School of Medicine, Chongqing University, Chongqing, 400044, China; Department of Medical Oncology, Chongqing University Cancer Hospital, Chongqing, 400030, China.
Department of Medical Oncology, Chongqing University Cancer Hospital, Chongqing, 400030, China.
Comput Biol Med. 2024 May;174:108404. doi: 10.1016/j.compbiomed.2024.108404. Epub 2024 Apr 3.
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 WGCNA 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 WGCNA, 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 splicing, 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.
脑胶质瘤是一种常见且侵袭性强的原发性恶性肿瘤，其发病率、死亡率和复发率都很高。尽管如此，目前脑胶质瘤的治疗选择仍然有限。RBP 的失调与多种类型的癌症的进展有关，但它们在脑胶质瘤进化中的确切作用仍不完全清楚。本研究旨在探讨 RBP 如何影响脑胶质瘤的发生和预后，为预后和治疗提供潜在的依据。
首先收集 CGGA 数据库中脑胶质瘤的 RNA-seq 谱和相应的临床数据进行分析。利用无监督聚类方法识别脑胶质瘤发展中的关键肿瘤亚型。随后采用时间序列分析和 MS 模型跟踪这些已识别亚型的进展。利用 WGCNA 和 Lasso Cox 回归模型确定在脑胶质瘤进展中起重要作用的 RBP。通过 GSEA 对这些关键 RBP 相关基因进行功能分析。此外，利用 CIBERSORT 算法估计免疫浸润细胞，利用 STRING 数据库揭示鉴定生物标志物的潜在机制。
鉴定出 6 个肿瘤亚组，每个亚组内高度同质。通过时间序列分析和 MS 模型确定这些肿瘤亚组的进展阶段。通过 WGCNA、Lasso Cox 和多变量 Cox 回归分析，证实 BCLAF1 与脑胶质瘤患者的生存相关，与脑胶质瘤的进展密切相关。功能注释表明，BCLAF1 可能通过影响 RNA 剪接来影响脑胶质瘤的进展，进而影响细胞周期、Wnt 信号通路和其他癌症发展途径。
本研究首先鉴定了脑胶质瘤进展的 6 个亚型，并评估了它们的恶性程度排名。此外，确定 BCLAF1 可以作为 RBP 相关的预后标志物，对脑胶质瘤的临床诊断和个性化治疗具有重要意义。
