Abstract
Objective
To construct and verificate an RNA-binding protein (RBP)-associated prognostic model for gliomas using integrated bioinformatics analysis.
Methods
RNA-sequencing and clinic pathological data of glioma patients from The Cancer Genome Atlas (TCGA) database and the Chinese Glioma Genome Atlas database (CGGA) were downloaded. The aberrantly expressed RBPs were investigated between gliomas and normal samples in TCGA database. We then identified prognosis related hub genes and constructed a prognostic model. This model was further validated in the CGGA-693 and CGGA-325 cohorts.
Results
Totally 174 differently expressed genes-encoded RBPs were identified, containing 85 down-regulated and 89 up-regulated genes. We identified five genes-encoded RBPs (ERI1, RPS2, BRCA1, NXT1, and TRIM21) as prognosis related key genes and constructed a prognostic model. Overall survival (OS) analysis revealed that the patients in the high-risk subgroup based on the model were worse than those in the low-risk subgroup. The area under the receiver operator characteristic curve (AUC) of the prognostic model was 0.836 in the TCGA dataset and 0.708 in the CGGA-693 dataset, demonstrating a favorable prognostic model. Survival analyses of the five RBPs in the CGGA-325 cohort validated the findings. A nomogram was constructed based on the five genes and validated in the TCGA cohort, confirming a promising discriminating ability for gliomas.
Conclusion
The prognostic model of the five RBPs might serve as an independent prognostic algorithm for gliomas.
References
Keene JD. RNA regulons: coordination of posttranscriptional events. Nat Rev Genet, 2007,8(7):533–543
Turner M, Díaz-Muñoz MD. RNA-binding proteins control gene expression and cell fate in the immune system. Nat Immunol, 2018,19(2):120–129
Hentze MW, Castello A, Schwarzl T, et al. A brave new world of RNA-binding proteins. Nat Rev Mol Cell Biol, 2018,19(5):327–341
Corley M, Burns MC, Yeo GW. How RNA-Binding Proteins Interact with RNA: Molecules and Mechanisms. Mol Cell, 2020,78 (1):9–29
Bohnsack KE, Bohnsack MT. RNA-Binding Proteins Chaperone Ribonucleoprotein Complex Assembly to Solve the RNA-Folding Problem. Cell, 2019,179(6):1248–1250
Marx V. Profiling the dress codes of RNA-binding proteins. Nat Methods, 2018,15(9):655–658
Ye J, Blelloch R. Regulation of pluripotency by RNA binding proteins. Cell Stem Cell, 2014,15(3):271–280
Chénard CA, Richard S. New implications for the QUAKING RNA binding protein in human disease. J Neurosci Res, 2008,86(2):233–242
Neelamraju Y, Gonzalez-Perez A, Bhat-Nakshatri P, et al. Mutational landscape of RNA-binding proteins in human cancers. RNA Biol, 2018,15(1):115–129
Majumder P, Chu JF, Chatterjee B, et al. Co-regulation of mRNA translation by TDP-43 and Fragile X Syndrome protein FMRP. Acta Neuropathol, 2016,132(5):721–738
Wang GS, Cooper TA. Splicing in disease: disruption of the splicing code and the decoding machinery. Nat Rev Genet, 2007,8(10):749–761
Ostrom QT, Gittleman H, Truitt G, et al. CBTRUS Statistical Report: Primary Brain and Other Central Nervous System Tumors Diagnosed in the United States in 2011–2015. Neuro-oncology, 2018,20 (suppl_4): iv1–iv86
Louis DN, Perry A, Reifenberger G, et al. The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary. Acta Neuropathol, 2016,131(6):803–820
Correa BR, De Araujo PR, Qiao M, et al. Functional genomics analyses of RNA-binding proteins reveal the splicing regulator SNRPB as an oncogenic candidate in glioblastoma. Genome Biol, 2016,17(1):125
Cheung HC, Hai T, Zhu W, et al. Splicing factors PTBP1 and PTBP2 promote proliferation and migration of glioma cell lines. Brain, 2009,132(Pt 8):2277–2288
Gerstberger S, Hafner M, Tuschl T. A census of human RNA-binding proteins. Nat Rev Genet, 2014,15(12):829–845
Wen PY, Reardon DA. Neuro-oncology in 2015: Progress in glioma diagnosis, classification and treatment. Nat Rev Neurol, 2016,12(2):69–70
Mesrati MH, Behrooz AB, Abuhamad AY, et al. Understanding Glioblastoma Biomarkers: Knocking a Mountain with a Hammer. Cells, 2020,9(5):1236
Delgado-Martín B, Medina MÁ. Advances in the Knowledge of the Molecular Biology of Glioblastoma and Its Impact in Patient Diagnosis, Stratification, and Treatment. Adv Sci (Weinh), 2020,7(9):1902971
Rivera AL, Pelloski CE, Gilbert MR, et al. MGMT promoter methylation is predictive of response to radiotherapy and prognostic in the absence of adjuvant alkylating chemotherapy for glioblastoma. Neurooncology, 2010,12(2):116–121
Zhang C, Moore LM, Li X, et al. IDH1/2 mutations target a key hallmark of cancer by deregulating cellular metabolism in glioma. Neuro-oncology, 2013,15(9):1114-1126
Siegal T. Clinical Relevance of Prognostic and Predictive Molecular Markers in Gliomas. Adv Tech Stand Neurosurg, 2016 (43):91–108
Pereira B, Billaud M, Almeida R. RNA-Binding Proteins in Cancer: Old Players and New Actors. Trends Cancer, 2017,3(7):506–528
Wang J, Qi J, Hou X. Systematically Dissecting the Function of RNA-Binding Proteins During Glioma Progression. Front Genet, 2019,10:1394
Cao S, Zheng J, Liu X, et al. FXR1 promotes the malignant biological behavior of glioma cells via stabilizing MIR17HG. J Exp Clin Cancer Res, 2019,38(1):37
Zhao Z, Wang Y, Yun D, et al. cell migration and cell senescence in human glioma. Am J Cancer Res, 2020,10(1):114–130
Lee JH, Liu R, Li J, et al. Stabilization of phosphofructokinase 1 platelet isoform by AKT promotes tumorigenesis. Nat Commun, 2017,8(1):949
Macdonald TJ, Pollack IF, Okada H, et al. Progressionassociated genes in astrocytoma identified by novel microarray gene expression data reanalysis. Methods Mol Biol, 2007,377:203–222
Cho J, Park J, Shin SC, et al. USP47 Promotes Tumorigenesis by Negative Regulation of p53 through Deubiquitinating Ribosomal Protein S2. Cancers (Basel), 2020,12(5):1137
Rasmussen RD, Gajjar MK, Tuckova L, et al. BRCA1-regulated RRM2 expression protects glioblastoma cells from endogenous replication stress and promotes tumorigenicity. Nat Commun, 2016,7:13398
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
The authors declare no conflicts of interest.
Additional information
This study was supported by the National Natural Science Foundation of China (No. 82072795).
Supplementary data
Rights and permissions
About this article
Cite this article
Peng, P., Chen, Zr., Zhang, Xl. et al. Construction and Verification of an RNA-Binding Protein-Associated Prognostic Model for Gliomas. CURR MED SCI 43, 156–165 (2023). https://doi.org/10.1007/s11596-022-2694-1
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11596-022-2694-1