences in AT/RT tissues as assayed by qPCR, and analyses using the miRTarBase database identified MAP7 mRNA as a target gene of hsa-miR-17-5p. Conclusions: Our findings suggest that the dysregulation of hsa-miR-17-5p may be a pivotal event in AT/RT and MAP7 miRNAs that may represent potential therapeutic targets and diagnostic biomarkers. Cancer Biology Atypical teratoid mRNA microRNA Expression profiles Immunocyte infiltration Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Background Atypical teratoid/rhabdoid tumor (AT/RT) is the most common malignant embryonal central nervous system (CNS) tumor in children below 12 months of age and its incidence rate decreases with age thereafter [ 1 , 2 ]. AT/RT was first identified as one of the embryo tumors that represent approximately 1–2% of pediatric intracranial tumors [ 3 ]. Because of the lack of clinical manifestation and radiography characteristics, the early clinical diagnosis of AT/RT remains challenging [ 4 ]. The treatment options for AT/RT currently include surgical resection, chemotherapy and radiotherapy [ 5 – 7 ]. However, the prognosis for pediatric patients with AT/RT is still dismal, with a median survival of 15.4 months. Studies have shown that the majority of AT/RT patients show genomic mutations in SMARCB1 (also known as INI1 ) [ 8 ]. However, the precise pathogenesis of this disease is unclear. The identification of novel therapeutics based on the specific mechanism of AT/RT carcinogenesis is therefore critical. Recent studies have shown that microRNAs (miRNAs) play a vital role in CNS tumorigenesis. MiRNAs, a subtype of small non-coding RNAs, regulate gene expression through recognizing and binding to seed sequence–matching sites in the 3' untranslated regions of target mRNAs [ 9 – 11 ]. MiRNAs are involved in the pathogenesis of human malignant tumors and function as oncogenes or tumor suppressors, depending on their downstream targets [ 12 – 14 ]. Previous studies have identified abnormal miRNA levels in patients with tumors in the CNS, indicating that miRNAs may play a key role in CNS tumor development [ 15 ]. However, knowledge of the miRNA expression profile of AT/RT patients is still limited. In this study, we analyzed miRNA expression profiles of pediatric AT/RT tumors by analyzing public datasets GSE42656 and GSE42657. Our results revealed that 5 miRNAs were significantly upregulated and 16 miRNAs were significantly downregulated in tumor tissue. Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was applied to evaluate the regulatory network for these differentially expressed miRNAs that may exert vital regulatory functions in the tumorigenesis of AT/RT. Our results suggest that abnormal miRNA expression may play key functions in the tumorigenesis in AT/RT and may represent potential targets for clinical treatment. 2. Methods 2.1 Differential expression analysis of GEO datasets AT/RT expression datasets GSE42656 ( https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE42656 ) and GSE42657 ( https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE42657 ) were processed by edgeR package in RStudio (version 3.5.0), with a significant cutoff |log2FC|>2 and P -value <0.01 [ 16 ]. The gene expression profile GSE42656 contains eight control and five AT/RT patients. The miRNA expression dataset is derived from GSE42657, which includes seven control and five tumor tissues. Detailed information for the expression profiles are listed in Table 1 . 2.2 Functional analysis Based on the differential expression analysis, we identified the related signaling pathways using Gene Ontology (GO) enrichment analysis. GO terms have three different modules: biological process (BP), molecular function (MF), and cellular component (CC). KEGG pathway analysis was then used to identify the significant pathways for dysregulated mRNAs. GO and KEGG analysis were both used in cluster profiler package in R studio [ 17 ]. The P -value was calculated for each enriched function and/or pathway. 2.3 Immunocyte infiltration annotation We used the CIBERSORT approach to identify inflammatory gene expression signatures in silico to identify the characteristics of the immune response in AT/RT. CIBERSORT is a computational framework for high-throughput characterization of immune cells [ 18 ]. 2.4 miRNA-mRNA pair analysis We used miRTarBase to predict the target genes of the differentially expressed miRNAs ( http://mirtarbase.mbc.nctu.edu.tw/ ) [ 19 ]. Differentially Expressed Genes (DEGs) were extracted and the putative miRNA-mRNA regulatory network was constructed using Cytoscape software (version 3.7.0). To validate the miRNA-mRNA network, we calculated the Pearson values and depicted the correlograms through R software. We evaluated the negative correlation between the key miRNA and target expression. 2.5 Reverse transcription quantitative Real-time PCR (RT-qPCR) We used a gene chip to analyze the gene expression profiles. cDNA fragments were purified with a PCR extraction kit (XXXX) following the manufacturer’s instruction and then enriched by RT-PCR. Total RNA was extracted using TRIzol reagent (Life Technologies, USA) and quantified using Thermo Nanodrop 2000. RNA (0.5 µg) was subjected to reverse transcription using the Script cDNA Synthesis Kit (Takara, China). miRNA and mRNA primer sequences are listed in Tables 6 and 7 . 2.6 Statistical analysis Statistical analyses were performed using t test or ANOVA followed by Bonferonni’s test, using the GraphPad 6 Prism software (San Diego, CA, USA). Data are expressed as mean ± S.E.M. P 2 and P -value < 0.01 as a threshold, we identified a total of 581 DEGs in the tumor group compared with the control group. Among the DEGs, 179 were up-regulated and 402 were down-regulated (Table 2 , Figure 1 A). In addition, 21 differentially expressed miRNAs (DEmiRNAs) were identified, including 5 up-regulated DEmiRNAs and 16 down-regulated DEmiRNAs (Table 3 , Figure 1 B–C). 3.2 GO enrichment analysis for DEGs To identify the biological characteristics and signaling pathways involved in the pathogenesis of AT/RT, we next used Clusterprofile in R package to enrich DEGs. The enrichment results of the top 20 genes from the CC, MF and BP categories are shown in Figure 2 . The results indicated that many of the DEGs are closely involved in the formation of synapses. Molecular functions analysis indicated that DEGs were involved in binding to specific molecules, such as growth factor binding, calmodulin binding, and activity of passive membrane transporters. The DEGs were also involved in several critical biological progresses including the regulation of synaptic plasticity, modulation of chemical synaptic transmission, and transportation and secretion of the neurotransmitters, which are all involved in the regulation of nervous system plasticity. 3.3 KEGG enrichment analysis for DEGs and the immune infiltration correlation of the expression profile The KEGG signaling pathway results are shown in Figure 3 . DEGs are highly involved in synaptic function and neurotransmitter transmission. The top enriched pathways include the regulation of “Synaptic vesicle cycle,” “GABAergic synapse” and “Glutamatergic synapse,” which are consistent with the results of GO enrichment, indicating that impaired synaptogenesis and synaptic dysfunction could contribute to the formation and clinical manifestation of AT/RT. DEGs were also shown to modulate the “cAMP signaling pathway,” which could affect cell differentiation. We also analyzed the correlation between the expression profile and immune infiltration pathways to identify the association between immune cell types and AT. The proportions of certain immune cells such as memory T cells, resting dendritic cells, neutrophils, and neutrophils were relatively lower in tumor tissues compared with levels in normal tissues. B cells, activated NK cells, and T follicular helper cells showed no difference between tumor tissues and normal tissues. 3.4 Construction of the AT/RT-associated miRNA-mRNA correlation and network To clarify the potential roles of significantly dysregulated miRNAs and to further explore miRNA-mRNA regulatory mechanisms in AT/RT, we identified the potential targets of DEmiRNAs and the genes that were inversely co-expressed with DEmiRNAs using the previously shown gene expression profile. The 581 DEmRNAs and 21 mature DEmiRNAs were analyzed using the miRTarBase database ( http://mirtarbase.mbc.nctu.edu.tw/ ). A total of 17 DEmiRNAs were found to negatively regulate at least one of the targets in DEmRNAs. Detailed information for each miRNA-mRNA targeting pair is shown in Table 4 . The co-expression network of DEmiRNAs and DEmRNAs was constructed and visualized using Cytoscape software; the results are shown in Figure 4 . miR-17a-5p appeared to play the central role in the DEG network; therefore, miR-17A-5p was selected for further analysis. We next examined the regulatory relationship of miR-17a-5p. The subnetworks shown in Figure 4 revealed the molecular pathways that were altered by miR-17a-5p. There were 15 mRNAs downregulated by miR-17a-5p. In addition, correlation analysis by Pearson coefficient revealed that KIF5C and DPYSL2 had the highest correlation with miR-17a-5p (Figure 4 , Table 5 ). 3.5 Validation of related miRNA expression levels in AT/RT using qRT-PCR Previous studies have shown that miRNAs play a vital role in tumor progression in AT/RT. We next evaluated the performance of the seven candidate miRNAs (hsa-miR-17-5p, has-miR-18a-5p, hsa-miR-488-5p, hsa-miR-128-3p, hsa-miR-495-3p, hsa-miR-668-3p, hsa-miR-874-3p) in diagnosing AT/RT. qPCR assays demonstrated that higher expression of miR-17-5p and miR-18a-5p in AT/RT compared with normal brain tissues (Figure 5 ). In addition, the expression of miR-874-3p was lower in AT/RT compared with levels in normal brain tissues. 