FEN1 status and its correlation with clinicopathologic characteristic in colorectal cancer

Author:

Guo Yundi1,Du Zixuan2,Zhou Yuanshuai3,Sun Haijun1,Liang Rui1,Sun Min-Xuan3,Tang Zaixiang2,Liu Song-Bai1

Affiliation:

1. Suzhou Key laboratory of Medical Biotechnology, Suzhou Vocational Health College, Suzhou 215009, Jiangsu Province, China

2. Department of Biostatistics, School of Public Health, Medical College of Soochow University, Suzhou 215123, China

3. Jiangsu Key Laboratory of Medical Optics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215008, China

Abstract

Objective: The goal of this study was to investigate the status of FEN1 in Colorectal cancer (CRC) and determine the potential correlation between FEN1 expression level and clinicopathological parameters in CRC patients. Methods: Expression of FEN1 in CRC tissue on tissue microarray was detected using immunohistochemistry (IHC). The relationship between FEN1 expression status and clinicopathologic characteristics of CRC was analyzed by Chi-square test. The survival data of TCGA Colon Cancer (COAD) were obtained from ucsc xena browser (https://xenabrowser.net/). Patients were separated into higher and lower expression groups by median FEN1 expression. The association with prognosis of CRC patients was determined by Kaplan-Meier survival analysis with Log-rank test. Results: FEN1expression level and cellular localization had wide variability among different individuals, we classified the staining results into four types: both positive in nucleus and cytoplasm, both negative in nucleus and cytoplasm, only positive in nucleus, only positive in cytoplasm. Moreover, FEN1 expression status only correlated with patient’s metastasis status, and the patients in NLCL group showed more risk of cancer cell metastasis. Conclusion: Our results indicate that FEN1 expression level and cellular localization had wide variability in CRC and is not a good biomarker in CRC.

Publisher

Bentham Science Publishers Ltd.

Subject

Organic Chemistry,Computer Science Applications,Drug Discovery,General Medicine

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