Jiaqi Li1, Bo Li2, Qiyu Jiang3, Yingshi Zhang2, Aixia Liu2, Huan Wang2, Juling Zhang2, Qin Qin4, Zhixian Hong5, Bo-An Li6. 1. Basic Medicine College, Navy Military Medical University, Shanghai 200433, PR China. 2. Center for Clinical Laboratory, The 302nd Hospital of Chinese PLA, Beijing 100039, PR China. 3. Research Center for Clinical and Transitional Medicine, The 302nd Hospital of Chinese PLA, Beijing 100039, PR China. 4. Department of Laboratory Medicine, Changhai Hospital, The Second Military Medical University, Shanghai 200433, PR China. Electronic address: qinq78@163.com. 5. Department of Hepatobiliary Surgery, The 302nd Hospital of Chinese PLA, Beijing 100039, PR China. Electronic address: zqyhzx@sina.com. 6. Center for Clinical Laboratory, The 302nd Hospital of Chinese PLA, Beijing 100039, PR China. Electronic address: lba@263.net.
Abstract
BACKGROUND: To identify the most suitable genetic model for detecting the risk of breast cancer (BC)/ovarian cancer (OC) in specific populations. METHODS: Databases were searched for related studies published up to October 2017. First, VDR genetic polymorphisms were compared in patients with and without cancer. Second, a network meta-analysis was used to reveal the relation between VDR genetic polymorphisms with disease outcomes. Subgroup analyses and a meta-regression were performed according to cancer types, ethnicity and genotypic method. The study is registered in PROSPERO with an ID: CRD42017075505. RESULTS: Forty-five studies were eligible, which included 65,754 patients and 55 clinical analyses. Of genetic models, results suggested that the recessive model with the CDX2 polymorphism predicted the risk of BC in all cases. The recessive polymorphism model with the rs2228570 (FokI) polymorphism seemed to the best predictor of BC in Caucasian patients, whereas the homozygote model with the CDX2 polymorphism appeared to best predict BC in African-American patients. The homozygote model with the rs2228570 (FokI) polymorphism model appeared to detect the risk of OC in all cases, whereas the heterozygote model with the rs1544410 (BsmI) polymorphism seemed to detect the risk of OC in Caucasian patients. CONCLUSIONS: By detecting the risk of BC, the recessive model with the rs2228570 (FokI) polymorphism is likely the best genetic model in Caucasian patients, and the homozygote model with the CDX2 polymorphism appears to be best genetic model in African-American patients. Moreover, for detecting clinical risk of OC, heterozygote models with the rs1544410 (BsmI) polymorphism is likely the best genetic model for detecting the risk of OC in Caucasian patients.
BACKGROUND: To identify the most suitable genetic model for detecting the risk of breast cancer (BC)/ovarian cancer (OC) in specific populations. METHODS: Databases were searched for related studies published up to October 2017. First, VDR genetic polymorphisms were compared in patients with and without cancer. Second, a network meta-analysis was used to reveal the relation between VDR genetic polymorphisms with disease outcomes. Subgroup analyses and a meta-regression were performed according to cancer types, ethnicity and genotypic method. The study is registered in PROSPERO with an ID: CRD42017075505. RESULTS: Forty-five studies were eligible, which included 65,754 patients and 55 clinical analyses. Of genetic models, results suggested that the recessive model with the CDX2 polymorphism predicted the risk of BC in all cases. The recessive polymorphism model with the rs2228570 (FokI) polymorphism seemed to the best predictor of BC in Caucasian patients, whereas the homozygote model with the CDX2 polymorphism appeared to best predict BC in African-American patients. The homozygote model with the rs2228570 (FokI) polymorphism model appeared to detect the risk of OC in all cases, whereas the heterozygote model with the rs1544410 (BsmI) polymorphism seemed to detect the risk of OC in Caucasian patients. CONCLUSIONS: By detecting the risk of BC, the recessive model with the rs2228570 (FokI) polymorphism is likely the best genetic model in Caucasian patients, and the homozygote model with the CDX2 polymorphism appears to be best genetic model in African-American patients. Moreover, for detecting clinical risk of OC, heterozygote models with the rs1544410 (BsmI) polymorphism is likely the best genetic model for detecting the risk of OC in Caucasian patients.
Authors: Cruz M Nazario; Rosa V Rosario-Rosado; Michelle Schelske-Santos; Imar Mansilla-Rivera; Farah A Ramírez-Marrero; Jing Nie; Paola Piovanetti-Fiol; Johan Hernández-Santiago; Jo L Freudenheim Journal: Cancer Epidemiol Biomarkers Prev Date: 2021-11-22 Impact factor: 4.090