3.6 Verification for related mRNA expression levels using qRT-PCR To investigate the potential function and underlying mechanism of miR-17-5p in AT/RT, we used bioinformatics algorithms and mRNA profiling from AT/RT patients to identify potential target genes of miR-17-5p. The binding of a miRNA to its target mRNA can induce translational silencing or degradation, leading to inhibition or enhancement of gene expression. Various studies have performed expression profiling to identify the roles of miRNAs in AT/RT. Our results indicated that MAP7, PRKCB, CDK1, PPP3R1, CCND1, HDAC1 and CDC20 mRNAs were differentially expressed in AT/RT (Figure 6 ). It is worth to mention that MAP7 plays an important regulatory role in AT/RT. Discussion AT/RT is an aggressive pediatric tumor of the CNS. The limited available treatments and poor prognosis of AT/RT warrants the urgent need to identify novel therapeutic targets and develop innovative treatment strategies for this disease [ 20 , 21 ]. Mutations and/or deletions of the SMARCB1 (BAF47/INI1/SNF5) gene are hallmarks of AT/RT tumors, and so far no other recurrent genetic abnormalities have been identified [ 22 ]. Previous studies showed that HMGA2, LIN28, RPL5, RPL10 and SUN2 are crucial regulators in AT/RT [ 23 , 24 ]. However, the precise molecular mechanism of AT/RT remains largely unknown. miRNAs play crucial roles in regulating gene expression at the transcriptional, post-transcriptional and epigenetic levels. Previous studies have established that miRNAs participate in a wide variety of biological processes including genomic imprinting, cell cycle, cell differentiation, invasion and migration [ 25 , 26 ]. Hsiehet et al. showed that miR-221/222 represents a promising new target in AT/RT [ 24 ]. Our multi-omics analysis identified 5 upregulated miRNAs (hsa-miR-301a-3p, hsa-miR-18a-5p, hsa-miR-335-3p, hsa-miR-18b-5p, hsa-miR-17-5p) and 16 downregulated miRNAs (hsa-miR-129-1-3p, hsa-miR-128-3p, hsa-miR-656-3p, hsa-miR-329-3p, hsa-miR-1224-5p, hsa-miR-668-3p, hsa-miR-488-5p, hsa-miR-29c-5p, etc.) in AT/RT. Hsa-miR-129-1-3p was the most-downregulated in AT/RT while hsa-miR-17-5p was the most up-regulated miRNA in AT/RT. We further found that 179 mRNAs were up-regulated and 402 mRNAs were down-regulated, which could be the result of the dysregulated miRNA networks in AT/RT, as miRNAs regulate the levels and functions of their target mRNAs. GO analyses revealed that these mRNAs are involved in critical pathways such as the regulation of synaptic plasticity, modulation of chemical synaptic transmission, neurotransmitter transportation and secretion. KEGG pathway analysis showed that “Synaptic vesicle cycle,” “GABAergic synapse” and “Glutamatergic synapse” were related to the DEGs, which is consistent with GO enrichment analysis. These findings suggest that altered synaptogenesis and synaptic dysfunction could contribute to the formation and clinical manifestation of AT/RT. Additionally, DEGs were involved in the canonical pathways such as cAMP signaling pathway, which may contribute to the stemness of the AT/RT tumor cells. Several recent studies have analyzed the influence of the host immune system on cancer prognosis [ 27 ]. We performed analyses using CIBERSORT, a computational method for high-throughput characterization of different types of immune cells in complex tissues. Our results demonstrated there was no difference in immune-related cells in AT/RT. MiRTarBase database is a database that predict targets for miRNAs [ 28 ]. Seventeen DEmiRNAs were found to have at least one negatively regulated miRNA-mRNA pair in the DEmRNAs. Notably, over 30 mRNAs were predicted to be regulated by hsa-miR-17-5p. To further probe the negative correlations between hsa-miR-17-5p and its target mRNAs, we calculated the Pearson values using R software. A total of 15 mRNAs were negatively correlated with hsa-miR-17-5p. In addition to the protein-protein interaction networks constructed between DEmiRNAs and DEmRNAs, we also further verified the expression of hsa-miR-17-5p, hsa-miR-18a-5p, hsa-miR-488-5p, hsa-miR-128-3p, hsa-miR-495-3p, hsa-miR-668-3p, and hsa-miR-874-3p using qPCR. These results further demonstrated the importance of hsa-miR-17-5p in AT/RT. Zeng et al previously reported that miRNA-17-5p expression is upregulated in glioblastoma and is a potential marker for the proneural subtype [ 29 ]. However, the mechanisms by which miRNA-17-5p expression regulates tumorigenesis are not well elucidated. We screened and identified possible targets of miRNA-17-5p and the results suggested that CCND1, THBS1, WEE1, SIRPA, SOX4, UBE2C, MDK, KIF5C, PTBP1, GPM6A, DPYSL2, PTTG1, TPRG1L, KIAA0513, SCAMP5, RAPGEF4, NRIP3, MAP7, RAB11FIP1, BTG3, MELK, TSPAN6, PEA15, PPP3R1, PGM2L1, LAMC1, IER3, GABBR1, CD47, and ABCA1 genes may play important roles in the pathogenesis of AT/RT. qPCR experiments verified that the expressions of MAP7, CDK1, PPP3R1, PRKC1, CCND1 and HDAC1 genes were indeed altered in AT/RT tumor tissue. Interestingly, CCND1 , which encodes a crucial regulator of the cell cycle [ 30 ], was upregulated in AT/RT. We hypothesize that miRNA-17-5p promotes tumorigenesis in AT/RT by promoting CCND1 expression and cell cycle entry and progression. In addition, we reported that MAP7 mRNA showed the greatest down-regulation in AT/RT among all identified mRNAs. Together, these studies point to a potential role of miR-17-5p in AT/RT tumorigenesis. Conclusion Our findings suggest that the dysregulation of hsa-miR-17-5p may be a pivotal event in AT/RT and MAP7 miRNAs that may represent potential therapeutic targets and diagnostic biomarkers. Abbreviations AT/RT: Atypical teratoid/rhabdoid tumor CNS: Central nervous system qPCR: Quantitative Real-time PCR KEEG: Kyoto Encyclopedia of Genes and Genomes GO: Gene Ontology BP: Biological process MF: Molecular function CC: Cellular component DEGs: Differentially Expressed Genes RT-qPCR: Reverse transcription quantitative Real-time PCR DEmiRNAs: Differentially expressed miRNAs Declarations Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Availability of data and materials: The authors declare are no conflicts of interest. Competing interests: The authors declare are no conflicts of interest. Funding: This research was funded by grants from the National Natural Science Foundation Committee of China (No.81572497; 81703011; 81873739; 81372713; 81672497) and the Guangdong Provincial Department of Science and Technology, China (No.2017A030313487). Authors' contributions: FCL conceived and designed the study. XKX, HYY, CC, and WC performed the experiments, analyzed the data and wrote the manuscript. YL, HYY, and PJP performed the analysis using bioinformatics. HYY and YL assisted in performing the research, and YL and PJP provided language help and assisted in analyzing data. All authors read and approved the final manuscript. Acknowledgements: Not applicable. References Biegel JA, Zhou J-Y, Rorke LB, Stenstrom C, Wainwright LM, Fogelgren B. 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Tables Table 1 Datasets for AT/RT Datasets Platform Description Controls Tumors GSE42656 GPL6947 gene 8 5 GSE42657 GPL8179 miRNA 7 5 Table 2 Top 20 DEGs Gene symbol logFC P -value dysregulated COL3A1 5.009728 2.82E-66 up CLIC6 4.963553 2.11E-11 up COL1A1 4.322956 4.55E-14 up COL1A2 4.049388 5.94E-16 up COL4A1 4.022476 1.25E-29 up CTGF 3.988644 6.66E-20 up ID3 3.752354 3.04E-36 up TOP2A 3.702338 3.67E-58 up FSTL1 3.681477 1.07E-31 up S100A4 3.647612 4.79E-14 up TF -5.80568 7.29E-58 down MBP -5.63473 1.01E-23 down PVALB -5.57699 6.54E-11 down SNAP25 -5.44596 4.61E-49 down NDRG2 -5.22185 1.61E-53 down CAMK2A -5.22113 2.86E-08 down EEF1A2 -4.98239 5.91E-41 down PLP1 -4.89204 9.96E-39 down FAIM2 -4.79694 2.94E-33 down SH3GL2 -4.65622 3.74E-23 down Table 3 DEmiRNAs miRNA logFC P- value dysregulated hsa-miR-129-1-3p -4.59055 2.23E-25 down hsa-miR-128-3p -4.46518 4.64E-22 down hsa-miR-656-3p -3.58948 5.81E-10 down hsa-miR-329-3p -3.45779 1.42E-11 down hsa-miR-1224-5p -3.22655 1.05E-07 down hsa-miR-668-3p -3.13363 3.91E-07 down hsa-miR-488-5p -3.11733 1.15E-09 down hsa-miR-29c-5p -3.0582 2.44E-10 down hsa-miR-379-5p -3.03907 1.70E-07 down hsa-miR-885-5p -2.88115 2.84E-05 down hsa-miR-433-3p -2.60679 5.77E-05 down hsa-miR-874-3p -2.4917 1.26E-07 down hsa-miR-409-5p -2.44799 5.69E-06 down hsa-miR-487b-3p -2.39918 1.40E-09 down hsa-miR-495-3p -2.20978 6.25E-06 down hsa-miR-889-3p -2.10228 9.37E-08 down hsa-miR-301a-3p 2.157525 8.66E-07 up hsa-miR-18a-5p 2.319174 3.73E-10 up hsa-miR-335-3p 2.374372 3.30E-06 up hsa-miR-18b-5p 3.442157 7.63E-10 up hsa-miR-17-5p 3.53329 7.91E-08 up Table 4 The co-expression information of DEmiRNAs and DEmRNAs DEmiRNA Targets (DEmRNAs) hsa-miR-1224-5p CAMK2N1, CLDN1 hsa-miR-128-3p WEE1, INA, UNC13C, KCNJ6, GAS7, GPR83, TSPAN6, ITPR1, TAGLN, TM4SF1, SOX11, ABCA1, TGFBR3, FAM84B, TPPP, SLC6A17, KBTBD11, GDF15 hsa-miR-129-1-3p SOX4, SCD5 hsa-miR-17-5p CCND1, THBS1, WEE1, SIRPA, SOX4, UBE2C, MDK, KIF5C, PTBP1, GPM6A, DPYSL2, PTTG1, TPRG1L, KIAA0513, SCAMP5, RAPGEF4, NRIP3, MAP7, RAB11FIP1, BTG3, MELK, TSPAN6, PEA15, PPP3R1, PGM2L1, LAMC1, IER3, GABBR1, CD47, ABCA1 hsa-miR-18a-5p IGF2BP2, CTGF, CA12, DAAM2, CDC20, RDH10, CCND1 hsa-miR-18b-5p CTGF, RDH10, CA12, CCND1 hsa-miR-301a-3p SERPINE1, NPTX1, SOX4, ATP6V1B2, RAB11FIP1, DPYSL2, MAP7 hsa-miR-329-3p TIAM1, KCNK1, CTGF, SV2B, KIF5C, MOBP, NECAB1, DAAM2, GPC4, FZD2, NDRG4, SLITRK4, CDK6, STK36, IL1RAPL1, BSN, RIMS3 hsa-miR-335-3p NECAP1, XKR4, SLC38A1 hsa-miR-379-5p MICAL2, MICAL2 hsa-miR-433-3p TYMS hsa-miR-487b-3p THBS1 hsa-miR-495-3p COL4A1 hsa-miR-656-3p PPP3R1 hsa-miR-668-3p OSBPL10, CCND1 hsa-miR-874-3p CNP, HDAC1, NRIP3, MAPT, CAMKV, PEA15 hsa-miR-889-3p SLC38A1, LOX Table 5 Correlation Analysis of Target Genes of miR-17a-5p Gene r 2 P -value KIF5C -0.8132933 0.0007215 DPYSL2 -0.7761295 0.001813395 PEA15 -0.7679643 0.002171028 SIRPA -0.7668815 0.002222304 SCAMP5 -0.7661486 0.002257544 KIAA0513 -0.7638543 0.002370676 MAP7 -0.7522732 0.003010815 CD47 -0.7433326 0.003590814 TPRG1L -0.7379651 0.003978361 RAPGEF4 -0.7284424 0.004744666 GPM6A -0.7216386 0.005358348 PPP3R1 -0.6832816 0.010037493 NRIP3 -0.6627694 0.01355686 TSPAN6 0.2707255 0.370982354 ABCA1 0.3972861 0.178873767 WEE1 0.5946464 0.032071943 BTG3 0.6999231 0.007731892 MELK 0.7468654 0.003352146 PTTG1 0.8412606 0.000312887 CCND1 0.8464124 0.0002637 MDK 0.8483379 0.000246983 UBE2C 0.8598805 0.000163567 Table 6 miRNA Primers Gene Species Sequence hsa-miR-17-5p hsa-miR-18a-5p hsa-miR-488-5p hsa-miR-128-3p hsa-miR-495-3p