PTPN13 rs989902 and CHEK2 rs738722 are associated with esophageal cancer

Abstract

Purpose

Individual genetic background can play an essential role in determining the development of esophageal squamous cell carcinoma (ESCC). PTPN13 and CHEK2 play important roles in the pathogenesis of ESCC. This case-control study aimed to analyze the association between gene polymorphisms and ESCC susceptibility.

Methods

DNA was extracted from the peripheral blood of patients. The Agena MassARRAY platform was used for the genotyping. Statistical analysis was conducted using the chi-squared test or Fisher’s exact test, logistic regression analysis, and stratification analysis.

Results

The ‘G’ allele of rs989902 (PTPN13) and the ‘T’ allele of rs738722 (CHEK2) were both associated with an increased risk of ESCC (rs989902: OR = 1.23, 95% CI = 1.02–1.47, p = 0.028; rs738722: OR = 1.28, 95% CI = 1.06–1.55, p = 0.011). Stratification analysis showed that SNPs (rs989902 and rs738722) were notably correlated with an increased risk of ESCC after stratification for age, sex, smoking, and drinking status. In addition, rs738722 might be associated with lower stage, while rs989902 had a lower risk of metastasis.

Conclusion

Our findings display that PTPN13 rs989902 and CHEK2 rs738722 are associated with an increased risk of ESCC in the Chinese Han population.

Keywords:

• Esophageal squamous cell carcinoma (ESCC)
• PTPN13
• CHEK2
• gene
• polymorphisms

Acknowledgments

We thank all patients and individuals for their participation, as well as clinicians and other hospital staff. We are also grateful to the editors and reviewers for their patience and valuable comments on this work.

Ethics approval and consent to participate

This study was approved by the Ethics Committee of Hainan Cancer Hospital. This study conformed to the ethical principles for medical research involving humans outlined in the World Medical Association Declaration of Helsinki. All participants signed an informed consent form before participating in the study.

Consent to publication

All authors agreed to publish the manuscript.

Authors’ contributions

Conceptualization, Jian Song; methodology, Dunjing Zhong; Ping Li and Yongyu Li, software; Zhuang Chen and Feixiang Hu; data curation, Guihong Yuan, Zhaowei Chen, and Shuyong Yu; writing, review, and editing; Ruisha Tu. All authors have read and approved the manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The datasets used and analyzed in the current study are available from the corresponding author upon reasonable request.

Additional information

Funding

This work was supported by the 2020 Hainan Provincial Major Science and Technology Project (grant number: ZDKJ202005) and the specific research fund of The Innovation Platform for Academicians of Hainan Province (grant number: YSPTZX202029).