基于融合基因作用于横纹肌肉瘤的miRNA-mRNA调控网络的生物信息学分析

doi:10.13481/j.1671-587X.20220119

Abstract

Abstract: Objective

To construct the potential miRNA-mRNA regulatory network of fusion genes in the pathogenesis of rhabdomyosarcoma （RMS）with bioinformatics analysis， and to provide a new direction for the study of RMS.

Methods

GEO2R analysis tool was used to screen the differentially expressed genes （DEGs） and differentially expressed miRNA in fusion-gene-positive and -negative RMS tissues； the target genes of differentially expressed miRNA were predicted； and the target genes on the basis of overlapping DEGs and target genes were screened out. DAVID database was implemented for the GO and KEGG enrichment analysis of target genes. STRING and Cytoscape software were utilized to construct the protein protein interation （PPI） network， the Top10 hub genes were screened out and the molecular regulation networks of hub genes and miRNA were constructed， and the Kaplan-Meier survival curves of the sarcoma patients were drawn.

Results

A total of 891 DEGs （P<0.01，|logFC|≥1） and 14 differentially expressed miRNAs （P<0.05， |logFC|≥3） were screened out. Moreover， 1 654 target genes differentially expressing miRNAs were predicted， and 115 target genes were identified by overlapping the target genes and DEGs. The GO enrichment analysis revealed that the target genes were mainly enriched in the positive regulation of cell proliferation， cell surface， protein binding， and other biological processes. The KEGG signaling pathway analysis revealed that the target genes were mainly enriched in the extracellular matrix-receptor interaction， proteoglycan in cancer， and other pathways. The Top10 hub genes screened out from the PPI network were ERBB4， PTPRD， IRS1， ADAM10， YAP1， TFAP2A， CADM1， ELAVL2， SNAI1， and ERRFI1. The survival analysis showed that the increased expression levels of PTPRD （HR=1.79， P=0.005），ADAM10 （HR =1.94，P=0.010）， ELAVL2 （HR = 1.56，P=0.031），and ERRFI1 （HR=2.05，P=0.005） were related to the bad prognosis of the sarcoma patients.

Conclusion

The miRNA-mRNA network is constructed by selecting the hub genes and corresponding miRNA involed in the pathogenesis of RMS， and the study provides a theoretical basis for further study of the relationship between fusion genes and RMS.

Key words: Rhabdomyosarcoma, Fusion gene, Bioinformatics, MiRNA-mRNA regulatory network, Differentially expressed genes

CLC Number:

R738.6

Zhijuan ZHAO,Lian MENG,Chunxia LIU. Bioinformatics analysis on miRNA-mRNA regulatory networks based on fusion genes acting in rhabdomyosarcoma[J].Journal of Jilin University(Medicine Edition), 2022, 48(1): 154-162.

