1
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Lopes Cardozo JM, Andrulis IL, Bojesen SE, Dörk T, Eccles DM, Fasching PA, Hooning MJ, Keeman R, Nevanlinna H, Rutgers EJ, Easton DF, Hall P, Pharoah PD, van 't Veer LJ, Schmidt MK. Associations of a Breast Cancer Polygenic Risk Score With Tumor Characteristics and Survival. J Clin Oncol 2023; 41:1849-1863. [PMID: 36689693 PMCID: PMC10082287 DOI: 10.1200/jco.22.01978] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 10/25/2022] [Accepted: 12/16/2022] [Indexed: 01/24/2023] Open
Abstract
PURPOSE A polygenic risk score (PRS) consisting of 313 common genetic variants (PRS313) is associated with risk of breast cancer and contralateral breast cancer. This study aimed to evaluate the association of the PRS313 with clinicopathologic characteristics of, and survival following, breast cancer. METHODS Women with invasive breast cancer were included, 98,397 of European ancestry and 12,920 of Asian ancestry, from the Breast Cancer Association Consortium (BCAC), and 683 women from the European MINDACT trial. Associations between PRS313 and clinicopathologic characteristics, including the 70-gene signature for MINDACT, were evaluated using logistic regression analyses. Associations of PRS313 (continuous, per standard deviation) with overall survival (OS) and breast cancer-specific survival (BCSS) were evaluated with Cox regression, adjusted for clinicopathologic characteristics and treatment. RESULTS The PRS313 was associated with more favorable tumor characteristics. In BCAC, increasing PRS313 was associated with lower grade, hormone receptor-positive status, and smaller tumor size. In MINDACT, PRS313 was associated with a low risk 70-gene signature. In European women from BCAC, higher PRS313 was associated with better OS and BCSS: hazard ratio (HR) 0.96 (95% CI, 0.94 to 0.97) and 0.96 (95% CI, 0.94 to 0.98), but the association disappeared after adjustment for clinicopathologic characteristics (and treatment): OS HR, 1.01 (95% CI, 0.98 to 1.05) and BCSS HR, 1.02 (95% CI, 0.98 to 1.07). The results in MINDACT and Asian women from BCAC were consistent. CONCLUSION An increased PRS313 is associated with favorable tumor characteristics, but is not independently associated with prognosis. Thus, PRS313 has no role in the clinical management of primary breast cancer at the time of diagnosis. Nevertheless, breast cancer mortality rates will be higher for women with higher PRS313 as increasing PRS313 is associated with an increased risk of disease. This information is crucial for modeling effective stratified screening programs.
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Affiliation(s)
- Josephine M.N. Lopes Cardozo
- Department of Surgery, The Netherlands Cancer Institute—Antoni van Leeuwenhoek Hospital, Amsterdam, the Netherlands
- European Organisation for Research and Treatment of Cancer Headquarters, Brussels, Belgium
| | - Irene L. Andrulis
- Fred A. Litwin Center for Cancer Genetics, Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Stig E. Bojesen
- Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Thilo Dörk
- Gynaecology Research Unit, Hannover Medical School, Hannover, Germany
| | - Diana M. Eccles
- Faculty of Medicine, University of Southampton, Southampton, United Kingdom
| | - Peter A. Fasching
- Department of Gynecology and Obstetricss, Comprehensive Cancer Center Erlangen-EMN, Friedrich-Alexander University Erlangen-Nuremberg, University Hospital Erlangen, Erlangen, Germany
| | - Maartje J. Hooning
- Department of Medical Oncology, Erasmus MC Cancer Institute, Rotterdam, the Netherlands
| | - Renske Keeman
- Division of Molecular Pathology, The Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Heli Nevanlinna
- Department of Obstetrics and Gynecology, Helsinki University Hospital, University of Helsinki, Helsinki, Finland
| | - Emiel J.T. Rutgers
- Department of Surgery, The Netherlands Cancer Institute—Antoni van Leeuwenhoek Hospital, Amsterdam, the Netherlands
| | - Douglas F. Easton
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, United Kingdom
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Oncology, Södersjukhuset, Stockholm, Sweden
| | - Paul D.P. Pharoah
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, United Kingdom
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Laura J. van 't Veer
- UCSF Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA
| | - Marjanka K. Schmidt
- Division of Molecular Pathology, The Netherlands Cancer Institute, Amsterdam, the Netherlands
- Division of Psychosocial Research and Epidemiology, The Netherlands Cancer Institute—Antoni van Leeuwenhoek Hospital, Amsterdam, the Netherlands
- Department of Clinical Genetics, Leiden University Medical Center, Leiden, the Netherlands
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2
