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Updated: Dec 1, 2025

Detection of a Circulating MicroRNA Custom Panel in Patients with Metastatic Colorectal Cancer
Published on: March 14, 2019
Identification of an MiRNA-mRNA Regulatory Network in Colorectal Cancer
Ming-Fu Cui1, Yuan-Yu Wu2, Ming-Yan Chen3
1Department of Gastrointestinal Colorectal and Anal Surgery, China-Japan Union Hospital of Jilin University, Changchun, Jilin 130033, China.
Background:
Colorectal cancer (CRC) is the fourth most prevalent cancer in the world. However, the molecular mechanism underlying CRC is largely unknown.
Objective:
To explore the pathogenic mechanism of CRC and to facilitate better diagnosis and treatment of this disease.
Methods:
Differentially expressed miRNAs (DEMs) and genes (DEGs) in CRC vs. Control samples from the miRNA expression data in GSE115513 and the miRNA and mRNA expression data in the TCGA-COAD dataset were screened, followed by the construction of the miRNAmRNA regulatory network. Functional and pathway enrichment analysis, protein-protein interaction (PPI) analysis, and survival analysis were then performed for these DEGs and DEMs.
Results:
We identified 64 DEMs from the GSE115513 dataset and 265 DEMs and 2218 DEGs from the TCGA-COAD dataset. miR-27a-3p was a hub DEM with the highest degree in the miRNA-mRNA network, while GRIN2B and PCDH10 were hub DEGs targeted by multiple miRNAs, including miR-27a-3p. SNAP25 and GRIN2B were also hub DEGs with the highest degree of interactions in the PPI network. These DEMs and DEGs were significantly enriched in multiple KEGG pathways, including proteoglycans expression and cAMP signaling pathway in cancer. Finally, seven DEGs, including FJX1 Dsc2, and hsa-miR-375, were revealed to be correlated with CRC prognosis.
Conclusion:
Aberrant expressions of genes and miRNAs were involved in the pathogenesis of CRC, probably by regulating proteoglycans expression and cAMP signaling. miR-27a-3p, PCDH10, GRIN2B, FJX1, Dsc2, and hsa-miR-375 were identified as potential targets for understanding the pathogenic mechanism of CRC. In addition, FJX1, Dsc2 and hsa-miR-375 were identified as potential predictive markers for CRC prognosis.
Insights
This study identifies key microRNAs (miRNAs) and genes involved in colorectal cancer (CRC) pathogenesis. Specific molecules like miR-27a-3p and GRIN2B may offer new diagnostic and prognostic insights for CRC.
Area of Science:
- Genomics
- Molecular Biology
- Cancer Research
Background:
- Colorectal cancer (CRC) is a major global health concern, ranking as the fourth most common cancer worldwide.
- The intricate molecular mechanisms driving CRC development and progression remain largely unelucidated, hindering effective diagnosis and treatment strategies.
Purpose of the Study:
- To elucidate the molecular pathogenesis of colorectal cancer.
- To identify potential biomarkers for improved diagnosis and therapeutic targeting of CRC.
Main Methods:
- Screening of differentially expressed microRNAs (DEMs) and genes (DEGs) in CRC versus control samples using TCGA-COAD and GSE115513 datasets.
- Construction of a miRNA-mRNA regulatory network, followed by functional enrichment, pathway analysis, and protein-protein interaction (PPI) network analysis.
- Survival analysis was conducted to identify genes and miRNAs correlated with CRC prognosis.
Main Results:
- Identification of 64 DEMs in GSE115513 and 265 DEMs and 2218 DEGs in TCGA-COAD.
- miR-27a-3p emerged as a key regulatory miRNA, targeting hub genes GRIN2B and PCDH10. GRIN2B and SNAP25 were identified as significant nodes in the PPI network.
- Enrichment analysis revealed involvement in pathways such as proteoglycans expression and cAMP signaling. Seven DEGs, including FJX1 and Dsc2, and hsa-miR-375 showed correlation with CRC prognosis.
Conclusions:
- Aberrant gene and miRNA expression, particularly involving proteoglycans and cAMP signaling, contributes to CRC pathogenesis.
- miR-27a-3p, PCDH10, GRIN2B, FJX1, Dsc2, and hsa-miR-375 are proposed as potential targets for understanding CRC mechanisms.
- FJX1, Dsc2, and hsa-miR-375 demonstrate potential as predictive biomarkers for colorectal cancer patient outcomes.
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