Identification and validation of LY6H and GRM3 as candidate biomarkers for Glioma-related epilepsy
Abstract Gliomas are the most common primary tumors of the central nervous system, with epilepsy serving as a frequent clinical manifestation. Glioma-related epilepsy (GRE) significantly affects patients’ quality of life and prognosis. In this study, we integrated bioinformatics and multiple machine...
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| Format: | Article |
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Nature Portfolio
2025-04-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-97333-4 |
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| author | Zhenpan Zhang Jianhuang Huang Caihou Lin Risheng Liang |
| author_facet | Zhenpan Zhang Jianhuang Huang Caihou Lin Risheng Liang |
| author_sort | Zhenpan Zhang |
| collection | DOAJ |
| description | Abstract Gliomas are the most common primary tumors of the central nervous system, with epilepsy serving as a frequent clinical manifestation. Glioma-related epilepsy (GRE) significantly affects patients’ quality of life and prognosis. In this study, we integrated bioinformatics and multiple machine learning methods to perform a proteomic analysis of brain tumor samples from patients with GRE and from those with gliomas none epilepsy (GNE). Our findings identified LY6H and GRM3 as potential signature proteins of GRE. Further investigation showed that LY6H and GRM3 expression levels were markedly reduced in GRE samples, with favorable diagnostic performance according to ROC curve analyses. Finally, we conducted an independent external validation using the Bluk-RNA dataset GSE199759, and the results corroborated our prior analyses. This work not only provides new biomarkers for the early detection of GRE but also offers valuable insights into its molecular mechanisms and potential therapeutic strategies. |
| format | Article |
| id | doaj-art-5383fe48bbb945e2bf0a2621bc05fc38 |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-5383fe48bbb945e2bf0a2621bc05fc382025-08-20T03:18:34ZengNature PortfolioScientific Reports2045-23222025-04-0115111410.1038/s41598-025-97333-4Identification and validation of LY6H and GRM3 as candidate biomarkers for Glioma-related epilepsyZhenpan Zhang0Jianhuang Huang1Caihou Lin2Risheng Liang3Department of Neurosurgery, Fujian Medical University Union HospitalDepartment of Neurosurgery, Affiliated Hospital of Putian UniversityDepartment of Neurosurgery, Fujian Medical University Union HospitalDepartment of Neurosurgery, Fujian Medical University Union HospitalAbstract Gliomas are the most common primary tumors of the central nervous system, with epilepsy serving as a frequent clinical manifestation. Glioma-related epilepsy (GRE) significantly affects patients’ quality of life and prognosis. In this study, we integrated bioinformatics and multiple machine learning methods to perform a proteomic analysis of brain tumor samples from patients with GRE and from those with gliomas none epilepsy (GNE). Our findings identified LY6H and GRM3 as potential signature proteins of GRE. Further investigation showed that LY6H and GRM3 expression levels were markedly reduced in GRE samples, with favorable diagnostic performance according to ROC curve analyses. Finally, we conducted an independent external validation using the Bluk-RNA dataset GSE199759, and the results corroborated our prior analyses. This work not only provides new biomarkers for the early detection of GRE but also offers valuable insights into its molecular mechanisms and potential therapeutic strategies.https://doi.org/10.1038/s41598-025-97333-4Glioma-related epilepsyProteomicBiomarkersLassoMachine learning |
| spellingShingle | Zhenpan Zhang Jianhuang Huang Caihou Lin Risheng Liang Identification and validation of LY6H and GRM3 as candidate biomarkers for Glioma-related epilepsy Scientific Reports Glioma-related epilepsy Proteomic Biomarkers Lasso Machine learning |
| title | Identification and validation of LY6H and GRM3 as candidate biomarkers for Glioma-related epilepsy |
| title_full | Identification and validation of LY6H and GRM3 as candidate biomarkers for Glioma-related epilepsy |
| title_fullStr | Identification and validation of LY6H and GRM3 as candidate biomarkers for Glioma-related epilepsy |
| title_full_unstemmed | Identification and validation of LY6H and GRM3 as candidate biomarkers for Glioma-related epilepsy |
| title_short | Identification and validation of LY6H and GRM3 as candidate biomarkers for Glioma-related epilepsy |
| title_sort | identification and validation of ly6h and grm3 as candidate biomarkers for glioma related epilepsy |
| topic | Glioma-related epilepsy Proteomic Biomarkers Lasso Machine learning |
| url | https://doi.org/10.1038/s41598-025-97333-4 |
| work_keys_str_mv | AT zhenpanzhang identificationandvalidationofly6handgrm3ascandidatebiomarkersforgliomarelatedepilepsy AT jianhuanghuang identificationandvalidationofly6handgrm3ascandidatebiomarkersforgliomarelatedepilepsy AT caihoulin identificationandvalidationofly6handgrm3ascandidatebiomarkersforgliomarelatedepilepsy AT rishengliang identificationandvalidationofly6handgrm3ascandidatebiomarkersforgliomarelatedepilepsy |