hsa-miR-668-3p hsa-miR-874-3p U6-F U6-R Universal-R Homo sapiens Homo sapiens Homo sapiens Homo sapiens Homo sapiens Homo sapiens Homo sapiens Homo sapiens Homo sapiens Homo sapiens CAAAGTGCTTACAGTGCAGGTAG TAAGGTGCATCTAGTGCAGATAG CCCAGATAATGGCACTCTCAA TCACAGTGAACCGGTCTCTTT AAACAAACATGGTGCACTTCTT TGTCACTCGGCTCGGCCCACTAC CTGCCCTGGCCCGAGGGACCGA CTCGCTTCGGCAGCACA AACGCTTCACGAATTTGCGT GCTGTCAACGATACGCTACG Table 7 mRNA Primers Gene Species Sequences CCND1 CCND1 CDC20 CDC20 CDK1 CDK1 PTTG1 PTTG1 PPP3R1 PPP3R1 CDCA5 CDCA5 PRKCB PRKCB HDAC1 HDAC1 MAP7 MAP7 DPYSL2 DPYSL2 CD47 CD47 GAPDH GAPDH Homo sapiens Homo sapiens Homo sapiens Homo sapiens Homo sapiens Homo sapiens Homo sapiens Homo sapiens Homo sapiens Homo sapiens Homo sapiens Homo sapiens Homo sapiens Homo sapiens Homo sapiens Homo sapiens Homo sapiens Homo sapiens Homo sapiens Homo sapiens Homo sapiens Homo sapiens Homo sapiens Homo sapiens TGAGGGACGCTTTGTCTGTC TGAGGGACGCTTTGTCTGTC AATGTGTGGCCTAGTGCTCC AGCACACATTCCAGATGCGA GGCTCTGATTGGCTGCTTTG ATGGCTACCACTTGACCTGT TAACTGGACCAACGGCAACT AGAGCTAAACAGCGGAACAGT CGGGTGTTAGGCCAGCTATT AGCTCTTGGCAGTAGCAATGA CTGAGCAGTTTGATCTCCTGGT CTCAAAGGCAGACAGTCCTCA GACCAAACACCCAGGCAAAC GATGGCGGGTGAAAAATCGG TGCTAAAGTATCACCAGAGGGT GGAGCGGGTAGTTAACAGCA TGCCAAGTGGCTGGTACTAT GGAATTGGCCTTGCATTGGT AGATCCAACTTTGCCGCTT CGTCTGCCAGTCCCTAAGT ACCTCCTAGGAATAACTGAAGTG GGGTCTCATAGGTGACAACCA AACGGATTTGGTCGTATTGGG CCTGGAAGATGGTGATGGGAT Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revision 08 Nov, 2021 Reviews received at journal 28 Oct, 2021 Reviewers agreed at journal 28 Oct, 2021 Reviewers invited by journal 28 Oct, 2021 Editor assigned by journal 25 Oct, 2021 Editor invited by journal 25 Oct, 2021 Submission checks completed at journal 25 Oct, 2021 First submitted to journal 17 Oct, 2021 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-986121","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":58837602,"identity":"947b9acc-90d3-4640-9737-1123b0ac0b83","order_by":0,"name":"Xinke Xu","email":"","orcid":"","institution":"The First Affiliated Hospital of Jinan University","correspondingAuthor":false,"prefix":"","firstName":"Xinke","middleName":"","lastName":"Xu","suffix":""},{"id":58837603,"identity":"16ac3946-49d5-4d49-b207-82a4f1b16abe","order_by":1,"name":"Hongyao Yuan","email":"","orcid":"","institution":"The First Affiliated Hospital of Jinan University","correspondingAuthor":false,"prefix":"","firstName":"Hongyao","middleName":"","lastName":"Yuan","suffix":""},{"id":58837604,"identity":"208d2f70-cd38-4579-a92f-58f7ed075bf8","order_by":2,"name":"Junping Pan","email":"","orcid":"","institution":"The First Affiliated Hospital of Jinan University","correspondingAuthor":false,"prefix":"","firstName":"Junping","middleName":"","lastName":"Pan","suffix":""},{"id":58837605,"identity":"0430e460-7aa6-4fa0-b871-940c0ccb2f82","order_by":3,"name":"Wei Chen","email":"","orcid":"","institution":"Guangzhou Women and Children's Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Chen","suffix":""},{"id":58837606,"identity":"8c406f29-61b8-444c-b425-1bb32782b18c","order_by":4,"name":"Cheng Chen","email":"","orcid":"","institution":"Guangzhou Women and Children's Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Cheng","middleName":"","lastName":"Chen","suffix":""},{"id":58837607,"identity":"65d01470-034a-4923-b7e0-5dfc3facbce4","order_by":5,"name":"Yang Li","email":"","orcid":"","institution":"Guangzhou Women and Children's Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Yang","middleName":"","lastName":"Li","suffix":""},{"id":58837608,"identity":"b88b1681-3f44-41fb-9194-ad6866626514","order_by":6,"name":"Fangcheng Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvklEQVRIie2PMQrCQBBFJwTWJmibyvUIK2klZ5mwYJqkTxkRthJrKz1EwHrSpNrgAWwCXkCwSeliZefYCe6r/+P/D+Dx/CQUwrCCuZhs6QsF15BMow7ZNS8lO8bFgpeXG5soxDQ3UACM1fmzosgmiKhLAz0FO3tlKNA3lI1UmmCPYWAYiqydgki5CCPFU4D6xg0jFIKrKLo83H29NJHAlvVFHjod3zGV8nRrh7HiDIvpbSQj75jVvJzH4/H8MU+7rz8Q9KcpKAAAAABJRU5ErkJggg==","orcid":"","institution":"The First Affiliated Hospital of Jinan University","correspondingAuthor":true,"prefix":"","firstName":"Fangcheng","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2021-10-17 13:44:04","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-986121/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-986121/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":14911106,"identity":"f3738229-9009-4ce9-8949-2ccb01154b2b","added_by":"auto","created_at":"2021-10-26 15:47:22","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1618372,"visible":true,"origin":"","legend":"Differential gene expression analysis of pediatric atypical teratoid tumors. A: Heat map depicting gene expression from 13 AT/RT cases and normal brain (columns; ordered automatically by hierarchical clustering). A gradient 'heat spectrum' appears at the right; red indicates increased expression, whereas blue denotes decreased levels. B: Heat map illustrating the expression of 50 mRNAs. C: Heat map illustrating the expression of 21 differentially expressed miRNAs (fold change\u003e 2 and P-value \u003c 0.01).","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-986121/v1/e244c0c8dcf6e3425f965fb8.png"},{"id":14911110,"identity":"a1ebd993-6f72-4b59-977a-b8399a7663bf","added_by":"auto","created_at":"2021-10-26 15:47:22","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1130520,"visible":true,"origin":"","legend":"GO enrichment analysis for DEGs in pediatric atypical teratoid tumors. A, C, E: Barplots show the top 20 enrichment terms of CC, MF, and BP, respectively. Each bar represents a term, and the length represents the number of genes enriched. B, D, F: Dotplots represent the top 20 enrichment results of CC, MF, and BP, respectively. The size of each point represents the number of genes enriched; the color represents the degree of enrichment. ","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-986121/v1/8cd8241b3c351e16b16c883d.png"},{"id":14911105,"identity":"e6076468-edf2-4fa9-8d17-4e188542e1df","added_by":"auto","created_at":"2021-10-26 15:47:22","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1131072,"visible":true,"origin":"","legend":"KEGG enrichment analysis for DEGs and the immune infiltration correlation of the expression profile in pediatric AT/RT. A: Barplot shows the top 20 enrichment results from KEGG. The length represents the number of genes enriched. B: Dotplot presents the top 20 enrichment results from KEGG. The size of each point represents the number of genes enriched. C: Bar charts summarize immune cell subset proportions against AT/RT p-value by study","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-986121/v1/a4e1ac5b434c4efc896a0362.png"},{"id":14911109,"identity":"890e9506-60fb-4ec5-83be-dacca9e910ba","added_by":"auto","created_at":"2021-10-26 15:47:22","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":699761,"visible":true,"origin":"","legend":"Correlation analysis and network of AT/RT-associated miRNA-mRNA. A: The correlation analysis of miR-17A-5p and 15 downregulated mRNAs by Pearson coefficient. B: The subnetworks revealed the molecular pathways that were altered by miR-17a-5p. C: The co-expression network of differentially expressed miRNAs and mRNAs was constructed.","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-986121/v1/f5c980cef5c16869ad377b07.png"},{"id":14911219,"identity":"abaf5067-6d53-4949-8992-14a4470bf01b","added_by":"auto","created_at":"2021-10-26 15:50:22","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":84449,"visible":true,"origin":"","legend":"The related miRNA expression level using quantitative real-time PCR in AT/RT. A–G: The relative expression levels of hsa-miR-17-5p, has-miR-18a-5p, hsa-miR-488-5p, hsa-miR-128-3p, hsa-miR-495-3p, hsa-miR-668-3p, and hsa-miR-874-3p (*P\u003c0.05, compared with control; **P\u003c0.01, compared with control; ***P\u003c0.001 compared with control).","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-986121/v1/4c67ff3749a6e6e1771b9730.png"},{"id":14911107,"identity":"ffb19e11-7601-49cb-ace5-e791790b6fc8","added_by":"auto","created_at":"2021-10-26 15:47:22","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":115096,"visible":true,"origin":"","legend":"Quantitative real-time PCR of related mRNAs in AT/RT. A–K: The relative expression levels of MAP7, PRKCB, PPP3R1, CDK1, HDAC1, PPTG1, DPYSL2, CDCA5, CD47, CCND1 and CDC20 mRNAs (*P\u003c0.05, compared with control; **P\u003c0.01, compared with control; ***P\u003c0.001 compared with control).","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-986121/v1/cd9a8e3c75b28fd14debef29.png"},{"id":14911246,"identity":"64d9fde1-f550-485c-a3fa-1b6e1dafff51","added_by":"auto","created_at":"2021-10-26 15:50:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2526733,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-986121/v1/e9a6f8b3-9b94-401a-b958-e5d64aa09517.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eThe Identification of MiRNA and MRNA Expression Profiles Associated with Pediatric Atypical Teratoid/rhabdoid Tumor\u003c/p\u003e","fulltext":[{"header":"1. Background","content":"\u003cp\u003eAtypical teratoid/rhabdoid tumor (AT/RT) is the most common malignant embryonal central nervous system (CNS) tumor in children below 12 months of age and its incidence rate decreases with age thereafter [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. AT/RT was first identified as one of the embryo tumors that represent approximately 1\u0026ndash;2% of pediatric intracranial tumors [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Because of the lack of clinical manifestation and radiography characteristics, the early clinical diagnosis of AT/RT remains challenging [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The treatment options for AT/RT currently include surgical resection, chemotherapy and radiotherapy [\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. However, the prognosis for pediatric patients with AT/RT is still dismal, with a median survival of 15.4 months. Studies have shown that the majority of AT/RT patients show genomic mutations in \u003cem\u003eSMARCB1\u003c/em\u003e (also known as \u003cem\u003eINI1\u003c/em\u003e) [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. However, the precise pathogenesis of this disease is unclear. The identification of novel therapeutics based on the specific mechanism of AT/RT carcinogenesis is therefore critical.