scholarly journals No Association between Ovarian Cancer Susceptibility Variants and Breast Cancer Risk among Chinese Women

2013 ◽  
Vol 22 (3) ◽  
pp. 467-469 ◽  
Author(s):  
Xiangyu Ma ◽  
Qiuyin Cai ◽  
Ryan J. Delahanty ◽  
Xiao-Ou Shu ◽  
Ben Zhang ◽  
...  
Author(s):  
Thanh Thi Ngoc Nguyen ◽  
Giau Thi Ngoc Mai ◽  
Hue Thi Nguyen

Breast cancer is the most common cancer for women around the world. The presence of single nucleotide polymorphisms (SNP) on or near the coding region of breast cancer susceptibility genes can affect the regulation of gene expression, which may increase or decrease the risk of breast cancer. BARX2 was showed to stimulate the expression of ERS1, which involved in the development of breast cancer. SNP rs7107217 on 152kb downstream of the BARX2 could affect the level of protein BARX2 and had been proved to associate with the breast cancer risk in populations similar to Vietnamese, including Chinese and Korean. In this study, rs7107217 was genotyped and initially detemined the association with the breast cancer risk in Vietnamese. Real-time PCR HRM was optimized and used to genotype rs7107217 in 117 breast cancer cases and 105 healthy controls. Thereafter, the correlation of this SNP with the risk of breast cancer was initially determined by analyzing the differences in allelic and genotypic frequencies between cases and control groups. The results showed the optimal rs7107217 genotyping condition was successfully developed with the high sensitivity, specificity, and consistency. SNP rs7107217 had high polymorphism with the frequency of minor allele C of 29.9% and 35.3% in case and control, respectively. SNP rs7107217 had been found no association with the breast cancer risk (C vs A: P = 0.23, OR (95% CI) = 0.79 (0.53 – 1.17)). However with the low reliability of the analysis (11.71%) and the high potential related to the formation of breast cancer, the association between rs7107217 and breast cancer risk in Vietnamese population should be further conducted on a larger sample size to get higher accuracy.


Oncotarget ◽  
2017 ◽  
Vol 8 (22) ◽  
pp. 36462-36468 ◽  
Author(s):  
Jing Han ◽  
Jing Zhou ◽  
Hua Yuan ◽  
Longbiao Zhu ◽  
Hongxia Ma ◽  
...  

2016 ◽  
Vol 50 (5) ◽  
pp. 312-317 ◽  
Author(s):  
Z. Pan ◽  
Y. Bao ◽  
X. Zheng ◽  
W. Cao ◽  
W. Cheng ◽  
...  

2020 ◽  
Author(s):  
Meng Wang ◽  
Jia Yao ◽  
Yi Zheng ◽  
Yuyao Yao ◽  
Shuqian Wang ◽  
...  

Abstract Studies have suggested that thymidylate (TYMS) polymorphisms are associated with breast cancer. However, inconsistent results were obtained and data from Asian populations are largely lacking. In this study, the relationships between two common TYMS polymorphisms (rs2790 and rs1059394) and the breast cancer risk were evaluated. We also studied the TYMS expression between tumor and para-carcinoma tissues, and the association between TYMS levels and prognosis of breast cancer. This hospital-based study included 434 patients and 450 cancer-free individuals. Genotying was performed using Sequenom Mass-ARRAY. The microarray dataset GSE115144 was downloaded to compare the differences in TYMS expression between tumor and para-carcinoma tissues. The microarray dataset GSE20685 was used to analysis the metastasis free survival (MFS) and overall survival (OS) of patients. The rs2790 polymorphism was related to a higher risk of breast cancer (recessive model: OR=1.50, 95%CI=1.02-2.21, P=0.038) and the C allele of rs1059394 was overrepresented in patients with tumor stage III-IV (heterozygote model: OR=0.60, 95%CI=0.39-0.94, P=0.025; dominant model: OR=0.59, 95%CI=0.39-0.89, P=0.013). The tumor tissues had a higher TYMS expression levels and patients with higher TYMS expression levels had worse OS. Overall, TYMS polymorphism may increase susceptibility to breast cancer in Chinese Han women and TYMS expression levels may be a predictive factor for breast cancer patients.


2017 ◽  
Vol 146 (1) ◽  
pp. 205-214 ◽  
Author(s):  
Mary Linton Peters ◽  
Judy E. Garber ◽  
Nadine Tung

2003 ◽  
Vol 105 (1) ◽  
pp. 92-97 ◽  
Author(s):  
Herbert Yu ◽  
Xiao-Ou Shu ◽  
Runhua Shi ◽  
Qi Dai ◽  
Fan Jin ◽  
...  

2010 ◽  
Author(s):  
Shimian Qu ◽  
Hui Cai ◽  
Jirong Long ◽  
Qiuyin Cai ◽  
Regina Courtney ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document