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Association between XRCC3 Thr241Met Polymorphism and Risk of Breast Cancer: Meta-Analysis of 23 Case-Control Studies.

Chai F, Liang Y, Chen L, Zhang F, Jiang J - Med. Sci. Monit. (2015)

Bottom Line: However, the finding remains controversial.We included 23 studies consisting of 13513 cases and 14100 controls in our study.We can conclude that XRCC3 Thr241Met polymorphism might be associated with breast cancer risk, especially in Asian populations and in patients without family history of breast cancer.

View Article: PubMed Central - PubMed

Affiliation: Breast Disease Center, Southwest Hospital, Third Military Medical University, Chongqing, China (mainland).

ABSTRACT

Background: Studies have shown that gene and environmental factors, such as BRCA1/2 mutations, ionized radiation, and chemical carcinogens, are related with breast cancer. X-ray repair cross-complementing group 3 (XRCC3) is involved in homologous repair of double DNA breaks. It was reported that Thr241Met single-nucleotide polymorphism (SNP) in XRCC3 is associated with increased risk of breast cancer. However, the finding remains controversial. The current meta-analysis aims to determine whether XRCC3 Thr241Met polymorphism is associated with increased risk of breast cancer.

Material and methods: We performed a meta-analysis of association between XRCC3 T241M polymorphism and the risk of breast cancer. Crude odds ratios (ORs) together with 95% confidence intervals (CIs) were used to assess the strength of association in dominant, recessive, and homozygote models.

Results: We included 23 studies consisting of 13513 cases and 14100 controls in our study. For meta-analysis on the entire database, association of the SNP and breast cancer risk was observed in recessive (OR=1.10, 95% CI: 1.03-1.18, p=0.005) and homozygote (OR=1.09, 95% CI: 1.01-1.18, p=0.023) models. For the analysis on the Asian population subgroup, association of the SNP and breast cancer risk was also observed in recessive (OR=1.615, 95% CI: 1.17-2.228, p=0.004) and homozygote (OR=1.609, 95% CI: 1.154-2.241, p=0.005) models. For the evaluation of the patients without family history of breast cancer, association of the SNP and breast cancer risk was observed in dominant (OR=1.364, 95% CI: 1.096-1.698, p=0.005), recessive (OR=1.336, 95% CI: 0.999-1.788, p=0.051) and homozygote (OR=1.492, 95% CI: 1.085-2.051, p=0.014) models.

Conclusions: We can conclude that XRCC3 Thr241Met polymorphism might be associated with breast cancer risk, especially in Asian populations and in patients without family history of breast cancer.

No MeSH data available.


Related in: MedlinePlus

Forest plots for Asian subgroup. (A) Dominant model: TM+MM vs. TT. (B) Recessive model: MM vs. TM+TT. (C) Homozygote model: MM vs. TT.
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f3-medscimonit-21-3231: Forest plots for Asian subgroup. (A) Dominant model: TM+MM vs. TT. (B) Recessive model: MM vs. TM+TT. (C) Homozygote model: MM vs. TT.

