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Kanbayti IH, Alzahrani MA, Yeslam YO, Habib NH, Hadadi I, Almaimoni Y, Alahmadi A, Ekpo EU. Association between Family History of Breast Cancer and Breast Density in Saudi Premenopausal Women Participating in Mammography Screening. Clin Pract 2024; 14:164-172. [PMID: 38391399 PMCID: PMC10887693 DOI: 10.3390/clinpract14010013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2023] [Revised: 12/24/2023] [Accepted: 01/11/2024] [Indexed: 02/24/2024] Open
Abstract
BACKGROUND Mammographic density and family history of breast cancer (FHBC) are well-established independent factors affecting breast cancer risk; however, the association between these two risk factors in premenopausal-screened women remains unclear. The aim of this study is to investigate the relationship between mammographic density and FHBC among Saudi premenopausal-screened women. METHODS A total of 446 eligible participants were included in the study. Mammographic density was assessed qualitatively using the Breast Imaging Reporting and Data System (BIRADS 4th edition). Logistic regression models were built to investigate the relationship between mammographic density and FHBC. RESULTS Women with a family history of breast cancer demonstrated an 87% greater chance of having dense tissue than women without a family history of breast cancer (95% CI: 1.14-3.08; p = 0.01). Having a positive family history for breast cancer in mothers was significantly associated with dense tissue (adjusted odds ratio (OR): 5.6; 95% CI: 1.3-24.1; p = 0.02). CONCLUSION Dense breast tissue in Saudi premenopausal women undergoing screening may be linked to FHBC. If this conclusion is replicated in larger studies, then breast cancer risk prediction models must carefully consider these breast cancer risk factors.
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Affiliation(s)
- Ibrahem Hussain Kanbayti
- Radiologic Sciences Department, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Mayada A Alzahrani
- Radiologic Sciences Department, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Yara O Yeslam
- Radiologic Sciences Department, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Noora H Habib
- Radiologic Sciences Department, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Ibrahim Hadadi
- Department of Radiological Sciences, College of Applied Medical Sciences, King Khalid University, Abha, Saudi Arabia
| | - Yousef Almaimoni
- Radiologic Sciences Department, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Adnan Alahmadi
- Radiologic Sciences Department, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Ernest U Ekpo
- Medical Image Optimization and Perception Group (MIOPeG), Faculty of Medicine and Health, The University of Sydney, Campus C4 75 East Street, Sydney, NSW 2141, Australia
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Mariapun S, Ho WK, Eriksson M, Tai MC, Mohd Taib NA, Yip CH, Rahmat K, Li J, Hartman M, Hall P, Easton DF, Lindstrom S, Teo SH. Evaluation of SNPs associated with mammographic density in European women with mammographic density in Asian women from South-East Asia. Breast Cancer Res Treat 2023; 201:237-245. [PMID: 37338730 PMCID: PMC10865780 DOI: 10.1007/s10549-023-06984-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2022] [Accepted: 05/24/2023] [Indexed: 06/21/2023]
Abstract
PURPOSE Mammographic density (MD), after accounting for age and body mass index (BMI), is a strong heritable risk factor for breast cancer. Genome-wide association studies (GWAS) have identified 64 SNPs in 55 independent loci associated with MD in women of European ancestry. Their associations with MD in Asian women, however, are largely unknown. METHOD Using linear regression adjusting for age, BMI, and ancestry-informative principal components, we evaluated the associations of previously reported MD-associated SNPs with MD in a multi-ethnic cohort of Asian ancestry. Area and volumetric mammographic densities were determined using STRATUS (N = 2450) and Volpara™ (N = 2257). We also assessed the associations of these SNPs with breast cancer risk in an Asian population of 14,570 cases and 80,870 controls. RESULTS Of the 61 SNPs available in our data, 21 were associated with MD at a nominal threshold of P value < 0.05, all in consistent directions with those reported in European ancestry populations. Of the remaining 40 variants with a P-value of association > 0.05, 29 variants showed consistent directions of association as those previously reported. We found that nine of the 21 MD-associated SNPs in this study were also associated with breast cancer risk in Asian women (P < 0.05), seven of which showed a direction of associations that was consistent with that reported for MD. CONCLUSION Our study confirms the associations of 21 SNPs (19/55 or 34.5% out of all known MD loci identified in women of European ancestry) with area and/or volumetric densities in Asian women, and further supports the evidence of a shared genetic basis through common genetic variants for MD and breast cancer risk.
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Affiliation(s)
- Shivaani Mariapun
- Cancer Research Malaysia, Subang Jaya, Selangor, Malaysia
- School of Mathematical Sciences, Faculty of Science and Engineering, University of Nottingham Malaysia, Semenyih, Selangor, Malaysia
| | - Weang Kee Ho
- Cancer Research Malaysia, Subang Jaya, Selangor, Malaysia
- School of Mathematical Sciences, Faculty of Science and Engineering, University of Nottingham Malaysia, Semenyih, Selangor, Malaysia
| | - Mikael Eriksson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Mei Chee Tai
- Cancer Research Malaysia, Subang Jaya, Selangor, Malaysia
| | - Nur Aishah Mohd Taib
- Faculty of Medicine, University Malaya Cancer Research Institute, University Malaya, Kuala Lumpur, Malaysia
- Department of Surgery, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Cheng Har Yip
- Department of Surgery, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
- Subang Jaya Medical Centre, Subang Jaya, Malaysia
| | - Kartini Rahmat
- Faculty of Medicine, University Malaya Cancer Research Institute, University Malaya, Kuala Lumpur, Malaysia
- Biomedical Imaging Department, Faculty of Medicine, Universiti Malaya Research Imaging Centre, University of Malaya, Kuala Lumpur, Malaysia
| | - Jingmei Li
- Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
- Human Genetics, Genome Institute of Singapore, Singapore, Singapore
| | - Mikael Hartman
- Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Department of Surgery, National University Hospital and National University Health System, Singapore, Singapore
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Oncology, Södersjukhuset, Stockholm, Sweden
| | - Douglas F Easton
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Sara Lindstrom
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Soo-Hwang Teo
- Cancer Research Malaysia, Subang Jaya, Selangor, Malaysia.
- Faculty of Medicine, University Malaya Cancer Research Institute, University Malaya, Kuala Lumpur, Malaysia.
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Khorshid Shamshiri A, Alidoust M, Hemmati Nokandei M, Pasdar A, Afzaljavan F. Genetic architecture of mammographic density as a risk factor for breast cancer: a systematic review. CLINICAL & TRANSLATIONAL ONCOLOGY : OFFICIAL PUBLICATION OF THE FEDERATION OF SPANISH ONCOLOGY SOCIETIES AND OF THE NATIONAL CANCER INSTITUTE OF MEXICO 2023; 25:1729-1747. [PMID: 36639603 DOI: 10.1007/s12094-022-03071-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 12/30/2022] [Indexed: 01/15/2023]
Abstract
BACKGROUND Mammography Density (MD) is a potential risk marker that is influenced by genetic polymorphisms and can subsequently modulate the risk of breast cancer. This qualitative systematic review summarizes the genes and biological pathways involved in breast density and discusses the potential clinical implications in view of the genetic risk profile for breast density. METHODS The terms related to "Common genetic variations" and "Breast density" were searched in Scopus, PubMed, and Web of Science databases. Gene pathways analysis and assessment of protein interactions were also performed. RESULTS Eighty-six studies including 111 genes, reported a significant association between mammographic density in different populations. ESR1, IGF1, IGFBP3, and ZNF365 were the most prevalent genes. Moreover, estrogen metabolism, signal transduction, and prolactin signaling pathways were significantly related to the associated genes. Mammography density was an associated phenotype, and eight out of 111 genes, including COMT, CYP19A1, CYP1B1, ESR1, IGF1, IGFBP1, IGFBP3, and LSP1, were modifiers of this trait. CONCLUSION Genes involved in developmental processes and the evolution of secondary sexual traits play an important role in determining mammographic density. Due to the effect of breast tissue density on the risk of breast cancer, these genes may also be associated with breast cancer risk.
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Affiliation(s)
- Asma Khorshid Shamshiri
- Department of Medical Genetics and Molecular Medicine, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
- Student Research Committee, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Maryam Alidoust
- Department of Medical Genetics and Molecular Medicine, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
- Student Research Committee, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Mahboubeh Hemmati Nokandei
- Department of Medical Genetics and Molecular Medicine, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
- Student Research Committee, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Alireza Pasdar
- Department of Medical Genetics and Molecular Medicine, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
- Division of Applied Medicine, Medical School, University of Aberdeen, Foresterhill, Aberdeen, AB25 2ZD, UK.
| | - Fahimeh Afzaljavan
- Clinical Research Development Unit, Faculty of Medicine, Imam Reza Hospital, Mashhad University of Medical Sciences, Mashhad, 917794-8564, Iran.
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Chen J, Xiao Q, Li X, Liu R, Long X, Liu Z, Xiong H, Li Y. The correlation of leukocyte-specific protein 1 (LSP1) rs3817198(T>C) polymorphism with breast cancer: A meta-analysis. Medicine (Baltimore) 2022; 101:e31548. [PMID: 36397430 PMCID: PMC9666160 DOI: 10.1097/md.0000000000031548] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Multiple studies have investigated the correlation of single nucleotide polymorphisms (SNPs) in leukocyte-specific protein 1 (LSP1) with susceptibility to breast cancer (BC) and have yielded inconsistent conclusions, particularly rs3817198(T > C). Consequently, we performed a meta-analysis to estimate this relationship more comprehensively. METHODS Four databases were utilized to locate eligible publications: PubMed, Embase, Web of Science, and China National Knowledge Infrastructure. This meta-analysis included 14 studies, including 22 reports of 33194 cases and 36661 controls. The relationship of rs3817198 polymorphism with breast cancer was estimated using odds ratios (ORs) with 95% confidence intervals (CIs). The LSP1 co-expression network was constructed by STRING, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed using DAVIDE. Download TCGA breast cancer mRNA-seq data and analyze the relationship between LSP1 expression and breast cancer chemotherapy sensitivity. RESULTS The results indicated that rs3817198(T > C) was positively correlated to with breast malignancy (dominant model: OR = 1.11, 95%CI = 1.06-1.17; recessive model: OR = 1.10, 95%CI = 1.04-1.15; heterozygous model: OR = 1.09, 95%CI = 1.04-1.15; homozygous model: OR = 1.18, 95%CI = 1.09-1.28; additive model: OR = 1.09, 95%CI = 1.05-1.13), among Caucasians and Asians. However, rs3817198(T > C) may reduce the risk of breast carcinoma in Africans. Rs3817198(T > C) might result in breast carcinoma in individuals with BRCA1 and BRCA2 variants and can contribute to estrogen receptor (ER)-positive breast carcinoma. The expression of LSP1 was inversely correlated with the IC50 of doxorubicin (P = 8.91e-15, Cor = -0.23), 5-fluorouracil (P = 1.18e-22, Cor = -0.29), and cisplatin (P = 1.35e-42, Cor = -0.40). CONCLUSION Our study identified that LSP1 rs3817198 polymorphism might result in breast malignancy, particularly among Caucasians and Asians, but lower breast cancer susceptibility in African populations. The expression of LSP1 was negatively correlated with the IC50 of doxorubicin, 5-fluorouracil, and cisplatin.
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Affiliation(s)
- Jian Chen
- General Surgery Department, First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Qiang Xiao
- General Surgery Department, First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Xudong Li
- Surgery Department, Wannian Maternal and Child Health Hospital, Shangrao, Jiangxi, China
| | - Ruihao Liu
- General Surgery Department, First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Xiaozhou Long
- General Surgery Department, First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Zhigao Liu
- General Surgery Department, First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Haiwei Xiong
- General Surgery Department, First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Yingliang Li
- General Surgery Department, First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
- * Correspondence: Yingliang Li, First Affiliated Hospital of Nanchang University, No 17, YongWaiZheng Street, DongHu District, Nanchang 330006, Jiangxi, China (e-mail: )
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Yang H, Ting X, Geng YH, Xie Y, Nierenberg JL, Huo YF, Zhou YT, Huang Y, Yu YQ, Yu XY, Li XF, Ziv E, Zhang H, Fang WG, Shen Y, Tian XX. The risk variant rs11836367 contributes to breast cancer onset and metastasis by attenuating Wnt signaling via regulating NTN4 expression. SCIENCE ADVANCES 2022; 8:eabn3509. [PMID: 35687692 PMCID: PMC9187238 DOI: 10.1126/sciadv.abn3509] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Accepted: 04/27/2022] [Indexed: 06/15/2023]
Abstract
Most genome-wide association study (GWAS)-identified breast cancer-associated causal variants remain uncharacterized. To provide a framework of understanding GWAS-identified variants to function, we performed a comprehensive study of noncoding regulatory variants at the NTN4 locus (12q22) and NTN4 gene in breast cancer etiology. We find that rs11836367 is the more likely causal variant, disrupting enhancer activity in both enhancer reporter assays and endogenous genome editing experiments. The protective T allele of rs11837367 increases the binding of GATA3 to the distal enhancer and up-regulates NTN4 expression. In addition, we demonstrate that loss of NTN4 gene in mice leads to tumor earlier onset, progression, and metastasis. We discover that NTN4, as a tumor suppressor, can attenuate the Wnt signaling pathway by directly binding to Wnt ligands. Our findings bridge the gaps among breast cancer-associated single-nucleotide polymorphisms, transcriptional regulation of NTN4, and breast cancer biology, which provides previously unidentified insights into breast cancer prediction and prevention.
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Affiliation(s)
- Han Yang
- Department of Pathology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), School of Basic Medical Sciences, Peking University Third Hospital, Peking University Health Science Center, Beijing 100191, China
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Xia Ting
- Department of Pathology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), School of Basic Medical Sciences, Peking University Third Hospital, Peking University Health Science Center, Beijing 100191, China
| | - Yue-Hang Geng
- Department of Pathology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), School of Basic Medical Sciences, Peking University Third Hospital, Peking University Health Science Center, Beijing 100191, China
| | - Yuntao Xie
- Breast Center, Peking University School of Oncology, Beijing Cancer Hospital and Institute, Beijing 100142, China
| | - Jovia L. Nierenberg
- Department of Epidemiology and Biostatistics, University of California, San Francisco School of Medicine, San Francisco, CA, USA
| | - Yan-Fei Huo
- Department of Pathology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), School of Basic Medical Sciences, Peking University Third Hospital, Peking University Health Science Center, Beijing 100191, China
| | - Yan-Ting Zhou
- Department of Pathology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), School of Basic Medical Sciences, Peking University Third Hospital, Peking University Health Science Center, Beijing 100191, China
| | - Yang Huang
- Department of Pathology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), School of Basic Medical Sciences, Peking University Third Hospital, Peking University Health Science Center, Beijing 100191, China
| | - Yu-Qing Yu
- Department of Pathology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), School of Basic Medical Sciences, Peking University Third Hospital, Peking University Health Science Center, Beijing 100191, China
| | - Xin-Yao Yu
- Department of Pathology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), School of Basic Medical Sciences, Peking University Third Hospital, Peking University Health Science Center, Beijing 100191, China
| | - Xiao-Fei Li
- Department of Pathology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), School of Basic Medical Sciences, Peking University Third Hospital, Peking University Health Science Center, Beijing 100191, China
| | - Elad Ziv
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
- Division of General Internal Medicine, Department of Medicine, and Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
| | - Hongquan Zhang
- Department of Anatomy, Histology and Embryology, Peking University Health Science Center, Beijing 100191, China
| | - Wei-Gang Fang
- Department of Pathology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), School of Basic Medical Sciences, Peking University Third Hospital, Peking University Health Science Center, Beijing 100191, China
| | - Yin Shen
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Xin-Xia Tian
- Department of Pathology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), School of Basic Medical Sciences, Peking University Third Hospital, Peking University Health Science Center, Beijing 100191, China
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Li S, Nguyen TL, Nguyen-Dumont T, Dowty JG, Dite GS, Ye Z, Trinh HN, Evans CF, Tan M, Sung J, Jenkins MA, Giles GG, Hopper JL, Southey MC. Genetic Aspects of Mammographic Density Measures Associated with Breast Cancer Risk. Cancers (Basel) 2022; 14:2767. [PMID: 35681745 PMCID: PMC9179294 DOI: 10.3390/cancers14112767] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2022] [Revised: 04/27/2022] [Accepted: 05/30/2022] [Indexed: 11/26/2022] Open
Abstract
Cumulus, Altocumulus, and Cirrocumulus are measures of mammographic density defined at increasing pixel brightness thresholds, which, when converted to mammogram risk scores (MRSs), predict breast cancer risk. Twin and family studies suggest substantial variance in the MRSs could be explained by genetic factors. For 2559 women aged 30 to 80 years (mean 54 years), we measured the MRSs from digitized film mammograms and estimated the associations of the MRSs with a 313-SNP breast cancer polygenic risk score (PRS) and 202 individual SNPs associated with breast cancer risk. The PRS was weakly positively correlated (correlation coefficients ranged 0.05−0.08; all p < 0.04) with all the MRSs except the Cumulus-white MRS based on the “white but not bright area” (correlation coefficient = 0.04; p = 0.06). After adjusting for its association with the Altocumulus MRS, the PRS was not associated with the Cumulus MRS. There were MRS associations (Bonferroni-adjusted p < 0.04) with one SNP in the ATXN1 gene and nominally with some ESR1 SNPs. Less than 1% of the variance of the MRSs is explained by the genetic markers currently known to be associated with breast cancer risk. Discovering the genetic determinants of the bright, not white, regions of the mammogram could reveal substantial new genetic causes of breast cancer.
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Affiliation(s)
- Shuai Li
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3051, Australia; (S.L.); (T.L.N.); (J.G.D.); (G.S.D.); (Z.Y.); (H.N.T.); (C.F.E.); (M.A.J.); (G.G.G.)
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3168, Australia; (T.N.-D.); (M.C.S.)
| | - Tuong L. Nguyen
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3051, Australia; (S.L.); (T.L.N.); (J.G.D.); (G.S.D.); (Z.Y.); (H.N.T.); (C.F.E.); (M.A.J.); (G.G.G.)
| | - Tu Nguyen-Dumont
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3168, Australia; (T.N.-D.); (M.C.S.)
- Department of Clinical Pathology, The University of Melbourne, Parkville, VIC 3051, Australia
| | - James G. Dowty
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3051, Australia; (S.L.); (T.L.N.); (J.G.D.); (G.S.D.); (Z.Y.); (H.N.T.); (C.F.E.); (M.A.J.); (G.G.G.)
| | - Gillian S. Dite
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3051, Australia; (S.L.); (T.L.N.); (J.G.D.); (G.S.D.); (Z.Y.); (H.N.T.); (C.F.E.); (M.A.J.); (G.G.G.)
- Genetic Technologies Limited, Fitzroy, VIC 3065, Australia
| | - Zhoufeng Ye
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3051, Australia; (S.L.); (T.L.N.); (J.G.D.); (G.S.D.); (Z.Y.); (H.N.T.); (C.F.E.); (M.A.J.); (G.G.G.)
| | - Ho N. Trinh
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3051, Australia; (S.L.); (T.L.N.); (J.G.D.); (G.S.D.); (Z.Y.); (H.N.T.); (C.F.E.); (M.A.J.); (G.G.G.)
| | - Christopher F. Evans
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3051, Australia; (S.L.); (T.L.N.); (J.G.D.); (G.S.D.); (Z.Y.); (H.N.T.); (C.F.E.); (M.A.J.); (G.G.G.)
| | - Maxine Tan
- Electrical and Computer Systems Engineering Discipline, School of Engineering, Monash University Malaysia, Bandar Sunway 47500, Malaysia;
- School of Electrical and Computer Engineering, The University of Oklahoma, Norman, OK 73019, USA
| | - Joohon Sung
- Department of Public Health Sciences, Division of Genome and Health Big Data, Graduate School of Public Health, Seoul National University, Seoul 08826, Korea;
| | - Mark A. Jenkins
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3051, Australia; (S.L.); (T.L.N.); (J.G.D.); (G.S.D.); (Z.Y.); (H.N.T.); (C.F.E.); (M.A.J.); (G.G.G.)
| | - Graham G. Giles
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3051, Australia; (S.L.); (T.L.N.); (J.G.D.); (G.S.D.); (Z.Y.); (H.N.T.); (C.F.E.); (M.A.J.); (G.G.G.)
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3168, Australia; (T.N.-D.); (M.C.S.)
