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The Association and Risk Prediction of the Ubiquitination Pathway Genetic Variants and Lung Cancer Incidence: A
Jianing Mao1, Lingyun Leng1, Tianyi Zhu1
1Department of Epidemiology, School of Public Health; Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China.
Background:
Dysregulation of the ubiquitin-proteasome system (UPS) promotes tumorigenesis, but population-level evidence linking UPS variants to lung cancer risk is limited.
Methods:
We conducted a two-stage genetic association study. In the discovery stage, using a nested case-control design, 70,801 SNPs from 750 UPS-related genes were analyzed in 612 lung cancer cases and 901 controls from the Shanghai Suburban Adult Cohort Biobank. Significant loci were validated in an independent case-control cohort consisting of 2,718 individuals. We further evaluated the predictive performance of validated SNPs and performed functional analyses, including expression quantitative trait locus, enhancer-promoter interaction, and The Cancer Genome Atlas analyses.
Results:
We identified 2,527 SNPs associated with lung cancer risk in the discovery cohort, six of which were validated. Incorporating these variants significantly improved risk prediction beyond traditional risk models in both cohorts (AUCdiscovery: 0.64 vs. 0.53; AUCvalidation: 0.72 vs. 0.57; all P < 0.001). The MGRN1 rs11640681 A>G variant was associated with increased risk of lung cancer [ORdiscovery(95% CI), 1.26 (1.04-1.53), P = 0.017; ORvalidation(95% CI), 1.32(1.07-1.64), P = 0.011]. Functional analyses suggest the G allele may downregulate MGRN1 expression by enhancer-promoter interaction. Higher MGRN1 expression was present in normal lung compared with non-small cell lung cancer tissues and was associated with longer survival of patients with lung cancer.
Conclusions:
Our findings suggest UPS genetic variants contribute to lung cancer risk, with the G allele of rs11640681 potentially increasing risk by downregulating MGRN1, a potential tumor-suppressor.
Impact:
These findings enhance the understanding of lung cancer etiology and highlight potential biomarkers for risk stratification in a population setting.
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