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Xu J, Li G, Chen M, Li W, Wu Y, Zhang X, Cui Y, Zhang B. rs12537 Is a Novel Susceptibility SNP Associated With Estrogen Receptor Positive Breast Cancer in Chinese Han Population. Front Med (Lausanne) 2021; 8:708644. [PMID: 34395483 PMCID: PMC8355624 DOI: 10.3389/fmed.2021.708644] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Accepted: 06/21/2021] [Indexed: 01/15/2023] Open
Abstract
Genetic testing is widely used in breast cancer and has identified a lot of susceptibility genes and single nucleotide polymorphisms (SNPs). However, for many SNPs, evidence of an association with breast cancer is weak, underlying risk estimates are imprecise, and reliable subtype-specific risk estimates are not in place. A recent genome-wide long non-coding RNA (lncRNA) association study in Chinese Han has verified a genetic association between rs12537 and breast cancer. This study is aimed at investigating the association between rs12537 and the phenotype. We collected the clinical information of 5,634 breast cancer patients and 6,308 healthy controls in the early study. And χ2 test was used for the comparison between different groups in genotype. The frequency of genotypic distribution among SNP rs12537 has no statistically significant correlation with family history (p = 0.8945), menopausal status (p = 0.3245) or HER-2 (p = 0.2987), but it is statistically and significantly correlated with ER (p = 0.004006) and PR (p = 0.01379). Most importantly, compared to the healthy control, rs12537 variant is significantly correlated with ER positive patients and the p-value has reached the level of the whole genome (p = 1.66E-08 <5.00E-08). Furthermore, we found rs12537 associated gene MTMR3 was lower expressed in breast cancer tissues but highly methylated. In conclusion, our findings indicate that rs12537 is a novel susceptibility gene in ER positive breast cancer in Chinese Han population and it may influence the methylation of MTMR3.
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Affiliation(s)
- Jingkai Xu
- Department of Dermatology, China-Japan Friendship Hospital, Beijing, China.,Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Guozheng Li
- School of Life Sciences, Anhui Medical University, Hefei, China.,Department of Oncology, No. 2 Hospital, Anhui Medical University, Hefei, China
| | - Mengyun Chen
- Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Wenjing Li
- School of Life Sciences, Anhui Medical University, Hefei, China.,Department of Oncology, No. 2 Hospital, Anhui Medical University, Hefei, China
| | - Yaxing Wu
- School of Life Sciences, Anhui Medical University, Hefei, China.,Department of Oncology, No. 2 Hospital, Anhui Medical University, Hefei, China
| | - Xuejun Zhang
- Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yong Cui
- Department of Dermatology, China-Japan Friendship Hospital, Beijing, China
| | - Bo Zhang
- School of Life Sciences, Anhui Medical University, Hefei, China.,Department of Oncology, No. 2 Hospital, Anhui Medical University, Hefei, China
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3
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Yanes T, Young MA, Meiser B, James PA. Clinical applications of polygenic breast cancer risk: a critical review and perspectives of an emerging field. Breast Cancer Res 2020; 22:21. [PMID: 32066492 PMCID: PMC7026946 DOI: 10.1186/s13058-020-01260-3] [Citation(s) in RCA: 80] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2019] [Accepted: 02/07/2020] [Indexed: 01/04/2023] Open
Abstract
Polygenic factors are estimated to account for an additional 18% of the familial relative risk of breast cancer, with those at the highest level of polygenic risk distribution having a least a twofold increased risk of the disease. Polygenic testing promises to revolutionize health services by providing personalized risk assessments to women at high-risk of breast cancer and within population breast screening programs. However, implementation of polygenic testing needs to be considered in light of its current limitations, such as limited risk prediction for women of non-European ancestry. This article aims to provide a comprehensive review of the evidence for polygenic breast cancer risk, including the discovery of variants associated with breast cancer at the genome-wide level of significance and the use of polygenic risk scores to estimate breast cancer risk. We also review the different applications of this technology including testing of women from high-risk breast cancer families with uninformative genetic testing results, as a moderator of monogenic risk, and for population screening programs. Finally, a potential framework for introducing testing for polygenic risk in familial cancer clinics and the potential challenges with implementing this technology in clinical practice are discussed.