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC 3004, Australia
| | - John L. Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3051, Australia; (S.L.); (T.L.N.); (J.G.D.); (G.S.D.); (Z.Y.); (H.N.T.); (C.F.E.); (M.A.J.); (G.G.G.)
| | - Melissa C. Southey
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3168, Australia; (T.N.-D.); (M.C.S.)
- Department of Clinical Pathology, The University of Melbourne, Parkville, VIC 3051, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC 3004, Australia
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Recent Advances of m6A Demethylases Inhibitors and Their Biological Functions in Human Diseases. Int J Mol Sci 2022; 23:ijms23105815. [PMID: 35628623 PMCID: PMC9144293 DOI: 10.3390/ijms23105815] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2022] [Revised: 05/15/2022] [Accepted: 05/17/2022] [Indexed: 12/12/2022] Open
Abstract
N6-methyladenosine (m6A) is a post-transcriptional RNA modification and one of the most abundant types of RNA chemical modifications. m6A functions as a molecular switch and is involved in a range of biomedical aspects, including cardiovascular diseases, the central nervous system, and cancers. Conceptually, m6A methylation can be dynamically and reversibly modulated by RNA methylation regulatory proteins, resulting in diverse fates of mRNAs. This review focuses on m6A demethylases fat-mass- and obesity-associated protein (FTO) and alkB homolog 5 (ALKBH5), which especially erase m6A modification from target mRNAs. Recent advances have highlighted that FTO and ALKBH5 play an oncogenic role in various cancers, such as acute myeloid leukemias (AML), glioblastoma, and breast cancer. Moreover, studies in vitro and in mouse models confirmed that FTO-specific inhibitors exhibited anti-tumor effects in several cancers. Accumulating evidence has suggested the possibility of FTO and ALKBH5 as therapeutic targets for specific diseases. In this review, we aim to illustrate the structural properties of these two m6A demethylases and the development of their specific inhibitors. Additionally, this review will summarize the biological functions of these two m6A demethylases in various types of cancers and other human diseases.
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Yu T, Ye DM. The epidemiologic factors associated with breast density: A review. JOURNAL OF RESEARCH IN MEDICAL SCIENCES 2022; 27:53. [PMID: 36092490 PMCID: PMC9450246 DOI: 10.4103/jrms.jrms_962_21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Revised: 01/14/2022] [Accepted: 01/26/2022] [Indexed: 11/04/2022]
Abstract
In recent years, some studies have evaluated the epidemiologic factors associated with breast density. However, the variant and inconsistent results exist. In addition, breast density has been proved to be a significant risk factor associated with breast cancer. Our review summarized the published studies and emphasized the crucial factors including epidemiological factors associated with breast density. In addition, we also discussed the potential reasons for the discrepant results with risk factors. To decrease the incidence and mortality rates for breast cancer, in clinical practice, breast density should be included for clinical risk models in addition to epidemiological factors, and physicians should get more concentrate on those women with risk factors and provide risk-based breast cancer screening regimens.
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Wang YS, Guo R, Yang DC, Xu Y, Hui YX, Li DD, Tang SC, Tang YY. The Interaction of NTN4 and miR-17-92 Polymorphisms on Breast Cancer Susceptibility in a Chinese Population. Clin Breast Cancer 2021; 22:e544-e551. [DOI: 10.1016/j.clbc.2021.12.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 10/31/2021] [Accepted: 12/05/2021] [Indexed: 11/03/2022]
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10
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Is Mammographic Breast Density an Endophenotype for Breast Cancer? Cancers (Basel) 2021; 13:cancers13153916. [PMID: 34359817 PMCID: PMC8345387 DOI: 10.3390/cancers13153916] [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: 06/14/2021] [Revised: 07/26/2021] [Accepted: 07/28/2021] [Indexed: 12/03/2022] Open
Abstract
Simple Summary Candidate endophenotypes should be systematically assessed against five criteria: (i) the endophenotype is associated with disease in the population; (ii) the endophenotype is heritable; (iii) within families, endophenotype and disease co-segregate; (iv) the endophenotype found in affected family members is found in non-affected family members at a higher rate than in the general population and (v) the endophenotype is primarily state independent (manifests in an individual whether or not disease is active). This study assesses the suitability of mammographic breast density as an endophenotype for breast cancer. Formally establishing a trait as a disease endophenotype confirms that the trait and endophenotype share a biological basis, thereby enabling genetic dissection of an endophenotype to inform disease risk. As breast density can be measured for any woman who has had a mammogram, studies investigating the genetic architecture of breast density could identify breast cancer risk variants that act through effects on this trait. Abstract Mammographic breast density (MBD) is a strong and highly heritable predictor of breast cancer risk and a biomarker for the disease. This study systematically assesses MBD as an endophenotype for breast cancer—a quantitative trait that is heritable and genetically correlated with disease risk. Using data from the family-based kConFab Study and the 1994/1995 cross-sectional Busselton Health Study, participants were divided into three status groups—cases, relatives of cases and controls. Participant’s mammograms were used to measure absolute dense area (DA) and percentage dense area (PDA). To address each endophenotype criterion, linear mixed models and heritability analysis were conducted. Both measures of MBD were significantly associated with breast cancer risk in two independent samples. These measures were also highly heritable. Meta-analyses of both studies showed that MBD measures were higher in cases compared to relatives (β = 0.48, 95% CI = 0.10, 0.86 and β = 0.41, 95% CI = 0.06, 0.78 for DA and PDA, respectively) and in relatives compared to controls (β = 0.16, 95% CI = −0.24, 0.56 and β = 0.16, 95% CI = −0.21, 0.53 for DA and PDA, respectively). This study formally demonstrates, for the first time, that MBD is an endophenotype for breast cancer.
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11
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Sartor H, Zackrisson S, Hegardt C, Larsson C. "Association of mammographic features with molecular breast tumor profiles". Cancer Treat Res Commun 2021; 28:100387. [PMID: 34004506 DOI: 10.1016/j.ctarc.2021.100387] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Revised: 04/28/2021] [Accepted: 05/02/2021] [Indexed: 01/29/2023]
Abstract
PURPOSE Mammographic density and tumor appearance are breast cancer prognostic factors. Conceivably, mammographic features are macroscopic reflections of tumor´s molecular composition, but to an unknown extent. Our aim was to study associations of mammographic features with molecular tumor profiles. METHODS Invasive breast cancers (2007-2016) in Malmö Diet and Cancer Study (MDCS) for which there were tumor RNA-sequencing analyses within Sweden Cancerome Analysis Network - Breast (SCAN-B) (n=102) or All Breast Cancer in Malmö (ABIM) (n=50) were identified. Density (fatty vs. dense), tumor appearance (mass vs. spiculation), and intrinsic subtypes were registered. Differences in gene/metagene expression and Microenvironment Cell Population Counter were analyzed with R. Overall survival was used as endpoint. RESULTS No gene expression differences between density groups was observed. In one cohort (but not the other), Luminal A tumors associated with fatty breasts. For spiculation vs. mass, (p<0.01, t-test) 86 genes were differentially expressed; only one gene was differentially expressed comparing density. Gene set enrichment analysis showed genes highly expressed in spiculated tumors were enriched for extracellular matrix-associated genes whereas genes highly expressed with masses were associated with proliferation. A spiculation metagene, based on differentially expressed genes, showed association with estrogen receptor positivity, lower grade, and improved survival, but it was not an independent prognostic factor. CONCLUSION There are clear differences in molecular composition between breast tumors with a spiculated appearance vs. a mass as the dominant tumor appearance. However, there are no apparent molecular differences related to the density of the breast in which the tumor has arisen.
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Affiliation(s)
- Hanna Sartor
- Diagnostic Radiology, Department of Translational Medicine, Skåne University Hospital, Lund University, Sweden.
| | - Sophia Zackrisson
- Diagnostic Radiology, Department of Translational Medicine, Skåne University Hospital, Lund University, Sweden
| | - Cecilia Hegardt
- Division of Oncology, Department of Clinical Sciences Lund, Lund University, Lund, Sweden
| | - Christer Larsson
- Division of Translational Cancer Research, Department of Laboratory Medicine, Lund University, Lund, Sweden
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12
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Pubertal mammary gland development is a key determinant of adult mammographic density. Semin Cell Dev Biol 2020; 114:143-158. [PMID: 33309487 DOI: 10.1016/j.semcdb.2020.11.011] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Revised: 11/25/2020] [Accepted: 11/28/2020] [Indexed: 01/04/2023]
Abstract
Mammographic density refers to the radiological appearance of fibroglandular and adipose tissue on a mammogram of the breast. Women with relatively high mammographic density for their age and body mass index are at significantly higher risk for breast cancer. The association between mammographic density and breast cancer risk is well-established, however the molecular and cellular events that lead to the development of high mammographic density are yet to be elucidated. Puberty is a critical time for breast development, where endocrine and paracrine signalling drive development of the mammary gland epithelium, stroma, and adipose tissue. As the relative abundance of these cell types determines the radiological appearance of the adult breast, puberty should be considered as a key developmental stage in the establishment of mammographic density. Epidemiological studies have pointed to the significance of pubertal adipose tissue deposition, as well as timing of menarche and thelarche, on adult mammographic density and breast cancer risk. Activation of hypothalamic-pituitary axes during puberty combined with genetic and epigenetic molecular determinants, together with stromal fibroblasts, extracellular matrix, and immune signalling factors in the mammary gland, act in concert to drive breast development and the relative abundance of different cell types in the adult breast. Here, we discuss the key cellular and molecular mechanisms through which pubertal mammary gland development may affect adult mammographic density and cancer risk.
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13
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Evans DG, van Veen EM, Howell A, Astley S. Heritability of mammographic breast density. Quant Imaging Med Surg 2020; 10:2387-2391. [PMID: 33269237 DOI: 10.21037/qims-2020-20] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Affiliation(s)
- D Gareth Evans
- Clinical Genetics Service, Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, UK.,NW Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, UK.,Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.,Prevent Breast Cancer Centre, Wythenshawe Hospital Manchester Universities Foundation Trust, Wythenshawe, Manchester, UK.,Manchester Breast Centre, The Christie Hospital, Manchester, UK
| | - Elke M van Veen
- NW Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, UK.,Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Anthony Howell
- Prevent Breast Cancer Centre, Wythenshawe Hospital Manchester Universities Foundation Trust, Wythenshawe, Manchester, UK.,Manchester Breast Centre, The Christie Hospital, Manchester, UK
| | - Susan Astley
- Prevent Breast Cancer Centre, Wythenshawe Hospital Manchester Universities Foundation Trust, Wythenshawe, Manchester, UK.,Manchester Breast Centre, The Christie Hospital, Manchester, UK.,Division of Informatics, Imaging and Data Science, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
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14
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Holowko N, Eriksson M, Kuja-Halkola R, Azam S, He W, Hall P, Czene K. Heritability of Mammographic Breast Density, Density Change, Microcalcifications, and Masses. Cancer Res 2020; 80:1590-1600. [PMID: 32241951 DOI: 10.1158/0008-5472.can-19-2455] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2019] [Revised: 12/10/2019] [Accepted: 01/28/2020] [Indexed: 11/16/2022]
Abstract
Mammographic features influence breast cancer risk and are used in risk prediction models. Understanding how genetics influence mammographic features is important because the mechanisms through which they are associated with breast cancer are not well known. Here, using mammographic screening history and detailed questionnaire data from 56,820 women from the KARMA prospective cohort study, we investigated the association between a genetic predisposition to breast cancer and mammographic features among women with a family history of breast cancer (N = 49,674) and a polygenic risk score (PRS, N = 9,365). The heritability of mammographic features such as dense area (MD), microcalcifications, masses, and density change (MDC, cm2/year) was estimated using 1,940 sister pairs. Heritability was estimated at 58% [95% confidence interval (CI), 48%-67%) for MD, 23% (2%-45%) for microcalcifications, and 13% (1%-25%)] for masses. The estimated heritability for MDC was essentially null (2%; 95% CI, -8% to 12%). The association between a genetic predisposition to breast cancer (using PRS) and MD and microcalcifications was positive, while for masses this was borderline significant. In addition, for MDC, having a family history of breast cancer was associated with slightly greater MD reduction. In summary, we have confirmed previous findings of heritability in MD, and also established heritability of the number of microcalcifications and masses at baseline. Because these features are associated with breast cancer risk and can improve detecting women at short-term risk of breast cancer, further investigation of common loci associated with mammographic features is warranted to better understand the etiology of breast cancer. SIGNIFICANCE: These findings provide novel data on the heritability of microcalcifications, masses, and density change, which are all associated with breast cancer risk and can indicate women at short-term risk.
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Affiliation(s)
- Natalie Holowko
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
| | - Mikael Eriksson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Ralf Kuja-Halkola
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Shadi Azam
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Wei He
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Oncology, South General Hospital, Stockholm, Sweden
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
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15
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Sartor H, Brandt J, Grassmann F, Eriksson M, Czene K, Melander O, Zackrisson S. The association of single nucleotide polymorphisms (SNPs) with breast density and breast cancer survival: the Malmö Diet and Cancer Study. Acta Radiol 2020; 61:1326-1334. [PMID: 32036684 PMCID: PMC7564305 DOI: 10.1177/0284185119900436] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Background Genetic factors are important in determining breast density, and heritable factors account for 60% of the variation. Certain single nucleotide polymorphisms (SNPs) are associated with density and risk of breast cancer but the association with prognosis is not clear. Purpose To investigate associations between selected SNPs and breast cancer survival in the Malmö Diet and Cancer Study (MDCS). Material and Methods A total of 724 unrelated women with breast cancer and registered radiological and pathological data were identified in MDCS 1991–2007, with genotyping available for 672 women. Associations among 15 SNPs, density, and breast cancer-specific survival were analyzed using logistic/Cox regression, adjusted for factors affecting density and survival. Variants significantly associated with either density or survival were validated in a large independent breast cancer cohort (LIBRO-1). Results Minor homozygotes of SNPs rs9383589, CCDC170 and rs6557161, ESR1 were associated with high breast density (adjusted odds ratio [AOR] 8.97, 95% confidence interval [CI] 1.35–59.57; AOR 2.08, 95% CI 1.19–3.65, respectively) and poorer breast cancer survival (adjusted hazard ratio [HRadj] 6.46, 95% CI 1.95–21.39; HRadj 2.30, 95% CI 1.33–3.96, respectively) compared to major homozygotes. For SNP rs3757318, ESR1, minor homozygotes (HRadj 7.46, 95% CI 2.28–24.45) were associated with poorer survival. We confirmed that rs6557161, ESR1 was significantly associated with both density and survival in the LIBRO-1 study. Conclusion These findings support a shared genetic basis for density and breast cancer survival. The SNP significantly associated with both density and survival in both cohorts may be of interest in future research investigating polygenic risk scores for breast cancer risk and screening stratification purposes.
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Affiliation(s)
- Hanna Sartor
- Diagnostic Radiology, Department of Translational Medicine, Skåne University Hospital, Lund University, Lund, Sweden
| | - Jasmine Brandt
- Department of Surgery, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Felix Grassmann
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Mikael Eriksson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Olle Melander
- Hypertension and Cardiovascular Disease, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Sophia Zackrisson
- Diagnostic Radiology, Department of Translational Medicine, Skåne University Hospital, Lund University, Lund, Sweden
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16
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Bodelon C, Oh H, Derkach A, Sampson JN, Sprague BL, Vacek P, Weaver DL, Fan S, Palakal M, Papathomas D, Xiang J, Patel DA, Linville L, Clare SE, Visscher DW, Mies C, Hewitt SM, Brinton LA, Storniolo AMV, He C, Chanock SJ, Garcia-Closas M, Gierach GL, Figueroa JD. Polygenic risk score for the prediction of breast cancer is related to lesser terminal duct lobular unit involution of the breast. NPJ Breast Cancer 2020; 6:41. [PMID: 32964115 PMCID: PMC7477555 DOI: 10.1038/s41523-020-00184-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2019] [Accepted: 08/06/2020] [Indexed: 12/26/2022] Open
Abstract
Terminal duct lobular units (TDLUs) are the predominant anatomical structures where breast cancers originate. Having lesser degrees of age-related TDLU involution, measured as higher TDLUs counts or more epithelial TDLU substructures (acini), is related to increased breast cancer risk among women with benign breast disease (BBD). We evaluated whether a recently developed polygenic risk score (PRS) based on 313-common variants for breast cancer prediction is related to TDLU involution in the background, normal breast tissue, as this could provide mechanistic clues on the genetic predisposition to breast cancer. Among 1398 women without breast cancer, higher values of the PRS were significantly associated with higher TDLU counts (P = 0.004), but not with acini counts (P = 0.808), in histologically normal tissue samples from donors and diagnostic BBD biopsies. Mediation analysis indicated that TDLU counts may explain a modest proportion (≤10%) of the association of the 313-variant PRS with breast cancer risk. These findings suggest that TDLU involution might be an intermediate step in the association between common genetic variation and breast cancer risk.
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Affiliation(s)
- Clara Bodelon
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD USA
| | - Hannah Oh
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD USA
- Division of Health Policy and Management, College of Health Sciences, Korea University, Seoul, Korea
| | - Andriy Derkach
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD USA
| | - Joshua N. Sampson
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD USA
| | - Brian L. Sprague
- University of Vermont College of Medicine and Vermont Cancer Center, Burlington, VT USA
| | - Pamela Vacek
- University of Vermont College of Medicine and Vermont Cancer Center, Burlington, VT USA
| | - Donald L. Weaver
- University of Vermont College of Medicine and Vermont Cancer Center, Burlington, VT USA
| | - Shaoqi Fan
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD USA
| | - Maya Palakal
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD USA
| | - Daphne Papathomas
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD USA
| | - Jackie Xiang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD USA
| | - Deesha A. Patel
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD USA
| | - Laura Linville
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD USA
| | - Susan E. Clare
- Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL USA
| | - Daniel W. Visscher
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN USA
| | - Carolyn Mies
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA USA
| | - Stephen M. Hewitt
- Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, Bethesda, MD USA
| | - Louise A. Brinton
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD USA
| | - Anna Maria V. Storniolo
- Susan G. Komen Tissue Bank at the Indiana University Simon Cancer Center, Indianapolis, IN USA
| | - Chunyan He
- Department Internal Medicine, Division of Medical Oncology, College of Medicine, University of Kentucky, Lexington, KY USA
- Markey Cancer Center, University of Kentucky, Lexington, KY USA
| | - Stephen J. Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD USA
| | | | - Gretchen L. Gierach
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD USA
| | - Jonine D. Figueroa
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD USA
- Usher Institute of Population Health Sciences and Informatics and Cancer Research UK Edinburgh Centre, University of Edinburgh, Edinburgh, UK
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17
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Qian G, Ho JWK. Challenges and emerging systems biology approaches to discover how the human gut microbiome impact host physiology. Biophys Rev 2020; 12:851-863. [PMID: 32638331 PMCID: PMC7429608 DOI: 10.1007/s12551-020-00724-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Accepted: 07/02/2020] [Indexed: 02/07/2023] Open
Abstract
Research in the human gut microbiome has bloomed with advances in next generation sequencing (NGS) and other high-throughput molecular profiling technologies. This has enabled the generation of multi-omics datasets which holds promises for big data-enabled knowledge acquisition in the form of understanding the normal physiological and pathological involvement of gut microbiomes. Ample evidence suggests that distinct microbial compositions in the human gut are associated with different diseases. However, the biological mechanisms underlying these associations are often unclear. There is a need to move beyond statistical associations to discover how changes in the gut microbiota mechanistically affect host physiology and disease development. This review summarises state-of-the-art big data and systems biology approaches for mechanism discovery.
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Affiliation(s)
- Gordon Qian
- School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong
| | - Joshua W K Ho
- School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong.
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18
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Abstract
Mammographic density, which is determined by the relative amounts of fibroglandular tissue and fat in the breast, varies between women. Mammographic density is associated with a range of factors, including age and body mass index. The description of mammographic density has been transformed by the digitalization of mammography, which has allowed automation of the assessment of mammographic density, rather than using visual inspection by a radiologist. High mammographic density is important because it is associated with reduced sensitivity for the detection of breast cancer at the time of mammographic screening. High mammographic density is also associated with an elevated risk of developing breast cancer. Mammographic density appears to be on the causal pathway for some breast cancer risk factors, but not others. Mammographic density needs to be considered in the context of a woman's background risk of breast cancer. There is intense debate about the use of supplementary imaging for women with high mammographic density. Should supplementary imaging be used in women with high mammographic density and a clear mammogram? If so, what modalities of imaging should be used and in which women? Trials are underway to address the risks and benefits of supplementary imaging.