\u003c/p\u003e \u003cp\u003eRecent studies have shown that microRNAs (miRNAs) play a vital role in CNS tumorigenesis. MiRNAs, a subtype of small non-coding RNAs, regulate gene expression through recognizing and binding to seed sequence\u0026ndash;matching sites in the 3' untranslated regions of target mRNAs [\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. MiRNAs are involved in the pathogenesis of human malignant tumors and function as oncogenes or tumor suppressors, depending on their downstream targets [\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Previous studies have identified abnormal miRNA levels in patients with tumors in the CNS, indicating that miRNAs may play a key role in CNS tumor development [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. However, knowledge of the miRNA expression profile of AT/RT patients is still limited.\u003c/p\u003e \u003cp\u003eIn this study, we analyzed miRNA expression profiles of pediatric AT/RT tumors by analyzing public datasets GSE42656 and GSE42657. Our results revealed that 5 miRNAs were significantly upregulated and 16 miRNAs were significantly downregulated in tumor tissue. Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was applied to evaluate the regulatory network for these differentially expressed miRNAs that may exert vital regulatory functions in the tumorigenesis of AT/RT. Our results suggest that abnormal miRNA expression may play key functions in the tumorigenesis in AT/RT and may represent potential targets for clinical treatment.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv class=\"Section2\" id=\"Sec3\"\u003e\n \u003ch2\u003e2.1 Differential expression analysis of GEO datasets\u003c/h2\u003e\n \u003cp\u003eAT/RT expression datasets GSE42656 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE42656\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"Underline\" name=\"Emphasis\" type=\"Underline\"\u003e)\u003c/span\u003e and GSE42657 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE42657\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"Underline\" name=\"Emphasis\" type=\"Underline\"\u003e)\u003c/span\u003e were processed by edgeR package in RStudio (version 3.5.0), with a significant cutoff |log2FC|\u0026gt;2 and \u003cem\u003eP\u003c/em\u003e-value \u0026lt;0.01 [\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e]. The gene expression profile GSE42656 contains eight control and five AT/RT patients. The miRNA expression dataset is derived from GSE42657, which includes seven control and five tumor tissues. Detailed information for the expression profiles are listed in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n \u003cdiv class=\"Section2\" id=\"Sec4\"\u003e\n \u003ch2\u003e2.2 Functional analysis\u003c/h2\u003e\n \u003cp\u003eBased on the differential expression analysis, we identified the related signaling pathways using Gene Ontology (GO) enrichment analysis. GO terms have three different modules: biological process (BP), molecular function (MF), and cellular component (CC). KEGG pathway analysis was then used to identify the significant pathways for dysregulated mRNAs. GO and KEGG analysis were both used in cluster profiler package in R studio [\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e]. The \u003cem\u003eP\u003c/em\u003e-value was calculated for each enriched function and/or pathway.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv class=\"Section2\" id=\"Sec5\"\u003e\n \u003ch2\u003e2.3 Immunocyte infiltration annotation\u003c/h2\u003e\n \u003cp\u003eWe used the CIBERSORT approach to identify inflammatory gene expression signatures in silico to identify the characteristics of the immune response in AT/RT. CIBERSORT is a computational framework for high-throughput characterization of immune cells [\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv class=\"Section2\" id=\"Sec6\"\u003e\n \u003ch2\u003e2.4 miRNA-mRNA pair analysis\u003c/h2\u003e\n \u003cp\u003eWe used miRTarBase to predict the target genes of the differentially expressed miRNAs (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://mirtarbase.mbc.nctu.edu.tw/\u003c/span\u003e\u003c/span\u003e) [\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e]. Differentially Expressed Genes (DEGs) were extracted and the putative miRNA-mRNA regulatory network was constructed using Cytoscape software (version 3.7.0). To validate the miRNA-mRNA network, we calculated the Pearson values and depicted the correlograms through R software. We evaluated the negative correlation between the key miRNA and target expression.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv class=\"Section2\" id=\"Sec7\"\u003e\n \u003ch2\u003e2.5 Reverse\u0026ensp;transcription quantitative Real-time PCR (RT-qPCR)\u003c/h2\u003e\n \u003cp\u003eWe used a gene chip to analyze the gene expression profiles. cDNA fragments were purified with a PCR extraction kit (XXXX) following the manufacturer\u0026rsquo;s instruction and then enriched by RT-PCR. Total RNA was extracted using TRIzol reagent (Life Technologies, USA) and quantified using Thermo Nanodrop 2000. RNA (0.5 \u0026micro;g) was subjected to reverse transcription using the Script cDNA Synthesis Kit (Takara, China). miRNA and mRNA primer sequences are listed in Tables \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv class=\"Section2\" id=\"Sec8\"\u003e\n \u003ch2\u003e2.6 Statistical analysis\u003c/h2\u003e\n \u003cp\u003eStatistical analyses were performed using t test or ANOVA followed by Bonferonni\u0026rsquo;s test, using the GraphPad 6 Prism software (San Diego, CA, USA). Data are expressed as mean \u0026plusmn; S.E.M. \u003cem\u003eP\u003c/em\u003e\u0026lt;0.05 was considered statistically significant.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv class=\"Section2\" id=\"Sec10\"\u003e\n \u003ch2\u003e3.1 Differential expression profiles for pediatric AT/RT\u003c/h2\u003e\n \u003cp\u003eUsing |fold change|\u0026gt; 2 and \u003cem\u003eP\u003c/em\u003e-value \u0026lt; 0.01 as a threshold, we identified a total of 581 DEGs in the tumor group compared with the control group. Among the DEGs, 179 were up-regulated and 402 were down-regulated (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, Figure \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eA). In addition, 21 differentially expressed miRNAs (DEmiRNAs) were identified, including 5 up-regulated DEmiRNAs and 16 down-regulated DEmiRNAs (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, Figure \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eB\u0026ndash;C).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec11\"\u003e\n \u003ch2\u003e3.2 GO enrichment analysis for DEGs\u003c/h2\u003e\n \u003cp\u003eTo identify the biological characteristics and signaling pathways involved in the pathogenesis of AT/RT, we next used Clusterprofile in R package to enrich DEGs. The enrichment results of the top 20 genes from the CC, MF and BP categories are shown in Figure \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. The results indicated that many of the DEGs are closely involved in the formation of synapses. Molecular functions analysis indicated that DEGs were involved in binding to specific molecules, such as growth factor binding, calmodulin binding, and activity of passive membrane transporters. The DEGs were also involved in several critical biological progresses including the regulation of synaptic plasticity, modulation of chemical synaptic transmission, and transportation and secretion of the neurotransmitters, which are all involved in the regulation of nervous system plasticity.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec12\"\u003e\n \u003ch2\u003e3.3 KEGG enrichment analysis for DEGs and the immune infiltration correlation of the expression profile\u003c/h2\u003e\n \u003cp\u003eThe KEGG signaling pathway results are shown in Figure \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e. DEGs are highly involved in synaptic function and neurotransmitter transmission. The top enriched pathways include the regulation of \u0026ldquo;Synaptic vesicle cycle,\u0026rdquo; \u0026ldquo;GABAergic synapse\u0026rdquo; and \u0026ldquo;Glutamatergic synapse,\u0026rdquo; which are consistent with the results of GO enrichment, indicating that impaired synaptogenesis and synaptic dysfunction could contribute to the formation and clinical manifestation of AT/RT. DEGs were also shown to modulate the \u0026ldquo;cAMP signaling pathway,\u0026rdquo; which could affect cell differentiation.\u003c/p\u003e\n \u003cp\u003eWe also analyzed the correlation between the expression profile and immune infiltration pathways to identify the association between immune cell types and AT. The proportions of certain immune cells such as memory T cells, resting dendritic cells, neutrophils, and neutrophils were relatively lower in tumor tissues compared with levels in normal tissues. B cells, activated NK cells, and T follicular helper cells showed no difference between tumor tissues and normal tissues.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec13\"\u003e\n \u003ch2\u003e3.4 Construction of the AT/RT-associated miRNA-mRNA correlation and network\u003c/h2\u003e\n \u003cp\u003eTo clarify the potential roles of significantly dysregulated miRNAs and to further explore miRNA-mRNA regulatory mechanisms in AT/RT, we identified the potential targets of DEmiRNAs and the genes that were inversely co-expressed with DEmiRNAs using the previously shown gene expression profile. The 581 DEmRNAs and 21 mature DEmiRNAs were analyzed using the miRTarBase database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://mirtarbase.mbc.nctu.edu.tw/\u003c/span\u003e\u003c/span\u003e). A total of 17 DEmiRNAs were found to negatively regulate at least one of the targets in DEmRNAs. Detailed information for each miRNA-mRNA targeting pair is shown in Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e. The co-expression network of DEmiRNAs and DEmRNAs was constructed and visualized using Cytoscape software; the results are shown in Figure \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e. miR-17a-5p appeared to play the central role in the DEG network; therefore, miR-17A-5p was selected for further analysis.