Mentions: First of all, we performed the analysis for the entire database. The M-H fixed-effects model was applied on the subgroup dataset as well as the entire database with 3 different analysis models (dominant, recessive, and homozygote) to assess the heterogeneity. Based on the results, we selected different methods (M-H fixed-effects model or D-L random-effects model [29]) for different analyses. By definition, with I2<25%, the fixed-effects model should be applied, whereas with I2>75%, the random-effects model should be used due to significant heterogeneity. For medium heterogeneity, it is reasonable to use either fixed- or random-effects models. However, for databases smaller than 10 studies, it is more reasonable to apply the fixed-effects model in the analysis. ORs were derived based on the analysis, and corresponding p value was acquired as well. Final results for the entire database are presented in Table 3. Corresponding forest plots for each model are shown in Figure 2. For recessive and homozygote models, the fixed-effects model was applied based on their medium heterogeneity. A significant increase of risk of breast cancer was observed in both models, with the overall OR as 1.10 [95% CI, 1.03–1.18, p=0.005] and 1.09 [95% CI, 1.01–1.18, p=0.023], respectively. For the dominant model, the overall OR was 1.01 [95% CI, 0.06–1.06, p=0.765]. No significant heterogeneity was observed (I2=24%). However, there was no evidence of a strong association between the polymorphism and the risk of breast cancer. In the subgroup analysis, as shown in Table 4, significantly increased risks were detected in recessive and homozygote models within Asian populations. We could not find a significant association between XRCC3 T241M and the risk of breast cancer in white and American populations. A shift pattern was observed with all 3 models within these 2 subgroups. For the white subgroup, overall OR for the dominant model was 0.97 [95% CI, 0.91–1.04, p=0.364] and heterogeneity index I2 was 29%. For the recessive model, the overall OR was 1.07 [95% CI, 0.98–1.17, p=0.117] and heterogeneity index I2 was 54.8%. For homozygote comparison, the overall OR was 1.04 [95% CI, 0.95–1.14, p=0.429] and heterogeneity index I2 was 58.1%. For the American subgroup, with the dominant model the overall OR was 1.07 [95% CI, 0.96–1.18, p=0.239]. For the recessive model, the overall OR was 1.11 [95% CI, 0.95–1.28, p=0.176]. For the homozygote model, the overall OR was 1.13 [95% CI, 0.97–1.32, p=0.124]. Similar to the white subgroup, no association between XRCC3 Thr241Met and increased risk of breast cancer was found within the American population. With the Asian subgroup, the forest plots of all 3 models are shown in Figure 3. Overall OR was 1.08 [95% CI, 0.93–1.26, p=0.314] with the dominant model. For the recessive model, the overall OR was 1.62 [95% CI, 1.17–2.23, p=0.004]. For the homozygote model, the overall OR was 1.61 [95% CI, 1.15–2.24, p=0.005]. An association between the SNP and breast cancer risk was observed among Asian populations with the recessive model and homozygote comparison.


Association between XRCC3 Thr241Met Polymorphism and Risk of Breast Cancer: Meta-Analysis of 23 Case-Control Studies.

Chai F, Liang Y, Chen L, Zhang F, Jiang J - Med. Sci. Monit. (2015)

Forest plots for Asian subgroup. (A) Dominant model: TM+MM vs. TT. (B) Recessive model: MM vs. TM+TT. (C) Homozygote model: MM vs. TT.
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Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4627365&req=5