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Affiliation(s)
- R J Bell
- Women's Health Research Program, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
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19
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Wang Q, Ye J, Fang D, Lv L, Wu W, Shi D, Li Y, Yang L, Bian X, Wu J, Jiang X, Wang K, Wang Q, Hodson MP, Thibaut LM, Ho JWK, Giannoulatou E, Li L. Multi-omic profiling reveals associations between the gut mucosal microbiome, the metabolome, and host DNA methylation associated gene expression in patients with colorectal cancer. BMC Microbiol 2020; 20:83. [PMID: 32321427 PMCID: PMC7178946 DOI: 10.1186/s12866-020-01762-2] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Accepted: 03/23/2020] [Indexed: 12/24/2022] Open
Abstract
Background The human gut microbiome plays a critical role in the carcinogenesis of colorectal cancer (CRC). However, a comprehensive analysis of the interaction between the host and microbiome is still lacking. Results We found correlations between the change in abundance of microbial taxa, butyrate-related colonic metabolites, and methylation-associated host gene expression in colonic tumour mucosa tissues compared with the adjacent normal mucosa tissues. The increase of genus Fusobacterium abundance was correlated with a decrease in the level of 4-hydroxybutyric acid (4-HB) and expression of immune-related peptidase inhibitor 16 (PI16), Fc Receptor Like A (FCRLA) and Lymphocyte Specific Protein 1 (LSP1). The decrease in the abundance of another potentially 4-HB-associated genus, Prevotella 2, was also found to be correlated with the down-regulated expression of metallothionein 1 M (MT1M). Additionally, the increase of glutamic acid-related family Halomonadaceae was correlated with the decreased expression of reelin (RELN). The decreased abundance of genus Paeniclostridium and genus Enterococcus were correlated with increased lactic acid level, and were also linked to the expression change of Phospholipase C Beta 1 (PLCB1) and Immunoglobulin Superfamily Member 9 (IGSF9) respectively. Interestingly, 4-HB, glutamic acid and lactic acid are all butyrate precursors, which may modify gene expression by epigenetic regulation such as DNA methylation. Conclusions Our study identified associations between previously reported CRC-related microbial taxa, butyrate-related metabolites and DNA methylation-associated gene expression in tumour and normal colonic mucosa tissues from CRC patients, which uncovered a possible mechanism of the role of microbiome in the carcinogenesis of CRC. In addition, these findings offer insight into potential new biomarkers, therapeutic and/or prevention strategies for CRC.
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Affiliation(s)
- Qing Wang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.,Collaborative Innovation Centre for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China.,Computational Genomics Laboratory, Victor Chang Cardiac Research Institute, Sydney, Australia
| | - Jianzhong Ye
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.,Collaborative Innovation Centre for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Daiqiong Fang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.,Collaborative Innovation Centre for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Longxian Lv
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.,Collaborative Innovation Centre for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Wenrui Wu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.,Collaborative Innovation Centre for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Ding Shi
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.,Collaborative Innovation Centre for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Yating Li
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.,Collaborative Innovation Centre for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Liya Yang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.,Collaborative Innovation Centre for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Xiaoyuan Bian
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.,Collaborative Innovation Centre for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Jingjing Wu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.,Collaborative Innovation Centre for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Xianwan Jiang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.,Collaborative Innovation Centre for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Kaicen Wang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.,Collaborative Innovation Centre for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Qiangqiang Wang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.,Collaborative Innovation Centre for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Mark P Hodson
- Freedman Foundation Metabolomics Facility, Victor Chang Innovation Centre, Victor Chang Cardiac Research Institute, Sydney, Australia.,School of Pharmacy, University of Queensland, Woolloongabba, QLD 4102, Australia
| | - Loïc M Thibaut
- Computational Genomics Laboratory, Victor Chang Cardiac Research Institute, Sydney, Australia.,School of Mathematics and Statistics, UNSW Sydney, Sydney, Australia
| | - Joshua W K Ho
- Bioinformatics and Systems Medicine Laboratory, Victor Chang Cardiac Research Institute, Sydney, Australia.,School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Eleni Giannoulatou
- Computational Genomics Laboratory, Victor Chang Cardiac Research Institute, Sydney, Australia. .,St Vincent's Clinical School, UNSW Sydney, Sydney, Australia.
| | - Lanjuan Li
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China. .,Collaborative Innovation Centre for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China.
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20
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Hopper JL, Nguyen TL, Schmidt DF, Makalic E, Song YM, Sung J, Dite GS, Dowty JG, Li S. Going Beyond Conventional Mammographic Density to Discover Novel Mammogram-Based Predictors of Breast Cancer Risk. J Clin Med 2020; 9:jcm9030627. [PMID: 32110975 PMCID: PMC7141100 DOI: 10.3390/jcm9030627] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Revised: 02/15/2020] [Accepted: 02/17/2020] [Indexed: 12/12/2022] Open
Abstract
This commentary is about predicting a woman’s breast cancer risk from her mammogram, building on the work of Wolfe, Boyd and Yaffe on mammographic density. We summarise our efforts at finding new mammogram-based risk predictors, and how they combine with the conventional mammographic density, in predicting risk for interval cancers and screen-detected breast cancers across different ages at diagnosis and for both Caucasian and Asian women. Using the OPERA (odds ratio per adjusted standard deviation) concept, in which the risk gradient is measured on an appropriate scale that takes into account other factors adjusted for by design or analysis, we show that our new mammogram-based measures are the strongest of all currently known breast cancer risk factors in terms of risk discrimination on a population-basis. We summarise our findings graphically using a path diagram in which conventional mammographic density predicts interval cancer due to its role in masking, while the new mammogram-based risk measures could have a causal effect on both interval and screen-detected breast cancer. We discuss attempts by others to pursue this line of investigation, the measurement challenge that allows different measures to be compared in an open and transparent manner on the same datasets, as well as the biological and public health consequences.
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21
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Vachon CM, Scott CG, Tamimi RM, Thompson DJ, Fasching PA, Stone J, Southey MC, Winham S, Lindström S, Lilyquist J, Giles GG, Milne RL, MacInnis RJ, Baglietto L, Li J, Czene K, Bolla MK, Wang Q, Dennis J, Haeberle L, Eriksson M, Kraft P, Luben R, Wareham N, Olson JE, Norman A, Polley EC, Maskarinec G, Le Marchand L, Haiman CA, Hopper JL, Couch FJ, Easton DF, Hall P, Chatterjee N, Garcia-Closas M. Joint association of mammographic density adjusted for age and body mass index and polygenic risk score with breast cancer risk. Breast Cancer Res 2019; 21:68. [PMID: 31118087 PMCID: PMC6532188 DOI: 10.1186/s13058-019-1138-8] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2018] [Accepted: 04/15/2019] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Mammographic breast density, adjusted for age and body mass index, and a polygenic risk score (PRS), comprised of common genetic variation, are both strong risk factors for breast cancer and increase discrimination of risk models. Understanding their joint contribution will be important to more accurately predict risk. METHODS Using 3628 breast cancer cases and 5126 controls of European ancestry from eight case-control studies, we evaluated joint associations of a 77-single nucleotide polymorphism (SNP) PRS and quantitative mammographic density measures with breast cancer. Mammographic percent density and absolute dense area were evaluated using thresholding software and examined as residuals after adjusting for age, 1/BMI, and study. PRS and adjusted density phenotypes were modeled both continuously (per 1 standard deviation, SD) and categorically. We fit logistic regression models and tested the null hypothesis of multiplicative joint associations for PRS and adjusted density measures using likelihood ratio and global and tail-based goodness of fit tests within the subset of six cohort or population-based studies. RESULTS Adjusted percent density (odds ratio (OR) = 1.45 per SD, 95% CI 1.38-1.52), adjusted absolute dense area (OR = 1.34 per SD, 95% CI 1.28-1.41), and the 77-SNP PRS (OR = 1.52 per SD, 95% CI 1.45-1.59) were associated with breast cancer risk. There was no evidence of interaction of the PRS with adjusted percent density or dense area on risk of breast cancer by either the likelihood ratio (P > 0.21) or goodness of fit tests (P > 0.09), whether assessed continuously or categorically. The joint association (OR) was 2.60 in the highest categories of adjusted PD and PRS and 0.34 in the lowest categories, relative to women in the second density quartile and middle PRS quintile. CONCLUSIONS The combined associations of the 77-SNP PRS and adjusted density measures are generally well described by multiplicative models, and both risk factors provide independent information on breast cancer risk.
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Affiliation(s)
- Celine M. Vachon
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, 55905 MN USA
| | - Christopher G. Scott
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, 55905 MN USA
| | - Rulla M. Tamimi
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, 02115 MA USA
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA 02115 USA
- Program in Genetic Epidemiology and Statistical Genetics, Harvard TH Chan School of Public Health, Boston, MA 02115 USA
| | - Deborah J. Thompson
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN UK
| | - Peter A. Fasching
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen Nuremberg, University Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nuremberg, 91054 Erlangen, Germany
- Department of Medicine, Division of Hematology and Oncology, University of California at Los Angeles, David Geffen School of Medicine, Los Angeles, CA 90095 USA
| | - Jennifer Stone
- The Curtin UWA Centre for Genetic Origins of Health and Disease, Curtin University and University of Western Australia, Perth, Western Australia 6009 Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria 3010 Australia
| | - Melissa C. Southey
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria 3168 Australia
- Department of Clinical Pathology, The University of Melbourne, Melbourne, Victoria 3010 Australia
| | - Stacey Winham
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, 55905 MN USA
| | - Sara Lindström
- Department of Epidemiology, University of Washington School of Public Health, Seattle, WA 98195 USA
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109 USA
| | - Jenna Lilyquist
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, 55905 MN USA
| | - Graham G. Giles
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria 3010 Australia
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, Victoria 3004 Australia
- Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria Australia
| | - Roger L. Milne
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria 3010 Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria 3168 Australia
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, Victoria 3004 Australia
| | - Robert J. MacInnis
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria 3010 Australia
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, Victoria 3004 Australia
| | - Laura Baglietto
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, Victoria 3004 Australia
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Jingmei Li
- Human Genetics, Genome Institute of Singapore, Singapore, Singapore
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 65 Stockholm, Sweden
| | - Manjeet K. Bolla
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN UK
| | - Qin Wang
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN UK
| | - Joe Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN UK
| | - Lothar Haeberle
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen Nuremberg, University Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nuremberg, 91054 Erlangen, Germany
| | - Mikael Eriksson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 65 Stockholm, Sweden
| | - Peter Kraft
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, 02115 MA USA
- Program in Genetic Epidemiology and Statistical Genetics, Harvard TH Chan School of Public Health, Boston, MA 02115 USA
| | - Robert Luben
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN UK
| | - Nick Wareham
- Medical Research Council (MRC) Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, CB1 8RN UK
| | - Janet E. Olson
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, 55905 MN USA
| | - Aaron Norman
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, 55905 MN USA
| | - Eric C. Polley
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, 55905 MN USA
| | - Gertraud Maskarinec
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, 96813 HI USA
| | - Loic Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, 96813 HI USA
| | - Christopher A. Haiman
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033 USA
| | - John L. Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria 3010 Australia
| | - Fergus J. Couch
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905 USA
| | - Douglas F. Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN UK
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, CB1 8RN UK
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 65 Stockholm, Sweden
- Department of Oncology, South General Hospital, 118 83 Stockholm, Sweden
| | - Nilanjan Chatterjee
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892 USA
- Department of Biostatistics, Bloomberg School of Public Health, John Hopkins University, Baltimore, 21218 MD USA
- Department of Oncology, School of Medicine, John Hopkins University, Baltimore, 21218 MD USA
| | - Montse Garcia-Closas
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD 20850 USA
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22
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Lux MP, Emons J, Bani MR, Wunderle M, Sell C, Preuss C, Rauh C, Jud SM, Heindl F, Langemann H, Geyer T, Brandl AL, Hack CC, Adler W, Schulz-Wendtland R, Beckmann MW, Fasching PA, Gass P. Diagnostic Accuracy of Breast Medical Tactile Examiners (MTEs): A Prospective Pilot Study. Breast Care (Basel) 2019; 14:41-47. [PMID: 31019442 DOI: 10.1159/000495883] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
Background The usefulness of clinical breast examination (CBE) in general and in breast cancer screening programs has been a matter of debate. This study investigated whether adding vision-impaired medical tactile examiners (MTEs) improves the predictiveness of CBE for suspicious lesions and analyzed the feasibility and acceptability of this approach. Methods The prospective study included 104 patients. Physicians and MTEs performed CBEs, and mammography and ultrasound results were used as the gold standard. Sensitivity and specificity were calculated and logistic regression models were used to compare the predictive value of CBE by physicians alone, MTEs alone, and physicians and MTEs combined. Results For CBEs by physicians alone, MTEs alone, and both combined, sensitivity was 71, 82, and 89% and specificity was 55, 45, and 35%, respectively. Using adjusted logistic regression models, the validated areas under the curve were 0.685, 0.692, and 0.710 (median bootstrapped p value (DeLong) = 0.381). Conclusion The predictive value for a suspicious breast lesion in CBEs performed by MTEs in patients without prior surgery was similar to that of physician-conducted CBEs. Including MTEs in the CBE procedure in breast units thus appears feasible and could be a way of utilizing their skills.
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Affiliation(s)
- Michael P Lux
- Department of Gynecology and Obstetrics, Erlangen University Hospital, Comprehensive Cancer Center Erlangen - EMN, Friedrich Alexander University of Erlangen-Nuremberg, Erlangen
| | - Julius Emons
- Department of Gynecology and Obstetrics, Erlangen University Hospital, Comprehensive Cancer Center Erlangen - EMN, Friedrich Alexander University of Erlangen-Nuremberg, Erlangen
| | - Mayada R Bani
- Department of Gynecology and Obstetrics, Erlangen University Hospital, Comprehensive Cancer Center Erlangen - EMN, Friedrich Alexander University of Erlangen-Nuremberg, Erlangen
| | - Marius Wunderle
- Department of Gynecology and Obstetrics, Erlangen University Hospital, Comprehensive Cancer Center Erlangen - EMN, Friedrich Alexander University of Erlangen-Nuremberg, Erlangen
| | - Charlotte Sell
- Department of Gynecology and Obstetrics, Erlangen University Hospital, Comprehensive Cancer Center Erlangen - EMN, Friedrich Alexander University of Erlangen-Nuremberg, Erlangen
| | - Caroline Preuss
- Department of Gynecology and Obstetrics, Erlangen University Hospital, Comprehensive Cancer Center Erlangen - EMN, Friedrich Alexander University of Erlangen-Nuremberg, Erlangen
| | - Claudia Rauh
- Department of Gynecology and Obstetrics, Erlangen University Hospital, Comprehensive Cancer Center Erlangen - EMN, Friedrich Alexander University of Erlangen-Nuremberg, Erlangen
| | - Sebastian M Jud
- Department of Gynecology and Obstetrics, Erlangen University Hospital, Comprehensive Cancer Center Erlangen - EMN, Friedrich Alexander University of Erlangen-Nuremberg, Erlangen
| | - Felix Heindl
- Department of Gynecology and Obstetrics, Erlangen University Hospital, Comprehensive Cancer Center Erlangen - EMN, Friedrich Alexander University of Erlangen-Nuremberg, Erlangen
| | - Hanna Langemann
- Department of Gynecology and Obstetrics, Erlangen University Hospital, Comprehensive Cancer Center Erlangen - EMN, Friedrich Alexander University of Erlangen-Nuremberg, Erlangen
| | - Thomas Geyer
- Department of Gynecology and Obstetrics, Erlangen University Hospital, Comprehensive Cancer Center Erlangen - EMN, Friedrich Alexander University of Erlangen-Nuremberg, Erlangen
| | - Anna-Lisa Brandl
- Department of Gynecology and Obstetrics, Erlangen University Hospital, Comprehensive Cancer Center Erlangen - EMN, Friedrich Alexander University of Erlangen-Nuremberg, Erlangen
| | - Carolin C Hack
- Department of Gynecology and Obstetrics, Erlangen University Hospital, Comprehensive Cancer Center Erlangen - EMN, Friedrich Alexander University of Erlangen-Nuremberg, Erlangen
| | - Werner Adler
- Institute of Biometry and Epidemiology, Friedrich Alexander University of Erlangen-Nuremberg, Erlangen
| | | | - Matthias W Beckmann
- Department of Gynecology and Obstetrics, Erlangen University Hospital, Comprehensive Cancer Center Erlangen - EMN, Friedrich Alexander University of Erlangen-Nuremberg, Erlangen
| | - Peter A Fasching
- Department of Gynecology and Obstetrics, Erlangen University Hospital, Comprehensive Cancer Center Erlangen - EMN, Friedrich Alexander University of Erlangen-Nuremberg, Erlangen
| | - Paul Gass
- Department of Gynecology and Obstetrics, Erlangen University Hospital, Comprehensive Cancer Center Erlangen - EMN, Friedrich Alexander University of Erlangen-Nuremberg, Erlangen
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23
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Lippey J, Keogh LA, Mann GB, Campbell IG, Forrest LE. "A Natural Progression": Australian Women's Attitudes About an Individualized Breast Screening Model. Cancer Prev Res (Phila) 2019; 12:383-390. [PMID: 31003994 DOI: 10.1158/1940-6207.capr-18-0443] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2018] [Revised: 03/01/2019] [Accepted: 04/09/2019] [Indexed: 11/16/2022]
Abstract
Individualized screening is our logical next step to improve population breast cancer screening in Australia. To explore breast screening participants' views of the current program in Victoria, Australia, examine their openness to change, and attitudes toward an individualized screening model, this qualitative work was performed from a population-based breast screening cohort. This work was designed to inform the development of a decision aid to facilitate women's decisions about participating in individualized screening, and to elicit Australian consumer perspectives on the international movement toward individualized breast screening. A total of 52 women participated in one of four focus groups, and were experienced with screening with 90% of participants having had more than three mammograms. Focus group discussion was facilitated following three main themes: (i) experience of breast screening; (ii) breast cancer risk perception, and (iii) views on individualized screening. Participants had strong, positive, emotional ties to breast screening in its current structure but were supportive, with some reservations, of the idea of individualized screening. There was good understanding about the factors contributing to personalized risk and a wide range of opinions about the inclusion of genetic testing with genetic testing being considered a foreign and evolving domain. Individualized breast screening that takes account of risk factors such as mammographic density, lifestyle, and genetic factors would be acceptable to a population of women who are invested in the current system. The communication and implementation of a new program would be critical to its acceptance and potential success. Reservations may be had in regards to uptake of genetic testing, motivations behind the change, and management of the women allocated to a lower risk category.
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Affiliation(s)
- Jocelyn Lippey
- Department of Surgery, University of Melbourne, Melbourne, Australia. .,St. Vincent's Hospital, Victoria, Australia
| | - Louise A Keogh
- Melbourne School of Population and Global Health, University of Melbourne, Carlton, Australia
| | - G Bruce Mann
- Department of Surgery, University of Melbourne, Melbourne, Australia.,Royal Melbourne Hospital, Victoria, Australia
| | - Ian G Campbell
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, Australia.,Cancer Genetics Laboratory, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Laura E Forrest
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, Australia.,Parkville Familial Cancer Centre, Peter MacCallum Cancer Centre, Melbourne, Australia
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24
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Li S, Dugué PA, Baglietto L, Severi G, Wong EM, Nguyen TL, Stone J, English DR, Southey MC, Giles GG, Hopper JL, Milne RL. Genome-wide association study of peripheral blood DNA methylation and conventional mammographic density measures. Int J Cancer 2019; 145:1768-1773. [PMID: 30694562 DOI: 10.1002/ijc.32171] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2018] [Revised: 01/18/2019] [Accepted: 01/22/2019] [Indexed: 02/06/2023]
Abstract
Age- and body mass index (BMI)-adjusted mammographic density is one of the strongest breast cancer risk factors. DNA methylation is a molecular mechanism that could underlie inter-individual variation in mammographic density. We aimed to investigate the association between breast cancer risk-predicting mammographic density measures and blood DNA methylation. For 436 women from the Australian Mammographic Density Twins and Sisters Study and 591 women from the Melbourne Collaborative Cohort Study, mammographic density (dense area, nondense area and percentage dense area) defined by the conventional brightness threshold was measured using the CUMULUS software, and peripheral blood DNA methylation was measured using the HumanMethylation450 (HM450) BeadChip assay. Associations between DNA methylation at >400,000 sites and mammographic density measures adjusted for age and BMI were assessed within each cohort and pooled using fixed-effect meta-analysis. Associations with methylation at genetic loci known to be associated with mammographic density were also examined. We found no genome-wide significant (p < 10-7 ) association for any mammographic density measure from the meta-analysis, or from the cohort-specific analyses. None of the 299 methylation sites located at genetic loci associated with mammographic density was associated with any mammographic density measure after adjusting for multiple testing (all p > 0.05/299 = 1.7 × 10-4 ). In summary, our study did not find evidence for associations between blood DNA methylation, as measured by the HM450 assay, and conventional mammographic density measures that predict breast cancer risk.
