ArticleFrontiers in genetics2020
Effects of RNA Binding Proteins on the Prognosis and Malignant Progression in Prostate Cancer.
Article in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 23 citations in OpenAlex.
- Mechanistic insights and clinical implications of RNA-binding proteins in prostate cancer.Discover oncology · 2026Review
- MSI1 Accelerates Prostate Cancer Cell Proliferation, Migration and Glycolysis by Promoting ABHD2 Transcription.Biochemical genetics · 2026Article
- YTHDC1 orchestrates oncogenic splicing via the CLK1-SRSF1 splicing machinery to regulate castration-resistant prostate cancer progression.Molecular and cellular biochemistry · 2025Article
- Pathway-based cancer transcriptome deciphers a high-resolution intrinsic heterogeneity within bladder cancer classification.Journal of translational medicine · 2025Article
- Insulin-Like Growth Factor 2 mRNA-Binding Protein 2 (IGF2BP2) Promotes Castration-Resistant Prostate Cancer Progression by Regulating AR-V7 mRNA Stability.Cancer reports (Hoboken, N.J.) · 2025Article
- Identification of the gene signatures related to NK/T cell communication to evaluate the tumor microenvironment and prognostic outcomes of patients with prostate adenocarcinoma.Frontiers in immunology · 2025Article
- PABPC1L Induces IDO1 to Promote Tryptophan Metabolism and Immune Suppression in Renal Cell Carcinoma.Cancer research · 2024Article
- Bridging Health Disparities: a Genomics and Transcriptomics Analysis by Race in Prostate Cancer.Journal of racial and ethnic health disparities · 2024Article
- Cancer metastasis under the magnifying glass of epigenetics and epitranscriptomics.Cancer metastasis reviews · 2023Review
- Development of multivariable risk signature based on four immune-related RNA-binding proteins to predict survival and immune status in lung adenocarcinoma.Translational cancer research · 2022Article
- Exploring Potential Regulatory Anesthetic Drugs Based on RNA Binding Protein and Constructing CESC Prognosis Model: A Study Based on TCGA Database.Frontiers in surgery · 2022Article
- Expression profile of RNA binding protein in cervical cancer using bioinformatics approach.Cancer cell international · 2021Article
- Article
- Identification of DNA Damage Repair-Associated Prognostic Biomarkers for Prostate Cancer Using Transcriptomic Data Analysis.International journal of molecular sciences · 2021Article
- RUNX1 and REXO2 are associated with the heterogeneity and prognosis of IDH wild type lower grade glioma.Scientific reports · 2021Article
- Article
- Development and Validation of a Five-RNA-Based Signature and Identification of Candidate Drugs for Neuroblastoma.Frontiers in genetics · 2021Article
- Cervical Cancer Stem-Like Cell Transcriptome Profiles Predict Response to Chemoradiotherapy.Frontiers in oncology · 2021Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Prostate cancer (PCa) is a common lethal malignancy in men. RNA binding proteins (RBPs) have been proven to regulate the biological processes of various tumors, but their roles in PCa remain less defined. In the present study, we used bioinformatics analysis to identify RBP genes with prognostic and diagnostic values. A total of 59 differentially expressed RBPs in PCa were obtained, comprising 28 upregulated and 31 downregulated RBP genes, which may play important roles in PCa. Functional enrichment analyses showed that these RBPs were mainly involved in mRNA processing, RNA splicing, and regulation of RNA splicing. Additionally, we identified nine RBP genes (EXO1, PABPC1L, REXO2, MBNL2, MSI1, CTU1, MAEL, YBX2, and ESRP2) and their prognostic values by a protein-protein interaction network and Cox regression analyses. The expression of these nine RBPs was validated using immunohistochemical staining between the tumor and normal samples. Further, the associations between the expression of these nine RBPs and pathological T staging, Gleason score, and lymph node metastasis were evaluated. Moreover, these nine RBP genes showed good diagnostic values and could categorize the PCa patients into two clusters with different malignant phenotypes. Finally, we constructed a prognostic model based on these nine RBP genes and validated them using three external datasets. The model showed good efficiency in predicting patient survival and was independent of other clinical factors. Therefore, our model could be used as a supplement for clinical factors to predict patient prognosis and thereby improve patient survival.
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