\u003c/p\u003e\n \u003cp\u003eWe next examined the regulatory relationship of miR-17a-5p. The subnetworks shown in Figure \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e revealed the molecular pathways that were altered by miR-17a-5p. There were 15 mRNAs downregulated by miR-17a-5p. In addition, correlation analysis by Pearson coefficient revealed that KIF5C and DPYSL2 had the highest correlation with miR-17a-5p (Figure \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e, Table \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec14\"\u003e\n \u003ch2\u003e3.5 Validation of related miRNA expression levels in AT/RT using qRT-PCR\u003c/h2\u003e\n \u003cp\u003ePrevious studies have shown that miRNAs play a vital role in tumor progression in AT/RT. We next evaluated the performance of the seven candidate miRNAs (hsa-miR-17-5p, has-miR-18a-5p, hsa-miR-488-5p, hsa-miR-128-3p, hsa-miR-495-3p, hsa-miR-668-3p, hsa-miR-874-3p) in diagnosing AT/RT. qPCR assays demonstrated that higher expression of miR-17-5p and miR-18a-5p in AT/RT compared with normal brain tissues (Figure \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e). In addition, the expression of miR-874-3p was lower in AT/RT compared with levels in normal brain tissues.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec15\"\u003e\n \u003ch2\u003e3.6 Verification for related mRNA expression levels using qRT-PCR\u003c/h2\u003e\n \u003cp\u003eTo investigate the potential function and underlying mechanism of miR-17-5p in AT/RT, we used bioinformatics algorithms and mRNA profiling from AT/RT patients to identify potential target genes of miR-17-5p. The binding of a miRNA to its target mRNA can induce translational silencing or degradation, leading to inhibition or enhancement of gene expression. Various studies have performed expression profiling to identify the roles of miRNAs in AT/RT. Our results indicated that MAP7, PRKCB, CDK1, PPP3R1, CCND1, HDAC1 and CDC20 mRNAs were differentially expressed in AT/RT (Figure \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e). It is worth to mention that MAP7 plays an important regulatory role in AT/RT.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eAT/RT is an aggressive pediatric tumor of the CNS. The limited available treatments and poor prognosis of AT/RT warrants the urgent need to identify novel therapeutic targets and develop innovative treatment strategies for this disease\u0026nbsp;[\u003ca href=\"#_ENREF_20\" title=\"Eaton, 2011 #278\"\u003e20\u003c/a\u003e,\u0026nbsp;\u003ca href=\"#_ENREF_21\" title=\"Gump, 2015 #279\"\u003e21\u003c/a\u003e]. Mutations and/or deletions of the\u003cem\u003e\u0026nbsp;SMARCB1\u003c/em\u003e (BAF47/INI1/SNF5) gene are hallmarks of AT/RT tumors, and so far no other recurrent genetic abnormalities have been identified\u0026nbsp;[\u003ca href=\"#_ENREF_22\" title=\"Weingart, 2015 #280\"\u003e22\u003c/a\u003e]. Previous studies showed that HMGA2, LIN28, RPL5, RPL10 and SUN2 are crucial regulators in AT/RT\u0026nbsp;[\u003ca href=\"#_ENREF_23\" title=\"Ren, 2018 #281\"\u003e23\u003c/a\u003e,\u0026nbsp;\u003ca href=\"#_ENREF_24\" title=\"Hsieh, 2014 #282\"\u003e24\u003c/a\u003e]. However, the precise molecular mechanism of AT/RT remains largely unknown.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003emiRNAs play crucial roles in regulating gene expression at the transcriptional, post-transcriptional and epigenetic levels. Previous studies have established that miRNAs participate in a wide variety of biological processes including genomic imprinting, cell cycle, cell differentiation, invasion and migration\u0026nbsp;[\u003ca href=\"#_ENREF_25\" title=\"Sato, 2011 #284\"\u003e25\u003c/a\u003e,\u0026nbsp;\u003ca href=\"#_ENREF_26\" title=\"Kanwal, 2012 #285\"\u003e26\u003c/a\u003e]. Hsiehet et al. showed that miR-221/222 represents a promising new target in AT/RT\u0026nbsp;[\u003ca href=\"#_ENREF_24\" title=\"Hsieh, 2014 #282\"\u003e24\u003c/a\u003e]. Our multi-omics analysis identified 5 upregulated miRNAs (hsa-miR-301a-3p, hsa-miR-18a-5p, hsa-miR-335-3p, hsa-miR-18b-5p, hsa-miR-17-5p) and 16 downregulated miRNAs (hsa-miR-129-1-3p, hsa-miR-128-3p, hsa-miR-656-3p, hsa-miR-329-3p, hsa-miR-1224-5p, hsa-miR-668-3p, hsa-miR-488-5p, hsa-miR-29c-5p, etc.) in AT/RT. Hsa-miR-129-1-3p was the most-downregulated in AT/RT while hsa-miR-17-5p was the most up-regulated miRNA in AT/RT.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe further found that 179 mRNAs were up-regulated and 402 mRNAs were down-regulated, which could be the result of the dysregulated miRNA networks in AT/RT, as miRNAs regulate the levels and functions of their target mRNAs. GO analyses revealed that these mRNAs are involved in critical pathways such as the regulation of synaptic plasticity, modulation of chemical synaptic transmission, neurotransmitter transportation and secretion. KEGG pathway analysis showed that \u0026ldquo;Synaptic vesicle cycle,\u0026rdquo; \u0026ldquo;GABAergic synapse\u0026rdquo; and \u0026ldquo;Glutamatergic synapse\u0026rdquo; were related to the DEGs, which is consistent with GO enrichment analysis. These findings suggest that altered synaptogenesis and synaptic dysfunction could contribute to the formation and clinical manifestation of AT/RT. Additionally, DEGs were involved in the canonical pathways such as cAMP signaling pathway, which may contribute to the stemness of the AT/RT tumor cells.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSeveral recent studies have analyzed the influence of the host immune system on cancer prognosis\u0026nbsp;[\u003ca href=\"#_ENREF_27\" title=\"Schmidt, 2008 #286\"\u003e27\u003c/a\u003e]. We performed analyses using CIBERSORT, a computational method for high-throughput characterization of different types of immune cells in complex tissues. Our results demonstrated there was no difference in immune-related cells in AT/RT.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMiRTarBase database is a database that predict targets for miRNAs\u0026nbsp;[\u003ca href=\"#_ENREF_28\" title=\"Chou, 2015 #287\"\u003e28\u003c/a\u003e]. Seventeen DEmiRNAs were found to have at least one negatively regulated miRNA-mRNA pair in the DEmRNAs. Notably, over 30 mRNAs were predicted to be regulated by hsa-miR-17-5p. To further probe the negative correlations between hsa-miR-17-5p and its target mRNAs, we calculated the Pearson values using R software. A total of 15 mRNAs were negatively correlated with hsa-miR-17-5p. In addition to the protein-protein interaction networks constructed between DEmiRNAs and DEmRNAs, we also further verified the expression of hsa-miR-17-5p, hsa-miR-18a-5p, hsa-miR-488-5p, hsa-miR-128-3p, hsa-miR-495-3p, hsa-miR-668-3p, and hsa-miR-874-3p using qPCR. These results further demonstrated the importance of hsa-miR-17-5p in AT/RT.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eZeng et al previously reported that miRNA-17-5p expression is upregulated in glioblastoma and is a potential marker for the proneural subtype\u0026nbsp;[\u003ca href=\"#_ENREF_29\" title=\"Zeng, 2018 #288\"\u003e29\u003c/a\u003e]. However, the mechanisms by which miRNA-17-5p expression regulates tumorigenesis are not well elucidated. We screened and identified possible targets of miRNA-17-5p and the results suggested that CCND1, THBS1, WEE1, SIRPA, SOX4, UBE2C, MDK, KIF5C, PTBP1, GPM6A, DPYSL2, PTTG1, TPRG1L, KIAA0513, SCAMP5, RAPGEF4, NRIP3, MAP7, RAB11FIP1, BTG3, MELK, TSPAN6, PEA15, PPP3R1, PGM2L1, LAMC1, IER3, GABBR1, CD47, and ABCA1 genes may play important roles in the pathogenesis of AT/RT. qPCR experiments verified that the expressions of MAP7, CDK1, PPP3R1, PRKC1, CCND1 and HDAC1 genes were indeed altered in AT/RT tumor tissue. Interestingly, \u003cem\u003eCCND1\u003c/em\u003e, which encodes a crucial regulator of the cell cycle\u0026nbsp;[\u003ca href=\"#_ENREF_30\" title=\"Gennaro, 2018 #289\"\u003e30\u003c/a\u003e], was upregulated in AT/RT. We hypothesize that miRNA-17-5p promotes tumorigenesis in AT/RT by promoting \u003cem\u003eCCND1\u003c/em\u003e expression and cell cycle entry and progression. In addition, we reported that MAP7 mRNA showed the greatest down-regulation in AT/RT among all identified mRNAs. Together, these studies point to a potential role of miR-17-5p in AT/RT tumorigenesis.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur findings suggest that the dysregulation of hsa-miR-17-5p may be a pivotal event in AT/RT and MAP7 miRNAs that may represent potential therapeutic targets and diagnostic biomarkers.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAT/RT: Atypical teratoid/rhabdoid tumor\u003c/p\u003e\n\u003cp\u003eCNS: Central nervous system\u003c/p\u003e\n\u003cp\u003eqPCR: Quantitative Real-time PCR\u003c/p\u003e\n\u003cp\u003eKEEG: Kyoto Encyclopedia of Genes and Genomes\u003c/p\u003e\n\u003cp\u003eGO: Gene Ontology\u003c/p\u003e\n\u003cp\u003eBP: Biological process\u003c/p\u003e\n\u003cp\u003eMF: Molecular function\u003c/p\u003e\n\u003cp\u003eCC: Cellular component\u003c/p\u003e\n\u003cp\u003eDEGs:\u0026nbsp;Differentially Expressed Genes\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRT-qPCR: Reverse\u0026ensp;transcription\u0026nbsp;quantitative Real-time PCR\u003c/p\u003e\n\u003cp\u003eDEmiRNAs: Differentially expressed miRNAs\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate:\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eConsent for publication:\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eAvailability of data and materials:\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThe authors declare are no conflicts of interest.\u003c/p\u003e\n\u003ch2\u003eCompeting interests:\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThe authors declare are no conflicts of interest.