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Affiliation(s)
- Shuai Li
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, Australia.,Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Pierre-Antoine Dugué
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, Australia.,Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia.,Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia
| | - Laura Baglietto
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Gianluca Severi
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, Australia.,Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia.,Centre de Recherche en Épidémiologie et Santé des Populations (INSERM U1018), Université Paris-Saclay, Université Paris-Sud, Université Versailles Saint-Quentin-en-Yvelines, Institut Gustave Roussy, Villejuif, France
| | - Ee Ming Wong
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia.,Genetic Epidemiology Laboratory, Department of Clinical Pathology, The University of Melbourne, Parkville, VIC, Australia
| | - Tuong L Nguyen
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, Australia
| | - Jennifer Stone
- Centre for Genetic Origins of Health and Disease, Curtin University and the University of Western Australia, Perth, WA, Australia
| | - Dallas R English
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, Australia.,Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia
| | - Melissa C Southey
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia.,Genetic Epidemiology Laboratory, Department of Clinical Pathology, The University of Melbourne, Parkville, VIC, Australia
| | - Graham G Giles
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, Australia.,Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, Australia.,Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia
| | - Roger L Milne
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, Australia.,Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia.,Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia
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25
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Nguyen TL, Aung YK, Li S, Trinh NH, Evans CF, Baglietto L, Krishnan K, Dite GS, Stone J, English DR, Song YM, Sung J, Jenkins MA, Southey MC, Giles GG, Hopper JL. Predicting interval and screen-detected breast cancers from mammographic density defined by different brightness thresholds. Breast Cancer Res 2018; 20:152. [PMID: 30545395 PMCID: PMC6293866 DOI: 10.1186/s13058-018-1081-0] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2018] [Accepted: 11/19/2018] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Case-control studies show that mammographic density is a better risk factor when defined at higher than conventional pixel-brightness thresholds. We asked if this applied to interval and/or screen-detected cancers. METHOD We conducted a nested case-control study within the prospective Melbourne Collaborative Cohort Study including 168 women with interval and 422 with screen-detected breast cancers, and 498 and 1197 matched controls, respectively. We measured absolute and percent mammographic density using the Cumulus software at the conventional threshold (Cumulus) and two increasingly higher thresholds (Altocumulus and Cirrocumulus, respectively). Measures were transformed and adjusted for age and body mass index (BMI). Using conditional logistic regression and adjusting for BMI by age at mammogram, we estimated risk discrimination by the odds ratio per adjusted standard deviation (OPERA), calculated the area under the receiver operating characteristic curve (AUC) and compared nested models using the likelihood ratio criterion and models with the same number of parameters using the difference in Bayesian information criterion (ΔBIC). RESULTS For interval cancer, there was very strong evidence that the association was best predicted by Cumulus as a percentage (OPERA = 2.33 (95% confidence interval (CI) 1.85-2.92); all ΔBIC > 14), and the association with BMI was independent of age at mammogram. After adjusting for percent Cumulus, no other measure was associated with risk (all P > 0.1). For screen-detected cancer, however, the associations were strongest for the absolute and percent Cirrocumulus measures (all ΔBIC > 6), and after adjusting for Cirrocumulus, no other measure was associated with risk (all P > 0.07). CONCLUSION The amount of brighter areas is the best mammogram-based measure of screen-detected breast cancer risk, while the percentage of the breast covered by white or bright areas is the best mammogram-based measure of interval breast cancer risk, irrespective of BMI. Therefore, there are different features of mammographic images that give clinically important information about different outcomes.
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Affiliation(s)
- Tuong L Nguyen
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Level 3/207 Bouverie Street, Carlton, VIC, 3053, Australia
| | - Ye K Aung
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Level 3/207 Bouverie Street, Carlton, VIC, 3053, Australia
| | - Shuai Li
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Level 3/207 Bouverie Street, Carlton, VIC, 3053, Australia
| | - Nhut Ho Trinh
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Level 3/207 Bouverie Street, Carlton, VIC, 3053, Australia
| | - Christopher F Evans
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Level 3/207 Bouverie Street, Carlton, VIC, 3053, Australia
| | - Laura Baglietto
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Level 3/207 Bouverie Street, Carlton, VIC, 3053, Australia.,Department of Clinical and Experimental Medicine, University of Pisa, ᅟPisa, Italy
| | - Kavitha Krishnan
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Level 3/207 Bouverie Street, Carlton, VIC, 3053, Australia
| | - Gillian S Dite
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Level 3/207 Bouverie Street, Carlton, VIC, 3053, Australia
| | - Jennifer Stone
- Curtin UWA Centre for Genetic Origins of Health and Disease, Curtin University and the University of Western Australia, Perth, Western WA, 6009, Australia
| | - Dallas R English
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Level 3/207 Bouverie Street, Carlton, VIC, 3053, Australia.,Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia
| | - Yun-Mi Song
- Department of Family Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Irwon-ro 81, Gangnamgu, Seoul, 06351, South Korea
| | - Joohon Sung
- Department of Epidemiology School of Public Health, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 151-742, Korea.,Institute of Health and Environment, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 151-742, Korea
| | - Mark A Jenkins
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Level 3/207 Bouverie Street, Carlton, VIC, 3053, Australia
| | - Melissa C Southey
- Department of Pathology, University of Melbourne, Carlton, Victoria, 3053, Australia.,Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Graham G Giles
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Level 3/207 Bouverie Street, Carlton, VIC, 3053, Australia.,Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Level 3/207 Bouverie Street, Carlton, VIC, 3053, Australia.
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26
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Fiorino S, Di Saverio S, Leandri P, Tura A, Birtolo C, Silingardi M, de Biase D, Avisar E. The role of matricellular proteins and tissue stiffness in breast cancer: a systematic review. Future Oncol 2018; 14:1601-1627. [PMID: 29939077 DOI: 10.2217/fon-2017-0510] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
Abstract
Malignancies consist not only of cancerous and nonmalignant cells, but also of additional elements, as extracellular matrix. The aim of this review is to summarize meta-analyses, describing breast tissue stiffness and risk of breast carcinoma (BC) assessing the potential relationship between matricellular proteins (MPs) and survival. A systematic computer-based search of published articles, according to PRISMA statement, was conducted through Ovid interface. Mammographic density and tissue stiffness are associated with the risk of BC development, suggesting that MPs may influence BC prognosis. No definitive conclusions are available and additional researches are required to definitively clarify the role of each MP, mammographic density and stiffness in BC development and the mechanisms involved in the onset of this malignancy.
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Affiliation(s)
- Sirio Fiorino
- Internal Medicine 'C' Unit, Maggiore Hospital, Local Health Unit of Bologna, Bologna, Italy
| | - Salomone Di Saverio
- Cambridge Colorectal Unit, Box 201, Cambridge University Hospitals NHS Foundation Trust, Addenbrooke's Hospital, Cambridge Biomedical Campus, Hills Road, Cambridge CB2 0QQ, UK
| | - Paolo Leandri
- Internal Medicine 'C' Unit, Maggiore Hospital, Local Health Unit of Bologna, Bologna, Italy
| | - Andrea Tura
- Metabolic Unit, CNR Institute of Neuroscience, Padova, Italy
| | - Chiara Birtolo
- Geriatric Unit, Azienda USL-Maggiore Hospital, Largo Nigrisoli 3, Bologna, Italy
| | - Mauro Silingardi
- Internal Medicine 'A' Unit, Maggiore Hospital, Local Health Unit of Bologna, Bologna, Italy
| | - Dario de Biase
- Department of Pharmacy & Biotechnology, Molecular Pathology Unit, University of Bologna, Bologna, Italy
| | - Eli Avisar
- Division of Surgical Oncology, Department of Surgery, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
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27
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Zhao X, Li Y, Wu H. A novel scoring system for acute myeloid leukemia risk assessment based on the expression levels of six genes. Int J Mol Med 2018; 42:1495-1507. [PMID: 29956722 PMCID: PMC6089755 DOI: 10.3892/ijmm.2018.3739] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2017] [Accepted: 05/14/2018] [Indexed: 12/19/2022] Open
Abstract
Acute myeloid leukemia (AML) is the most common type of acute leukemia and is a heterogeneous clonal disorder. At present, the pathogenesis of AML and potential methods to effectively prevent AML have become areas of interest in research. In the present study, two messenger ribonucleic acid sequencing datasets of patients with AML were downloaded from the Cancer Genome Atlas and Gene Expression Omnibus databases. The differentially expressed genes (DEGs) of the poor and good prognosis groups were screened using the Linear Models for Microarray Data package, and the prognosis-related genes were screened using univariate Cox regression analysis. A total of 206 significant DEGs were identified. Following univariate and multivariate Cox regression analysis, 14 genes significantly associated with prognosis were screened and six of these genes, including triggering receptor expressed on myeloid cells 2 (TREML2), cysteine-glutamate transporter (SLC7A11), NACHT, LRR, and PYD domains-containing protein 2 (NLRP2), DNA damage-inducible transcript 4 protein (DDIT4), lymphocyte‑specific protein 1 (LSP1) and C-type lectin domain family 11 member A (CLEC11A), were used to construct model equations for risk assessment. The prognostic scoring system was used to evaluate risk for each patient, and the results showed that patients in the low-risk group had a longer survival time, compared with those in the high-risk group (P=9.59e-06 for the training dataset and P=0.00543 for the validation dataset). A total of eight main Kyoto Encyclopedia of Genes and Genomes pathways were identified, the top three of which were hematopoietic cell lineage, focal adhesion, and regulation of actin cytoskeleton. Taken together, the results showed that the scoring system established in the present study was credible and that the six genes were identified, which were significantly associated with the risk assessment of AML, offer potential as prognostic biomarkers. These findings may provide clues for further clarifying the pathogenesis of AML.
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Affiliation(s)
- Xiaoyan Zhao
- Department of Hematology, The First Hospital of Jiaxing, Jiaxing, Zhejiang 314000, P.R. China
| | - Yuan Li
- Department of Hematology, The First Hospital of Jiaxing, Jiaxing, Zhejiang 314000, P.R. China
| | - Haibing Wu
- Department of Hematology, The First Hospital of Jiaxing, Jiaxing, Zhejiang 314000, P.R. China
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28
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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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29
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Flister MJ, Bergom C. Genetic Modifiers of the Breast Tumor Microenvironment. Trends Cancer 2018; 4:429-444. [PMID: 29860987 DOI: 10.1016/j.trecan.2018.04.003] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2017] [Revised: 04/13/2018] [Accepted: 04/16/2018] [Indexed: 02/06/2023]
Abstract
Multiple nonmalignant cell types in the tumor microenvironment (TME) impact breast cancer risk, metastasis, and response to therapy, yet most heritable mechanisms that influence TME cell function and breast cancer outcomes are largely unknown. Breast cancer risk is ∼30% heritable and >170 genetic loci have been associated with breast cancer traits. However, the majority of candidate genes have poorly defined mechanistic roles in breast cancer biology. Research indicates that breast cancer risk modifiers directly impact cancer cells, yet it is equally plausible that some modifier alleles impact the nonmalignant TME. The objective of this review is to examine the list of current breast cancer candidate genes that may modify breast cancer risk and outcome through the TME.
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Affiliation(s)
- Michael J Flister
- Genomic Sciences and Precision Medicine Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA; Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA; Department of Physiology, Medical College of Wisconsin, Milwaukee, WI 53226, USA.
| | - Carmen Bergom
- Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA; Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI 53226, USA
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30
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Brand JS, Humphreys K, Li J, Karlsson R, Hall P, Czene K. Common genetic variation and novel loci associated with volumetric mammographic density. Breast Cancer Res 2018; 20:30. [PMID: 29665850 PMCID: PMC5904990 DOI: 10.1186/s13058-018-0954-6] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2017] [Accepted: 03/09/2018] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND Mammographic density (MD) is a strong and heritable intermediate phenotype of breast cancer, but much of its genetic variation remains unexplained. METHODS We conducted a genetic association study of volumetric MD in a Swedish mammography screening cohort (n = 9498) to identify novel MD loci. Associations with volumetric MD phenotypes (percent dense volume, absolute dense volume, and absolute nondense volume) were estimated using linear regression adjusting for age, body mass index, menopausal status, and six principal components. We also estimated the proportion of MD variance explained by additive contributions from single-nucleotide polymorphisms (SNP-based heritability [h2SNP]) in 4948 participants of the cohort. RESULTS In total, three novel MD loci were identified (at P < 5 × 10- 8): one for percent dense volume (HABP2) and two for the absolute dense volume (INHBB, LINC01483). INHBB is an established locus for ER-negative breast cancer, and HABP2 and LINC01483 represent putative new breast cancer susceptibility loci, because both loci were associated with breast cancer in available meta-analysis data including 122,977 breast cancer cases and 105,974 control subjects (P < 0.05). h2SNP (SE) estimates for percent dense, absolute dense, and nondense volume were 0.29 (0.07), 0.31 (0.07), and 0.25 (0.07), respectively. Corresponding ratios of h2SNP to previously observed narrow-sense h2 estimates in the same cohort were 0.46, 0.72, and 0.41, respectively. CONCLUSIONS These findings provide new insights into the genetic basis of MD and biological mechanisms linking MD to breast cancer risk. Apart from identifying three novel loci, we demonstrate that at least 25% of the MD variance is explained by common genetic variation with h2SNP/h2 ratios varying between dense and nondense MD components.
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Affiliation(s)
- Judith S Brand
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Väg 12A, 171 77, Stockholm, Sweden.
| | - Keith Humphreys
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Väg 12A, 171 77, Stockholm, Sweden
| | - Jingmei Li
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Väg 12A, 171 77, Stockholm, Sweden.,Human Genetics, Genome Institute of Singapore, Singapore, Singapore
| | - Robert Karlsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Väg 12A, 171 77, Stockholm, Sweden
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Väg 12A, 171 77, Stockholm, Sweden
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Väg 12A, 171 77, Stockholm, Sweden
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31
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Stone J. Should breast cancer screening programs routinely measure mammographic density? J Med Imaging Radiat Oncol 2018; 62:151-158. [DOI: 10.1111/1754-9485.12652] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2016] [Accepted: 08/05/2017] [Indexed: 11/29/2022]
Affiliation(s)
- Jennifer Stone
- Centre for Genetic Origins of Health and Disease; Curtin University and The University of Western Australia; Perth Western Australia Australia
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32
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Lilyquist J, Ruddy KJ, Vachon CM, Couch FJ. Common Genetic Variation and Breast Cancer Risk-Past, Present, and Future. Cancer Epidemiol Biomarkers Prev 2018; 27:380-394. [PMID: 29382703 PMCID: PMC5884707 DOI: 10.1158/1055-9965.epi-17-1144] [Citation(s) in RCA: 86] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2017] [Revised: 01/05/2018] [Accepted: 01/11/2018] [Indexed: 11/16/2022] Open
Abstract
Breast cancer is the most common cancer among women in the United States, with up to 30% of those diagnosed displaying a family history of breast cancer. To date, 18% of the familial risk of breast cancer can be explained by SNPs. This review summarizes the discovery of risk-associated SNPs using candidate gene and genome-wide association studies (GWAS), including discovery and replication in large collaborative efforts such as The Collaborative Oncologic Gene-environment Study and OncoArray. We discuss the evolution of GWAS studies, efforts to discover additional SNPs, and methods for identifying causal variants. We summarize findings associated with overall breast cancer, pathologic subtypes, and mutation carriers (BRCA1, BRCA2, and CHEK2). In addition, we summarize the development of polygenic risk scores (PRS) using the risk-associated SNPs and show how PRS can contribute to estimation of individual risks for developing breast cancer. Cancer Epidemiol Biomarkers Prev; 27(4); 380-94. ©2018 AACRSee all articles in this CEBP Focus section, "Genome-Wide Association Studies in Cancer."
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Affiliation(s)
- Jenna Lilyquist
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
| | | | - Celine M Vachon
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota
| | - Fergus J Couch
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota.
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
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33
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Rice MS, Tamimi RM, Bertrand KA, Scott CG, Jensen MR, Norman AD, Visscher DW, Chen YY, Brandt KR, Couch FJ, Shepherd JA, Fan B, Wu FF, Ma L, Collins LC, Cummings SR, Kerlikowske K, Vachon CM. Does mammographic density mediate risk factor associations with breast cancer? An analysis by tumor characteristics. Breast Cancer Res Treat 2018; 170:129-141. [PMID: 29502324 DOI: 10.1007/s10549-018-4735-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2017] [Accepted: 02/26/2018] [Indexed: 11/29/2022]
Abstract
BACKGROUND Though mammographic density (MD) has been proposed as an intermediate marker of breast cancer risk, few studies have examined whether the associations between breast cancer risk factors and risk are mediated by MD, particularly by tumor characteristics. METHODS Our study population included 3392 cases (1105 premenopausal) and 8882 (3192 premenopausal) controls from four case-control studies. For established risk factors, we estimated the percent of the total risk factor association with breast cancer that was mediated by percent MD (secondarily, by dense area and non-dense area) for invasive breast cancer as well as for subtypes defined by the estrogen receptor (ER+/ER-), progesterone receptor (PR+/PR-), and HER2 (HER2+/HER2-). Analyses were conducted separately in pre- and postmenopausal women. RESULTS Positive associations between prior breast biopsy and risk of invasive breast cancer as well as all subtypes were partially mediated by percent MD in pre- and postmenopausal women (percent mediated = 11-27%, p ≤ 0.02). In postmenopausal women, nulliparity and hormone therapy use were positively associated with invasive, ER+ , PR+ , and HER2- breast cancer; percent MD partially mediated these associations (percent mediated ≥ 31%, p ≤ 0.02). Further, among postmenopausal women, percent MD partially mediated the positive association between later age at first birth and invasive as well as ER+ breast cancer (percent mediated = 16%, p ≤ 0.05). CONCLUSION Percent MD partially mediated the associations between breast biopsy, nulliparity, age at first birth, and hormone therapy with risk of breast cancer, particularly among postmenopausal women, suggesting that these risk factors at least partially influence breast cancer risk through changes in breast tissue composition.
