Abstract
BackgroundGlioma is the most common central nervous system tumor in adults, and a considerable part of them are high‐degree ones with high malignancy and poor prognosis. At present, the classification and treatment of glioma are mainly based on its histological characteristics, so studies at the molecular level are needed.MethodsRNA‐seq data from The Cancer Genome Atlas (TCGA) datasets (n = 703) and Chinese Glioma Genome Atlas (CGGA) were utilized to find out the differentially expressed RNA‐binding proteins (RBPs) between normal cerebral tissue and glioma. A prediction system for the prognosis of glioma patients based on 11 RBPs was established and validated using uni‐ and multi‐variate Cox regression analyses. STITCH and CMap databases were exploited to identify putative drugs and their targets. Single sample gene set enrichment analysis (ssGSEA) was used to calculate scores of specific immune‐related gene sets. IC50 of over 20,000 compounds in 60 cancer cell lines was collected from the CellMiner database to test the drug sensitivity prediction value of the RBP‐based signature.ResultsWe established a reliable prediction system for the prognosis of glioma patients based on 11 RBPs including THOC3, LSM11, SARNP, PABPC1L2B, SMN1, BRCA1, ZC3H8, DZIP1L, HEXIM2, LARP4B, and ZC3H12B. These RBPs were primarily associated with ribosome and post‐transcriptional regulation. RBP‐based risk scores were closely related to immune cells and immune function. We also confirmed the potential of the signature to predict the drug sensitivity of currently approved or evaluated drugs.ConclusionsDifferentially expressed RBPs in glioma can be used as a basis for prognosis prediction, new drugs screening and drug sensitivity prediction. As RBP‐based glioma risk scores were associated with immunity, immunotherapy may become an important treatment for glioma in the future.
Highlights
Glioma is the most common central nervous system tumor in adults, and a considerable part of them are high-degree ones with high malignancy and poor prognosis
In order to further prove that the RNA-binding proteins (RBPs)-based risk score established by us has good reliability, we studied the drug sensitivity of the compounds selected according to this model
We screened out genes with significant differential expression between glioma samples and normal samples based on The Cancer Genome Atlas (TCGA)-GBM, TCGA-L GG, and Chinese Glioma Genome Atlas (CGGA) datasets, and through univariate and multivariate Cox, we screened out 11 RBPs that can provide a reference for the prognosis prediction of glioma, established a model and a rigorous verification was carried out
Summary
RNA-b inding proteins (RBPs) comprise a large family of more than 2000 proteins that bind to double or single- stranded RNA through RNA-b inding domains (RBDs) to form ribonucleoprotein complexes.[1]. Some RBPs played the role of tumor suppressors and their expression often decreases in human glioma tissue and cell lines, while some others who acted as promoters are upregulated. KHSRP played a key role in metastasis of non-small cell lung cancer and may be a prognostic predictor.[3] FXR1 was another important RBP for non-small cell lung cancer (NSCLC) development, and research has found that its expression was a candidate biomarker for poor survival in a variety of solid tumors, including NSCLC. To demonstrate and annotate the integrative roles of RBPs in gliomas, in our present study, we identified the aberrantly expressed RBPs of prognostic based on Low- Grade Glioma and Glioblastoma Multiforme cohorts from the TCGA database. The top three scored subnetworks were visualized in our study
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