{"title":"Three Liquid-Liquid Phase Separation-Related Genes Associated with Prognosis in Glioma","authors":"Ling Lv, Xin Zhang, Yajun Liu, Xutong Zhu, Ruihan Pan, Lifa Huang","doi":"10.2147/pgpm.s442000","DOIUrl":null,"url":null,"abstract":"<strong>Purpose:</strong> Dysregulated liquid-liquid phase separation (LLPS) instigates tumorigenesis through biomolecular condensate dysfunction. However, the association between LLPS-associated genes and glioma remains underexplored.<br/><strong>Patients and Methods:</strong> Differentially expressed genes (DEGs) of glioma were obtained from the GSE50161 dataset, including 34 glioma and 13 normal samples. We analyzed differentially expressed LLPS-related genes in glioma from public databases. These genes informed refined molecular subtyping on the TCGA-glioma dataset. CIBERSORT assessed immune cell infiltration across three subclusters. A prognostic model was devised using univariate and lasso Cox regressions on intersecting genes. Prognostic gene expression was validated in glioma cells via RT-qPCR.<br/><strong>Results:</strong> A total of 673 differentially expressed LLPS-associated genes were identified in glioma. Three distinct molecular subtypes (C1, C2, and C3) of glioma were obtained with a marked variance in the expression of immune checkpoint genes PD1 and PDL1. Differences in immune cell infiltration were observed across subtypes. In addition, a tri-gene prognostic signature (<em>TAGLN2, NTNG2</em>, and <em>IGF2BP2</em>) was derived with significant survival differences between high and low-risk groups. The prognostic model displayed impressive AUC values for 1, 3, and 5-year survival in both training and validation sets. Further analysis highlighted a notable correlation between the three prognostic genes and immune cells in glioma samples. Furthermore, we found the upregulation of TAGLN2 and IGF2BP2 and the downregulation of NTNG2 in glioma tumors and cells.<br/><strong>Conclusion:</strong> This study innovatively uncovers the significant role of LLPS-related genes in glioma tumor grading and prognosis. The constructed tri-gene prognostic model holds promise for enhancing personalized prognosis assessments and optimizing immunotherapy strategies for glioma patients.<br/><br/><strong>Keywords:</strong> liquid-liquid phase separation, glioma, prognostic model, molecular subtype, immune cell infiltration<br/>","PeriodicalId":501056,"journal":{"name":"Pharmacogenomics and Personalized Medicine","volume":"87 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pharmacogenomics and Personalized Medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2147/pgpm.s442000","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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Abstract
Purpose: Dysregulated liquid-liquid phase separation (LLPS) instigates tumorigenesis through biomolecular condensate dysfunction. However, the association between LLPS-associated genes and glioma remains underexplored. Patients and Methods: Differentially expressed genes (DEGs) of glioma were obtained from the GSE50161 dataset, including 34 glioma and 13 normal samples. We analyzed differentially expressed LLPS-related genes in glioma from public databases. These genes informed refined molecular subtyping on the TCGA-glioma dataset. CIBERSORT assessed immune cell infiltration across three subclusters. A prognostic model was devised using univariate and lasso Cox regressions on intersecting genes. Prognostic gene expression was validated in glioma cells via RT-qPCR. Results: A total of 673 differentially expressed LLPS-associated genes were identified in glioma. Three distinct molecular subtypes (C1, C2, and C3) of glioma were obtained with a marked variance in the expression of immune checkpoint genes PD1 and PDL1. Differences in immune cell infiltration were observed across subtypes. In addition, a tri-gene prognostic signature (TAGLN2, NTNG2, and IGF2BP2) was derived with significant survival differences between high and low-risk groups. The prognostic model displayed impressive AUC values for 1, 3, and 5-year survival in both training and validation sets. Further analysis highlighted a notable correlation between the three prognostic genes and immune cells in glioma samples. Furthermore, we found the upregulation of TAGLN2 and IGF2BP2 and the downregulation of NTNG2 in glioma tumors and cells. Conclusion: This study innovatively uncovers the significant role of LLPS-related genes in glioma tumor grading and prognosis. The constructed tri-gene prognostic model holds promise for enhancing personalized prognosis assessments and optimizing immunotherapy strategies for glioma patients.
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