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ORIGINAL RESEARCH

The Network of miRNA–mRNA Interactions in Circulating T Cells of Patients Following Major Trauma – A Pilot Study

, , , , , , , , & ORCID Icon show all
Pages 5491-5503 | Received 09 Jun 2022, Accepted 15 Sep 2022, Published online: 22 Sep 2022

References

  • Di Battista AP, Rhind SG, Hutchison MG, et al. Inflammatory cytokine and chemokine profiles are associated with patient outcome and the hyperadrenergic state following acute brain injury. J Neuroinflammation. 2016;13:40. doi:10.1186/s12974-016-0500-3
  • Catania A, Lonati C, Sordi A, Gatti S. Detrimental consequences of brain injury on peripheral cells. Brain Behav Immun. 2009;23:877–884. doi:10.1016/j.bbi.2009.04.006
  • Xiao W, Mindrinos MN, Seok J, et al. A genomic storm in critically injured humans. J Exp Med. 2011;208:2581–2590. doi:10.1084/jem.20111354
  • Wu SC, Rau CS, Kuo PJ, et al. Profiling the expression of circulating acute-phase proteins, cytokines, and checkpoint proteins in patients with major trauma: a pilot study. J Inflamm Res. 2021;14:3739–3753. doi:10.2147/jir.S324056
  • Bonaroti J, Abdelhamid S, Kar U, et al. The use of multiplexing to identify cytokine and chemokine networks in the immune-inflammatory response to trauma. Antioxid Redox Signal. 2021;35:1393–1406. doi:10.1089/ars.2021.0054
  • Finlay LD, Conway Morris A, Deane AM, Wood AJ. Neutrophil kinetics and function after major trauma: a systematic review. World J Crit Care Med. 2021;10:260–277. doi:10.5492/wjccm.v10.i5.260
  • Hotchkiss RS, Karl IE. The pathophysiology and treatment of sepsis. N Engl J Med. 2003;348:138–150. doi:10.1056/NEJMra021333
  • Dong X, Wang C, Liu X, Bai X, Li Z. The trajectory of alterations in immune-cell counts in severe-trauma patients is related to the later occurrence of sepsis and mortality: retrospective study of 917 cases. Front Immunol. 2020;11:603353. doi:10.3389/fimmu.2020.603353
  • Keel M, Trentz O. Pathophysiology of polytrauma. Injury. 2005;36:691–709. doi:10.1016/j.injury.2004.12.037
  • Huo J, Wang L, Tian Y, et al. Gene co-expression analysis identified preserved and survival-related modules in severe blunt trauma, burns, sepsis, and systemic inflammatory response syndrome. Int J Gen Med. 2021;14:7065–7076. doi:10.2147/ijgm.S336785
  • Vidigal JA, Ventura A. The biological functions of miRNAs: lessons from in vivo studies. Trends Cell Biol. 2015;25:137–147. doi:10.1016/j.tcb.2014.11.004
  • O’Brien J, Hayder H, Zayed Y, Peng C. Overview of MicroRNA biogenesis, mechanisms of actions, and circulation. Front Endocrinol. 2018;9:402. doi:10.3389/fendo.2018.00402
  • Hirschberger S, Hinske LC, Kreth S. MiRNAs: dynamic regulators of immune cell functions in inflammation and cancer. Cancer Lett. 2018;431:11–21. doi:10.1016/j.canlet.2018.05.020
  • Xiao C, Rajewsky K. MicroRNA control in the immune system: basic principles. Cell. 2009;136:26–36. doi:10.1016/j.cell.2008.12.027
  • Nanbakhsh A, Malarkannan S. The role of microRNAs in NK cell development and function. Cells. 2021;10:2020. doi:10.3390/cells10082020
  • Xiao C, Nemazee D, Gonzalez-Martin A. MicroRNA control of B cell tolerance, autoimmunity and cancer. Semin Cancer Biol. 2020;64:102–107. doi:10.1016/j.semcancer.2019.04.004
  • Uhlich RM, Konie JA, Davis JW, et al. Novel microRNA correlations in the severely injured. Surgery. 2014;156:834–840. doi:10.1016/j.surg.2014.06.017
  • Hsieh CH, Hsu SY, Hsieh HY, Chen YC. Differences between the sexes in motorcycle-related injuries and fatalities at a Taiwanese level I trauma center. Biomed J. 2017;40:113–120. doi:10.1016/j.bj.2016.10.005
  • Hsieh CH, Liu HT, Hsu SY, Hsieh HY, Chen YC. Motorcycle-related hospitalizations of the elderly. Biomed J. 2017;40:121–128. doi:10.1016/j.bj.2016.10.006
