ArticleCancer management and research2021
Development and Validation of a Prognostic Model of RNA-Binding Proteins in Colon Adenocarcinoma: A Study Based on TCGA and GEO Databases.
Article in Cancer management and research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed, 8 citations in OpenAlex.
- Article
- Constructing a novel mitochondrial metabolism-related genes signature to evaluate tumor immune microenvironment and predict survival of colorectal cancer.Frontiers in medicine · 2025Article
- Machine learning-informed liquid-liquid phase separation for personalized breast cancer treatment assessment.Frontiers in immunology · 2024Article
- Article
- Comprehensive Characterization of RNA-Binding Proteins in Colon Adenocarcinoma Identifies a Novel Prognostic Signature for Predicting Clinical Outcomes and Immunotherapy Responses Based on Machine Learning.Combinatorial chemistry & high throughput screening · 2023Article
- Article
- Establishment and verification of a prognostic model of liver cancer by RNA-binding proteins based on the TCGA database.Translational cancer research · 2022Article
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3 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundPrevious studies reported that dysregulation of RNA-binding proteins (RBPs) is significantly associated with the development of cancer. However, there are few studies to date on the role of RBPs in colon adenocarcinoma (COAD).
methodsRNA sequencing and clinical data for COAD patients were downloaded from The Cancer Genome Atlas (TCGA) database to identify differentially expressed (DE) RBPs between COAD tissue and normal colon tissue, and then the expression and prognostic significance of these RBPs were investigated in detail by systematic bioinformatics analysis. qRT-PCR was used to validate the expressions of prognosis-related RBP-encoding genes.
resultsSeven RBPs (RPL10L, ERI1, POP1, CAPRIN2, TDRD7, SNIP1 and PPARGC1A) were identified as hub genes associated with prognosis by a series of regression analyses, and were then used to construct a prognostic model. Further analysis based on this model indicated that the overall survival (OS) of the high-risk groups was lower than that of the low-risk groups. In this prognostic model, the area under the ROC curve (AUC) was 0.694, 0.709 and 0.665 for the TCGA cohort at 1, 3 and 5 years, respectively, while the AUC was 0.671, 0.633 and 0.601 for the GEO combined cohort at 1, 3 and 5 years, respectively, indicating the good predictive ability of the model. We also built a nomogram based on the 7 RBPs in the TCGA cohort, and the model showed good discriminatory ability for COAD.
conclusionWe screened seven prognosis-related genes in COAD patients based on RBP-related genes, validated the expressions of the seven prognosis-related RBP-encoding genes by qRT-PCR and constructed a prognosis-related nomogram for patients with COAD.
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