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.
Abbreviations
LLPS, Liquid-liquid phase separation; Geo, Gene Expression Omnibus; DEGs, Differentially Expressed Genes; KM, Kaplan-Meier; DMEM, Dulbecco’s Modified Eagle Medium; cDNA, complementary DNA; CDF, cumulative distribution function; PCA, principal component analysis.
Data Sharing Statement
The data that support the findings of this study are available from the corresponding author, [LH], on special request.
Ethical Approval
This study is based on open-source data, there are no ethical issues and other conflicts of interest. Thus, the study was exempted from the approval of local ethics committees (Ethics Committees of The First Affiliated Hospital of Zhejiang Chinese Medical University).
Author Contributions
All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.
Disclosure
The authors report no conflicts of interest in this work.