\u003c/p\u003e\n\u003ch2\u003eFunding:\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThis research was funded by grants from the National Natural Science Foundation Committee of China (No.81572497; 81703011; 81873739; 81372713; 81672497) and the Guangdong Provincial Department of Science and Technology, China (No.2017A030313487).\u003c/p\u003e\n\u003ch2\u003eAuthors\u0026apos; contributions:\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eFCL conceived and designed the study. XKX, HYY, CC, and WC performed the experiments, analyzed the data and wrote the manuscript. YL, HYY, and PJP performed the analysis using bioinformatics. HYY and YL assisted in performing the research, and YL and PJP provided language help and assisted in analyzing data. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements:\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBiegel JA, Zhou J-Y, Rorke LB, Stenstrom C, Wainwright LM, Fogelgren B. Germ-line and acquired mutations of INI1 in atypical teratoid and rhabdoid tumors. Cancer research. 1999;59:74\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBiswas A, Kashyap L, Kakkar A, Sarkar C, Julka PK. Atypical teratoid/rhabdoid tumors: challenges and search for solutions. 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Omics: a journal of integrative biology. 2012;16:284\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNewman AM, Liu CL, Green MR, Gentles AJ, Feng W, Xu Y, et al. Robust enumeration of cell subsets from tissue expression profiles. Nature methods. 2015;12:453.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHsu S-D, Lin F-M, Wu W-Y, Liang C, Huang W-C, Chan W-L, et al. miRTarBase: a database curates experimentally validated microRNA\u0026ndash;target interactions. Nucleic acids research. 2010;39:D163-D9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEaton KW, Tooke LS, Wainwright LM, Judkins AR, Biegel JA. Spectrum of SMARCB1/INI1 mutations in familial and sporadic rhabdoid tumors. Pediatric blood \u0026amp; cancer. 2011;56:7\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGump JM, Donson AM, Birks DK, Amani VM, Rao KK, Griesinger AM, et al. Identification of targets for rational pharmacological therapy in childhood craniopharyngioma. Acta neuropathologica communications. 2015;3:30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWeingart MF, Roth JJ, Hutt-Cabezas M, Busse TM, Kaur H, Price A, et al. Disrupting LIN28 in atypical teratoid rhabdoid tumors reveals the importance of the mitogen activated protein kinase pathway as a therapeutic target. Oncotarget. 2015;6:3165.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRen Y, Tao C, Wang X, Ju Y. Identification of RPL5 and RPL10 as novel diagnostic biomarkers of Atypical teratoid/rhabdoid tumors. Cancer cell international. 2018;18:190.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHsieh T-H, Chien C-L, Lee Y-H, Lin C-I, Hsieh J-Y, Chao M-E, et al. Downregulation of SUN2, a novel tumor suppressor, mediates miR-221/222-induced malignancy in central nervous system embryonal tumors. Carcinogenesis. 2014;35:2164\u0026ndash;74.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSato F, Tsuchiya S, Meltzer SJ, Shimizu K. MicroRNAs and epigenetics. The FEBS journal. 2011;278:1598\u0026ndash;609.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKanwal R, Gupta S. Epigenetic modifications in cancer. Clinical genetics. 2012;81:303\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchmidt M, B\u0026ouml;hm D, Von T\u0026ouml;rne C, Steiner E, Puhl A, Pilch H, et al. The humoral immune system has a key prognostic impact in node-negative breast cancer. Cancer research. 2008;68:5405\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChou C-H, Chang N-W, Shrestha S, Hsu S-D, Lin Y-L, Lee W-H, et al. miRTarBase 2016: updates to the experimentally validated miRNA-target interactions database. Nucleic acids research. 2015;44:D239-D47.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZeng A, Yin J, Wang Z, Zhang C, Li R, Zhang Z, et al. miR-17-5p-CXCL14 axis related transcriptome profile and clinical outcome in diffuse gliomas. Oncoimmunology. 2018;7:e1510277.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGennaro VJ, Stanek TJ, Peck AR, Sun Y, Wang F, Qie S, et al. Control of CCND1 ubiquitylation by the catalytic SAGA subunit USP22 is essential for cell cycle progression through G1 in cancer cells. Proceedings of the National Academy of Sciences. 2018;115:E9298-E307.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDatasets for AT/RT\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDatasets\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePlatform\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDescription\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eControls\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTumors\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGSE42656\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGPL6947\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003egene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGSE42657\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGPL8179\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emiRNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cdiv class=\"gridtable\" style='color: rgb(0, 0, 0); font-family: \"Times New Roman\"; font-size: medium; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; text-decoration-style: initial; text-decoration-color: initial;'\u003e\n \u003ctable border=\"1\" style=\"border: none; border-collapse: collapse; empty-cells: show; max-width: 100%;\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003eTop 20 DEGs\u003c/strong\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003cth align=\"left\" style=\"border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eGene symbol\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003elogFC\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003edysregulated\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cem\u003eCOL3A1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e5.009728\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e2.82E-66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eup\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cem\u003eCLIC6\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e4.963553\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e2.11E-11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eup\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cem\u003eCOL1A1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e4.322956\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e4.55E-14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eup\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cem\u003eCOL1A2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e4.049388\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e5.94E-16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eup\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cem\u003eCOL4A1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e4.022476\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e1.25E-29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eup\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cem\u003eCTGF\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e3.988644\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e6.66E-20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eup\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cem\u003eID3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e3.752354\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e3.04E-36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eup\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cem\u003eTOP2A\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e3.702338\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e3.67E-58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eup\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cem\u003eFSTL1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e3.681477\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e1.07E-31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eup\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cem\u003eS100A4\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e3.647612\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e4.79E-14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eup\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cem\u003eTF\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e-5.80568\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e7.29E-58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cem\u003eMBP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e-5.63473\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e1.01E-23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cem\u003ePVALB\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e-5.57699\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e6.54E-11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cem\u003eSNAP25\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e-5.44596\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e4.61E-49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cem\u003eNDRG2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e-5.22185\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e1.61E-53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cem\u003eCAMK2A\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e-5.22113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e2.86E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cem\u003eEEF1A2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e-4.98239\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e5.91E-41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cem\u003ePLP1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e-4.89204\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e9.96E-39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cem\u003eFAIM2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e-4.79694\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e2.94E-33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cem\u003eSH3GL2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e-4.65622\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e3.74E-23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp