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Identification and classification of glioma subtypes based on RNA-binding proteins

胶质瘤 计算生物学 肿瘤进展 比例危险模型 生存分析 癌症 肿瘤科 生物 遗传学 内科学 癌症研究 医学
作者
Xudong Liu,Lei Wu,Lei Wang,Yongsheng Li
出处
期刊:Computers in Biology and Medicine [Elsevier BV]
卷期号:174: 108404-108404 被引量:5
标识
DOI:10.1016/j.compbiomed.2024.108404
摘要

Glioma is a common and aggressive primary malignant cancer known for its high morbidity, mortality, and recurrence rates. Despite this, treatment options for glioma are currently restricted. The dysregulation of RBPs has been linked to the advancement of several types of cancer, but their precise role in glioma evolution is still not fully understood. This study sought to investigate how RBPs may impact the development and prognosis of glioma, with potential implications for prognosis and therapy. RNA-seq profiles of glioma and corresponding clinical data from the CGGA database were initially collected for analysis. Unsupervised clustering was utilized to identify crucial tumor subtypes in glioma development. Subsequent time-series analysis and MS model were employed to track the progression of these identified subtypes. RBPs playing a significant role in glioma progression were then pinpointed using weighted gene co-expression network analysis and Lasso Cox regression models. Functional analysis of these key RBP-related genes was conducted through GSEA. Additionally, the CIBERSORT algorithm was utilized to estimate immune infiltrating cells, while the STRING database was consulted to uncover potential mechanisms of the identified biomarkers. Six tumor subgroups were identified and found to be highly homogeneous within each subgroup. The progression stages of these tumor subgroups were determined using time-series analysis and a MS model. Through weighted gene co-expression network analysis, Lasso Cox, and multivariate Cox regression analysis, it was confirmed that BCLAF1 is correlated with survival in glioma patients and is closely linked to glioma progression. Functional annotation suggests that BCLAF1 may impact glioma progression by influencing RNA shearing, which in turn affects the cell cycle, Wnt signaling pathway, and other cancer development pathways. The study initially identified six subtypes of glioma progression and assessed their malignancy ranking. Furthermore, it was determined that BCLAF1 could serve as an RBP-related prognostic marker, offering significant implications for the clinical diagnosis and personalized treatment of glioma.
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