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Affiliation(s)
- Megan S Rice
- Clinical and Translational Epidemiology Unit, Department of Medicine, Massachusetts General Hospital/Harvard Medical School, 55 Fruit Street, Bartlett 9, Boston, MA, 02116, USA.
| | - Rulla M Tamimi
- Channing Division of Network Medicine, Brigham and Women's Hospital/Harvard Medical School, Boston, MA, USA.,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | | | | | - Matthew R Jensen
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Aaron D Norman
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | | | - Yunn-Yi Chen
- Department of Pathology, University of California, San Francisco, CA, USA
| | | | - Fergus J Couch
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - John A Shepherd
- Department of Radiology, University of California, San Francisco, CA, USA
| | - Bo Fan
- Department of Radiology, University of California, San Francisco, CA, USA
| | - Fang-Fang Wu
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Lin Ma
- Department of Medicine, University of California, San Francisco, CA, USA
| | - Laura C Collins
- Department of Pathology, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, USA
| | - Steven R Cummings
- San Francisco Coordinating Center, California Pacific Medical Center Research Institute, San Francisco, CA, USA
| | - Karla Kerlikowske
- Departments of Epidemiology and Biostatistics and General Internal Medicine Section, Department of Veterans Affairs, University of California, San Francisco, CA, USA
| | - Celine M Vachon
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
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34
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McLean KE, Stone J. Role of breast density measurement in screening for breast cancer. Climacteric 2018; 21:214-220. [DOI: 10.1080/13697137.2018.1424816] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Affiliation(s)
- K. E. McLean
- Centre for Genetic Origins of Health and Disease, Curtin University and The University of Western Australia, Perth, WA, Australia
| | - J. Stone
- Centre for Genetic Origins of Health and Disease, Curtin University and The University of Western Australia, Perth, WA, Australia
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35
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Breast cancer risk factors and mammographic density among high-risk women in urban China. NPJ Breast Cancer 2018; 4:3. [PMID: 29423438 PMCID: PMC5802809 DOI: 10.1038/s41523-018-0055-9] [Citation(s) in RCA: 51] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2017] [Revised: 12/05/2017] [Accepted: 01/03/2018] [Indexed: 01/05/2023] Open
Abstract
Elevated mammographic density (MD) is an established breast cancer risk factor. Studies examining relationships between MD and breast cancer risk factors are limited in China, where established breast cancer risk factors are less prevalent but dense breasts are more prevalent than Western countries. This study included 11,478 women (45-69 years; 36% premenopausal) participating in an ongoing national cancer screening program in 11 urban provinces in China and predicted as having high-risk for breast cancer. Polytomous logistic regression was performed to assess associations between MD and risk factors by comparing each higher Breast Imaging Reporting and Data System (BI-RADS) category (2, 3, or 4) to the lowest category (BI-RADS, 1). We found associations of increasing age, body mass index, weight, postmenopausal status, and parity with lower MD. Higher levels of education, increasing height, and later first birth were associated with higher MD. These associations did not vary by menopausal status. Additionally, the association between longer period of breastfeeding and lower MD was seen among postmenopausal women only (Pinteraction = 0.003). Having first-degree relatives with breast cancer diagnosed before 50 years was associated with lower MD only among premenopausal women (Pinteraction = 0.061). We found effects of established breast cancer risk factors on MD showed similar directions in Chinese and Western women, supporting the hypothesis that MD represents cumulative exposure to breast cancer risk factors over the life course. Our findings help to understand the biological basis of the association of MD with breast cancer risk and have implications for breast cancer prevention research in China.
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36
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Zhou S, Bai ZL, Xia D, Zhao ZJ, Zhao R, Wang YY, Zhe H. FTO regulates the chemo-radiotherapy resistance of cervical squamous cell carcinoma (CSCC) by targeting β-catenin through mRNA demethylation. Mol Carcinog 2018; 57:590-597. [PMID: 29315835 DOI: 10.1002/mc.22782] [Citation(s) in RCA: 255] [Impact Index Per Article: 42.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2017] [Revised: 12/26/2017] [Accepted: 01/02/2018] [Indexed: 12/27/2022]
Abstract
The role of N6 -methyladenosine (m6 A) demethylase fat mass and obesity-associated protein (FTO) in the regulation of chemo-radiotherapy resistance remains largely unknown. Here, we show that the mRNA level of FTO is elevated in cervical squamous cell carcinoma (CSCC) tissues when compared with respective adjacent normal tissues. FTO enhances the chemo-radiotherapy resistance both in vitro and in vivo through regulating expression of β-catenin by reducing m6 A levels in its mRNA transcripts and in turn increases excision repair cross-complementation group 1 (ERCC1) activity. Clinically, the prognostic value of FTO for overall survival is found to be dependent on β-catenin expression in human CSCC samples. Taken together, these findings uncover a critical function for FTO and its substrate m6 A in the regulation of chemo-radiotherapy resistance, which may bear potential clinical implications for CSCC treatment.
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Affiliation(s)
- Shun Zhou
- Graduated School, Ningxia Medical University, Yinchuan, Ningxia, China.,Department of Radiation Oncology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, China
| | - Zhou-Lan Bai
- Department of Radiation Oncology, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, China.,Cancer Institute, Ningxia Medical University, Yinchuan, Ningxia, China
| | - Di Xia
- Graduated School, Ningxia Medical University, Yinchuan, Ningxia, China
| | - Zhi-Jun Zhao
- Department of Laboratory Medicine, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, China
| | - Ren Zhao
- Department of Radiation Oncology, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, China.,Cancer Institute, Ningxia Medical University, Yinchuan, Ningxia, China
| | - Yan-Yang Wang
- Department of Radiation Oncology, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, China.,Cancer Institute, Ningxia Medical University, Yinchuan, Ningxia, China
| | - Hong Zhe
- Department of Radiation Oncology, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, China.,Cancer Institute, Ningxia Medical University, Yinchuan, Ningxia, China
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37
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Ironside AJ, Jones JL. Stromal characteristics may hold the key to mammographic density: the evidence to date. Oncotarget 2017; 7:31550-62. [PMID: 26784251 PMCID: PMC5058777 DOI: 10.18632/oncotarget.6912] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2015] [Accepted: 01/02/2016] [Indexed: 12/11/2022] Open
Abstract
There is strong epidemiological data indicating a role for increased mammographic density (MD) in predisposing to breast cancer, however, the biological mechanisms underlying this phenomenon are less well understood. Recently, studies of human breast tissues have started to characterise the features of mammographically dense breasts, and a number of in-vitro and in-vivo studies have explored the potential mechanisms through which dense breast tissue may exert this tumourigenic risk. This article aims to review both the pathological and biological evidence implicating a key role for the breast stromal compartment in MD, how this may be modified and the clinical significance of these findings. The epidemiological context will be briefly discussed but will not be covered in detail.
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Affiliation(s)
- Alastair J Ironside
- Centre for Tumour Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - J Louise Jones
- Centre for Tumour Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
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38
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Vinnicombe SJ. Breast density: why all the fuss? Clin Radiol 2017; 73:334-357. [PMID: 29273225 DOI: 10.1016/j.crad.2017.11.018] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2017] [Accepted: 11/17/2017] [Indexed: 01/06/2023]
Abstract
The term "breast density" or mammographic density (MD) denotes those components of breast parenchyma visualised at mammography that are denser than adipose tissue. MD is composed of a mixture of epithelial and stromal components, notably collagen, in variable proportions. MD is most commonly assessed in clinical practice with the time-honoured method of visual estimation of area-based percent density (PMD) on a mammogram, with categorisation into quartiles. The computerised semi-automated thresholding method, Cumulus, also yielding area-based percent density, is widely used for research purposes; however, the advent of fully automated volumetric methods developed as a consequence of the widespread use of digital mammography (DM) and yielding both absolute and percent dense volumes, has resulted in an explosion of interest in MD recently. Broadly, the importance of MD is twofold: firstly, the presence of marked MD significantly reduces mammographic sensitivity for breast cancer, even with state-of-the-art DM. Recognition of this led to the formation of a powerful lobby group ('Are You Dense') in the US, as a consequence of which 32 states have legislated for mandatory disclosure of MD to women undergoing mammography. Secondly, it is now widely accepted that MD is in itself a risk factor for breast cancer, with a four-to sixfold increased relative risk in women with PMD in the highest quintile compared to those with PMD in the lowest quintile. Consequently, major research efforts are underway to assess whether use of MD could provide a major step forward towards risk-adapted, personalised breast cancer prevention, imaging, and treatment.
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Affiliation(s)
- S J Vinnicombe
- Cancer Research, School of Medicine, Level 7, Mailbox 4, Ninewells Hospital and Medical School, University of Dundee, Dundee DD1 9SY, UK.
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Bodelon C, Oh H, Chatterjee N, Garcia-Closas M, Palakal M, Sherman ME, Pfeiffer RM, Geller B, Vacek P, Weaver DL, Chicoine R, Papathomas D, Xiang J, Patel DA, Khodr ZG, Linville L, Clare SE, Visscher DW, Mies C, Hewitt SM, Brinton LA, Storniolo AMV, He C, Chanock SJ, Gierach GL, Figueroa JD. Association between breast cancer genetic susceptibility variants and terminal duct lobular unit involution of the breast. Int J Cancer 2016; 140:825-832. [PMID: 27859137 DOI: 10.1002/ijc.30512] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2016] [Accepted: 10/05/2016] [Indexed: 01/06/2023]
Abstract
Terminal duct lobular units (TDLUs) are the predominant source of future breast cancers, and lack of TDLU involution (higher TDLU counts, higher acini count per TDLU and the product of the two) is a breast cancer risk factor. Numerous breast cancer susceptibility single nucleotide polymorphisms (SNPs) have been identified, but whether they are associated with TDLU involution is unknown. In a pooled analysis of 872 women from two studies, we investigated 62 established breast cancer SNPs and relationships with TDLU involution. Poisson regression models with robust variance were used to calculate adjusted per-allele relative risks (with the non-breast cancer risk allele as the referent) and 95% confidence intervals between TDLU measures and each SNP. All statistical tests were two-sided; P < 0.05 was considered statistically significant. Overall, 36 SNPs (58.1%) were related to higher TDLU counts although this was not statistically significant (p = 0.25). Six of the 62 SNPs (9.7%) were nominally associated with at least one TDLU measure: rs616488 (PEX14), rs11242675 (FOXQ1) and rs6001930 (MKL1) were associated with higher TDLU count (p = 0.047, 0.045 and 0.031, respectively); rs1353747 (PDE4D) and rs6472903 (8q21.11) were associated with higher acini count per TDLU (p = 0.007 and 0.027, respectively); and rs1353747 (PDE4D) and rs204247 (RANBP9) were associated with the product of TDLU and acini counts (p = 0.024 and 0.017, respectively). Our findings suggest breast cancer SNPs may not strongly influence TDLU involution. Agnostic genome-wide association studies of TDLU involution may provide new insights on its biologic underpinnings and breast cancer susceptibility.
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Affiliation(s)
- Clara Bodelon
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD
| | - Hannah Oh
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD
| | - Nilanjan Chatterjee
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD
| | | | - Maya Palakal
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD
| | - Mark E Sherman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD.,Division of Cancer Prevention, National Cancer Institute, Bethesda, MD
| | - Ruth M Pfeiffer
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD
| | | | | | | | | | - Daphne Papathomas
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD
| | - Jackie Xiang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD
| | - Deesha A Patel
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD
| | - Zeina G Khodr
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD
| | - Laura Linville
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD
| | - Susan E Clare
- Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL
| | - Daniel W Visscher
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Carolyn Mies
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA
| | - Stephen M Hewitt
- Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, Bethesda, MD
| | - Louise A Brinton
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD
| | - Anna Maria V Storniolo
- Susan G. Komen Tissue Bank at the Indiana University Simon Cancer Center, Indianapolis, IN
| | - Chunyan He
- Department of Epidemiology, Richard M. Fairbanks School of Public Health, Indiana University, Indianapolis, IN
| | - Stephen J Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD
| | - Gretchen L Gierach
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD
| | - Jonine D Figueroa
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD.,Usher Institute of Population Health Sciences and Informatics and Edinburgh Cancer Research Centre, University of Edinburgh, Edinburgh, UK
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Zhang H, Wang Y, Liu Z, Yao B, Dou C, Xu M, Li Q, Jia Y, Wu S, Tu K, Liu Q. Lymphocyte-specific protein 1 inhibits the growth of hepatocellular carcinoma by suppressing ERK1/2 phosphorylation. FEBS Open Bio 2016; 6:1227-1237. [PMID: 28255535 PMCID: PMC5324767 DOI: 10.1002/2211-5463.12139] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2016] [Revised: 08/29/2016] [Accepted: 09/27/2016] [Indexed: 12/13/2022] Open
Abstract
Lymphocyte‐specific protein 1 (LSP1) has been reported to regulate cell biology in several human cancers including lymphoma and breast cancer. However, the functions of LSP1 in human hepatocellular carcinoma (HCC) are still unknown. In this study, we found that LSP1 expression was downregulated in HCC tissues and cell lines, and lower LSP1 expression was correlated with poor clinicopathological features including large tumor size, high Edmondson–Steiner grading and advanced tumor–node–metastasis (TNM) stage. Additionally, we demonstrated that patients with high LSP1 expression had significantly better overall survival and disease‐free survival. Moreover, LSP1 was found to be an independent factor for predicting the prognosis of HCC patients. In vitro and in vivo assays showed that overexpressing LSP1 inhibited HCC growth by inducing both apoptosis and growth arrest. Mechanistically, we found that expression of phosphorylated extracellular regulated protein kinases 1 and 2 (ERK1/2) was downregulated after LSP1 overexpression, indicating LSP1 could suppress HCC growth by inhibiting the ERK pathway in HCC cells. Taken together, these results indicate that LSP1 may serve as a prognostic marker and a potential therapeutic target in human HCC.
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Affiliation(s)
- Hongyong Zhang
- Department of Hepatobiliary Surgery The First Affiliated Hospital of Xi'an Jiaotong University China
| | - Yufeng Wang
- Department of Hepatobiliary Surgery The First Affiliated Hospital of Xi'an Jiaotong University China
| | - Zhikui Liu
- Department of Hepatobiliary Surgery The First Affiliated Hospital of Xi'an Jiaotong University China
| | - Bowen Yao
- Department of Hepatobiliary Surgery The First Affiliated Hospital of Xi'an Jiaotong University China
| | - Changwei Dou
- Department of Hepatobiliary Surgery The First Affiliated Hospital of Xi'an Jiaotong University China
| | - Meng Xu
- Department of Hepatobiliary Surgery The First Affiliated Hospital of Xi'an Jiaotong University China
| | - Qing Li
- Department of Hepatobiliary Surgery The First Affiliated Hospital of Xi'an Jiaotong University China
| | - Yuli Jia
- Department of Hepatobiliary Surgery The First Affiliated Hospital of Xi'an Jiaotong University China
| | - Shengli Wu
- Department of Hepatobiliary Surgery The First Affiliated Hospital of Xi'an Jiaotong University China
| | - Kangsheng Tu
- Department of Hepatobiliary Surgery The First Affiliated Hospital of Xi'an Jiaotong University China
| | - Qingguang Liu
- Department of Hepatobiliary Surgery The First Affiliated Hospital of Xi'an Jiaotong University China
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41
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Genetic variants of ESR1 and SGSM3 are associated with the susceptibility of breast cancer in the Chinese population. Breast Cancer 2016; 24:369-374. [DOI: 10.1007/s12282-016-0712-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2016] [Accepted: 07/11/2016] [Indexed: 12/15/2022]
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Krishnan K, Baglietto L, Apicella C, Stone J, Southey MC, English DR, Giles GG, Hopper JL. Mammographic density and risk of breast cancer by mode of detection and tumor size: a case-control study. Breast Cancer Res 2016; 18:63. [PMID: 27316945 PMCID: PMC4912759 DOI: 10.1186/s13058-016-0722-4] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2016] [Accepted: 05/28/2016] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND Risk of screen-detected breast cancer mostly reflects inherent risk, while risk of interval cancer reflects inherent risk and risk of masking (risk of the tumor not being detected due to increased dense tissue). Therefore the predictors of whether a breast cancer is interval or screen-detected include those that predict masking. Our aim was to investigate the associations between mammographic measures and (1) inherent risk, and (2) masking. METHODS We conducted a case-control study nested within the Melbourne collaborative cohort study of 244 screen-detected cases (192 small tumors (<2 cm)) matched to 700 controls and 148 interval cases (76 small tumors) matched to 446 controls. Dense area (DA), percent dense area (PDA), and non-dense area (NDA) were measured using the Cumulus software. Conditional and unconditional logistic regression were applied as appropriate to estimate the odds per adjusted standard deviation (OPERA) adjusted for age and body mass index (BMI), allowing for the association with BMI to be a function of age at diagnosis. Tests of fit were performed using the Bayesian information criterion (BIC) and the area under the receiver operating characteristic curve. RESULTS For screen-detected cancer, the association with BMI had a marginally significant dependence on age at diagnosis, and after adjustment both DA and PDA were associated with risk (OPERA approximately 1.2) and gave a similar fit. NDA was not associated with risk. For interval cancer, the BMI risk association was not dependent on age at diagnosis and the best fitting model was PDA alone (OPERA = 2.24, 95 % confidence interval 1.75, 2.86). Prediction of interval versus screen-detected cancer was best achieved by PDA alone (OPERA = 1.76, 95 % confidence interval 1.39, 2.22) with no association with BMI. When the analysis was restricted to small tumors to reduce the influence of tumor growth, we obtained similar results. CONCLUSIONS Inherent breast cancer risk is predicted by BMI and DA or PDA, but not NDA. Masking is predicted by PDA, and not by BMI. Understanding risk and masking could help tailor mammographic screening.
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Affiliation(s)
- Kavitha Krishnan
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Level 3, 207 Bouverie Street, Carlton, VIC, 3053, Australia
| | - Laura Baglietto
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Level 3, 207 Bouverie Street, Carlton, VIC, 3053, Australia
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia
- Université Paris-Saclay, Univ. Paris-Sud, UVSQ, CESP, INSERM, Villejuif, France
- Gustave Roussy, F-94805, Villejuif, France
| | - Carmel Apicella
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Level 3, 207 Bouverie Street, Carlton, VIC, 3053, Australia
| | - Jennifer Stone
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Level 3, 207 Bouverie Street, Carlton, VIC, 3053, Australia
- Centre for Genetic Origins of Health and Disease, Curtin University and University of Western Australia, Crawley, Australia
| | - Melissa C Southey
- Genetic Epidemiology Laboratory, Department of Pathology, University of Melbourne, Melbourne, Australia
| | - Dallas R English
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Level 3, 207 Bouverie Street, Carlton, VIC, 3053, Australia
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia
| | - Graham G Giles
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Level 3, 207 Bouverie Street, Carlton, VIC, 3053, Australia
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia
- Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Level 3, 207 Bouverie Street, Carlton, VIC, 3053, Australia.
- Seoul Department of Epidemiology, School of Public Health, Seoul National University, Seoul, Korea.
- Institute of Health and Environment, Seoul National University, Seoul, Korea.
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43
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Sherratt MJ, McConnell JC, Streuli CH. Raised mammographic density: causative mechanisms and biological consequences. Breast Cancer Res 2016; 18:45. [PMID: 27142210 PMCID: PMC4855337 DOI: 10.1186/s13058-016-0701-9] [Citation(s) in RCA: 56] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
High mammographic density is the most important risk factor for breast cancer, after ageing. However, the composition, architecture, and mechanical properties of high X-ray density soft tissues, and the causative mechanisms resulting in different mammographic densities, are not well described. Moreover, it is not known how high breast density leads to increased susceptibility for cancer, or the extent to which it causes the genomic changes that characterise the disease. An understanding of these principals may lead to new diagnostic tools and therapeutic interventions.
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Affiliation(s)
- Michael J Sherratt
- Faculties of Life and Medical and Human Sciences, University of Manchester, Oxford Road, Manchester, M13 9PT, UK
| | - James C McConnell
- Faculties of Life and Medical and Human Sciences, University of Manchester, Oxford Road, Manchester, M13 9PT, UK
| | - Charles H Streuli
- Faculties of Life and Medical and Human Sciences, University of Manchester, Oxford Road, Manchester, M13 9PT, UK.