f3-medscimonit-21-3231: Forest plots for Asian subgroup. (A) Dominant model: TM+MM vs. TT. (B) Recessive model: MM vs. TM+TT. (C) Homozygote model: MM vs. TT.
Mentions: First of all, we performed the analysis for the entire database. The M-H fixed-effects model was applied on the subgroup dataset as well as the entire database with 3 different analysis models (dominant, recessive, and homozygote) to assess the heterogeneity. Based on the results, we selected different methods (M-H fixed-effects model or D-L random-effects model [29]) for different analyses. By definition, with I2<25%, the fixed-effects model should be applied, whereas with I2>75%, the random-effects model should be used due to significant heterogeneity. For medium heterogeneity, it is reasonable to use either fixed- or random-effects models. However, for databases smaller than 10 studies, it is more reasonable to apply the fixed-effects model in the analysis. ORs were derived based on the analysis, and corresponding p value was acquired as well. Final results for the entire database are presented in Table 3. Corresponding forest plots for each model are shown in Figure 2. For recessive and homozygote models, the fixed-effects model was applied based on their medium heterogeneity. A significant increase of risk of breast cancer was observed in both models, with the overall OR as 1.10 [95% CI, 1.03–1.18, p=0.005] and 1.09 [95% CI, 1.01–1.18, p=0.023], respectively. For the dominant model, the overall OR was 1.01 [95% CI, 0.06–1.06, p=0.765]. No significant heterogeneity was observed (I2=24%). However, there was no evidence of a strong association between the polymorphism and the risk of breast cancer. In the subgroup analysis, as shown in Table 4, significantly increased risks were detected in recessive and homozygote models within Asian populations. We could not find a significant association between XRCC3 T241M and the risk of breast cancer in white and American populations. A shift pattern was observed with all 3 models within these 2 subgroups. For the white subgroup, overall OR for the dominant model was 0.97 [95% CI, 0.91–1.04, p=0.364] and heterogeneity index I2 was 29%. For the recessive model, the overall OR was 1.07 [95% CI, 0.98–1.17, p=0.117] and heterogeneity index I2 was 54.8%. For homozygote comparison, the overall OR was 1.04 [95% CI, 0.95–1.14, p=0.429] and heterogeneity index I2 was 58.1%. For the American subgroup, with the dominant model the overall OR was 1.07 [95% CI, 0.96–1.18, p=0.239]. For the recessive model, the overall OR was 1.11 [95% CI, 0.95–1.28, p=0.176]. For the homozygote model, the overall OR was 1.13 [95% CI, 0.97–1.32, p=0.124]. Similar to the white subgroup, no association between XRCC3 Thr241Met and increased risk of breast cancer was found within the American population. With the Asian subgroup, the forest plots of all 3 models are shown in Figure 3. Overall OR was 1.08 [95% CI, 0.93–1.26, p=0.314] with the dominant model. For the recessive model, the overall OR was 1.62 [95% CI, 1.17–2.23, p=0.004]. For the homozygote model, the overall OR was 1.61 [95% CI, 1.15–2.24, p=0.005]. An association between the SNP and breast cancer risk was observed among Asian populations with the recessive model and homozygote comparison.

Bottom Line: However, the finding remains controversial.We included 23 studies consisting of 13513 cases and 14100 controls in our study.We can conclude that XRCC3 Thr241Met polymorphism might be associated with breast cancer risk, especially in Asian populations and in patients without family history of breast cancer.

View Article: PubMed Central - PubMed

Affiliation: Breast Disease Center, Southwest Hospital, Third Military Medical University, Chongqing, China (mainland).

ABSTRACT

Background: Studies have shown that gene and environmental factors, such as BRCA1/2 mutations, ionized radiation, and chemical carcinogens, are related with breast cancer. X-ray repair cross-complementing group 3 (XRCC3) is involved in homologous repair of double DNA breaks. It was reported that Thr241Met single-nucleotide polymorphism (SNP) in XRCC3 is associated with increased risk of breast cancer. However, the finding remains controversial. The current meta-analysis aims to determine whether XRCC3 Thr241Met polymorphism is associated with increased risk of breast cancer.

Material and methods: We performed a meta-analysis of association between XRCC3 T241M polymorphism and the risk of breast cancer. Crude odds ratios (ORs) together with 95% confidence intervals (CIs) were used to assess the strength of association in dominant, recessive, and homozygote models.

Results: We included 23 studies consisting of 13513 cases and 14100 controls in our study. For meta-analysis on the entire database, association of the SNP and breast cancer risk was observed in recessive (OR=1.10, 95% CI: 1.03-1.18, p=0.005) and homozygote (OR=1.09, 95% CI: 1.01-1.18, p=0.023) models. For the analysis on the Asian population subgroup, association of the SNP and breast cancer risk was also observed in recessive (OR=1.615, 95% CI: 1.17-2.228, p=0.004) and homozygote (OR=1.609, 95% CI: 1.154-2.241, p=0.005) models. For the evaluation of the patients without family history of breast cancer, association of the SNP and breast cancer risk was observed in dominant (OR=1.364, 95% CI: 1.096-1.698, p=0.005), recessive (OR=1.336, 95% CI: 0.999-1.788, p=0.051) and homozygote (OR=1.492, 95% CI: 1.085-2.051, p=0.014) models.

Conclusions: We can conclude that XRCC3 Thr241Met polymorphism might be associated with breast cancer risk, especially in Asian populations and in patients without family history of breast cancer.

No MeSH data available.


Related in: MedlinePlus