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Breast Cancer Research
Published in: Breast Cancer Research 3/2006

01-06-2006 | Review

High-throughput genomic technology in research and clinical management of breast cancer. Evolving landscape of genetic epidemiological studies

Authors: Yen-Ling Low, Sara Wedrén, Jianjun Liu

Published in: Breast Cancer Research | Issue 3/2006

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Abstract

Candidate polymorphism-based genetic epidemiological studies have yielded little success in the search for low-penetrance breast cancer susceptibility genes. The lack of progress is partially due to insufficient coverage of genomic regions with genetic markers, as well as economic constraints, limiting both the number of genetic targets and the number of individuals being studied. Recent rapid advances in high-throughput genotyping technology and our understanding of genetic variation patterns across the human genome are now revolutionizing the way in which genetic epidemiological studies are being designed and conducted. Genetic epidemiological studies are quickly progressing from candidate gene studies to comprehensive pathway investigation and, further, to genomic epidemiological studies where the whole human genome is being interrogated to identify susceptibility alleles. This paper reviews the evolving approaches in the search for low-penetrance breast cancer susceptibility gene variants and discusses their potential promises and pitfalls.
Literature
1.
Anglian Breast Cancer Study Group: Prevalence and penetrance of BRCA1 and BRCA2 mutations in a population-based series of breast cancer cases. Anglian Breast Cancer Study Group. Br J Cancer. 2000, 83: 1301-1308. 10.1054/bjoc.2000.1407.CrossRefPubMedCentral
2.
Pharoah PD, Antoniou A, Bobrow M, Zimmern RL, Easton DF, Ponder BA: Polygenic susceptibility to breast cancer and implications for prevention. Nat Genet. 2002, 31: 33-36. 10.1038/ng853.CrossRefPubMed
3.
Colhoun HM, McKeigue PM, Davey Smith G: Problems of reporting genetic associations with complex outcomes. Lancet. 2003, 361: 865-872. 10.1016/S0140-6736(03)12715-8.CrossRefPubMed
4.
Hall JM, Lee MK, Newman B, Morrow JE, Anderson LA, Huey B, King MC: Linkage of early-onset familial breast cancer to chromosome 17q21. Science. 1990, 250: 1684-1689.CrossRefPubMed
5.
Risch NJ: Searching for genetic determinants in the new millennium. Nature. 2000, 405: 847-856. 10.1038/35015718.CrossRefPubMed
6.
Savage SA, Chanock SJ: Using germ-line genetic variation to investigate and treat cancer. Drug Discov Today. 2004, 9: 610-618. 10.1016/S1359-6446(04)03179-4.CrossRefPubMed
7.
Kang D: Genetic polymorphisms and cancer susceptibility of breast cancer in Korean women. J Biochem Mol Biol. 2003, 36: 28-34.PubMed
8.
Dunning AM, Healey CS, Pharoah PD, Teare MD, Ponder BA, Easton DF: A systematic review of genetic polymorphisms and breast cancer risk. Cancer Epidemiol Biomarkers Prev. 1999, 8: 843-854.PubMed
9.
Coughlin SS, Piper M: Genetic polymorphisms and risk of breast cancer. Cancer Epidemiol Biomarkers Prev. 1999, 8: 1023-1032.PubMed
10.
Pharoah PD, Dunning AM, Ponder BA, Easton DF: Association studies for finding cancer-susceptibility genetic variants. Nat Rev Cancer. 2004, 4: 850-860. 10.1038/nrc1476.CrossRefPubMed
11.
Engle LJ, Simpson CL, Landers JE: Using high-throughput SNP technologies to study cancer. Oncogene. 2006, 25: 1594-1601. 10.1038/sj.onc.1209368.CrossRefPubMed
12.
Sobrino B, Brion M, Carracedo A: SNPs in forensic genetics: a review on SNP typing methodologies. Forensic Sci Int. 2005, 154: 181-194. 10.1016/j.forsciint.2004.10.020.CrossRefPubMed
13.
Syvanen AC: Accessing genetic variation: genotyping single nucleotide polymorphisms. Nat Rev Genet. 2001, 2: 930-942. 10.1038/35103535.CrossRefPubMed
14.
Gabriel SB, Schaffner SF, Nguyen H, Moore JM, Roy J, Blumenstiel B, Higgins J, DeFelice M, Lochner A, Faggart M, et al: The structure of haplotype blocks in the human genome. Science. 2002, 296: 2225-2229. 10.1126/science.1069424.CrossRefPubMed
15.
