In Silico-Identified miR-16-5p and miR-32-5p as a Shared Molecular Signature of Primary Gliomas and Parkinson's Disease: Plasma Levels Are Increased Only in Glioma Patients

计算机模拟鉴定出 miR-16-5p 和 miR-32-5p 是原发性胶质瘤和帕金森病的共同分子特征:血浆水平仅在胶质瘤患者中升高

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Abstract

OBJECTIVES: In this study, we explore the molecular basis of the literature-reported inverse association between brain neoplasms and neurodegenerative disorders, including Parkinson's disease (PD). As miRNAs are post-transcriptional regulators, we selected them as candidates underlying opposite processes of neurodegeneration and glioma development. METHODS: We used bioinformatic analyses for disease-gene extraction, miRNA target prediction, enrichment analyses, and miRNA ranking. We identified 953 shared genes between PD and glioblastoma (GBM) in DisGeNET, then prioritized miRNAs predicted to regulate the largest number of shared targets. Next, we collected peripheral blood from patients with PD (n = 12), patients with gliomas (the most advanced-grade IV, n = 10 and grade III n = 3) and controls undergoing spinal surgery for disk pathology (n = 10). Blood samples were obtained pre-operatively in controls and glioma patients. Tumor and peritumoral tissues were obtained from glioma patients, whereas tissue sampling is not feasible in PD. Brain tissues and plasma were analyzed using RT-qPCR (miRNA) and ELISA (p53). RESULTS: We observed increased levels of miR-16-5p (p < 0.05) and p53 protein (p < 0.05) in tumor tissues compared with peritumoral tissue. Additionally, miR-16-5p and miR-32-5p plasma levels were elevated in glioma patients compared with both PD patients (p < 0.01 and p < 0.001, respectively) and controls (p < 0.01 and p < 0.001, respectively). Plasma levels in PD did not differ from controls. CONCLUSIONS: Although these analyses highlight miR-16-5p and miR-32-5p as candidate biomarkers associated with glioma related pathways, the results did not provide evidence for the expected opposite regulation between PD and glioma. Future studies with a larger cohort of patients using high-throughput methods are needed to validate these findings and to elucidate the mechanisms driving neurodegeneration or excessive proliferation.

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