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Affiliation(s)
- Tatiane Yanes
- Psychosocial Research Group, Prince of Wales Clinical School, Faculty of Medicine, UNSW Sydney, Sydney, NSW, Australia. .,The University of Queensland Diamantina Institute, Dermatology Research Centre, University of Queensland, Brisbane, QLD, 4102, Australia.
| | - Mary-Anne Young
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Sydney, NSW, 2010, Australia
| | - Bettina Meiser
- Psychosocial Research Group, Prince of Wales Clinical School, Faculty of Medicine, UNSW Sydney, Sydney, NSW, Australia
| | - Paul A James
- Parkville Integrated Familial Cancer Centre, Peter MacCallum Cancer Centre, Melbourne, VIC, 3000, Australia
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4
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Prediction model for the efficacy of folic acid therapy on hyperhomocysteinaemia based on genetic risk score methods. Br J Nutr 2019; 122:39-46. [PMID: 30935434 DOI: 10.1017/s0007114519000783] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
No risk assessment tools for the efficacy of folic acid treatment for hyperhomocysteinaemia (HHcy) have been developed. We aimed to use two common genetic risk score (GRS) methods to construct prediction models for the efficacy of folic acid therapy on HHcy, and the best gene-environment prediction model was screened out. A prospective cohort study enrolling 638 HHcy patients was performed. We used a logistic regression model to estimate the associations of two GRS methods with the efficacy. Performances were compared using area under the receiver operating characteristic curve (AUC). The simple count genetic risk score (SC-GRS) and weighted genetic risk score (wGRS) were found to be independently associated with the efficacy of folic acid treatment for HHcy. Using the SC-GRS, per risk allele increased with a 1·46-fold increased failure risk (P < 0·001) after adjustment for traditional risk factors, including age, sex, BMI, smoking, alcohol consumption, history of diabetes, history of hypertension, history of hyperlipidaemia, history of stroke and history of CHD. When used the wGRS, the association was strengthened (OR = 2·08, P < 0·001). Addition of the SC-GRS and wGRS to the traditional risk model significantly improved the predictive ability by AUC (0·859). A precise gene-environment predictive model with good performance was developed for predicting the treatment failure rate of folic acid therapy for HHcy.
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5
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Yu C, Qin N, Pu Z, Song C, Wang C, Chen J, Dai J, Ma H, Jiang T, Jiang Y. Integrating of genomic and transcriptomic profiles for the prognostic assessment of breast cancer. Breast Cancer Res Treat 2019; 175:691-699. [PMID: 30868394 DOI: 10.1007/s10549-019-05177-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Accepted: 02/19/2019] [Indexed: 12/18/2022]
Abstract
PURPOSE To evaluate the prognostic effect of the integration of genomic and transcriptomic profiles in breast cancer. METHODS Eight hundred and ten samples from the Cancer Genome Atlas (TCGA) data sets were randomly divided into the training set (540 subjects) and validation set (270 subjects). We first selected single-nucleotide polymorphism (SNPs) and genes associated with breast cancer prognosis in the training set to construct the prognostic prediction model, and then replicated the prediction efficiency in the validation set. RESULTS Four SNPs and three genes associated with the prognosis of breast cancer in the training set were included in the prognostic model. Patients were divided into the high-risk group and low-risk group based on the four SNPs and three genes signature-based genetic prognostic index. High-risk patients showed a significant worse overall survival [Hazard Ratio (HR) 9.43, 95% confidence interval (CI) 3.81-23.33, P < 0.001] than the low-risk group. Compared to the model constructed with only gene expression, the C statistics for the signature-based genetic prognostic index [area under curves (AUC) = 0.79, 95% CI 0.72-0.86] showed a significant increase (P < 0.001). Additionally, we further replicated the prognostic prediction model in the validation set as patients in the high-risk group also showed a significantly worse overall survival (HR 4.55, 95% CI 1.50-13.88, P < 0.001), and the C statistics for the signature-based genetic prognostic index was 0.76 (95% CI 0.65-0.86). The following time-dependent ROC revealed that the mean of AUCs were 0.839 and 0.748 in the training set and the validation set, respectively. CONCLUSIONS Our findings suggested that integrating genomic and transcriptomic profiles could greatly improve the predictive efficiency of the prognosis of breast cancer patients.
