Arginase 2 Promotes Cisplatin-Induced Acute Kidney Injury by the Inflammatory Response of Macrophages

Uchida, Yuushi; Torisu, Kumiko; Aihara, Seishi; Imazu, Noriyuki; Ooboshi, Hiroaki; Kitazono, Takanari; Nakano, Toshiaki

doi:10.1016/j.labinv.2023.100227

Cited by 4 publications

(1 citation statement)

References 34 publications

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“…PLAT (plasminogen activator, tissue type) [325] and ALB (albumin) [326] might be involved in the occurrence and development of hypertension. BMI1 [327], AMH (anti-Mullerian hormone) [328], E2F1 [329], PF4 [330], VASH2 [331], GRIN1 [332], CYP11B2 [333], COMP (cartilage oligomeric matrix protein) [334], DES (desmin) [335], ANGPTL3 [336], CYP3A5 [337], DPEP1 [338], LRP2 [339], AGXT2 [340], FABP1 [341], SLC22A12 [342], CUBN (cubilin) [343], MIOX (myo-inositol oxygenase) [344], ARG2 [345], KHK (ketohexokinase) [346], CYP2C8 [347], SLC2A9 [348], GC (GC vitamin D binding protein) [349], VNN1 [350], NOX4 [351], EPHX2 [352], AKR1C3 [353], NR4A3 [354], PFKFB2 [355], SLC22A6 [356], F11 [357], SLC22A2 [358], AQP2 [171], EGF (epidermal growth factor) [359], KNG1 [360], SERPINA5 [361], KL (klotho) [362], ACE2 [363], NPNT (nephronectin) [364], SLC47A1 [358], MGAM (maltase-glucoamylase) [365], AQP3 [366], AZGP1 [367], GALNT3 [368], DPP4 [369], STC1 [370], ABCB1 [371], ERRFI1 [372], TREH (trehalase) [373], MANBA (mannosidase beta) [374], ERBB4 [375], VCAM1 [376] and ALB (albumin) [377] might play an important role in the pathophysiology of AKI. BMI1 [378], IGF2 [379], PRKCB (protein kinase C beta) [380], CCL5 [381], E2F1 [382], PF4 [111], CYP11B2 [383], WNT3A [384], COMP (cartilage oligomeric matrix protein) [385], DES (desmin) [335], ANGPTL3 [386], CYP3A5 [387], LRP2 [388], PAH (phenylalanine hydroxylase) [389], HMGCS2 [390]...…”

Section: Discussionmentioning

confidence: 99%

Identification of novel prognostic targets in acute kidney injury using bioinformatics and next generation sequencing data analysis

Vastrad,

Vastrad

2024

Preprint

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Acute kidney injury (AKI) is a type of renal disease occurs frequently in hospitalized patients, which may cause abnormal renal function and structure with increase in serum creatinine level with or without reduced urine output. With the incidence of AKI is increasing. However, the molecular mechanisms of AKI have not been elucidated. It is significant to further explore the molecular mechanisms of AKI. We downloaded the GSE139061 next generation sequencing (NGS) dataset from the Gene Expression Omnibus (GEO) database. Limma R bioconductor package was used to screen the differentially expressed genes (DEGs). Then, the enrichment analysis of DEGs in Gene Ontology (GO) function and REACTOME pathways was analyzed by g:Profiler. Next, the protein-protein interaction (PPI) network and modules was constructed and analyzed, and the hub genes were identified. Next, the miRNA-hub gene regulatory network and TF-hub gene regulatory network were built. We also validated the identified hub genes via receiver operating characteristic (ROC) curve analysis. Overall, 956 DEGs were identified, including 478 up regulated and 478 down regulated genes. The enrichment functions and pathways of DEGs involve primary metabolic process, small molecule metabolic process, striated muscle contraction and metabolism. Topological analysis of the PPI network and module revealed that hub genes, including PPP1CC, RPS2, MDFI, BMI1, RPL23A, VCAM1, ALB, SNCA, DPP4 and RPL26L1, might be involved in the development of AKI. miRNA-hub gene and TF-hub gene regulatory networks revealed that miRNAs and TFs including hsa-mir-510-3p, hsa-mir-6086 and mir-146a-5p, MAX and PAX2, might be involved in the development of AKI. Various known and newtherapeutic targets were obtained via network analysis. The results of the current investigation might be beneficial for the diagnosis and treatment of AKI.

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