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ITGB4 is a novel prognostic factor in colon cancer.

Meng Li | Xia Jiang | Guiqi Wang | Congjie Zhai | Ying Liu | Hongyan Li | Yan Zhang | Weifang Yu | Zengren Zhao
Journal of Cancer | 2019

Integrin β4 (ITGB4) has been reported to be involved in carcinomas. Currently, ITGB4 has been characterized in colon cancer, however, its clinical significance is not very clear. In the present study, we utilized the large public datasets from NCBI Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases and collected clinical samples in our center to investigate the transcriptional expressions of ITGB4 in colon cancer, and then explored the associations of ITGB4 with clinicopathological features and overall survival. The statistical analyses suggested that ITGB4 mRNA expressions were up-regulated significantly in colon cancer. High ITGB4 expression was observed to be associated with elder onset age, proximal tumor location, and high microsatellite instability (MSH) status. Further, Kaplan-Meier curves and univariate analysis demonstrated high ITGB4 expression was significantly associated with unfavorable overall survival in colon cancer (HR=1.292, 95%CI=1.084-1.540, P=0.004). And significant association was also found after adjusting the confounding factors including age, gender, and stage (adjusted HR=1.254, 95%CI=1.050-1.497, P=0.012). The annotation of ITGB4 co-expressed genes suggested the pathways including cell growth, positive regulation of cell migration, and apoptotic signaling might be involved in the potential mechanisms of ITGB4 in colon cancer development. The molecular regulation mechanism of ITGB4 ectopic expression in colon cancer was also explored and the results indicated that ITGB4 might be up-regulated by the transcription factor FOSL1 (FOS like 1, AP-1 Transcription Factor Subunit) and its promoter hypomethylation. Our results revealed that ITGB4 might be a therapeutic target and prognosis marker for individual therapy of colon cancer.

Pubmed ID: 31602273

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GraphPad Prism (tool)

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Statistical analysis software that combines scientific graphing, comprehensive curve fitting (nonlinear regression), understandable statistics, and data organization. Designed for biological research applications in pharmacology, physiology, and other biological fields for data analysis, hypothesis testing, and modeling.

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Thermo Fisher Scientific (tool)

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