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44
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Dunning AM, Michailidou K, Kuchenbaecker KB, Thompson D, French JD, Beesley J, Healey CS, Kar S, Pooley KA, Lopez-Knowles E, Dicks E, Barrowdale D, Sinnott-Armstrong NA, Sallari RC, Hillman KM, Kaufmann S, Sivakumaran H, Moradi Marjaneh M, Lee JS, Hills M, Jarosz M, Drury S, Canisius S, Bolla MK, Dennis J, Wang Q, Hopper JL, Southey MC, Broeks A, Schmidt MK, Lophatananon A, Muir K, Beckmann MW, Fasching PA, Dos-Santos-Silva I, Peto J, Sawyer EJ, Tomlinson I, Burwinkel B, Marme F, Guénel P, Truong T, Bojesen SE, Flyger H, González-Neira A, Perez JIA, Anton-Culver H, Eunjung L, Arndt V, Brenner H, Meindl A, Schmutzler RK, Brauch H, Hamann U, Aittomäki K, Blomqvist C, Ito H, Matsuo K, Bogdanova N, Dörk T, Lindblom A, Margolin S, Kosma VM, Mannermaa A, Tseng CC, Wu AH, Lambrechts D, Wildiers H, Chang-Claude J, Rudolph A, Peterlongo P, Radice P, Olson JE, Giles GG, Milne RL, Haiman CA, Henderson BE, Goldberg MS, Teo SH, Yip CH, Nord S, Borresen-Dale AL, Kristensen V, Long J, Zheng W, Pylkäs K, Winqvist R, Andrulis IL, Knight JA, Devilee P, Seynaeve C, Figueroa J, Sherman ME, Czene K, Darabi H, Hollestelle A, van den Ouweland AMW, Humphreys K, Gao YT, Shu XO, Cox A, Cross SS, Blot W, Cai Q, Ghoussaini M, Perkins BJ, Shah M, Choi JY, Kang D, Lee SC, Hartman M, Kabisch M, Torres D, Jakubowska A, Lubinski J, Brennan P, Sangrajrang S, Ambrosone CB, Toland AE, Shen CY, Wu PE, Orr N, Swerdlow A, McGuffog L, Healey S, Lee A, Kapuscinski M, John EM, Terry MB, Daly MB, Goldgar DE, Buys SS, Janavicius R, Tihomirova L, Tung N, Dorfling CM, van Rensburg EJ, Neuhausen SL, Ejlertsen B, Hansen TVO, Osorio A, Benitez J, Rando R, Weitzel JN, Bonanni B, Peissel B, Manoukian S, Papi L, Ottini L, Konstantopoulou I, Apostolou P, Garber J, Rashid MU, Frost D, Izatt L, Ellis S, Godwin AK, Arnold N, Niederacher D, Rhiem K, Bogdanova-Markov N, Sagne C, Stoppa-Lyonnet D, Damiola F, Sinilnikova OM, Mazoyer S, Isaacs C, Claes KBM, De Leeneer K, de la Hoya M, Caldes T, Nevanlinna H, Khan S, Mensenkamp AR, Hooning MJ, Rookus MA, Kwong A, Olah E, Diez O, Brunet J, Pujana MA, Gronwald J, Huzarski T, Barkardottir RB, Laframboise R, Soucy P, Montagna M, Agata S, Teixeira MR, Park SK, Lindor N, Couch FJ, Tischkowitz M, Foretova L, Vijai J, Offit K, Singer CF, Rappaport C, Phelan CM, Greene MH, Mai PL, Rennert G, Imyanitov EN, Hulick PJ, Phillips KA, Piedmonte M, Mulligan AM, Glendon G, Bojesen A, Thomassen M, Caligo MA, Yoon SY, Friedman E, Laitman Y, Borg A, von Wachenfeldt A, Ehrencrona H, Rantala J, Olopade OI, Ganz PA, Nussbaum RL, Gayther SA, Nathanson KL, Domchek SM, Arun BK, Mitchell G, Karlan BY, Lester J, Maskarinec G, Woolcott C, Scott C, Stone J, Apicella C, Tamimi R, Luben R, Khaw KT, Helland Å, Haakensen V, Dowsett M, Pharoah PDP, Simard J, Hall P, García-Closas M, Vachon C, Chenevix-Trench G, Antoniou AC, Easton DF, Edwards SL. Breast cancer risk variants at 6q25 display different phenotype associations and regulate ESR1, RMND1 and CCDC170. Nat Genet 2016; 48:374-86. [PMID: 26928228 PMCID: PMC4938803 DOI: 10.1038/ng.3521] [Citation(s) in RCA: 103] [Impact Index Per Article: 12.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2015] [Accepted: 02/05/2016] [Indexed: 12/14/2022]
Abstract
We analyzed 3,872 common genetic variants across the ESR1 locus (encoding estrogen receptor α) in 118,816 subjects from three international consortia. We found evidence for at least five independent causal variants, each associated with different phenotype sets, including estrogen receptor (ER(+) or ER(-)) and human ERBB2 (HER2(+) or HER2(-)) tumor subtypes, mammographic density and tumor grade. The best candidate causal variants for ER(-) tumors lie in four separate enhancer elements, and their risk alleles reduce expression of ESR1, RMND1 and CCDC170, whereas the risk alleles of the strongest candidates for the remaining independent causal variant disrupt a silencer element and putatively increase ESR1 and RMND1 expression.
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Affiliation(s)
- Alison M Dunning
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Kyriaki Michailidou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Karoline B Kuchenbaecker
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Deborah Thompson
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Juliet D French
- Cancer Division, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Jonathan Beesley
- Cancer Division, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Catherine S Healey
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Siddhartha Kar
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Karen A Pooley
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Elena Lopez-Knowles
- Breast Cancer Research, Breakthrough Breast Cancer Research Centre, London, UK
- Academic Biochemistry, Royal Marsden Hospital, London, UK
| | - Ed Dicks
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Daniel Barrowdale
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | | | - Richard C Sallari
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Kristine M Hillman
- Cancer Division, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Susanne Kaufmann
- Cancer Division, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Haran Sivakumaran
- Cancer Division, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Mahdi Moradi Marjaneh
- Cancer Division, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Jason S Lee
- Cancer Division, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Margaret Hills
- Academic Biochemistry, Royal Marsden Hospital, London, UK
| | - Monika Jarosz
- Breast Cancer Research, Breakthrough Breast Cancer Research Centre, London, UK
- Academic Biochemistry, Royal Marsden Hospital, London, UK
| | - Suzie Drury
- Breast Cancer Research, Breakthrough Breast Cancer Research Centre, London, UK
- Academic Biochemistry, Royal Marsden Hospital, London, UK
| | - Sander Canisius
- Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, the Netherlands
| | - Manjeet K Bolla
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Joe Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Qin Wang
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Melissa C Southey
- Department of Pathology, University of Melbourne, Melbourne, Victoria, Australia
| | - Annegien Broeks
- Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, the Netherlands
| | - Marjanka K Schmidt
- Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, the Netherlands
| | - Artitaya Lophatananon
- Division of Health Sciences, Warwick Medical School, Warwick University, Coventry, UK
| | - Kenneth Muir
- Division of Health Sciences, Warwick Medical School, Warwick University, Coventry, UK
- Institute of Population Health, University of Manchester, Manchester, UK
| | - Matthias W Beckmann
- Department of Gynecology and Obstetrics, University Hospital Erlangen, Friedrich Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-Nuremberg Metropolitan Region, Erlangen, Germany
| | - Peter A Fasching
- Department of Gynecology and Obstetrics, University Hospital Erlangen, Friedrich Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-Nuremberg Metropolitan Region, Erlangen, Germany
- Department of Medicine, Division of Hematology and Oncology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Isabel Dos-Santos-Silva
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - Julian Peto
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - Elinor J Sawyer
- Research Oncology, Division of Cancer Studies, King's College London, Guy's Hospital, London, UK
| | - Ian Tomlinson
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Barbara Burwinkel
- Division of Molecular Genetic Epidemiology, German Cancer Research Center, Heidelberg, Germany
- Molecular Epidemiology Group, German Cancer Research Center, Heidelberg, Germany
| | - Frederik Marme
- National Center for Tumor Diseases, University of Heidelberg, Heidelberg, Germany
- Department of Obstetrics and Gynecology, University of Heidelberg, Heidelberg, Germany
| | - Pascal Guénel
- Environmental Epidemiology of Cancer, Center for Research in Epidemiology and Population Health, INSERM, Villejuif, France
- University Paris-Sud, Villejuif, France
| | - Thérèse Truong
- Environmental Epidemiology of Cancer, Center for Research in Epidemiology and Population Health, INSERM, Villejuif, France
- University Paris-Sud, Villejuif, France
| | - Stig E Bojesen
- Copenhagen General Population Study, Herlev Hospital, Copenhagen University Hospital, Herlev, Denmark
- Department of Clinical Biochemistry, Herlev Hospital, Copenhagen University Hospital, Herlev, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Henrik Flyger
- Department of Breast Surgery, Herlev Hospital, Copenhagen University Hospital, Herlev, Denmark
| | - Anna González-Neira
- Human Cancer Genetics Program, Spanish National Cancer Centre (CNIO), Madrid, Spain
| | - Jose I A Perez
- Servicio de Cirugía General y Especialidades, Hospital Monte Naranco, Oviedo, Spain
| | - Hoda Anton-Culver
- Department of Epidemiology, University of California-Irvine, Irvine, California, USA
| | - Lee Eunjung
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Volker Arndt
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany
- German Cancer Consortium, German Cancer Research Center, Heidelberg, Germany
| | - Alfons Meindl
- Department of Gynaecology and Obstetrics, Technical University of Munich, Munich, Germany
| | - Rita K Schmutzler
- Division of Molecular Gyneco-Oncology, Department of Gynaecology and Obstetrics, University Hospital of Cologne, Cologne, Germany
- Centre of Familial Breast and Ovarian Cancer, University Hospital of Cologne, Cologne, Germany
- Center for Integrated Oncology, University Hospital, Cologne, Germany
| | - Hiltrud Brauch
- German Cancer Consortium, German Cancer Research Center, Heidelberg, Germany
- Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany
- University of Tübingen, Tübingen, Germany
| | - Ute Hamann
- Molecular Genetics of Breast Cancer, German Cancer Research Center, Heidelberg, Germany
| | - Kristiina Aittomäki
- Department of Clinical Genetics, Helsinki University Central Hospital, Helsinki, Finland
| | - Carl Blomqvist
- Department of Oncology, Helsinki University Central Hospital, University of Helsinki, Helsinki, Finland
| | - Hidemi Ito
- Division of Epidemiology and Prevention, Aichi Cancer Center Research Institute, Aichi, Japan
| | - Keitaro Matsuo
- Division of Molecular Medicine, Aichi Cancer Center Research Institute, Nagoya, Japan
| | - Natasha Bogdanova
- Radiation Oncology Research Unit, Hannover Medical School, Hannover, Germany
| | - Thilo Dörk
- Gynaecology Research Unit, Hannover Medical School, Hannover, Germany
| | - Annika Lindblom
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Sara Margolin
- Department of Oncology-Pathology, Karolinska University Hospital, Stockholm, Sweden
| | - Veli-Matti Kosma
- Cancer Center, Kuopio University Hospital, Kuopio, Finland
- Institute of Clinical Medicine, Pathology and Forensic Medicine, University of Eastern Finland, Kuopio, Finland
- Imaging Center, Department of Clinical Pathology, Kuopio University Hospital, Kuopio, Finland
| | - Arto Mannermaa
- Cancer Center, Kuopio University Hospital, Kuopio, Finland
- Institute of Clinical Medicine, Pathology and Forensic Medicine, University of Eastern Finland, Kuopio, Finland
- Imaging Center, Department of Clinical Pathology, Kuopio University Hospital, Kuopio, Finland
| | - Chiu-Chen Tseng
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Anna H Wu
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Diether Lambrechts
- Vesalius Research Center, Leuven, Belgium
- Laboratory for Translational Genetics, Department of Oncology, University of Leuven, Leuven, Belgium
| | - Hans Wildiers
- Multidisciplinary Breast Center, Department of General Medical Oncology, University Hospitals Leuven, Leuven, Belgium
| | - Jenny Chang-Claude
- Division of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany
- University Cancer Center Hamburg (UCCH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Anja Rudolph
- Division of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany
| | - Paolo Peterlongo
- IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, Italy
| | - Paolo Radice
- Unit of Molecular Basis of Genetic Risk and Genetic Testing, Department of Preventive and Predictive Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Janet E Olson
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | - Graham G Giles
- Centre for Epidemiology and Biostatistics, School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - Roger L Milne
- Centre for Epidemiology and Biostatistics, School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - Christopher A Haiman
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Brian E Henderson
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Mark S Goldberg
- Department of Medicine, McGill University, Montreal, Quebec, Canada
- Division of Clinical Epidemiology, Royal Victoria Hospital, McGill University, Montreal, Quebec, Canada
| | - Soo H Teo
- Cancer Research Initiatives Foundation, Sime Darby Medical Centre, Subang Jaya, Malaysia
- Breast Cancer Research Unit, University Malaya Cancer Research Institute, University Malaya Medical Centre, Kuala Lumpur, Malaysia
| | - Cheng Har Yip
- Breast Cancer Research Unit, University Malaya Cancer Research Institute, University Malaya Medical Centre, Kuala Lumpur, Malaysia
| | - Silje Nord
- Department of Genetics, Institute for Cancer Research, Oslo University Hospital, Radiumhospitalet, Oslo, Norway
| | - Anne-Lise Borresen-Dale
- Department of Genetics, Institute for Cancer Research, Oslo University Hospital, Radiumhospitalet, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Vessela Kristensen
- Department of Genetics, Institute for Cancer Research, Oslo University Hospital, Radiumhospitalet, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Clinical Molecular Biology, Oslo University Hospital, University of Oslo, Oslo, Norway
| | - Jirong Long
- Division of Epidemiology, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Katri Pylkäs
- Laboratory of Cancer Genetics and Tumor Biology, Department of Clinical Chemistry and Biocenter Oulu, University of Oulu, NordLab Oulu University Hospital, Oulu, Finland
- Laboratory of Cancer Genetics and Tumor Biology, Northern Finland Laboratory Centre NordLab, Oulu, Finland
| | - Robert Winqvist
- Laboratory of Cancer Genetics and Tumor Biology, Department of Clinical Chemistry and Biocenter Oulu, University of Oulu, NordLab Oulu University Hospital, Oulu, Finland
- Laboratory of Cancer Genetics and Tumor Biology, Northern Finland Laboratory Centre NordLab, Oulu, Finland
| | - Irene L Andrulis
- Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Julia A Knight
- Prosserman Centre for Health Research, Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Toronto, Ontario, Canada
- Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Peter Devilee
- Department of Pathology, Leiden University Medical Center, Leiden, the Netherlands
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - Caroline Seynaeve
- Department of Medical Oncology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Jonine Figueroa
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, USA
| | - Mark E Sherman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, USA
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Hatef Darabi
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Antoinette Hollestelle
- Department of Medical Oncology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | | | - Keith Humphreys
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Yu-Tang Gao
- Department of Epidemiology, Shanghai Cancer Institute, Shanghai, China
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Angela Cox
- Sheffield Cancer Research, Department of Oncology, University of Sheffield, Sheffield, UK
| | - Simon S Cross
- Academic Unit of Pathology, Department of Neuroscience, University of Sheffield, Sheffield, UK
| | - William Blot
- Division of Epidemiology, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
- International Epidemiology Institute, Rockville, Maryland, USA
| | - Qiuyin Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Maya Ghoussaini
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Barbara J Perkins
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Mitul Shah
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Ji-Yeob Choi
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea
| | - Daehee Kang
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea
- Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea
| | - Soo Chin Lee
- Department of Haematology-Oncology, National University Health System, Singapore
- Cancer Science Institute of Singapore, National University of Singapore, Singapore
| | - Mikael Hartman
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
- Department of Surgery, National University Health System, Singapore
| | - Maria Kabisch
- Molecular Genetics of Breast Cancer, German Cancer Research Center, Heidelberg, Germany
| | - Diana Torres
- Molecular Genetics of Breast Cancer, German Cancer Research Center, Heidelberg, Germany
- Institute of Human Genetics, Pontificia Universidad Javerianar, Bogota, Colombia
| | - Anna Jakubowska
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Jan Lubinski
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Paul Brennan
- International Agency for Research on Cancer, Lyon, France
| | | | | | - Amanda E Toland
- Department of Molecular Virology, Immunology and Medical Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio, USA
| | - Chen-Yang Shen
- School of Public Health, China Medical University, Taichung, Taiwan
- Taiwan Biobank, Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Pei-Ei Wu
- Taiwan Biobank, Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Nick Orr
- Division of Cancer Studies, Breakthrough Breast Cancer Research Centre, Institute of Cancer Research, London, UK
| | - Anthony Swerdlow
- Division of Genetics and Epidemiology, Institute of Cancer Research, London, UK
- Division of Breast Cancer Research, Institute of Cancer Research, London, UK
| | - Lesley McGuffog
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Sue Healey
- Cancer Division, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Andrew Lee
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Miroslav Kapuscinski
- Centre for Epidemiology and Biostatistics, University of Melbourne, Melbourne, Victoria, Australia
| | - Esther M John
- Department of Epidemiology, Cancer Prevention Institute of California, Fremont, California, USA
| | - Mary Beth Terry
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York, USA
| | - Mary B Daly
- Department of Clinical Genetics, Fox Chase Cancer Center, Philadelphia, Pennsylvania, USA
| | - David E Goldgar
- Department of Dermatology, Huntsman Cancer Institute, University of Utah School of Medicine, Salt Lake City, Utah, USA
| | - Saundra S Buys
- Department of Medicine, Huntsman Cancer Institute, University of Utah School of Medicine, Salt Lake City, Utah, USA
| | - Ramunas Janavicius
- State Research Institute Centre for Innovative Medicine, Vilnius, Lithuania
| | | | - Nadine Tung
- Department of Medical Oncology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
| | | | | | - Susan L Neuhausen
- Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, California, USA
| | - Bent Ejlertsen
- Department of Oncology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Thomas V O Hansen
- Center for Genomic Medicine, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Ana Osorio
- Human Genetics Group, Spanish National Cancer Centre (CNIO), Madrid, Spain
- Biomedical Network on Rare Diseases (CIBERER), Madrid, Spain
| | - Javier Benitez
- Human Genetics Group, Spanish National Cancer Centre (CNIO), Madrid, Spain
- Biomedical Network on Rare Diseases (CIBERER), Madrid, Spain
- Human Genotyping (CEGEN) Unit, Human Cancer Genetics Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Rachel Rando
- City of Hope Clinical Cancer Genomics Community Research Network, Duarte, California, USA
| | | | - Bernardo Bonanni
- Division of Cancer Prevention and Genetics, Istituto Europeo di Oncologia, Milan, Italy
| | - Bernard Peissel
- Unit of Medical Genetics, Department of Preventive and Predictive Medicine, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico, Istituto Nazionale Tumori, Milan, Italy
| | - Siranoush Manoukian
- Unit of Medical Genetics, Department of Preventive and Predictive Medicine, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico, Istituto Nazionale Tumori, Milan, Italy
| | - Laura Papi
- Unit of Medical Genetics, Department of Biomedical, Experimental and Clinical Sciences, University of Florence, Florence, Italy
| | - Laura Ottini
- Department of Molecular Medicine, University La Sapienza, Rome, Italy
| | - Irene Konstantopoulou
- Molecular Diagnostics Laboratory, INRASTES (Institute of Nuclear and Radiological Sciences and Technology), National Centre for Scientific Research 'Demokritos', Aghia Paraskevi Attikis, Athens, Greece
| | - Paraskevi Apostolou
- Molecular Diagnostics Laboratory, INRASTES (Institute of Nuclear and Radiological Sciences and Technology), National Centre for Scientific Research 'Demokritos', Aghia Paraskevi Attikis, Athens, Greece
| | - Judy Garber
- Cancer Risk and Prevention Clinic, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
| | - Muhammad Usman Rashid
- Molecular Genetics of Breast Cancer, German Cancer Research Center, Heidelberg, Germany
- Department of Basic Sciences, Shaukat Khanum Memorial Cancer Hospital and Research Centre, Lahore, Pakistan
| | - Debra Frost
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Louise Izatt
- Clinical Genetics, Guy's and St. Thomas' National Health Service (NHS) Foundation Trust, London, UK
| | - Steve Ellis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Andrew K Godwin
- Department of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, Kansas, USA
| | - Norbert Arnold
- Department of Gynaecology and Obstetrics, University Hospital of Schleswig-Holstein, Campus Kiel, Christian Albrechts University Kiel, Kiel, Germany
| | | | - Kerstin Rhiem
- Centre of Familial Breast and Ovarian Cancer, Department of Gynaecology and Obstetrics and Centre for Integrated Oncology, Center for Molecular Medicine Cologne, University Hospital of Cologne, Cologne, Germany
| | | | - Charlotte Sagne
- INSERM U1052, CNRS UMR 5286, Université Lyon, Centre de Recherche en Cancérologie de Lyon, Lyon, France
| | - Dominique Stoppa-Lyonnet
- Institut Curie, Department of Tumour Biology, Paris, France
- Université Paris Descartes, Sorbonne Paris Cité, Paris, France
| | - Francesca Damiola
- INSERM U1052, CNRS UMR 5286, Université Lyon, Centre de Recherche en Cancérologie de Lyon, Lyon, France
| | - Olga M Sinilnikova
- INSERM U1052, CNRS UMR 5286, Université Lyon, Centre de Recherche en Cancérologie de Lyon, Lyon, France
- Unité Mixte de Génétique Constitutionnelle des Cancers Fréquents, Hospices Civils de Lyon-Centre Léon Bérard, Lyon, France
| | - Sylvie Mazoyer
- INSERM U1052, CNRS UMR 5286, Université Lyon, Centre de Recherche en Cancérologie de Lyon, Lyon, France
| | - Claudine Isaacs
- Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, USA
| | | | - Kim De Leeneer
- Center for Medical Genetics, Ghent University, Ghent, Belgium
| | - Miguel de la Hoya
- Molecular Oncology Laboratory, Hospital Clinico San Carlos, IdISSC (El Instituto de Investigación Sanitaria del Hospital Clínico San Carlos), Madrid, Spain
| | - Trinidad Caldes
- Molecular Oncology Laboratory, Hospital Clinico San Carlos, IdISSC (El Instituto de Investigación Sanitaria del Hospital Clínico San Carlos), Madrid, Spain
| | - Heli Nevanlinna
- Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland
| | - Sofia Khan
- Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland
| | - Arjen R Mensenkamp
- Department of Human Genetics, Radboud University Nijmegen Medical Centre, Nijmegen, the Netherlands
| | - Maartje J Hooning
- Department of Medical Oncology, Family Cancer Clinic, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Matti A Rookus
- Department of Epidemiology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Ava Kwong
- Hong Kong Hereditary Breast Cancer Family Registry, Cancer Genetics Center, Hong Kong Sanatorium and Hospital, Hong Kong
- Department of Surgery, University of Hong Kong, Hong Kong
| | - Edith Olah
- Department of Molecular Genetics, National Institute of Oncology, Budapest, Hungary
| | - Orland Diez
- Oncogenetics Laboratory, Vall d'Hebron Institute of Oncology (VHIO), Vall d'Hebron University Hospital, Barcelona, Spain
| | - Joan Brunet
- Genetic Counseling Unit, Hereditary Cancer Program, IDIBGI (Institut d'Investigació Biomèdica de Girona), Catalan Institute of Oncology, Girona, Spain
| | - Miquel Angel Pujana
- Breast Cancer and Systems Biology Unit, IDIBELL (Bellvitge Biomedical Research Institute), Catalan Institute of Oncology, Barcelona, Spain
| | - Jacek Gronwald
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Tomasz Huzarski
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Rosa B Barkardottir
