MRI-based machine learning reveals proteasome subunit PSMB8-mediated malignant glioma phenotypes through activating TGFBR1/2-SMAD2/3 axis
Abstract Gliomas are the most prevalent and aggressive neoplasms of the central nervous system, representing a major challenge for effective treatment and patient prognosis. This study identifies the proteasome subunit beta type-8 (PSMB8/LMP7) as a promising prognostic biomarker for glioma. Using a...
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| Format: | Article |
| Language: | English |
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Springer
2025-05-01
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| Series: | Molecular Biomedicine |
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| Online Access: | https://doi.org/10.1186/s43556-025-00268-5 |
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| author | Dongling Pei Zeyu Ma Yuning Qiu Minkai Wang Zilong Wang Xianzhi Liu Long Zhang Zhenyu Zhang Ran Li Dongming Yan |
| author_facet | Dongling Pei Zeyu Ma Yuning Qiu Minkai Wang Zilong Wang Xianzhi Liu Long Zhang Zhenyu Zhang Ran Li Dongming Yan |
| author_sort | Dongling Pei |
| collection | DOAJ |
| description | Abstract Gliomas are the most prevalent and aggressive neoplasms of the central nervous system, representing a major challenge for effective treatment and patient prognosis. This study identifies the proteasome subunit beta type-8 (PSMB8/LMP7) as a promising prognostic biomarker for glioma. Using a multiparametric radiomic model derived from preoperative magnetic resonance imaging (MRI), we accurately predicted PSMB8 expression levels. Notably, radiomic prediction of poor prognosis was highly consistent with elevated PSMB8 expression. Our findings demonstrate that PSMB8 depletion not only suppressed glioma cell proliferation and migration but also induced apoptosis via activation of the transforming growth factor beta (TGF-β) signaling pathway. This was supported by downregulation of key receptors (TGFBR1 and TGFBR2). Furthermore, interference with PSMB8 expression impaired phosphorylation and nuclear translocation of SMAD2/3, critical mediators of TGF-β signaling. Consequently, these molecular alterations resulted in reduced tumor progression and enhanced sensitivity to temozolomide (TMZ), a standard chemotherapeutic agent. Overall, our findings highlight PSMB8's pivotal role in glioma pathophysiology and its potential as a prognostic marker. This study also demonstrates the clinical utility of MRI radiomics for preoperative risk stratification and pre-diagnosis. Targeted inhibition of PSMB8 may represent a therapeutic strategy to overcome TMZ resistance and improve glioma patient outcomes. |
| format | Article |
| id | doaj-art-b094156da19e431fbfdfdef94dffbf96 |
| institution | OA Journals |
| issn | 2662-8651 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Springer |
| record_format | Article |
| series | Molecular Biomedicine |
| spelling | doaj-art-b094156da19e431fbfdfdef94dffbf962025-08-20T02:15:08ZengSpringerMolecular Biomedicine2662-86512025-05-016111610.1186/s43556-025-00268-5MRI-based machine learning reveals proteasome subunit PSMB8-mediated malignant glioma phenotypes through activating TGFBR1/2-SMAD2/3 axisDongling Pei0Zeyu Ma1Yuning Qiu2Minkai Wang3Zilong Wang4Xianzhi Liu5Long Zhang6Zhenyu Zhang7Ran Li8Dongming Yan9Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou UniversityDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou UniversityDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou UniversityDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou UniversityDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou UniversityDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou UniversityMOE Laboratory of Biosystems Homeostasis & Protection and Innovation Center for Cell Signaling Network, Life Sciences Institute, Zhejiang UniversityDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou UniversitySchool of Medicine, Hangzhou City UniversityDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou UniversityAbstract Gliomas are the most prevalent and aggressive neoplasms of the central nervous system, representing a major challenge for effective treatment and patient prognosis. This study identifies the proteasome subunit beta type-8 (PSMB8/LMP7) as a promising prognostic biomarker for glioma. Using a multiparametric radiomic model derived from preoperative magnetic resonance imaging (MRI), we accurately predicted PSMB8 expression levels. Notably, radiomic prediction of poor prognosis was highly consistent with elevated PSMB8 expression. Our findings demonstrate that PSMB8 depletion not only suppressed glioma cell proliferation and migration but also induced apoptosis via activation of the transforming growth factor beta (TGF-β) signaling pathway. This was supported by downregulation of key receptors (TGFBR1 and TGFBR2). Furthermore, interference with PSMB8 expression impaired phosphorylation and nuclear translocation of SMAD2/3, critical mediators of TGF-β signaling. Consequently, these molecular alterations resulted in reduced tumor progression and enhanced sensitivity to temozolomide (TMZ), a standard chemotherapeutic agent. Overall, our findings highlight PSMB8's pivotal role in glioma pathophysiology and its potential as a prognostic marker. This study also demonstrates the clinical utility of MRI radiomics for preoperative risk stratification and pre-diagnosis. Targeted inhibition of PSMB8 may represent a therapeutic strategy to overcome TMZ resistance and improve glioma patient outcomes.https://doi.org/10.1186/s43556-025-00268-5GliomaProteasome subunit beta type-8 (PSMB8)ProliferationApoptosisRadiomics |
| spellingShingle | Dongling Pei Zeyu Ma Yuning Qiu Minkai Wang Zilong Wang Xianzhi Liu Long Zhang Zhenyu Zhang Ran Li Dongming Yan MRI-based machine learning reveals proteasome subunit PSMB8-mediated malignant glioma phenotypes through activating TGFBR1/2-SMAD2/3 axis Molecular Biomedicine Glioma Proteasome subunit beta type-8 (PSMB8) Proliferation Apoptosis Radiomics |
| title | MRI-based machine learning reveals proteasome subunit PSMB8-mediated malignant glioma phenotypes through activating TGFBR1/2-SMAD2/3 axis |
| title_full | MRI-based machine learning reveals proteasome subunit PSMB8-mediated malignant glioma phenotypes through activating TGFBR1/2-SMAD2/3 axis |
| title_fullStr | MRI-based machine learning reveals proteasome subunit PSMB8-mediated malignant glioma phenotypes through activating TGFBR1/2-SMAD2/3 axis |
| title_full_unstemmed | MRI-based machine learning reveals proteasome subunit PSMB8-mediated malignant glioma phenotypes through activating TGFBR1/2-SMAD2/3 axis |
| title_short | MRI-based machine learning reveals proteasome subunit PSMB8-mediated malignant glioma phenotypes through activating TGFBR1/2-SMAD2/3 axis |
| title_sort | mri based machine learning reveals proteasome subunit psmb8 mediated malignant glioma phenotypes through activating tgfbr1 2 smad2 3 axis |
| topic | Glioma Proteasome subunit beta type-8 (PSMB8) Proliferation Apoptosis Radiomics |
| url | https://doi.org/10.1186/s43556-025-00268-5 |
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