Literature DB >> 29742509

Screening of Differentiation-Specific Molecular Biomarkers for Colon Cancer.

Lu Qi1, Yanqing Ding1,2.   

Abstract

BACKGROUND/AIMS: Owing to the lack of effective molecular markers to evaluate colon cancer differentiation grade, screening of effective molecular markers for the diagnosis and treatment of colon cancer is of great significance. This study is a screening study for molecular markers related to the differentiation of colon using the tissue-specific genes of colon.
METHODS: This study compared the expression profiles of colon cancer at various differentiation grades and screened the down-regulated genes associated with decreased differentiation. IL22RA1 gene was derived from the intersection of obtained gene and colon tissue-specific genes. We used DriverDB and The Human Protein Atlas to analyze the expression level of IL22RA1 in various tissue cells, also used Kaplan-Meier method to analyze the correlation between IL22RA1 and the survival of colon cancer patients, and then used the ROC curve to analyze the specificity and sensitivity of IL22RA1 diagnosis of differentiated colon cancer.
RESULTS: We found that IL22RA1 gene expression was progressively down-regulated in high-differentiated, moderate-differentiated, low-differentiated, and undifferentiated colon cancer tissues. Both RNA and protein levels of IL22RA1 were higher in colon tissues and colon cancer tissues than in other normal and cancer tissues. Comparison of IL22RA1 expression in different cancer cells found that IL22RA1 expression was significantly higher in CACO-2 colon cancer cells than in other cancer cells. Survival analysis showed that IL22RA1 gene expression was positively correlated with the overall survival rate of colon cancer patients (P=0.0224). ROC curve analysis revealed that IL22RA1 expression had good specificity and sensitivity to stage II colon cancer.
CONCLUSION: These findings suggest that IL22RA1 serves as a specific molecular marker for the differentiation of colon cancer.
© 2018 The Author(s). Published by S. Karger AG, Basel.

Entities:  

Keywords:  Bioinformatics; Colon cancer; Differentiation grade; Molecular marker

Mesh:

Substances:

Year:  2018        PMID: 29742509     DOI: 10.1159/000489660

Source DB:  PubMed          Journal:  Cell Physiol Biochem        ISSN: 1015-8987


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