ArticlePloS one2022
Update of gene expression/methylation and MiRNA profiling in colorectal cancer; application in diagnosis, prognosis, and targeted therapy.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Research advances in key genes and regulatory mechanisms of posttranslational modifications in Parkinson's disease.PloS one · 2026Article
- Data-Driven Identification of Early Cancer-Associated Genes via Penalized Trans-Dimensional Hidden Markov Models.Biomolecules · 2025Article
- miR-4486 inhibits colorectal cancer proliferation via targeting MAP2K4 to inhibit the activation of the p38MAPK/JNK signaling.Heliyon · 2024Article
- Prognostic analysis of hepatocellular carcinoma based on cuproptosis -associated lncRNAs.BMC gastroenterology · 2024Article
- Bioinformatics Analysis of RNA-seq Data Reveals Genes Related to Cancer Stem Cells in Colorectal Cancerogenesis.International journal of molecular sciences · 2022Article
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2 authors.
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Abstract
backgroundColorectal cancer is one of the most deadliest malignancies worldwide. Due to the dearth of appropriate biomarkers, the diagnosis of this mortal disease is usually deferred, in its turn, culminating in the failure of prevention. By the same token, proper biomarkers are at play in determining the quality of prognosis. In other words, the survival rate is contingent upon the regulation of such biomarkers. MATERIALS AND
methodsThe information regarding expression (GSE41258, and GSE31905), methylation (GSE101764), and miRNA (dbDEMC) were downloaded. MEXPRESS and GEPIA confirmed the validated differentially expressed/methylated genes using TCGA data. Taking advantage of the correlation plots and receiver-operating-characteristic (ROC) curves, expression and methylation profiles were compared. The interactions between validated differentially expressed genes and differentially expressed miRNA were recognized and visualized by miRTarBase and Cytoscape, respectively. Then, the protein-protein interaction (PPI) network and hub genes were established via STRING and Cytohubba plugin. Utilizing R packages (DOSE, Enrichplot, and clusterProfiler) and DAVID database, the Functional Enrichment analysis and the detection of KEGG pathways were performed. Ultimately, in order to recognize the prognostic value of found biomarkers, they were evaluated through drawing survival plots for CRC patients.
resultsIn this research, we found an expression profile (with 13 novel genes), a methylation profile (with two novel genes), and a miRNA profile with diagnostic value. Concerning diagnosis, the expression profile was evaluated more powerful in comparison with the methylation profile. Furthermore, a prognosis-related expression profile was detected.
conclusionIn addition to diagnostic- and prognostic-applicability, the discerned profiles can assist in targeted therapy and current therapeutic strategies.
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