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Construction of a SUMOylation regulator-based prognostic model in low-grade glioma.

ABSTRACT: Low-grade glioma (LGG) is an intracranial malignant tumour that mainly originates from astrocytes and oligodendrocytes. SUMOylation is one of the post-translational modifications but studies of SUMOylation in LGG is quite limited. Transcriptome data, single nucleotide variant (SNV) data and clinical data of LGG were derived from public databases. The differences between the expression of SUMOylation regulators in LGG and normal brain tissue were analysed. Cox regression was used to construct a prognostic model in the training cohort. Kaplan-Meier survival curves and ROC curves were plotted in the training and the validation cohort to evaluate the effectiveness of the prognostic model. GO and KEGG analyses were applied to preliminarily analyse the biological functions. Compared with normal brain tissue, SENP1 and SENP7 were up-regulated and SENP5 was down-regulated in LGG. SUMOylation regulators may be involved in functions such as mRNA splicing, DNA replication, ATPase activity and spliceosome. One prognostic model was established based on the 4 SUMOylation regulator-related signatures (RFWD3, MPHOSPH9, WRN and NUP155), which had a good predictive ability for overall survival. This study is expected to provide targets for the diagnosis and treatment of low-grade glioma.

SUBMITTER: Li X

PROVIDER: S-EPMC8184686 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Introduction: The EORTC22033-26033 clinical trial investigated whether initial temozolomide (TMZ) chemotherapy confers survival advantage compared to radiotherapy (RT) in low grade glioma patients. In this study we performed gene expression profiling on tissues from this trial in order to identify markers associated with progression free survival and treatment response in this well-defined cohort of patients. Methods: Gene expression profiling, performed on 195 samples, was used to assign tumors to one of six intrinsic glioma subtypes (IGS; molecularly similar tumors predefined by unsupervised gene expression analysis) and to extract the cellular composition of immune infiltrates. DNA copy number changes were determined on samples assigned to IGS-16. Results: We confirm that IGS-subtypes are prognostic in EORTC22033-26033 clinical trial samples. Specific genetic changes segregate in distinct IGS subtypes: most samples assigned to IGS-9 have IDH-mutations combined with 1p19q codeletion, samples assigned to IGS-17 have IDH-mutations with intact 1p19q chromosomal arms and samples assigned to other intrinsic subtypes often are IDH-wildtype and 1p19q intact. A trend towards benefit from RT compared to TMZ was observed for samples assigned to IGS-9 (HR for TMZ is 1.90, 95% CI [0.95, 3.80], P=0.065), but not for samples assigned to IGS-17 (HR for TMZ vs RT is 0.87, 95% CI[0.50, 1.51], P=0.62). We did not identify genes significantly associated with progression free survival (PFS) within intrinsic subtypes, though follow-up time is limited. We also show that LGGs and GBMs differ in their immune-infiltrate with LGGs having higher suppressor and lower effector cell populations compared to GBMs. This suggests that LGGs are less amenable to checkpoint inhibitor type immune therapies than GBMs. Gene expression analysis and copy number analysis also identified one patient with a pilocytic astrocytoma (PA). Conclusion: Intrinsic glioma subtypes are prognostic for PFS in EORTC22033-26033 clinical trial samples.

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Construction of a SUMOylation regulator-based prognostic model in low-grade glioma.

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