A novel model-based identification and validation of pivotal RNA-binding protein in the evolution of glioma

Autor: Xudong Liu, Rui Li, Zhe Liu, Yafan Wang, Yu Zhang, Mengdi Fan, Ying Ma, Tao Peng, Lijun Zhao, Jinke Fan, Jiangshan Bai, Xinqiang Song, Yating Zhang, Lei Wang
Rok vydání: 2022
DOI: 10.21203/rs.3.rs-1778371/v1
Popis: Background Glioma is a primary malignant cancer of the most common and aggressive sort occurring in the neuroectoderm, with an extremely high incidence of morbidity, mortality, and recurrence. There are limited treatment options for glioma. It is recognized that dysregulation of RNA binding proteins (RBPs) is intimately involved in the occurrence and progression of multiple malignant cancers. However, the role of RBP in glioma is not fully understood. In the current study, we used a new model to predict the course of glioma development and prognosis related to RBP. Methods To begin with, we obtained RNA-seq profiles of glioma and matched clinical data from the Chinese Glioma Genome Data (CGGA) database. The unsupervised clustering algorithms such as the K-means clustering algorithm, t-SNE, U-MAP, and principal component analysis were used to identify tumor subtypes that were pivotal in the development of glioma. Subsequently the progression of tumor subtypes was determined by the MS scoring model and proposed time series analysis. Next, RBPs with a major role in the progression of glioma were identified by weighted gene co-expression network analysis and Lasso Cox regression models. Functional analysis of key RBP-related genes was performed by gene set enrichment analysis (GSEA) and the STRING database to reveal the potential mechanisms of the biomarker. Results A total of six tumor subgroups were identified and were strongly homogeneous among subgroups. The stages of progression of the six tumor subgroups were identified by the proposed time-series analysis and MS model. We confirmed that BCLAF1 was correlated with survival in glioma patients and was closely associated with the progression of glioma by weighted gene co-expression network analysis, Lasso Cox, and multivariate Cox regression analysis. Finally, Functional annotation shows that BCLAF1 may influence the progression of glioma through RNA shearing that affects cell cycle, Wnt signaling pathway, and other cancer development signals. Conclusions In summary, the present study first identified six subtypes of glioma progression as well as the malignancy ranking. Secondly, it was established that BCLAF1 could be used as an RBP-related prognostic marker with extremely important applications in the clinical diagnosis and personalized treatment of glioma.
Databáze: OpenAIRE