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Affiliation(s)
- Chengxiao Yu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China.,State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center of Cancer Medicine, Nanjing Medical University, Nanjing, 211166, China
| | - Na Qin
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China.,State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center of Cancer Medicine, Nanjing Medical University, Nanjing, 211166, China
| | - Zhening Pu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China.,State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center of Cancer Medicine, Nanjing Medical University, Nanjing, 211166, China.,Center of Clinical Research, Wuxi Institute of Translational Medicine, Wuxi People's Hospital of Nanjing Medical University, Wuxi, 214000, China
| | - Ci Song
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China.,State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center of Cancer Medicine, Nanjing Medical University, Nanjing, 211166, China
| | - Cheng Wang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China.,State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center of Cancer Medicine, Nanjing Medical University, Nanjing, 211166, China.,Department of Bioinformatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, 211166, China
| | - Jiaping Chen
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China.,State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center of Cancer Medicine, Nanjing Medical University, Nanjing, 211166, China
| | - Juncheng Dai
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China.,State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center of Cancer Medicine, Nanjing Medical University, Nanjing, 211166, China
| | - Hongxia Ma
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China.,State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center of Cancer Medicine, Nanjing Medical University, Nanjing, 211166, China
| | - Tao Jiang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China. .,State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, China. .,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center of Cancer Medicine, Nanjing Medical University, Nanjing, 211166, China.
| | - Yue Jiang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China. .,State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, China. .,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center of Cancer Medicine, Nanjing Medical University, Nanjing, 211166, China.
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6
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Zhou XL, Zeng D, Ye YH, Sun SM, Lu XF, Liang WQ, Chen CF, Lin HY. Prognostic values of the inhibitor of DNA‑binding family members in breast cancer. Oncol Rep 2018; 40:1897-1906. [PMID: 30066902 PMCID: PMC6111598 DOI: 10.3892/or.2018.6589] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2018] [Accepted: 07/17/2018] [Indexed: 02/05/2023] Open
Abstract
The inhibitor of DNA‑binding (ID) proteins are dominant‑negative modulators of transcription factors with basic helix‑loop‑helix (bHLH) structures, which control a variety of genes in cell cycle regulation. An increasing volume of evidence has demonstrated that the deregulated expression of IDs in several types of malignancy, including breast carcinoma, has been proven to serve crucial regulatory functions in tumorigenesis and the development of breast cancer (BC). The present study evaluated the prognostic values of the ID family members by investigating a set of publicly accessible databases, including Oncomine, bc‑GenExMiner, Kaplan‑Meier plotter and the Human Protein Atlas. The results demonstrated that mRNA levels of distinct IDs exhibited diverse profiles between BC and normal counterparts. The mRNA expression level of ID2 was significantly higher in breast cancer than normal tissues, while the mRNA expression levels of ID1, ID3 and ID4 were significantly lower in breast cancer tissues than in normal tissues. Furthermore, higher mRNA expression levels of ID1 and ID4 were associated with subgroups with lower pathological grades and fewer lymph node metastases. Survival analysis revealed that elevated mRNA levels of ID1 and ID4 predicted an improved survival in all patients with BC. Increased ID1 mRNA levels were associated with higher relapse‑free survival rates in all patients with BC, particularly in those with ER positive and Luminal A subtype tumors. Increased ID4 mRNA expression predicted longer survival times in all patients with BC, particularly in those with hormone receptor‑positive tumors or those treated with endocrine therapy. These results indicated that IDs are essential prognostic indicators in BC. Future studies on the effect of IDs on the pathogenesis and development of BC are warranted.
