Ery Kus Dwianingsih, Rachmat Andi Hartanto, Sekar Safitri, Yeshua Putra Krisnugraha, Christina Megawimanti Sianipar, Endro Basuki, Kusumo Dananjoyo, Ahmad Asmedi, Bo Sun, Rusdy Ghazali Malueka
{"title":"Analysis of Circulating Plasma MicroRNA Profile in Low-Grade and High-Grade Glioma - A Cross-Sectional Study.","authors":"Ery Kus Dwianingsih, Rachmat Andi Hartanto, Sekar Safitri, Yeshua Putra Krisnugraha, Christina Megawimanti Sianipar, Endro Basuki, Kusumo Dananjoyo, Ahmad Asmedi, Bo Sun, Rusdy Ghazali Malueka","doi":"10.12688/f1000research.153731.1","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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?\".</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>miR-518b, miR-1271-3p, and miR-598-3p demonstrate significant potentials in distinguishing LGG and HGG.</p>","PeriodicalId":12260,"journal":{"name":"F1000Research","volume":"13 ","pages":"1361"},"PeriodicalIF":0.0000,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11725040/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"F1000Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12688/f1000research.153731.1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"Pharmacology, Toxicology and Pharmaceutics","Score":null,"Total":0}
引用次数: 0
Abstract
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.
F1000ResearchPharmacology, Toxicology and Pharmaceutics-Pharmacology, Toxicology and Pharmaceutics (all)
CiteScore
5.00
自引率
0.00%
发文量
1646
审稿时长
1 weeks
期刊介绍:
F1000Research publishes articles and other research outputs reporting basic scientific, scholarly, translational and clinical research across the physical and life sciences, engineering, medicine, social sciences and humanities. F1000Research is a scholarly publication platform set up for the scientific, scholarly and medical research community; each article has at least one author who is a qualified researcher, scholar or clinician actively working in their speciality and who has made a key contribution to the article. Articles must be original (not duplications). All research is suitable irrespective of the perceived level of interest or novelty; we welcome confirmatory and negative results, as well as null studies. F1000Research publishes different type of research, including clinical trials, systematic reviews, software tools, method articles, and many others. Reviews and Opinion articles providing a balanced and comprehensive overview of the latest discoveries in a particular field, or presenting a personal perspective on recent developments, are also welcome. See the full list of article types we accept for more information.