style='margin-bottom: 10px !important; color: rgb(0, 0, 0); font-family: \"Times New Roman\"; font-size: medium; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; text-decoration-style: initial; text-decoration-color: initial;'\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cdiv class=\"gridtable\" style='color: rgb(0, 0, 0); font-family: \"Times New Roman\"; font-size: medium; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; text-decoration-style: initial; text-decoration-color: initial;'\u003e\n \u003ctable border=\"1\" style=\"border: none; border-collapse: collapse; empty-cells: show; max-width: 100%;\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eDEmiRNAs\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003cth align=\"left\" style=\"border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003emiRNA\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003elogFC\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cem\u003eP-\u003c/em\u003evalue\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003edysregulated\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003ehsa-miR-129-1-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e-4.59055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e2.23E-25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003ehsa-miR-128-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e-4.46518\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e4.64E-22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003ehsa-miR-656-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e-3.58948\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e5.81E-10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003ehsa-miR-329-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e-3.45779\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e1.42E-11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003ehsa-miR-1224-5p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e-3.22655\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e1.05E-07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003ehsa-miR-668-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e-3.13363\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e3.91E-07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003ehsa-miR-488-5p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e-3.11733\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e1.15E-09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003ehsa-miR-29c-5p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e-3.0582\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e2.44E-10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003ehsa-miR-379-5p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e-3.03907\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e1.70E-07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003ehsa-miR-885-5p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e-2.88115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e2.84E-05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003ehsa-miR-433-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e-2.60679\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e5.77E-05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003ehsa-miR-874-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e-2.4917\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e1.26E-07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003ehsa-miR-409-5p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e-2.44799\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e5.69E-06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003ehsa-miR-487b-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e-2.39918\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e1.40E-09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003ehsa-miR-495-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e-2.20978\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e6.25E-06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003ehsa-miR-889-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e-2.10228\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e9.37E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003ehsa-miR-301a-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e2.157525\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e8.66E-07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eup\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003ehsa-miR-18a-5p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e2.319174\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e3.73E-10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eup\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003ehsa-miR-335-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e2.374372\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e3.30E-06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eup\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003ehsa-miR-18b-5p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e3.442157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e7.63E-10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eup\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003ehsa-miR-17-5p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e3.53329\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e7.91E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eup\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec4\"\u003e\n \u003ch2\u003e\u003cbr\u003e\u003c/h2\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThe co-expression information of DEmiRNAs and DEmRNAs\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDEmiRNA\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTargets (DEmRNAs)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ehsa-miR-1224-5p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCAMK2N1, CLDN1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ehsa-miR-128-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWEE1, INA, UNC13C, KCNJ6, GAS7, GPR83, TSPAN6, ITPR1, TAGLN, TM4SF1, SOX11, ABCA1, TGFBR3, FAM84B, TPPP, SLC6A17, KBTBD11, GDF15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ehsa-miR-129-1-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSOX4, SCD5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ehsa-miR-17-5p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCCND1, THBS1, WEE1, SIRPA, SOX4, UBE2C, MDK, KIF5C, PTBP1, GPM6A, DPYSL2, PTTG1, TPRG1L, KIAA0513, SCAMP5, RAPGEF4, NRIP3, MAP7, RAB11FIP1, BTG3, MELK, TSPAN6, PEA15, PPP3R1, PGM2L1, LAMC1, IER3, GABBR1, CD47, ABCA1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ehsa-miR-18a-5p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIGF2BP2, CTGF, CA12, DAAM2, CDC20, RDH10, CCND1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ehsa-miR-18b-5p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCTGF, RDH10, CA12, CCND1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ehsa-miR-301a-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSERPINE1, NPTX1, SOX4, ATP6V1B2, RAB11FIP1, DPYSL2, MAP7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ehsa-miR-329-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTIAM1, KCNK1, CTGF, SV2B, KIF5C, MOBP, NECAB1, DAAM2, GPC4, FZD2, NDRG4, SLITRK4, CDK6, STK36, IL1RAPL1, BSN, RIMS3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ehsa-miR-335-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNECAP1, XKR4, SLC38A1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ehsa-miR-379-5p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMICAL2, MICAL2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ehsa-miR-433-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTYMS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ehsa-miR-487b-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTHBS1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ehsa-miR-495-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCOL4A1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ehsa-miR-656-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePPP3R1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ehsa-miR-668-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOSBPL10, CCND1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ehsa-miR-874-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCNP, HDAC1, NRIP3, MAPT, CAMKV, PEA15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ehsa-miR-889-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSLC38A1, LOX\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec7\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003ctable border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCorrelation Analysis of Target Genes of