Figures/Tables 7

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References 31

1	SKAPEK S， FERRARI A， GUPTA A， et al. Rhabdomyosarcoma ［J］.Nat Rev Dis Primers， 2019， 5（1）： 2.
2	SORENSEN P H， LYNCH J C， QUALMAN S J，et al. PAX3-FKHR and PAX7-FKHR gene fusions are prognostic indicators in alveolar rhabdomyosarcoma： a report from the children's oncology group［J］. J Clin Oncol， 2002， 20（11）： 2672-2679.
3	MISSIAGLIA E， SHEPHERD C J， ALADOWICZ E， et al. MicroRNA and gene co-expression networks characterize biological and clinical behavior of rhabdomyosarcomas［J］. Cancer Lett， 2017， 385： 251-260.
4	ZHANG L， PANG Y W， CUI X B， et al. MicroRNA-410-3p upregulation suppresses proliferation， invasion and migration， and promotes apoptosis in rhabdomyosarcoma cells［J］. Oncol Lett， 2019， 18（1）： 936-943.
5	SHANG H， LIU Y， LI Z Z， et al. MicroRNA-874 functions as a tumor suppressor in rhabdomyosarcoma by directly targeting GEFT［J］. Am J Cancer Res， 2019， 9（4）： 668-681.
6	ESPINOZA-SÁNCHEZ N A， GÖTTE M. Role of cell surface proteoglycans in cancer immunotherapy［J］. Semin Cancer Biol， 2020， 62： 48-67.
7	MACHACKOVA T， VYCHYTILOVA-FALTEJSKOVA P， SOUCKOVA K， et al. MiR-215-5p reduces liver metastasis in an experimental model of colorectal cancer through regulation of ECM-receptor interactions and focal adhesion［J］. Cancers （Basel）， 2020， 12（12）： E3518.
8	THEOCHARIS A D， KARAMANOS N K. Proteoglycans remodeling in cancer： Underlying molecular mechanisms［J］. Matrix Biol， 2019， 75/76： 220-259.
9	ZHAO X， WANG Q Y， LIN F F， et al. RNA sequencing of osteosarcoma gene expression profile revealed that miR-214-3p facilitates osteosarcoma cell proliferation via targeting ubiquinol-cytochrome c reductase core protein 1 （UQCRC1）［J］. Med Sci Monit， 2019， 25： 4982-4991.
10	PHATAK P， BYRNES K A， MANSOUR D， et al. Overexpression of miR-214-3p in esophageal squamous cancer cells enhances sensitivity to cisplatin by targeting survivin directly and indirectly through CUG-BP1 ［J］. Oncogene， 2016， 35（16）： 2087-2097.
11	HUANG H J， LIU J， HUA H， et al. MiR-214 and N-ras regulatory loop suppresses rhabdomyosarcoma cell growth and xenograft tumorigenesis［J］. Oncotarget， 2014， 5（8）： 2161-2175.
12	VEERIAH S， BRENNAN C， MENG S S， et al. The tyrosine phosphatase PTPRD is a tumor suppressor that is frequently inactivated and mutated in glioblastoma and other human cancers［J］. Proc Natl Acad Sci U S A， 2009， 106（23）： 9435-9440.
13	MEEHAN M， PARTHASARATHI L， MORAN N， et al. Protein tyrosine phosphatase receptor delta acts as a neuroblastoma tumor suppressor by destabilizing the aurora kinase A oncogene［J］. Mol Cancer， 2012， 11： 6.
14	SOLOMON D A， KIM J S， CRONIN J C， et al. Mutational inactivation of PTPRD in glioblastoma multiforme and malignant melanoma［J］. Cancer Res， 2008， 68（24）： 10300-10306.
15	FUNATO K， YAMAZUMI Y， ODA T， et al. Tyrosine phosphatase PTPRD suppresses colon cancer cell migration in coordination with CD44［J］. Exp Ther Med， 2011， 2（3）： 457-463.
16	WANG M， ZHAO Y， YU Z Y， et al. Glioma exosomal microRNA-148a-3p promotes tumor angiogenesis through activating the EGFR/MAPK signaling pathway via inhibiting ERRFI1 ［J］. Cancer Cell Int， 2020， 20： 518.
17	YU Y， CHEN Q Y， ZHANG X L， et al. Long noncoding RNA ANRIL promotes the malignant progression of cholangiocarcinoma by epigenetically repressing ERRFI1 expression［J］. Cancer Sci， 2020， 111（7）： 2297-2309.
18	YAN J W， LIN J S， HE X X. The emerging role of miR-375 in cancer［J］. Int J Cancer， 2014， 135（5）： 1011-1018.
19	YIN L H， ZHENG X Q， LI H Y， et al. Epigenetic deregulated miR-375 contributes to the constitutive activation of JAK2/STAT signaling in myeloproliferative neoplasm［J］.Leuk Res， 2015，39（4）：471-478.
20	HE X X， CHANG Y， MENG F Y， et al. MicroRNA-375 targets AEG-1 in hepatocellular carcinoma and suppresses liver cancer cell growth in vitro and in vivo ［J］. Oncogene， 2012， 31（28）： 3357-3369.
21	HE J， CAO Y N， SU T W， et al. Downregulation of miR-375 in aldosterone-producing adenomas promotes tumour cell growth via MTDH［J］. Clin Endocrinol （Oxf）， 2015， 83（4）： 581-589.
22	MAO Q Q， QUAN T， LUO B， et al. MiR-375 targets KLF4 and impacts the proliferation of colorectal carcinoma［J］. Tumour Biol， 2016， 37（1）： 463-471.
23	LIU W， ZHAO X T， ZHANG Y J， et al. MicroRNA-375 as a potential serum biomarker for the diagnosis， prognosis， and chemosensitivity prediction of osteosarcoma［J］. J Int Med Res， 2018，46（3）： 975-983.
24	XU X D， LIU Y， LI Y， et al. Selective exosome exclusion of miR-375 by glioma cells promotes glioma progression by activating the CTGF-EGFR pathway［J］. J Exp Clin Cancer Res， 2021， 40（1）： 16.
25	SZCZYRBA J， NOLTE E， WACH S， et al. Downregulation of Sec23A protein by miRNA-375 in prostate carcinoma［J］. Mol Cancer Res， 2011， 9（6）： 791-800.
26	ZHAO W S， YAN W P， CHEN D B， et al. Genome-scale CRISPR activation screening identifies a role of ELAVL2-CDKN1A axis in paclitaxel resistance in esophageal squamous cell carcinoma［J］. Am J Cancer Res， 2019， 9（6）： 1183-1200.
27	LI L， MOU Y P， WANG Y Y， et al. MiR-199a-3p targets ETNK1 to promote invasion and migration in gastric cancer cells and is associated with poor prognosis［J］. Pathol Res Pract， 2019， 215（9）： 152511.
28	WANG X M， ZOU J L， CHEN H J， et al. Long noncoding RNA NORAD regulates cancer cell proliferation and migration in human osteosarcoma by endogenously competing with miR-199a-3p［J］. IUBMB Life， 2019， 71（10）： 1482-1491.
29	LIU F， ZHUANG L， WU R X， et al. MiR-365 inhibits cell invasion and migration of triple negative breast cancer through ADAM10［J］. J BUON， 2019， 24（5）： 1905-1912.
30	WANG Y J， ZHOU N， LI P， et al. EphA8 Acts as an oncogene and contributes to poor prognosis in gastric cancer via regulation of ADAM10［J］. J Cell Physiol， 2019， 234（11）： 20408-20419.
31	ZHAO R， NI D J， TIAN Y， et al. Aberrant ADAM10 expression correlates with osteosarcoma progression［J］. Eur J Med Res， 2014， 19： 9.

miRNA_ID	P	logFC
hsa-miR-375	0.003 942	5.03
hsa-miR-30a-5p	0.006 482	3.11
hsa-miR-362-5p	0.021 800	3.13
hsa-miR-532-5p	0.027 706	3.36
hsa-miR-362-3p	0.030 996	3.00
hsa-miR-660-5p	0.039 330	3.55
hsa-miR-135a-5p	0.048 080	3.45
hsa-miR-196a-5p	0.006 482	－4.05
hsa-miR-199a-3p	0.010 458	－3.39
hsa-miR-455-3p	0.012 873	－4.43
hsa-miR-214-3p	0.012 873	－4.50
hsa-miR-199a-5p	0.021 800	－3.80
hsa-miR-99b-5p	0.021 800	－3.75
hsa-let-7e-5p	0.047 928	－3.84

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Bioinformatics analysis on miRNA-mRNA regulatory networks based on fusion genes acting in rhabdomyosarcoma

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