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Affiliation(s)
- Xiao-Ling Zhou
- Department of Gynecology and Obstetrics, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong 515000, P.R. China
| | - De Zeng
- Department of Medical Oncology, The Cancer Hospital of Shantou University Medical College, Shantou, Guangdong 515000, P.R. China
| | - Yan-Hong Ye
- Department of Thyroid and Breast Surgery, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong 515000, P.R. China
| | - Shu-Ming Sun
- Department of Thyroid and Breast Surgery, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong 515000, P.R. China
| | - Xiao-Feng Lu
- Department of Thyroid and Breast Surgery, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong 515000, P.R. China
| | - Wei-Quan Liang
- Department of Thyroid and Breast Surgery, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong 515000, P.R. China
| | - Chun-Fa Chen
- Department of Thyroid and Breast Surgery, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong 515000, P.R. China
| | - Hao-Yu Lin
- Department of Thyroid and Breast Surgery, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong 515000, P.R. China
- Correspondence to: Dr Hao-Yu Lin, Department of Thyroid and Breast Surgery, The First Affiliated Hospital of Shantou University Medical College (SUMC), 57 Changping Road, Shantou, Guangdong 515000, P.R. China, E-mail:
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7
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Wunderle M, Olmes G, Nabieva N, Häberle L, Jud SM, Hein A, Rauh C, Hack CC, Erber R, Ekici AB, Hoyer J, Vasileiou G, Kraus C, Reis A, Hartmann A, Schulz-Wendtland R, Lux MP, Beckmann MW, Fasching PA. Risk, Prediction and Prevention of Hereditary Breast Cancer - Large-Scale Genomic Studies in Times of Big and Smart Data. Geburtshilfe Frauenheilkd 2018; 78:481-492. [PMID: 29880983 PMCID: PMC5986564 DOI: 10.1055/a-0603-4350] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2018] [Revised: 04/09/2018] [Accepted: 04/09/2018] [Indexed: 12/24/2022] Open
Abstract
Over the last two decades genetic testing for mutations in
BRCA1
and
BRCA2
has become standard of care for women and men who are at familial risk for breast or ovarian cancer. Currently, genetic testing more often also includes so-called panel genes, which are assumed to be moderate-risk genes for breast cancer. Recently, new large-scale studies provided more information about the risk estimation of those genes. The utilization of information on panel genes with regard to their association with the individual breast cancer risk might become part of future clinical practice. Furthermore, large efforts have been made to understand the influence of common genetic variants with a low impact on breast cancer risk. For this purpose, almost 450 000 individuals have been genotyped for almost 500 000 genetic variants in the OncoArray project. Based on first results it can be assumed that – together with previously identified common variants – more than 170 breast cancer risk single nucleotide polymorphisms can explain up to 18% of familial breast cancer risk. The knowledge about genetic and non-genetic risk factors and its implementation in clinical practice could especially be of use for individualized prevention. This includes an individualized risk prediction as well as the individualized selection of screening methods regarding imaging and possible lifestyle interventions. The aim of this review is to summarize the most recent developments in this area and to provide an overview on breast cancer risk genes, risk prediction models and their utilization for the individual patient.
