Association between HULC rs7763881 and cancer risk: an updated Meta-analysis

Author(s):  
Xueren Gao ◽  
Jiaxin Yang ◽  
Dongbo Wang ◽  
Qinghang Zeng ◽  
Fangting Li ◽  
...  
Keyword(s):  
BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hui Zeng ◽  
Zhuoyu Yang ◽  
Jiang Li ◽  
Yan Wen ◽  
Zheng Wu ◽  
...  

Abstract Background Published findings suggest sex differences in lung cancer risk and a potential role for sex steroid hormones. Our aim was to perform a meta-analysis to investigate the effects of sex steroid hormone exposure specifically on the risk of lung cancer in women. Methods The PubMed, MEDLINE, Web of Science, and EMBASE databases were searched. The pooled odds ratios (ORs) and 95% confidence intervals (95% CIs) for female lung cancer risk associated with sex steroid hormones were calculated overall and by study design, publication year, population, and smoking status. Sensitivity analysis, publication bias, and subgroup analysis were performed. Results Forty-eight studies published between 1987 and 2019 were included in the study with a total of 31,592 female lung cancer cases and 1,416,320 subjects without lung cancer. Overall, higher levels of sex steroid hormones, both endogenous (OR: 0.92, 95% CI: 0.87–0.98) and exogenous (OR: 0.86, 95% CI: 0.80–0.93), significantly decreased the risk of female lung cancer by 10% (OR: 0.90, 95% CI: 0.86–0.95). The risk of lung cancer decreased more significantly with a higher level of sex steroid hormones in non-smoking women (OR: 0.88, 95% CI: 0.78–0.99) than in smoking women (OR: 0.98, 95% CI: 0.77–1.03), especially in Asia women (OR: 0.84, 95% CI: 0.74–0.96). Conclusions Our meta-analysis reveals an association between higher levels of sex steroid hormone exposure and the decreased risk of female lung cancer. Surveillance of sex steroid hormones might be used for identifying populations at high risk for lung cancer, especially among non-smoking women.


Urology ◽  
2011 ◽  
Vol 77 (3) ◽  
pp. 766-767
Author(s):  
Yan-Feng Zou ◽  
Fang Wang ◽  
Xiao-Liang Feng

2021 ◽  
Vol 49 (3) ◽  
pp. 030006052199295
Author(s):  
Yijuan Xin ◽  
Liu Yang ◽  
Mingquan Su ◽  
Xiaoli Cheng ◽  
Lin Zhu ◽  
...  

Objectives To investigate the association between poly(ADP-ribose) polymerase 1 ( PARP1) rs1136410 Val762Ala and cancer risk in Asian populations, as published findings remain controversial. Methods The PubMed and EMBASE databases were searched, and references of identified studies and reviews were screened, to find relevant studies. Meta-analyses were performed to evaluate the association between PARP1 rs1136410 Val762Ala and cancer risk, reported as odds ratio (OR) and 95% confidence interval (CI). Results A total of 24 studies with 8 926 cases and 15 295 controls were included. Overall, a significant association was found between PARP1 rs1136410 Val762Ala and cancer risk in East Asians (homozygous: OR 1.19, 95% CI 1.06, 1.35; heterozygous: OR 1.10, 95% CI 1.04, 1.17; recessive: OR 1.13, 95% CI 1.02, 1.25; dominant: OR 1.13, 95% CI 1.06, 1.19; and allele comparison: OR 1.09, 95% CI 1.03, 1.15). Stratification analyses by race and cancer type revealed similar results for gastric cancer among the Chinese population. Conclusion The findings suggest that PARP1 rs1136410 Val762Ala may be significantly associated with an increased cancer risk in Asians, particularly the Chinese population.


2021 ◽  
pp. 1-10
Author(s):  
Jiani Yang ◽  
Jun Ma ◽  
Yue Jin ◽  
Shanshan Cheng ◽  
Shan Huang ◽  
...  

2020 ◽  
Vol 35 (6) ◽  
pp. 1253-1255
Author(s):  
Zeev Blumenfeld ◽  
Norbert Gleicher ◽  
Eli Y Adashi

Abstract Whereas longstanding dogma has purported that pregnancies protect women from breast cancer, a recent meta-analysis now mandates reconsideration since it reported an actual higher breast cancer risk for more than two decades after childbirth before the relative risk turns negative. Moreover, the risk of breast cancer appears higher for women having their first birth at an older age and with a family history and it is not reduced by breastfeeding. The process of obtaining informed consent for all fertility treatments, therefore, must make patients aware of the facts that every pregnancy, to a small degree, will increase the short-term breast cancer risk. This observation may be even more relevant in cases of surrogacy where women agree to conceive without deriving benefits of offspring from assuming the risk, thus creating a substantially different risk-benefit ratio. Consequently, it appears prudent for professional societies in the field to update recommendations regarding consent information for all fertility treatments but especially for treatments involving surrogacy.


2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Weiqing Liu ◽  
Shumin Ma ◽  
Lei Liang ◽  
Zhiyong Kou ◽  
Hongbin Zhang ◽  
...  

Abstract Background Studies on the XRCC3 rs1799794 polymorphism show that this polymorphism is involved in a variety of cancers, but its specific relationships or effects are not consistent. The purpose of this meta-analysis was to investigate the association between rs1799794 polymorphism and susceptibility to cancer. Methods PubMed, Embase, the Cochrane Library, Web of Science, and Scopus were searched for eligible studies through June 11, 2019. All analyses were performed with Stata 14.0. Subgroup analyses were performed by cancer type, ethnicity, source of control, and detection method. A total of 37 studies with 23,537 cases and 30,649 controls were included in this meta-analysis. Results XRCC3 rs1799794 increased cancer risk in the dominant model and heterozygous model (GG + AG vs. AA: odds ratio [OR] = 1.04, 95% confidence interval [CI] = 1.00–1.08, P = 0.051; AG vs. AA: OR = 1.05, 95% CI = 1.00–1.01, P = 0.015). The existence of rs1799794 increased the risk of breast cancer and thyroid cancer, but reduced the risk of ovarian cancer. In addition, rs1799794 increased the risk of cancer in the Caucasian population. Conclusion This meta-analysis confirms that XRCC3 rs1799794 is related to cancer risk, especially increased risk for breast cancer and thyroid cancer and reduced risk for ovarian cancer. However, well-designed large-scale studies are required to further evaluate the results.


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