  • Hsieh CH, Chen YC, Hsu SY, Hsieh HY, Chien PC. Defining polytrauma by abbreviated injury scale >/= 3 for a least two body regions is insufficient in terms of short-term outcome: a cross-sectional study at a level I trauma center. Biomed J. 2018;41:321–327. doi:10.1016/j.bj.2018.08.007
  • Hsu SY, Wu SC, Rau CS, et al. Impact of adapting the Abbreviated Injury Scale (AIS)-2005 from AIS-1998 on injury severity scores and clinical outcome. Int J Environ Res Public Health. 2019;16:5033. doi:10.3390/ijerph16245033
  • Stewart KE, Cowan LD, Thompson DM. Changing to AIS 2005 and agreement of injury severity scores in a trauma registry with scores based on manual chart review. Injury. 2011;42:934–939. doi:10.1016/j.injury.2010.05.033
  • Newgard CD, Fu R, Lerner EB, et al. Deaths and high-risk trauma patients missed by standard trauma data sources. J Trauma Acute Care Surg. 2017;83:427–437. doi:10.1097/ta.0000000000001616
  • Sticht C, De La Torre C, Parveen A, Gretz N. miRWalk: an online resource for prediction of microRNA binding sites. PLoS One. 2018;13:e0206239. doi:10.1371/journal.pone.0206239
  • Ding J, Li X, Hu H. TarPmiR: a new approach for microRNA target site prediction. Bioinformatics. 2016;32:2768–2775. doi:10.1093/bioinformatics/btw318
  • McGeary SE, Lin KS, Shi CY, et al. The biochemical basis of microRNA targeting efficacy. Science. 2019;366. doi:10.1126/science.aav1741
  • Chen Y, Wang X. miRDB: an online database for prediction of functional microRNA targets. Nucleic Acids Res. 2020;48:D127–d131. doi:10.1093/nar/gkz757
  • Huang HY, Lin YC, Li J, et al. miRTarBase 2020: updates to the experimentally validated microRNA-target interaction database. Nucleic Acids Res. 2020;48:D148–d154. doi:10.1093/nar/gkz896
  • Gene Ontology Consortium. The Gene Ontology (GO) project in 2006. Nucleic Acids Res. 2006;34:D322–326. doi:10.1093/nar/gkj021
  • Draghici S, Khatri P, Tarca AL, et al. A systems biology approach for pathway level analysis. Genome Res. 2007;17:1537–1545. doi:10.1101/gr.6202607
  • Rajarathnam K, Schnoor M, Richardson RM, Rajagopal S. How do chemokines navigate neutrophils to the target site: dissecting the structural mechanisms and signaling pathways. Cell Signal. 2019;54:69–80. doi:10.1016/j.cellsig.2018.11.004
  • Zaja-Milatovic S, Richmond A. CXC chemokines and their receptors: a case for a significant biological role in cutaneous wound healing. Histol Histopathol. 2008;23:1399–1407. doi:10.14670/hh-23.1399
  • Xun Y, Yang H, Li J, Wu F, Liu F. CXC chemokine receptors in the tumor microenvironment and an update of antagonist development. Rev Physiol Biochem Pharmacol. 2020;178:1–40. doi:10.1007/112_2020_35
  • Li L, Du X, Ling H, et al. Gene correlation network analysis to identify regulatory factors in sciatic nerve injury. J Orthop Surg Res. 2021;16:622. doi:10.1186/s13018-021-02756-0
  • Cao XY, Qian X, Liu GD, Wang YH. Bioinformatics-based identification of key pathways and hub genes of traumatic brain injury in a rat model. Curr Med Sci. 2021;41:610–617. doi:10.1007/s11596-021-2365-7
  • Niu SP, Zhang YJ, Han N, Yin XF, Zhang DY, Kou YH. Identification of four differentially expressed genes associated with acute and chronic spinal cord injury based on bioinformatics data. Neural Regen Res. 2021;16:865–870. doi:10.4103/1673-5374.297087
  • Zhu Z, Shen Q, Zhu L, Wei X. Identification of pivotal genes and pathways for spinal cord injury via bioinformatics analysis. Mol Med Rep. 2017;16:3929–3937. doi:10.3892/mmr.2017.7060
  • Sabaie H, Talebi M, Gharesouarn J, et al. Identification and analysis of BCAS4/hsa-miR-185-5p/SHISA7 competing endogenous RNA axis in late-onset alzheimer’s disease using bioinformatic and experimental approaches. Front Aging Neurosci. 2022;14:812169. doi:10.3389/fnagi.2022.812169