- Department of Pathology, Landspitali University Hospital and Biomedical Centre (BMC), Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Rachel Laframboise
- Medical Genetic Division, Centre Hospitalier Universitaire de Québec and Laval University, Quebec City, Quebec, Canada
| | - Penny Soucy
- Centre Hospitalier Universitaire de Québec and Laval University, Quebec City, Quebec, Canada
| | - Marco Montagna
- Immunology and Molecular Oncology Unit, Istituto Oncologico Veneto (IOV), IRCCS (Istituto di Ricovero e Cura a Carattere Scientifico), Padua, Italy
| | - Simona Agata
- Immunology and Molecular Oncology Unit, Istituto Oncologico Veneto (IOV), IRCCS (Istituto di Ricovero e Cura a Carattere Scientifico), Padua, Italy
| | - Manuel R Teixeira
- Department of Genetics, Portuguese Oncology Institute, Porto, Portugal
- Biomedical Sciences Institute (ICBAS), Porto University, Porto, Portugal
| | - Sue Kyung Park
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea
- Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea
| | - Noralane Lindor
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | - Fergus J Couch
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
| | - Marc Tischkowitz
- Program in Cancer Genetics, McGill University, Montreal, Quebec, Canada
| | - Lenka Foretova
- Masaryk Memorial Cancer Institute and Medical Faculty, Masaryk University, Brno, Czech Republic
| | - Joseph Vijai
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Kenneth Offit
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Christian F Singer
- Department of Obstetrics and Gynecology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
| | - Christine Rappaport
- Department of Obstetrics and Gynecology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
| | - Catherine M Phelan
- Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, Florida, USA
| | - Mark H Greene
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, US National Institutes of Health, Rockville, Maryland, USA
| | - Phuong L Mai
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, US National Institutes of Health, Rockville, Maryland, USA
| | - Gad Rennert
- Department of Community Medicine and Epidemiology, Carmel Medical Center and B. Rappaport Faculty of Medicine, Haifa, Israel
- Clalit National Israeli Cancer Control Center, Haifa, Israel
| | | | - Peter J Hulick
- Center for Medical Genetics, NorthShore University Health System, Evanston, Illinois, USA
| | - Kelly-Anne Phillips
- Division of Cancer Medicine, Peter MacCallum Cancer Centre, East Melbourne, Victoria, Australia
| | - Marion Piedmonte
- NRG Oncology, Statistics and Data Management Center, Roswell Park Cancer Institute, Buffalo, New York, USA
| | - Anna Marie Mulligan
- Laboratory Medicine Program, University Health Network, Toronto, Ontario, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
| | - Gord Glendon
- Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Toronto, Ontario, Canada
| | - Anders Bojesen
- Department of Clinical Genetics, Vejle Hospital, Vejle, Denmark
| | - Mads Thomassen
- Department of Clinical Genetics, Odense University Hospital, Odense, Denmark
| | - Maria A Caligo
- Section of Genetic Oncology, Department of Laboratory Medicine, University of Pisa and University Hospital of Pisa, Pisa, Italy
| | - Sook-Yee Yoon
- Cancer Research Initiatives Foundation, Sime Darby Medical Centre, Subang Jaya, Malaysia
- University Malaya Cancer Research Institute, Faculty of Medicine, University Malaya Medical Centre, University Malaya, Kuala Lumpur, Malaysia
| | - Eitan Friedman
- Susanne Levy Gertner Oncogenetics Unit, Sheba Medical Center, Tel-Hashomer, Israel
| | - Yael Laitman
- Susanne Levy Gertner Oncogenetics Unit, Sheba Medical Center, Tel-Hashomer, Israel
| | - Ake Borg
- Department of Oncology, Lund University, Lund, Sweden
| | - Anna von Wachenfeldt
- Department of Oncology-Pathology, Karolinska University Hospital, Stockholm, Sweden
| | - Hans Ehrencrona
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
- Department of Clinical Genetics, Lund University Hospital, Lund, Sweden
| | - Johanna Rantala
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Olufunmilayo I Olopade
- Center for Clinical Cancer Genetics and Global Health, University of Chicago Medical Center, Chicago, Illinois, USA
| | - Patricia A Ganz
- Division of Cancer Prevention and Control Research, Jonsson Comprehensive Cancer Center, University of California Los Angeles School of Medicine and School of Public Health, Los Angeles, California, USA
| | - Robert L Nussbaum
- Department of Medicine and Genetics, University of California, San Francisco, San Francisco, California, USA
| | - Simon A Gayther
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Katherine L Nathanson
- Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Susan M Domchek
- Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Banu K Arun
- University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Gillian Mitchell
- Familial Cancer Centre, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia
| | - Beth Y Karlan
- Women's Cancer Program at the Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Jenny Lester
- Women's Cancer Program at the Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | | | - Christy Woolcott
- Department of Obstetrics, Gynaecology and Pediatrics, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Christopher Scott
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | - Jennifer Stone
- Centre for Genetic Origins of Health and Disease, University of Western Australia, Perth, Western Australia, Australia
| | - Carmel Apicella
- Centre for Epidemiology and Biostatistics, School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Rulla Tamimi
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
- Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA
- Program in Genetic Epidemiology and Statistical Genetics, Harvard School of Public Health, Boston, Massachusetts, USA
| | - Robert Luben
- Clinical Gerontology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Kay-Tee Khaw
- Clinical Gerontology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Åslaug Helland
- Department of Genetics, Institute for Cancer Research, Oslo University Hospital, Radiumhospitalet, Oslo, Norway
| | - Vilde Haakensen
- Department of Genetics, Institute for Cancer Research, Oslo University Hospital, Radiumhospitalet, Oslo, Norway
| | - Mitch Dowsett
- Breast Cancer Research, Breakthrough Breast Cancer Research Centre, London, UK
- Academic Biochemistry, Royal Marsden Hospital, London, UK
| | - Paul D P Pharoah
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Jacques Simard
- Centre Hospitalier Universitaire de Québec and Laval University, Quebec City, Quebec, Canada
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Montserrat García-Closas
- Division of Cancer Studies, Breakthrough Breast Cancer Research Centre, Institute of Cancer Research, London, UK
- Division of Genetics and Epidemiology, Institute of Cancer Research, London, UK
| | - Celine Vachon
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | | | - Antonis C Antoniou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Douglas F Easton
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Stacey L Edwards
- Cancer Division, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
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Hopper JL, Nguyen TL, Stone J, Aujard K, Matheson MC, Abramson MJ, Burgess JA, Walters EH, Dite GS, Bui M, Evans C, Makalic E, Schmidt DF, Ward G, Jenkins MA, Giles GG, Dharmage SC, Apicella C. Childhood body mass index and adult mammographic density measures that predict breast cancer risk. Breast Cancer Res Treat 2016; 156:163-70. [DOI: 10.1007/s10549-016-3719-x] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2015] [Accepted: 02/11/2016] [Indexed: 01/01/2023]
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Mandelblatt JS, Stout NK, Schechter CB, van den Broek JJ, Miglioretti DL, Krapcho M, Trentham-Dietz A, Munoz D, Lee SJ, Berry DA, van Ravesteyn NT, Alagoz O, Kerlikowske K, Tosteson AN, Near AM, Hoeffken A, Chang Y, Heijnsdijk EA, Chisholm G, Huang X, Huang H, Ergun MA, Gangnon R, Sprague BL, Plevritis S, Feuer E, de Koning HJ, Cronin KA. Collaborative Modeling of the Benefits and Harms Associated With Different U.S. Breast Cancer Screening Strategies. Ann Intern Med 2016; 164:215-25. [PMID: 26756606 PMCID: PMC5079106 DOI: 10.7326/m15-1536] [Citation(s) in RCA: 191] [Impact Index Per Article: 23.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Controversy persists about optimal mammography screening strategies. OBJECTIVE To evaluate screening outcomes, taking into account advances in mammography and treatment of breast cancer. DESIGN Collaboration of 6 simulation models using national data on incidence, digital mammography performance, treatment effects, and other-cause mortality. SETTING United States. PATIENTS Average-risk U.S. female population and subgroups with varying risk, breast density, or comorbidity. INTERVENTION Eight strategies differing by age at which screening starts (40, 45, or 50 years) and screening interval (annual, biennial, and hybrid [annual for women in their 40s and biennial thereafter]). All strategies assumed 100% adherence and stopped at age 74 years. MEASUREMENTS Benefits (breast cancer-specific mortality reduction, breast cancer deaths averted, life-years, and quality-adjusted life-years); number of mammograms used; harms (false-positive results, benign biopsies, and overdiagnosis); and ratios of harms (or use) and benefits (efficiency) per 1000 screens. RESULTS Biennial strategies were consistently the most efficient for average-risk women. Biennial screening from age 50 to 74 years avoided a median of 7 breast cancer deaths versus no screening; annual screening from age 40 to 74 years avoided an additional 3 deaths, but yielded 1988 more false-positive results and 11 more overdiagnoses per 1000 women screened. Annual screening from age 50 to 74 years was inefficient (similar benefits, but more harms than other strategies). For groups with a 2- to 4-fold increased risk, annual screening from age 40 years had similar harms and benefits as screening average-risk women biennially from 50 to 74 years. For groups with moderate or severe comorbidity, screening could stop at age 66 to 68 years. LIMITATION Other imaging technologies, polygenic risk, and nonadherence were not considered. CONCLUSION Biennial screening for breast cancer is efficient for average-risk populations. Decisions about starting ages and intervals will depend on population characteristics and the decision makers' weight given to the harms and benefits of screening. PRIMARY FUNDING SOURCE National Institutes of Health.
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Affiliation(s)
- Jeanne S. Mandelblatt
- From Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC; Harvard Pilgrim Health Care Institute, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, Massachusetts; Albert Einstein College of Medicine, Bronx, New York; Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- UC Davis School of Medicine, Davis, Stanford University, Stanford, and University of California, San Francisco, San Francisco, California; Group Health Research Institute, Seattle, Washington; Information Management Services, Calverton, and National Cancer Institute, Bethesda, Maryland; Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin; University of Texas MD Anderson Cancer Center, Houston, Texas
- Norris Cotton Cancer Center and Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire; and College of Medicine, and University of Vermont, Burlington, Vermont
| | - Natasha K. Stout
- From Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC; Harvard Pilgrim Health Care Institute, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, Massachusetts; Albert Einstein College of Medicine, Bronx, New York; Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- UC Davis School of Medicine, Davis, Stanford University, Stanford, and University of California, San Francisco, San Francisco, California; Group Health Research Institute, Seattle, Washington; Information Management Services, Calverton, and National Cancer Institute, Bethesda, Maryland; Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin; University of Texas MD Anderson Cancer Center, Houston, Texas
- Norris Cotton Cancer Center and Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire; and College of Medicine, and University of Vermont, Burlington, Vermont
| | - Clyde B. Schechter
- From Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC; Harvard Pilgrim Health Care Institute, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, Massachusetts; Albert Einstein College of Medicine, Bronx, New York; Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- UC Davis School of Medicine, Davis, Stanford University, Stanford, and University of California, San Francisco, San Francisco, California; Group Health Research Institute, Seattle, Washington; Information Management Services, Calverton, and National Cancer Institute, Bethesda, Maryland; Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin; University of Texas MD Anderson Cancer Center, Houston, Texas
- Norris Cotton Cancer Center and Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire; and College of Medicine, and University of Vermont, Burlington, Vermont
| | - Jeroen J. van den Broek
- From Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC; Harvard Pilgrim Health Care Institute, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, Massachusetts; Albert Einstein College of Medicine, Bronx, New York; Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- UC Davis School of Medicine, Davis, Stanford University, Stanford, and University of California, San Francisco, San Francisco, California; Group Health Research Institute, Seattle, Washington; Information Management Services, Calverton, and National Cancer Institute, Bethesda, Maryland; Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin; University of Texas MD Anderson Cancer Center, Houston, Texas
- Norris Cotton Cancer Center and Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire; and College of Medicine, and University of Vermont, Burlington, Vermont
| | - Diana L. Miglioretti
- From Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC; Harvard Pilgrim Health Care Institute, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, Massachusetts; Albert Einstein College of Medicine, Bronx, New York; Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- UC Davis School of Medicine, Davis, Stanford University, Stanford, and University of California, San Francisco, San Francisco, California; Group Health Research Institute, Seattle, Washington; Information Management Services, Calverton, and National Cancer Institute, Bethesda, Maryland; Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin; University of Texas MD Anderson Cancer Center, Houston, Texas
- Norris Cotton Cancer Center and Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire; and College of Medicine, and University of Vermont, Burlington, Vermont
| | - Martin Krapcho
- From Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC; Harvard Pilgrim Health Care Institute, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, Massachusetts; Albert Einstein College of Medicine, Bronx, New York; Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- UC Davis School of Medicine, Davis, Stanford University, Stanford, and University of California, San Francisco, San Francisco, California; Group Health Research Institute, Seattle, Washington; Information Management Services, Calverton, and National Cancer Institute, Bethesda, Maryland; Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin; University of Texas MD Anderson Cancer Center, Houston, Texas
- Norris Cotton Cancer Center and Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire; and College of Medicine, and University of Vermont, Burlington, Vermont
| | - Amy Trentham-Dietz
- From Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC; Harvard Pilgrim Health Care Institute, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, Massachusetts; Albert Einstein College of Medicine, Bronx, New York; Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- UC Davis School of Medicine, Davis, Stanford University, Stanford, and University of California, San Francisco, San Francisco, California; Group Health Research Institute, Seattle, Washington; Information Management Services, Calverton, and National Cancer Institute, Bethesda, Maryland; Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin; University of Texas MD Anderson Cancer Center, Houston, Texas
- Norris Cotton Cancer Center and Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire; and College of Medicine, and University of Vermont, Burlington, Vermont
| | - Diego Munoz
- From Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC; Harvard Pilgrim Health Care Institute, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, Massachusetts; Albert Einstein College of Medicine, Bronx, New York; Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- UC Davis School of Medicine, Davis, Stanford University, Stanford, and University of California, San Francisco, San Francisco, California; Group Health Research Institute, Seattle, Washington; Information Management Services, Calverton, and National Cancer Institute, Bethesda, Maryland; Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin; University of Texas MD Anderson Cancer Center, Houston, Texas
- Norris Cotton Cancer Center and Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire; and College of Medicine, and University of Vermont, Burlington, Vermont
| | - Sandra J. Lee
- From Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC; Harvard Pilgrim Health Care Institute, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, Massachusetts; Albert Einstein College of Medicine, Bronx, New York; Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- UC Davis School of Medicine, Davis, Stanford University, Stanford, and University of California, San Francisco, San Francisco, California; Group Health Research Institute, Seattle, Washington; Information Management Services, Calverton, and National Cancer Institute, Bethesda, Maryland; Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin; University of Texas MD Anderson Cancer Center, Houston, Texas
- Norris Cotton Cancer Center and Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire; and College of Medicine, and University of Vermont, Burlington, Vermont
| | - Donald A. Berry
- From Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC; Harvard Pilgrim Health Care Institute, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, Massachusetts; Albert Einstein College of Medicine, Bronx, New York; Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- UC Davis School of Medicine, Davis, Stanford University, Stanford, and University of California, San Francisco, San Francisco, California; Group Health Research Institute, Seattle, Washington; Information Management Services, Calverton, and National Cancer Institute, Bethesda, Maryland; Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin; University of Texas MD Anderson Cancer Center, Houston, Texas
- Norris Cotton Cancer Center and Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire; and College of Medicine, and University of Vermont, Burlington, Vermont
| | - Nicolien T. van Ravesteyn
- From Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC; Harvard Pilgrim Health Care Institute, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, Massachusetts; Albert Einstein College of Medicine, Bronx, New York; Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- UC Davis School of Medicine, Davis, Stanford University, Stanford, and University of California, San Francisco, San Francisco, California; Group Health Research Institute, Seattle, Washington; Information Management Services, Calverton, and National Cancer Institute, Bethesda, Maryland; Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin; University of Texas MD Anderson Cancer Center, Houston, Texas
- Norris Cotton Cancer Center and Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire; and College of Medicine, and University of Vermont, Burlington, Vermont
| | - Oguzhan Alagoz
- From Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC; Harvard Pilgrim Health Care Institute, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, Massachusetts; Albert Einstein College of Medicine, Bronx, New York; Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- UC Davis School of Medicine, Davis, Stanford University, Stanford, and University of California, San Francisco, San Francisco, California; Group Health Research Institute, Seattle, Washington; Information Management Services, Calverton, and National Cancer Institute, Bethesda, Maryland; Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin; University of Texas MD Anderson Cancer Center, Houston, Texas
- Norris Cotton Cancer Center and Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire; and College of Medicine, and University of Vermont, Burlington, Vermont
| | - Karla Kerlikowske
- From Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC; Harvard Pilgrim Health Care Institute, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, Massachusetts; Albert Einstein College of Medicine, Bronx, New York; Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- UC Davis School of Medicine, Davis, Stanford University, Stanford, and University of California, San Francisco, San Francisco, California; Group Health Research Institute, Seattle, Washington; Information Management Services, Calverton, and National Cancer Institute, Bethesda, Maryland; Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin; University of Texas MD Anderson Cancer Center, Houston, Texas
- Norris Cotton Cancer Center and Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire; and College of Medicine, and University of Vermont, Burlington, Vermont
| | - Anna N.A. Tosteson
- From Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC; Harvard Pilgrim Health Care Institute, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, Massachusetts; Albert Einstein College of Medicine, Bronx, New York; Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- UC Davis School of Medicine, Davis, Stanford University, Stanford, and University of California, San Francisco, San Francisco, California; Group Health Research Institute, Seattle, Washington; Information Management Services, Calverton, and National Cancer Institute, Bethesda, Maryland; Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin; University of Texas MD Anderson Cancer Center, Houston, Texas
- Norris Cotton Cancer Center and Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire; and College of Medicine, and University of Vermont, Burlington, Vermont
| | - Aimee M. Near
- From Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC; Harvard Pilgrim Health Care Institute, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, Massachusetts; Albert Einstein College of Medicine, Bronx, New York; Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- UC Davis School of Medicine, Davis, Stanford University, Stanford, and University of California, San Francisco, San Francisco, California; Group Health Research Institute, Seattle, Washington; Information Management Services, Calverton, and National Cancer Institute, Bethesda, Maryland; Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin; University of Texas MD Anderson Cancer Center, Houston, Texas
- Norris Cotton Cancer Center and Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire; and College of Medicine, and University of Vermont, Burlington, Vermont
| | - Amanda Hoeffken
- From Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC; Harvard Pilgrim Health Care Institute, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, Massachusetts; Albert Einstein College of Medicine, Bronx, New York; Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- UC Davis School of Medicine, Davis, Stanford University, Stanford, and University of California, San Francisco, San Francisco, California; Group Health Research Institute, Seattle, Washington; Information Management Services, Calverton, and National Cancer Institute, Bethesda, Maryland; Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin; University of Texas MD Anderson Cancer Center, Houston, Texas
- Norris Cotton Cancer Center and Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire; and College of Medicine, and University of Vermont, Burlington, Vermont
| | - Yaojen Chang
- From Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC; Harvard Pilgrim Health Care Institute, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, Massachusetts; Albert Einstein College of Medicine, Bronx, New York; Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- UC Davis School of Medicine, Davis, Stanford University, Stanford, and University of California, San Francisco, San Francisco, California; Group Health Research Institute, Seattle, Washington; Information Management Services, Calverton, and National Cancer Institute, Bethesda, Maryland; Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin; University of Texas MD Anderson Cancer Center, Houston, Texas
