Association studies of ERCC1 polymorphisms with lung cancer susceptibility: a systematic review and meta-analysis

Abstract

Background: Excision repair cross-complimentary group 1 (ERCC1) is an essential component of the nucleotide excision repair system that is responsible for repairing damaged DNA. Functional genetic variations in the ERCC1 gene may alter DNA repair capacity and modulate cancer risk. The putative roles of ERCC1 gene polymorphisms in lung cancer susceptibility have been widely investigated. However, the results remain controversial.

Objectives: An updated meta-analysis was conducted to explore whether lung cancer risk could be attributed to the following ERCC1 polymorphisms: rs11615 (T>C), rs3212986 (C>A), rs3212961 (A>C), rs3212948 (G>C), rs2298881 (C>A).

Methods: Several major databases (MEDLINE, EMBASE and Scopus) and the Chinese Biomedical database were searched for eligible studies. Crude odds ratios (ORs) with 95% confidence intervals (CIs) were used to measure the strength of associations.

Results: Sixteen studies with 10,106 cases and 13,238 controls were included in this meta-analysis. Pooled ORs from 11 eligible studies (8,215 cases vs. 11,402 controls) suggested a significant association of ERCC1 rs11615 with increased risk for lung cancer (homozygous: CC versus TT, OR = 1.24, 95% CI: 1.04-1.48, P = 0.02). However, such an association was disproportionately driven by a single study. Removal of that study led to null association. Moreover, initial analyses suggested that ERCC1 rs11615 exerts a more profound effect on the susceptibility of non-smokers to lung cancer than that of smokers. Moreover, no statistically significant association was found between remaining ERCC1 polymorphisms of interest and lung cancer risk, except for rs3212948 variation (heterozygous: CG vs.GG, OR = 0.78, 95% CI: 0.67-0.90, P = 0.001; dominant: CG/CC vs.GG, OR = 0.79, 95% CI: 0.69-0.91, P = 0.001).

Conclusion: Overall, this meta-analysis suggests that ERCC1 rs3212948 G>C, but not others, is a lung cancer risk-associated polymorphism. Carefully designed studies with large sample size involving different ethnicity, smoking status, and cancer types are needed to validate these findings.

Figure 1. Flow diagram of included studies for the associations between ERCC1 polymorphisms and lung cancer risk.

Figure 2. Forest plots of lung cancer risk associated with the ERCC1 polymorphism.

A, Forest plot of risk of lung cancer associated with the ERCC1 rs11615 polymorphism by a homozygous model. B,Forest plot of lung cancer risk associated with the ERCC1 rs11615 polymorphism in the stratified analyses by smoking status. The plots of heterozygous model were shown. SMK, smoker; NSMK, non-smoker. The estimate of OR and its 95% CI are plotted with a box and a horizontal line for each study; ◊ represents pooled ORs and its 95% CIs.

Figure 3. Forest plots of lung cancer risk associated with the ERCC1 polymorphisms.

A, Forest plot of lung cancer risk associated with the ERCC1 rs3212986 polymorphism. The plot of dominant model was shown. B, Forest plot of lung cancer risk associated with the ERCC1 rs3212948 polymorphism. The plot of dominant model was shown. C, Forest plot of lung cancer risk associated with the ERCC1 rs2298881 polymorphism. The plot of dominant model was shown.

Figure 4. Funnel plots of Begg's were used to detect publication bias on ERCC1 rs11615 (recessive model) and ERCC1 rs3212986 polymorphisms (homozygous model).

No significant publication bias was found. Each point represents a separate study for the indicated association. Size of each point is proportional to its weight.

Figure 5. ERCC1 mRNA expression by the genotypes of ERCC1 rs11615 and rs3212986 polymorphisms.