ArticleThe Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology2024
Identification of Novel Prognostic Biomarkers for Colorectal Cancer by Bioinformatics Analysis.
Article in The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Nocturnal Melatonin Deficiency in Colorectal Cancer: Independent Predictive Value Beyond Sleep Quality.The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology · 2026Article
- A machine learning-based transcriptomic signature for predicting tumor recurrence after curative resection in T1 colorectal cancer: a retrospective multicenter cohort study (The Tw1CE trial).International journal of surgery (London, England) · 2026Article
- Bioinformatics combined with machine learning for the identification of malignant transformation markers in colorectal polyps.Frontiers in molecular biosciences · 2026Article
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8 authors.
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Abstract
BACKGROUND/
aimsColorectal cancer (CRC) ranks third among malignancies in terms of global incidence and has a poor prognosis. The identification of effective diagnostic and prognostic biomarkers is critical for CRC treatment. This study intends to explore novel genes associated with CRC progression via bioinformatics analysis. MATERIALS AND
methodsDataset GSE184093 was selected from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs) between CRC and noncancerous specimens. Functional enrichment analyses were implemented for probing the biological functions of DEGs. Gene Expression Profiling Interactive Analysis and Kaplan-Meier plotter databases were employed for gene expression detection and survival analysis, respectively. Western blotting and real-time quantitative polymerase chain reaction were employed for detecting molecular protein and messenger RNA levels, respectively. Flow cytometry, Transwell, and CCK-8 assays were utilized for examining the effects of GBA2 and ST3GAL5 on CRC cell behaviors.
resultsThere were 6464 DEGs identified, comprising 3005 downregulated DEGs (dDEGs) and 3459 upregulated DEGs (uDEGs). Six dDEGs were significantly associated with the prognoses of CRC patients, including PLCE1, PTGS1, AMT, ST8SIA1, ST3GAL5, and GBA2. Upregulating ST3GAL5 or GBA2 repressed the malignant behaviors of CRC cells.
conclusionWe identified 6 genes related to CRC progression, which could improve the disease prognosis and treatment.
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