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Affiliation(s)
- Marius Wunderle
- Department of Gynecology and Obstetrics, University Hospital Erlangen, Comprehensive Cancer Center Erlangen-EMN, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Gregor Olmes
- Department of Gynecology and Obstetrics, University Hospital Erlangen, Comprehensive Cancer Center Erlangen-EMN, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Naiba Nabieva
- Department of Gynecology and Obstetrics, University Hospital Erlangen, Comprehensive Cancer Center Erlangen-EMN, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Lothar Häberle
- Department of Gynecology and Obstetrics, University Hospital Erlangen, Comprehensive Cancer Center Erlangen-EMN, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany.,Biostatistics Unit, Department of Gynecology and Obstetrics, Erlangen University Hospital, Comprehensive Cancer Center Erlangen-EMN, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Sebastian M Jud
- Department of Gynecology and Obstetrics, University Hospital Erlangen, Comprehensive Cancer Center Erlangen-EMN, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Alexander Hein
- Department of Gynecology and Obstetrics, University Hospital Erlangen, Comprehensive Cancer Center Erlangen-EMN, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Claudia Rauh
- Department of Gynecology and Obstetrics, University Hospital Erlangen, Comprehensive Cancer Center Erlangen-EMN, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Carolin C Hack
- Department of Gynecology and Obstetrics, University Hospital Erlangen, Comprehensive Cancer Center Erlangen-EMN, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Ramona Erber
- Institute of Pathology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Arif B Ekici
- Institute of Human Genetics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Juliane Hoyer
- Institute of Human Genetics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Georgia Vasileiou
- Institute of Human Genetics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Cornelia Kraus
- Institute of Human Genetics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - André Reis
- Institute of Human Genetics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Arndt Hartmann
- Institute of Pathology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Rüdiger Schulz-Wendtland
- Institute of Diagnostic Radiology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Michael P Lux
- Department of Gynecology and Obstetrics, University Hospital Erlangen, Comprehensive Cancer Center Erlangen-EMN, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Matthias W Beckmann
- Department of Gynecology and Obstetrics, University Hospital Erlangen, Comprehensive Cancer Center Erlangen-EMN, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Peter A Fasching
- Department of Gynecology and Obstetrics, University Hospital Erlangen, Comprehensive Cancer Center Erlangen-EMN, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
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8
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Zhao C, Zhu P, Shen Q, Jin L. Prospective association of a genetic risk score with major adverse cardiovascular events in patients with coronary artery disease. Medicine (Baltimore) 2017; 96:e9473. [PMID: 29390587 PMCID: PMC5758289 DOI: 10.1097/md.0000000000009473] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
Many susceptibility loci associated with coronary artery disease (CAD) have been identified using genome-wide association studies (GWAS). This study aimed to examine whether a composite of single nucleotide polymorphisms (SNPs) derived from GWAS could identify the risk of major adverse cardiovascular events (MACEs) in patients with established CAD. There were 1059 patients with CAD were included in the analysis. Of the participants, 686 were on statin treatment at the start of follow-up. A weighted genetic risk score (wGRS) was calculated as the sum of risk alleles multiplied by the hazard ratio for a particular SNP. In single variant analyses, rs579459, rs4420638, and rs2107595 were associated with an increased risk of MACE. A wGRS was further constructed to evaluate the cumulative effect of the 3 SNPs on the prognosis of CAD. The risk of MACE among patients with high and intermediate wGRS was 1.968- and 1.838-fold, respectively, higher than those with low wGRS. This effect was more evident in patients using lipid-lowering medication and with hypertension. Furthermore, the interaction analysis revealed that lipid-lowering medication and hypertension interacted with the genetic effect off wGRS on the risk of MACE in patients using lipid-lowering medication or with hypertension (Pinteraction < .001). We further analyzed the follow-up change in low-density lipoprotein cholesterol (LDL-C) level at 6 months after CAD disclosure and evaluated whether that was due to wGRS or statin use. The lowest reduction in LDL-C was observed in patients with high GRS who received statin treatment. Furthermore, LDL-C reduction of patients with intermediate wGRS was less than those with low wGRS in patients treated with statin. Taken together, a wGRS comprised of SNPs significantly predicts MACE in CAD patients receiving statin treatment and hypertension.
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Affiliation(s)
| | - Pin Zhu
- Department of Cardiology, Tongren Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
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