miR-17a-5p\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGene\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003er\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eKIF5C\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.8132933\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0007215\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eDPYSL2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.7761295\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.001813395\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePEA15\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.7679643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.002171028\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eSIRPA\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.7668815\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.002222304\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eSCAMP5\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.7661486\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.002257544\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eKIAA0513\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.7638543\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.002370676\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eMAP7\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.7522732\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.003010815\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eCD47\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.7433326\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.003590814\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eTPRG1L\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.7379651\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.003978361\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eRAPGEF4\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.7284424\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.004744666\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eGPM6A\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.7216386\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.005358348\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePPP3R1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.6832816\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.010037493\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eNRIP3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.6627694\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01355686\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eTSPAN6\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.2707255\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.370982354\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eABCA1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.3972861\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.178873767\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eWEE1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.5946464\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.032071943\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eBTG3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.6999231\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.007731892\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eMELK\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.7468654\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.003352146\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePTTG1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.8412606\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.000312887\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eCCND1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.8464124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0002637\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eMDK\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.8483379\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.000246983\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eUBE2C\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.8598805\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.000163567\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab2\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003emiRNA Primers\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGene\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSpecies\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSequence\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ehsa-miR-17-5p\u003c/p\u003e\n \u003cp\u003ehsa-miR-18a-5p\u003c/p\u003e\n \u003cp\u003ehsa-miR-488-5p\u003c/p\u003e\n \u003cp\u003ehsa-miR-128-3p\u003c/p\u003e\n \u003cp\u003ehsa-miR-495-3p\u003c/p\u003e\n \u003cp\u003ehsa-miR-668-3p\u003c/p\u003e\n \u003cp\u003ehsa-miR-874-3p\u003c/p\u003e\n \u003cp\u003eU6-F\u003c/p\u003e\n \u003cp\u003eU6-R\u003c/p\u003e\n \u003cp\u003eUniversal-R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCAAAGTGCTTACAGTGCAGGTAG\u003c/p\u003e\n \u003cp\u003eTAAGGTGCATCTAGTGCAGATAG\u003c/p\u003e\n \u003cp\u003eCCCAGATAATGGCACTCTCAA\u003c/p\u003e\n \u003cp\u003eTCACAGTGAACCGGTCTCTTT\u003c/p\u003e\n \u003cp\u003eAAACAAACATGGTGCACTTCTT\u003c/p\u003e\n \u003cp\u003eTGTCACTCGGCTCGGCCCACTAC\u003c/p\u003e\n \u003cp\u003eCTGCCCTGGCCCGAGGGACCGA\u003c/p\u003e\n \u003cp\u003eCTCGCTTCGGCAGCACA\u003c/p\u003e\n \u003cp\u003eAACGCTTCACGAATTTGCGT\u003c/p\u003e\n \u003cp\u003eGCTGTCAACGATACGCTACG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003ctable border=\"1\" id=\"Tab3\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003emRNA Primers\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGene\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSpecies\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSequences\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eCCND1\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eCCND1\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eCDC20\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eCDC20\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eCDK1\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eCDK1\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003ePTTG1\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003ePTTG1\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003ePPP3R1\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003ePPP3R1\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eCDCA5\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eCDCA5\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003ePRKCB\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003ePRKCB\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eHDAC1\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eHDAC1\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eMAP7\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eMAP7\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eDPYSL2\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eDPYSL2\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eCD47\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eCD47\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eGAPDH\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eGAPDH\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eHomo sapiens\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTGAGGGACGCTTTGTCTGTC\u003c/p\u003e\n \u003cp\u003eTGAGGGACGCTTTGTCTGTC\u003c/p\u003e\n \u003cp\u003eAATGTGTGGCCTAGTGCTCC\u003c/p\u003e\n \u003cp\u003eAGCACACATTCCAGATGCGA\u003c/p\u003e\n \u003cp\u003eGGCTCTGATTGGCTGCTTTG\u003c/p\u003e\n \u003cp\u003eATGGCTACCACTTGACCTGT\u003c/p\u003e\n \u003cp\u003eTAACTGGACCAACGGCAACT\u003c/p\u003e\n \u003cp\u003eAGAGCTAAACAGCGGAACAGT\u003c/p\u003e\n \u003cp\u003eCGGGTGTTAGGCCAGCTATT\u003c/p\u003e\n \u003cp\u003eAGCTCTTGGCAGTAGCAATGA\u003c/p\u003e\n \u003cp\u003eCTGAGCAGTTTGATCTCCTGGT\u003c/p\u003e\n \u003cp\u003eCTCAAAGGCAGACAGTCCTCA\u003c/p\u003e\n \u003cp\u003eGACCAAACACCCAGGCAAAC\u003c/p\u003e\n \u003cp\u003eGATGGCGGGTGAAAAATCGG\u003c/p\u003e\n \u003cp\u003eTGCTAAAGTATCACCAGAGGGT\u003c/p\u003e\n \u003cp\u003eGGAGCGGGTAGTTAACAGCA\u003c/p\u003e\n \u003cp\u003eTGCCAAGTGGCTGGTACTAT\u003c/p\u003e\n \u003cp\u003eGGAATTGGCCTTGCATTGGT\u003c/p\u003e\n \u003cp\u003eAGATCCAACTTTGCCGCTT\u003c/p\u003e\n \u003cp\u003eCGTCTGCCAGTCCCTAAGT\u003c/p\u003e\n \u003cp\u003eACCTCCTAGGAATAACTGAAGTG\u003c/p\u003e\n \u003cp\u003eGGGTCTCATAGGTGACAACCA\u003c/p\u003e\n \u003cp\u003eAACGGATTTGGTCGTATTGGG\u003c/p\u003e\n \u003cp\u003eCCTGGAAGATGGTGATGGGAT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n\u003c/div\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Atypical teratoid, mRNA, microRNA, Expression profiles, Immunocyte infiltration","lastPublishedDoi":"10.21203/rs.3.rs-986121/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-986121/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eAtypical teratoid/rhabdoid tumor (AT/RT) is a malignant pediatric tumor of the central nervous system (CNS) with high recurrence and low survival rates that is often misdiagnosed. MicroRNAs (miRNAs) are involved in the tumorigenesis of numerous pediatric cancers, but their roles in AT/RT remain unclear.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eIn this study, we used miRNA sequencing and gene expression microarrays from patient tissue to study both the miRNAome and transcriptome traits of AT/RT.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eOur findings demonstrate that 5 miRNAs were up-regulated, 16 miRNAs were down-regulated, 179 mRNAs were up-regulated and 402 mRNAs were down-regulated in AT/RT. The expressions of hsa-miR-17-5p and MAP7 mRNA showed the most significant differences in AT/RT tissues as assayed by qPCR, and analyses using the miRTarBase database identified MAP7 mRNA as a target gene of hsa-miR-17-5p. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eOur findings suggest that the dysregulation of hsa-miR-17-5p may be a pivotal event in AT/RT and MAP7 miRNAs that may represent potential therapeutic targets and diagnostic biomarkers.\u003c/p\u003e","manuscriptTitle":"The Identification of MiRNA and MRNA Expression Profiles Associated with Pediatric Atypical Teratoid/rhabdoid Tumor","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-10-26 15:47:20","doi":"10.21203/rs.3.rs-986121/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2021-11-08T10:08:48+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2021-10-28T16:11:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"7976468c-3a50-4b39-a30d-cfb6bb085719","date":"2021-10-28T11:22:06+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2021-10-28T11:14:19+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2021-10-25T07:47:12+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2021-10-25T07:09:10+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2021-10-25T07:03:50+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cancer","date":"2021-10-17T13:35:01+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fdb5ebdf-4c59-4c9d-b98e-f021a2bb1124","owner":[],"postedDate":"October 26th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":8112188,"name":"Cancer Biology"}],"tags":[],"updatedAt":"2022-04-11T08:14:23+00:00","versionOfRecord":[],"versionCreatedAt":"2021-10-26 15:47:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-986121","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-986121","identity":"rs-986121","version":["v1"]},"buildId":"J0_U0BvcaRcwD8yVFaRlm","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}