Establishment of an alternative splicing prognostic risk model and identification of FN1 as a potential biomarker in glioblastoma multiforme
Abstract Aberrant alternative splicing and abnormal alternative splicing events (ASEs) in glioblastoma multiforme (GBM) remain largely elusive. The prognostic-associated ASEs in GBM were identified and summarized into 123 genes using GBM and LGG datasets from ASCancer Atlas and TCGA. The eleven gene...
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Nature Portfolio
2025-02-01
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| author | Xi Liu Jinming Song Zhiming Zhou Yuting He Shaochun Wu Jin Yang Zhonglu Ren |
| author_facet | Xi Liu Jinming Song Zhiming Zhou Yuting He Shaochun Wu Jin Yang Zhonglu Ren |
| author_sort | Xi Liu |
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| description | Abstract Aberrant alternative splicing and abnormal alternative splicing events (ASEs) in glioblastoma multiforme (GBM) remain largely elusive. The prognostic-associated ASEs in GBM were identified and summarized into 123 genes using GBM and LGG datasets from ASCancer Atlas and TCGA. The eleven genes (C2, COL3A1, CTSL, EIF3L, FKBP9, FN1, HPCAL1, HSPB1, IGFBP4, MANBA, PRKAR1B) were screened to develop an alternative splicing prognostic risk score (ASRS) model through machine learning algorithms. The model was trained on the TCGA-GBM cohort and validated with four external datasets from CGGA and GEO, achieving AUC values of 0.808, 0.814, 0.763, 0.859, and 0.836 for 3-year survival rates, respectively. ASRS could be an independent prognostic factor for GBM patients (HR > 1.8 across three datasets) through multivariate Cox regression analysis. The high-risk group demonstrated poorer prognosis, elevated immune scores, increased levels of immune cell infiltration, and greater differences in drug sensitivity. We found that FN1, used for model construction, contained 4 abnormal ASEs resulting in high expression of non-canonical transcripts and the presence of premature termination codon. These abnormal ASEs may be regulated by tumour-related splicing factors according to the PPI network. Furthermore, both mRNA and protein levels of FN1 were highly expressed in GBM compared to LGG, correlating with poor prognosis in GBM. In conclusion, our findings highlight the role of ASEs in affecting the progression of GBM, and the model showed a potential application for prognostic risk of patients. FN1 may serve as a promising splicing biomarker for GBM, and mechanisms of processes of aberrant splicing need to be revealed in the future. |
| format | Article |
| id | doaj-art-ee7c27423f0d41d2896919ebe3e04370 |
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| language | English |
| publishDate | 2025-02-01 |
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| spelling | doaj-art-ee7c27423f0d41d2896919ebe3e043702025-08-20T02:16:40ZengNature PortfolioScientific Reports2045-23222025-02-0115111510.1038/s41598-025-91038-4Establishment of an alternative splicing prognostic risk model and identification of FN1 as a potential biomarker in glioblastoma multiformeXi Liu0Jinming Song1Zhiming Zhou2Yuting He3Shaochun Wu4Jin Yang5Zhonglu Ren6School of Medical Information and Engineering, Guangdong Pharmaceutical UniversitySchool of Medical Information and Engineering, Guangdong Pharmaceutical UniversitySchool of Medical Information and Engineering, Guangdong Pharmaceutical UniversitySchool of Medical Information and Engineering, Guangdong Pharmaceutical UniversitySchool of Medical Information and Engineering, Guangdong Pharmaceutical UniversitySchool of Medical Information and Engineering, Guangdong Pharmaceutical UniversitySchool of Medical Information and Engineering, Guangdong Pharmaceutical UniversityAbstract Aberrant alternative splicing and abnormal alternative splicing events (ASEs) in glioblastoma multiforme (GBM) remain largely elusive. The prognostic-associated ASEs in GBM were identified and summarized into 123 genes using GBM and LGG datasets from ASCancer Atlas and TCGA. The eleven genes (C2, COL3A1, CTSL, EIF3L, FKBP9, FN1, HPCAL1, HSPB1, IGFBP4, MANBA, PRKAR1B) were screened to develop an alternative splicing prognostic risk score (ASRS) model through machine learning algorithms. The model was trained on the TCGA-GBM cohort and validated with four external datasets from CGGA and GEO, achieving AUC values of 0.808, 0.814, 0.763, 0.859, and 0.836 for 3-year survival rates, respectively. ASRS could be an independent prognostic factor for GBM patients (HR > 1.8 across three datasets) through multivariate Cox regression analysis. The high-risk group demonstrated poorer prognosis, elevated immune scores, increased levels of immune cell infiltration, and greater differences in drug sensitivity. We found that FN1, used for model construction, contained 4 abnormal ASEs resulting in high expression of non-canonical transcripts and the presence of premature termination codon. These abnormal ASEs may be regulated by tumour-related splicing factors according to the PPI network. Furthermore, both mRNA and protein levels of FN1 were highly expressed in GBM compared to LGG, correlating with poor prognosis in GBM. In conclusion, our findings highlight the role of ASEs in affecting the progression of GBM, and the model showed a potential application for prognostic risk of patients. FN1 may serve as a promising splicing biomarker for GBM, and mechanisms of processes of aberrant splicing need to be revealed in the future.https://doi.org/10.1038/s41598-025-91038-4GlioblastomaAlternative splicingASRS prognostic modelFN1 |
| spellingShingle | Xi Liu Jinming Song Zhiming Zhou Yuting He Shaochun Wu Jin Yang Zhonglu Ren Establishment of an alternative splicing prognostic risk model and identification of FN1 as a potential biomarker in glioblastoma multiforme Scientific Reports Glioblastoma Alternative splicing ASRS prognostic model FN1 |
| title | Establishment of an alternative splicing prognostic risk model and identification of FN1 as a potential biomarker in glioblastoma multiforme |
| title_full | Establishment of an alternative splicing prognostic risk model and identification of FN1 as a potential biomarker in glioblastoma multiforme |
| title_fullStr | Establishment of an alternative splicing prognostic risk model and identification of FN1 as a potential biomarker in glioblastoma multiforme |
| title_full_unstemmed | Establishment of an alternative splicing prognostic risk model and identification of FN1 as a potential biomarker in glioblastoma multiforme |
| title_short | Establishment of an alternative splicing prognostic risk model and identification of FN1 as a potential biomarker in glioblastoma multiforme |
| title_sort | establishment of an alternative splicing prognostic risk model and identification of fn1 as a potential biomarker in glioblastoma multiforme |
| topic | Glioblastoma Alternative splicing ASRS prognostic model FN1 |
| url | https://doi.org/10.1038/s41598-025-91038-4 |
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