Analysis of Circulating Plasma MicroRNA Profile in Low-Grade and High-Grade Glioma – A Cross-Sectional Study [version 1; peer review: 2 approved, 1 approved with reservations, 1 not approved]
Background Glioma is the second most common type of brain tumor, accounting for 24% of all brain tumor cases. The current diagnostic procedure is through an invasive tissue sampling to obtain histopathological analysis, however, not all patients are able to undergo a high-risk procedure. Circulating...
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| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
F1000 Research Ltd
2024-11-01
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| Series: | F1000Research |
| Subjects: | |
| Online Access: | https://f1000research.com/articles/13-1361/v1 |
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| Summary: | Background Glioma is the second most common type of brain tumor, accounting for 24% of all brain tumor cases. The current diagnostic procedure is through an invasive tissue sampling to obtain histopathological analysis, however, not all patients are able to undergo a high-risk procedure. Circulating microRNAs (miRNAs) are considered as promising biomarkers for glioma due to their sensitivity, specificity, and non-invasive properties. There is currently no defined miRNA profile that contributes to determining the grade of glioma. This study aims to find the answer for “Is there any significant miRNA that able to distinguish different grades of glioma?”. Methods This study was conducted to compare the expression of miRNAs between low-grade glioma (LGG) and high-grade glioma (HGG). Eighteen blood plasma samples from glioma patients and 6 healthy controls were analyzed for 798 human miRNA profiles using NanoString nCounter Human v3 miRNA Expression Assay. The differential expressions of miRNAs were then analyzed to identify the differences in miRNA expression between LGG and HGG. Results Analyses showed significant expressions in 12 miRNAs between LGG and HGG, where all of them were downregulated. Out of these significant miRNAs, miR-518b, miR-1271-3p, and miR-598-3p showed the highest potential for distinguishing HGG from LGG, with area under curve (AUC) values of 0.912, 0.889, and 0.991, respectively. Conclusion miR-518b, miR-1271-3p, and miR-598-3p demonstrate significant potentials in distinguishing LGG and HGG. |
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| ISSN: | 2046-1402 |