  • Roy J, Mallick B. Altered gene expression in late-onset Alzheimer’s disease due to SNPs within 3’UTR microRNA response elements. Genomics. 2017;109:177–185. doi:10.1016/j.ygeno.2017.02.006
  • Sun J, Zhao J, Yang Z, Zhou Z, Lu P. Identification of gene signatures and potential therapeutic targets for acquired chemotherapy resistance in gastric cancer patients. J Gastrointest Oncol. 2021;12:407–422. doi:10.21037/jgo-21-81
  • Friedrich J, Steel DHW, Schlingemann RO, et al. microRNA expression profile in the vitreous of proliferative diabetic retinopathy patients and differences from patients treated with Anti-VEGF therapy. Transl Vis Sci Technol. 2020;9:16. doi:10.1167/tvst.9.6.16
  • Li M, Qi L, Li Y, et al. Association of pericardiac adipose tissue with coronary artery disease. Front Endocrinol. 2021;12:724859. doi:10.3389/fendo.2021.724859
  • Zhong XQ, Yan Q, Chen ZG, et al. Umbilical cord blood-derived exosomes from very preterm infants with bronchopulmonary dysplasia impaired endothelial angiogenesis: roles of exosomal MicroRNAs. Front Cell Dev Biol. 2021;9:637248. doi:10.3389/fcell.2021.637248
  • Guo J, Zhou P, Liu Z, et al. The aflibercept-induced MicroRNA profile in the vitreous of proliferative diabetic retinopathy patients detected by next-generation sequencing. Front Pharmacol. 2021;12:781276. doi:10.3389/fphar.2021.781276
  • Guo J, Zhou P, Pan M, et al. Relationship between elevated microRNAs and growth factors levels in the vitreous of patients with proliferative diabetic retinopathy. J Diabetes Complications. 2021;35:108021. doi:10.1016/j.jdiacomp.2021.108021
  • Liu N, Jiang F, Chen Z. A preliminary study on the pathogenesis of colorectal cancer by constructing a Hsa-circRNA-0067835-miRNA-mRNA regulatory network. Onco Targets Ther. 2021;14:4645–4658. doi:10.2147/ott.S319300
  • Zhang Q, Kang L, Li X, Li Z, Wen S, Fu X. Bioinformatics analysis predicts hsa_circ_0026337/miR-197-3p as a potential oncogenic ceRNA network for non-small cell lung cancers. Anticancer Agents Med Chem. 2022;22:874–886. doi:10.2174/1871520621666210712090721
  • Stokowy T, Eszlinger M, Świerniak M, et al. Analysis options for high-throughput sequencing in miRNA expression profiling. BMC Res Notes. 2014;7:144. doi:10.1186/1756-0500-7-144
  • Navarro-Quiroz E, Pacheco-Lugo L, Navarro-Quiroz R, et al. Profiling analysis of circulating microRNA in peripheral blood of patients with class IV lupus nephritis. PLoS One. 2017;12:e0187973. doi:10.1371/journal.pone.0187973
  • Li ZB, Shi LY, Han YS, et al. Pyridoxal phosphate, pyridoxamine phosphate, and folic acid based on ceRNA regulatory network as potential biomarkers for the diagnosis of pulmonary tuberculosis. Infect Genet Evol. 2022;99:105240. doi:10.1016/j.meegid.2022.105240
  • Jiang P, Xu C, Chen L, et al. Epigallocatechin-3-gallate inhibited cancer stem cell-like properties by targeting hsa-mir-485-5p/RXRα in lung cancer. J Cell Biochem. 2018;119:8623–8635. doi:10.1002/jcb.27117
  • Peng Y, Leng W, Duan S, Hong M. Long noncoding RNA BLACAT1 is overexpressed in hepatocellular carcinoma and its downregulation suppressed cancer cell development through endogenously competing against hsa-miR-485-5p. Biomed Pharmacother. 2019;116:109027. doi:10.1016/j.biopha.2019.109027
  • Lin XJ, He CL, Sun T, Duan XJ, Sun Y, Xiong SJ. hsa-miR-485-5p reverses epithelial to mesenchymal transition and promotes cisplatin-induced cell death by targeting PAK1 in oral tongue squamous cell carcinoma. Int J Mol Med. 2017;40:83–89. doi:10.3892/ijmm.2017.2992
  • Basso J, Paggi MG, Fortuna A, Vitorino C, Vitorino R. Deciphering specific miRNAs in brain tumors: a 5-miRNA signature in glioblastoma. Mol Genet Genomics. 2022;297:507–521. doi:10.1007/s00438-022-01866-6