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Identification of Serum miRNAs as Effective Diagnostic Biomarkers for Distinguishing Primary Central Nervous System Lymphoma from Glioma
Identification of Serum miRNAs as Effective Diagnostic Biomarkers for Distinguishing Primary Central Nervous System Lymphoma from Glioma
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Identification of Serum miRNAs as Effective Diagnostic Biomarkers for Distinguishing Primary Central Nervous System Lymphoma from Glioma
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Identification of Serum miRNAs as Effective Diagnostic Biomarkers for Distinguishing Primary Central Nervous System Lymphoma from Glioma
Identification of Serum miRNAs as Effective Diagnostic Biomarkers for Distinguishing Primary Central Nervous System Lymphoma from Glioma

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Identification of Serum miRNAs as Effective Diagnostic Biomarkers for Distinguishing Primary Central Nervous System Lymphoma from Glioma
Identification of Serum miRNAs as Effective Diagnostic Biomarkers for Distinguishing Primary Central Nervous System Lymphoma from Glioma
Journal Article

Identification of Serum miRNAs as Effective Diagnostic Biomarkers for Distinguishing Primary Central Nervous System Lymphoma from Glioma

2022
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Overview
Invasive surgical cerebrum biopsy results in delayed treatment for the definitive diagnosis of primary central nervous system lymphoma (PCNSL). The existent research was aimed at confirming the underlying diagnostic miRNAs of distinguishing PCNSL from glioma. A publicly available miRNA expression profiles (GSE139031) from adult PCNSL as well as glioma specimens were provided by GEO datasets. Differentially expressed miRNAs (DEMs) were filtered between 42 PCNSL patients and 170 glioma patients. Candidate miRNAs were identified through SVM-RFE analysis and LASSO model. ROC assays were operated to determine the diagnostic value of serum miRNAs in distinguishing PCNSL from glioma. StarBase v2.0 was applied to screen the targeting genes of miRNAs, and KEGG analysis was applied using the targeting genes of miRNAs. In this study, we identified 12 dysregulated miRNAs between PCNSL and glioma samples. The ten critical miRNAs (miR-6820-3p, miR-6803-3p, miR-30a-3p, miR-4751, miR-3918, miR-146a-3p, miR-548am-3p, miR-371a-3p, miR-487a-3p, and miR-4756-5p) between these two algorithms were ultimately identified. The results of KEGG revealed that the targeting genes of hsa-miR-3918 were primarily related to MAPK signal pathway, PI3K-Akt signal pathway, and human papillomavirus infection. Overall, bioinformatics analysis revealed that ten miRNAs are potential biomarker for distinguishing PCNSL from glioma.