- Norris Cotton Cancer Center and Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire; and College of Medicine, and University of Vermont, Burlington, Vermont
| | - Eveline A. Heijnsdijk
- From Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC; Harvard Pilgrim Health Care Institute, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, Massachusetts; Albert Einstein College of Medicine, Bronx, New York; Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- UC Davis School of Medicine, Davis, Stanford University, Stanford, and University of California, San Francisco, San Francisco, California; Group Health Research Institute, Seattle, Washington; Information Management Services, Calverton, and National Cancer Institute, Bethesda, Maryland; Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin; University of Texas MD Anderson Cancer Center, Houston, Texas
- Norris Cotton Cancer Center and Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire; and College of Medicine, and University of Vermont, Burlington, Vermont
| | - Gary Chisholm
- From Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC; Harvard Pilgrim Health Care Institute, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, Massachusetts; Albert Einstein College of Medicine, Bronx, New York; Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- UC Davis School of Medicine, Davis, Stanford University, Stanford, and University of California, San Francisco, San Francisco, California; Group Health Research Institute, Seattle, Washington; Information Management Services, Calverton, and National Cancer Institute, Bethesda, Maryland; Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin; University of Texas MD Anderson Cancer Center, Houston, Texas
- Norris Cotton Cancer Center and Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire; and College of Medicine, and University of Vermont, Burlington, Vermont
| | - Xuelin Huang
- From Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC; Harvard Pilgrim Health Care Institute, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, Massachusetts; Albert Einstein College of Medicine, Bronx, New York; Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- UC Davis School of Medicine, Davis, Stanford University, Stanford, and University of California, San Francisco, San Francisco, California; Group Health Research Institute, Seattle, Washington; Information Management Services, Calverton, and National Cancer Institute, Bethesda, Maryland; Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin; University of Texas MD Anderson Cancer Center, Houston, Texas
- Norris Cotton Cancer Center and Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire; and College of Medicine, and University of Vermont, Burlington, Vermont
| | - Hui Huang
- From Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC; Harvard Pilgrim Health Care Institute, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, Massachusetts; Albert Einstein College of Medicine, Bronx, New York; Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- UC Davis School of Medicine, Davis, Stanford University, Stanford, and University of California, San Francisco, San Francisco, California; Group Health Research Institute, Seattle, Washington; Information Management Services, Calverton, and National Cancer Institute, Bethesda, Maryland; Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin; University of Texas MD Anderson Cancer Center, Houston, Texas
- Norris Cotton Cancer Center and Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire; and College of Medicine, and University of Vermont, Burlington, Vermont
| | - Mehmet Ali Ergun
- From Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC; Harvard Pilgrim Health Care Institute, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, Massachusetts; Albert Einstein College of Medicine, Bronx, New York; Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- UC Davis School of Medicine, Davis, Stanford University, Stanford, and University of California, San Francisco, San Francisco, California; Group Health Research Institute, Seattle, Washington; Information Management Services, Calverton, and National Cancer Institute, Bethesda, Maryland; Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin; University of Texas MD Anderson Cancer Center, Houston, Texas
- Norris Cotton Cancer Center and Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire; and College of Medicine, and University of Vermont, Burlington, Vermont
| | - Ronald Gangnon
- From Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC; Harvard Pilgrim Health Care Institute, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, Massachusetts; Albert Einstein College of Medicine, Bronx, New York; Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- UC Davis School of Medicine, Davis, Stanford University, Stanford, and University of California, San Francisco, San Francisco, California; Group Health Research Institute, Seattle, Washington; Information Management Services, Calverton, and National Cancer Institute, Bethesda, Maryland; Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin; University of Texas MD Anderson Cancer Center, Houston, Texas
- Norris Cotton Cancer Center and Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire; and College of Medicine, and University of Vermont, Burlington, Vermont
| | - Brian L. Sprague
- From Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC; Harvard Pilgrim Health Care Institute, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, Massachusetts; Albert Einstein College of Medicine, Bronx, New York; Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- UC Davis School of Medicine, Davis, Stanford University, Stanford, and University of California, San Francisco, San Francisco, California; Group Health Research Institute, Seattle, Washington; Information Management Services, Calverton, and National Cancer Institute, Bethesda, Maryland; Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin; University of Texas MD Anderson Cancer Center, Houston, Texas
- Norris Cotton Cancer Center and Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire; and College of Medicine, and University of Vermont, Burlington, Vermont
| | - Sylvia Plevritis
- From Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC; Harvard Pilgrim Health Care Institute, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, Massachusetts; Albert Einstein College of Medicine, Bronx, New York; Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- UC Davis School of Medicine, Davis, Stanford University, Stanford, and University of California, San Francisco, San Francisco, California; Group Health Research Institute, Seattle, Washington; Information Management Services, Calverton, and National Cancer Institute, Bethesda, Maryland; Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin; University of Texas MD Anderson Cancer Center, Houston, Texas
- Norris Cotton Cancer Center and Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire; and College of Medicine, and University of Vermont, Burlington, Vermont
| | - Eric Feuer
- From Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC; Harvard Pilgrim Health Care Institute, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, Massachusetts; Albert Einstein College of Medicine, Bronx, New York; Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- UC Davis School of Medicine, Davis, Stanford University, Stanford, and University of California, San Francisco, San Francisco, California; Group Health Research Institute, Seattle, Washington; Information Management Services, Calverton, and National Cancer Institute, Bethesda, Maryland; Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin; University of Texas MD Anderson Cancer Center, Houston, Texas
- Norris Cotton Cancer Center and Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire; and College of Medicine, and University of Vermont, Burlington, Vermont
| | - Harry J. de Koning
- From Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC; Harvard Pilgrim Health Care Institute, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, Massachusetts; Albert Einstein College of Medicine, Bronx, New York; Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- UC Davis School of Medicine, Davis, Stanford University, Stanford, and University of California, San Francisco, San Francisco, California; Group Health Research Institute, Seattle, Washington; Information Management Services, Calverton, and National Cancer Institute, Bethesda, Maryland; Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin; University of Texas MD Anderson Cancer Center, Houston, Texas
- Norris Cotton Cancer Center and Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire; and College of Medicine, and University of Vermont, Burlington, Vermont
| | - Kathleen A. Cronin
- From Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC; Harvard Pilgrim Health Care Institute, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, Massachusetts; Albert Einstein College of Medicine, Bronx, New York; Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- UC Davis School of Medicine, Davis, Stanford University, Stanford, and University of California, San Francisco, San Francisco, California; Group Health Research Institute, Seattle, Washington; Information Management Services, Calverton, and National Cancer Institute, Bethesda, Maryland; Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin; University of Texas MD Anderson Cancer Center, Houston, Texas
- Norris Cotton Cancer Center and Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire; and College of Medicine, and University of Vermont, Burlington, Vermont
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Melnik BC. Milk: an epigenetic amplifier of FTO-mediated transcription? Implications for Western diseases. J Transl Med 2015; 13:385. [PMID: 26691922 PMCID: PMC4687119 DOI: 10.1186/s12967-015-0746-z] [Citation(s) in RCA: 50] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2015] [Accepted: 12/04/2015] [Indexed: 12/14/2022] Open
Abstract
Single-nucleotide polymorphisms within intron 1 of the FTO (fat mass and obesity-associated) gene are associated with enhanced FTO expression, increased body weight, obesity and type 2 diabetes mellitus (T2DM). The N6-methyladenosine (m6A) demethylase FTO plays a pivotal regulatory role for postnatal growth and energy expenditure. The purpose of this review is to provide translational evidence that links milk signaling with FTO-activated transcription of the milk recipient. FTO-dependent demethylation of m6A regulates mRNA splicing required for adipogenesis, increases the stability of mRNAs, and affects microRNA (miRNA) expression and miRNA biosynthesis. FTO senses branched-chain amino acids (BCAAs) and activates the nutrient sensitive kinase mechanistic target of rapamycin complex 1 (mTORC1), which plays a key role in translation. Milk provides abundant BCAAs and glutamine, critical components increasing FTO expression. CpG hypomethylation in the first intron of FTO has recently been associated with T2DM. CpG methylation is generally associated with gene silencing. In contrast, CpG demethylation generally increases transcription. DNA de novo methylation of CpG sites is facilitated by DNA methyltransferases (DNMT) 3A and 3B, whereas DNA maintenance methylation is controlled by DNMT1. MiRNA-29s target all DNMTs and thus reduce DNA CpG methylation. Cow´s milk provides substantial amounts of exosomal miRNA-29s that reach the systemic circulation and target mRNAs of the milk recipient. Via DNMT suppression, milk exosomal miRNA-29s may reduce the magnitude of FTO methylation, thereby epigenetically increasing FTO expression in the milk consumer. High lactation performance with increased milk yield has recently been associated with excessive miRNA-29 expression of dairy cow mammary epithelial cells (DCMECs). Notably, the galactopoietic hormone prolactin upregulates the transcription factor STAT3, which induces miRNA-29 expression. In a retrovirus-like manner milk exosomes may transfer DCMEC-derived miRNA-29s and bovine FTO mRNA to the milk consumer amplifying FTO expression. There is compelling evidence that obesity, T2DM, prostate and breast cancer, and neurodegenerative diseases are all associated with increased FTO expression. Maximization of lactation performance by veterinary medicine with enhanced miRNA-29s and FTO expression associated with increased exosomal miRNA-29 and FTO mRNA transfer to the milk consumer may represent key epigenetic mechanisms promoting FTO/mTORC1-mediated diseases of civilization.
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Affiliation(s)
- Bodo C Melnik
- Department of Dermatology, Environmental Medicine and Health Theory, University of Osnabrück, Sedanstrasse 115, 49090, Osnabrück, Germany.
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Mariapun S, Ho WK, Kang PCE, Li J, Lindström S, Yip CH, Teo SH. Variants in 6q25.1 Are Associated with Mammographic Density in Malaysian Chinese Women. Cancer Epidemiol Biomarkers Prev 2015; 25:327-33. [PMID: 26677210 DOI: 10.1158/1055-9965.epi-15-0746] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2015] [Accepted: 12/08/2015] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Mammographic density is an established risk factor for breast cancer and has a strong heritable component. Genome-wide association studies (GWAS) for mammographic density conducted in women of European descent have identified several genetic associations, but none of the studies have been tested in Asians. We sought to investigate whether these genetic loci, and loci associated with breast cancer risk and breast size, are associated with mammographic density in an Asian cohort. METHODS We conducted genotyping by mass spectrometry in 1,189 women (865 Chinese, 187 Indian, and 137 Malay). Quantitative measurements of mammographic density were performed using ImageJ, a fully automated thresholding technique. The associations of SNPs to densities were analyzed using linear regression models. RESULTS We successfully evaluated the associations of 36 SNPs with mammographic densities. After adjusting for age, body mass index, parity, and menopausal status, we found that in our cohort of 865 Malaysian Chinese, three SNPs in the 6q25.1 region near ESR1 (rs2046210, rs12173570, and rs10484919) that were associated with mammographic density, breast cancer risk, or breast size in previous GWAS were significantly associated with both percentage density and absolute dense area. We could not replicate the most significant association found previously in European women (rs10995190, ZNF365 gene) because the minor allele was absent for Asian women. CONCLUSION We found that the directions of genetic associations were similar to those reported in Caucasian women. IMPACT Our results show that even in Asian women with lower population risk to breast cancer, there is shared heritability between mammographic density and breast cancer risk.
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Affiliation(s)
- Shivaani Mariapun
- Cancer Research Malaysia (formerly known as Cancer Research Initiatives Foundation), Subang Jaya Medical Centre, Subang Jaya, Selangor, Malaysia. Breast Cancer Research Group, University Malaya Medical Centre, Kuala Lumpur, Malaysia
| | - Weang Kee Ho
- Department of Applied Mathematics, Faculty of Engineering, University of Nottingham Malaysia Campus, Semenyih, Selangor, Malaysia
| | - Peter Choon Eng Kang
- Cancer Research Malaysia (formerly known as Cancer Research Initiatives Foundation), Subang Jaya Medical Centre, Subang Jaya, Selangor, Malaysia
| | - Jingmei Li
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Sara Lindström
- Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts
| | | | - Soo Hwang Teo
- Cancer Research Malaysia (formerly known as Cancer Research Initiatives Foundation), Subang Jaya Medical Centre, Subang Jaya, Selangor, Malaysia. Breast Cancer Research Group, University Malaya Medical Centre, Kuala Lumpur, Malaysia.
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Tan A, Dang Y, Chen G, Mo Z. Overexpression of the fat mass and obesity associated gene (FTO) in breast cancer and its clinical implications. INTERNATIONAL JOURNAL OF CLINICAL AND EXPERIMENTAL PATHOLOGY 2015; 8:13405-13410. [PMID: 26722548 PMCID: PMC4680493] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 08/21/2015] [Accepted: 09/25/2015] [Indexed: 06/05/2023]
Abstract
BACKGROUND AND PURPOSE Incidence of breast cancer is increasing and seems to be associated with fatty foods, metabolism, and so on. The fat mass and obesity associated gene (FTO) has been intensively investigated in diabetes, obesity and the other diseases. Previous studies have reported that FTO SNPs are associated with breast cancer risk. Here, we investigated the expression of FTO in human breast cancer tissues and its relationship with the clinicopathological features. METHODS In this retrospective study, tissues from 79 patients with breast cancer were collected, as well as 43 cases of adjacent breast tissues. Immunohistochemistry was used to detect the expression of FTO. Statistical analysis was performed to assess the association between FTO expression and the clinicopathological features of breast cancer. RESULTS FTO was expressed in both mammary epithelial and breast cancer tissues, but with different degree. The expression level of FTO in breast cancer tissues was significantly higher than that in the adjacent breast tissues (P < 0.001). The percentage of FTO-positive expression in cases with hormone receptor (HR) negative and HER2 amplification was significantly higher than that in those with HR positive and HER2 negative (P = 0.001, P < 0.001). The positivity rate of FTO in breast cancer with P53 positive and histological grade 3 seemed to be higher than that with P53 negative and histological grade 1 or 2, respectively (P = 0.077, P = 0.082). There was no association between FTO expression and age, T stage, LN status, TNM stage, Ki67, and BMI in breast cancer. Besides, FTO expression in HER2-overexpressed subtype was significantly higher than that in Triple-negative and Luminal A/B1 subtypes (P < 0.001). CONCLUSION Our study suggests that FTO expression may have a vital role in the carcinogenesis of breast cancer, especially in HER2-overexpressed breast cancer.
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Affiliation(s)
- Aihua Tan
- Department of Chemotherapy, The Affiliated Tumor Hospital of Guangxi Medical UniversityNanning 530021, Guangxi, China
| | - Yiwu Dang
- Department of Pathology, First Affiliated Hospital of Guangxi Medical UniversityNanning 530021, Guangxi, China
| | - Gang Chen
- Department of Pathology, First Affiliated Hospital of Guangxi Medical UniversityNanning 530021, Guangxi, China
| | - Zengnan Mo
- Center for Genomic and Personalized Medicine, Guangxi Medical UniversityNanning 530021, Guangxi, China
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50
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Rudolph A, Fasching PA, Behrens S, Eilber U, Bolla MK, Wang Q, Thompson D, Czene K, Brand JS, Li J, Scott C, Pankratz VS, Brandt K, Hallberg E, Olson JE, Lee A, Beckmann MW, Ekici AB, Haeberle L, Maskarinec G, Le Marchand L, Schumacher F, Milne RL, Knight JA, Apicella C, Southey MC, Kapuscinski MK, Hopper JL, Andrulis IL, Giles GG, Haiman CA, Khaw KT, Luben R, Hall P, Pharoah PDP, Couch FJ, Easton DF, Dos-Santos-Silva I, Vachon C, Chang-Claude J. A comprehensive evaluation of interaction between genetic variants and use of menopausal hormone therapy on mammographic density. Breast Cancer Res 2015; 17:110. [PMID: 26275715 PMCID: PMC4537547 DOI: 10.1186/s13058-015-0625-9] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2015] [Accepted: 07/29/2015] [Indexed: 02/02/2023] Open
Abstract
INTRODUCTION Mammographic density is an established breast cancer risk factor with a strong genetic component and can be increased in women using menopausal hormone therapy (MHT). Here, we aimed to identify genetic variants that may modify the association between MHT use and mammographic density. METHODS The study comprised 6,298 postmenopausal women from the Mayo Mammography Health Study and nine studies included in the Breast Cancer Association Consortium. We selected for evaluation 1327 single nucleotide polymorphisms (SNPs) showing the lowest P-values for interaction (P int) in a meta-analysis of genome-wide gene-environment interaction studies with MHT use on risk of breast cancer, 2541 SNPs in candidate genes (AKR1C4, CYP1A1-CYP1A2, CYP1B1, ESR2, PPARG, PRL, SULT1A1-SULT1A2 and TNF) and ten SNPs (AREG-rs10034692, PRDM6-rs186749, ESR1-rs12665607, ZNF365-rs10995190, 8p11.23-rs7816345, LSP1-rs3817198, IGF1-rs703556, 12q24-rs1265507, TMEM184B-rs7289126, and SGSM3-rs17001868) associated with mammographic density in genome-wide studies. We used multiple linear regression models adjusted for potential confounders to evaluate interactions between SNPs and current use of MHT on mammographic density. RESULTS No significant interactions were identified after adjustment for multiple testing. The strongest SNP-MHT interaction (unadjusted P int <0.0004) was observed with rs9358531 6.5kb 5' of PRL. Furthermore, three SNPs in PLCG2 that had previously been shown to modify the association of MHT use with breast cancer risk were found to modify also the association of MHT use with mammographic density (unadjusted P int <0.002), but solely among cases (unadjusted P int SNP×MHT×case-status <0.02). CONCLUSIONS The study identified potential interactions on mammographic density between current use of MHT and SNPs near PRL and in PLCG2, which require confirmation. Given the moderate size of the interactions observed, larger studies are needed to identify genetic modifiers of the association of MHT use with mammographic density.
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Affiliation(s)
- Anja Rudolph
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, D-69120, Heidelberg, Germany.
| | - Peter A Fasching
- Department of Gynaecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany.
- David Geffen School of Medicine, Department of Medicine Division of Hematology and Oncology, University of California at Los Angeles, Los Angeles, CA, USA.
| | - Sabine Behrens
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, D-69120, Heidelberg, Germany.
| | - Ursula Eilber
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, D-69120, Heidelberg, Germany.
| | - Manjeet K Bolla
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
| | - Qin Wang
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
| | - Deborah Thompson
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
| | - Judith S Brand
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
| | - Jingmei Li
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
| | | | | | | | - Emily Hallberg
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
| | - Janet E Olson
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
| | - Adam Lee
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA.
| | - Matthias W Beckmann
- Department of Gynaecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany.
| | - Arif B Ekici
- Institute of Human Genetics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany.
| | - Lothar Haeberle
- Department of Gynaecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany.
| | | | | | - Fredrick Schumacher
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
| | - Roger L Milne
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia.
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia.
| | - Julia A Knight
- Prosserman Centre for Health Research, Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Toronto, Canada.
- Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada.
| | - Carmel Apicella
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia.
| | - Melissa C Southey
- Department of Pathology, The University of Melbourne, Melbourne, Australia.
| | - Miroslav K Kapuscinski
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia.
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia.
| | - Irene L Andrulis
- Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Toronto, Canada.
- Department of Molecular Genetics, University of Toronto, Toronto, Canada.
| | - Graham G Giles
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia.
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia.
| | - Christopher A Haiman
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
| | - Kay-Tee Khaw
- MRC Centre for Nutritional Epidemiology in Cancer Prevention and Survival (CNC), University of Cambridge, Cambridge, UK.
| | - Robert Luben
- Clinical Gerontology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
| | - Paul D P Pharoah
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK.
| | - Fergus J Couch
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA.
| | - Douglas F Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK.
| | - Isabel Dos-Santos-Silva
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.
| | - Celine Vachon
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
| | - Jenny Chang-Claude
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, D-69120, Heidelberg, Germany.
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