Terwilliger JD, Hiekkalinna T: An utter refutation of the "Fundamental Theorem of the HapMap". Eur J Hum Genet. 2006, 14: 426-437. 10.1038/sj.ejhg.5201583.CrossRefPubMed
16.
17.
Ke X, Miretti MM, Broxholme J, Hunt S, Beck S, Bentley DR, Deloukas P, Cardon LR: A comparison of tagging methods and their tagging space. Hum Mol Genet. 2005, 14: 2757-2767. 10.1093/hmg/ddi309.CrossRefPubMed
18.
Adkins RM: Comparison of the accuracy of methods of computational haplotype inference using a large empirical dataset. BMC Genet. 2004, 5: 22-10.1186/1471-2156-5-22.CrossRefPubMedPubMedCentral
19.
Clayton D, Chapman J, Cooper J: Use of unphased multilocus genotype data in indirect association studies. Genet Epidemiol. 2004, 27: 415-428. 10.1002/gepi.20032.CrossRefPubMed
20.
Haiman CA, Stram DO, Pike MC, Kolonel LN, Burtt NP, Altshuler D, Hirschhorn J, Henderson BE: A comprehensive haplotype analysis of CYP19 and breast cancer risk: the Multiethnic Cohort. Hum Mol Genet. 2003, 12: 2679-2692. 10.1093/hmg/ddg294.CrossRefPubMed
21.
Feigelson HS, Cox DG, Cann HM, Wacholder S, Kaaks R, Henderson BE, Albanes D, Altshuler D, Berglund G, Berrino F, et al: Haplotype analysis of the HSD17B1 gene and risk of breast cancer: A comprehensive approach to multicenter analyses of prospective cohort studies. Cancer Res. 2006, 66: 2468-2475. 10.1158/0008-5472.CAN-05-3574.CrossRefPubMed
22.
Benusiglio PR, Lesueur F, Luccarini C, McIntosh J, Luben RN, Smith P, Dunning A, Easton DF, Ponder BA, Pharoah PD: Common variation in EMSY and risk of breast and ovarian cancer: a case-control study using HapMap tagging SNPs. BMC Cancer. 2005, 5: 81-10.1186/1471-2407-5-81.CrossRefPubMedPubMedCentral
23.
Einarsdottir K, Humphreys K, Bonnard C, Palmgren J, Iles M, Sjolander A, Li Y, Chia KS, Liu E, Hall P, et al: Linkage disequilibrium mapping of CHEK2: Common variation and breast cancer risk. PLOS Medicine. 2006.
24.
Hirschhorn JN, Daly MJ: Genome-wide association studies for common diseases and complex traits. Nat Rev Genet. 2005, 6: 95-108. 10.1038/nrg1521.CrossRefPubMed
25.
de Bakker PI, Yelensky R, Pe'er I, Gabriel SB, Daly MJ, Altshuler D: Efficiency and power in genetic association studies. Nat Genet. 2005, 37: 1217-1223. 10.1038/ng1669.CrossRefPubMed
26.
Marchini J, Donnelly P, Cardon LR: Genome-wide strategies for detecting multiple loci that influence complex diseases. Nat Genet. 2005, 37: 413-417. 10.1038/ng1537.CrossRefPubMed
27.
Ioannidis JP, Gwinn M, Little J, Higgins JP, Bernstein JL, Boffetta P, Bondy M, Bray MS, Brenchley PE, Buffler PA, et al: A road map for efficient and reliable human genome epidemiology. Nat Genet. 2006, 38: 3-5.CrossRefPubMed
28.
Colditz GA, Hankinson SE: The Nurses' Health Study: lifestyle and health among women. Nat Rev Cancer. 2005, 5: 388-396. 10.1038/nrc1608.CrossRefPubMed
29.
Coyle YM: The effect of environment on breast cancer risk. Breast Cancer Res Treat. 2004, 84: 273-288. 10.1023/B:BREA.0000019964.33963.09.CrossRefPubMed
30.
Tsubura A, Uehara N, Kiyozuka Y, Shikata N: Dietary factors modifying breast cancer risk and relation to time of intake. J Mammary Gland Biol Neoplasia. 2005, 10: 87-100. 10.1007/s10911-005-2543-4.CrossRefPubMed
31.
Han J, Hankinson SE, Ranu H, De Vivo I, Hunter DJ: Polymorphisms in DNA double-strand break repair genes and breast cancer risk in the Nurses' Health Study. Carcinogenesis. 2004, 25: 189-195. 10.1093/carcin/bgh002.CrossRefPubMed
32.
Han J, Hankinson SE, Zhang SM, De Vivo I, Hunter DJ: Interaction between genetic variations in DNA repair genes and plasma folate on breast cancer risk. Cancer Epidemiol Biomarkers Prev. 2004, 13: 520-524. 10.1158/1055-9965.EPI-03-0332.CrossRefPubMed
Metadata
Title
High-throughput genomic technology in research and clinical management of breast cancer. Evolving landscape of genetic epidemiological studies
Authors
Yen-Ling Low
Sara Wedrén
Jianjun Liu
Publication date
01-06-2006
Publisher
BioMed Central
Published in
Breast Cancer Research / Issue 3/2006
Electronic ISSN: 1465-542X
DOI
https://doi.org/10.1186/bcr1511

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