Emma Howard - PowerPoint PPT Presentation

emma howard n.
Skip this Video
Loading SlideShow in 5 Seconds..
Emma Howard PowerPoint Presentation
Download Presentation
Emma Howard

play fullscreen
1 / 21
Download Presentation
Emma Howard
Download Presentation

Emma Howard

- - - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

  1. Discuss the studies on going to look at common low penetrance risk factors in cancer – concentrate primarily on breast cancer. Look at SNP tagging approach used for this work. Emma Howard

  2. Breast Cancer • Autosomal dominant high penetrance, BRCA1 and BRCA2 • Account for only 5% of all breast cancers • The remaining likely to be low penetrance genes – potentially with complex interactions gene and environment.

  3. Low Penetrance? • “Genes in which subtle sequence variants or polymorphisms may be associated with a small to moderate increased relative risk for breast cancer. • Also termed low penetrance genes, alleles, mutations and polys

  4. Approaches of identifying low-penetrance alleles • Candidate gene association, looking at genes in the same pathway as BRCA1/2. • Chek2 – 1100delC – encodes cell cycle checkpoint kinase implicated in DNA repair, increased association with breast cancer in a number of studies.

  5. Low penetrance genes

  6. Genome wide association studies • Powerful method to identify breast cancer susceptibility alleles that are common in the general population but are at low penetrance. • No prior knowledge required of the alleles position or function. • Takes advantages of new technology for analysing hundreds of thousands of SNPs.

  7. WGWAs A new approach • Each disease causing mutation arises on a particularly copy of the human genome, bears a specific set of common alleles in cis at nearby loci. • Recombination rate low (1 crossover per 100 megabases per generation) disease alleles in a population show association with nearby marker alleles for many generations – linkage disequilibrium.

  8. Genome wide Association studies • Genome wide association studies – analysing SNPs which are in non- random linkage disequilibrium with each other, i.e inherited together as a haplotype. They are associated with susceptibility to disease e.g. breast cancer. • They persist in the population as they are usually late onset (cancer) don’t effect reproductive fitness.

  9. SNP maps • Denser SNP maps available now e.g. HapMap and NCBI build 36.1 • Can analyse a fraction of SNPs as inferred knowledge of the haplotypes from these maps is known – termed tagged SNPs.

  10. Genome wide association studies • Using microarray can perform association studies on familial breast cancer families testing neg for BRCA1/2. • Three major studies identified six alleles conferring an increased risk to breast cancer at high stats level.

  11. Easton et al 2007 • Three stage process: First stage, genotyped 408 familial breast cancer cases and 400 controls across 266,722 SNPs. • Second stage: 5% of the SNPs selected based on genotype frequency in cases and controls designed an oligo array to assess the subset in an additional 3990 cases. • Third stage: 30 most significant SNPs from 2nd stage in 22,848 cases, identified 5 SNPs.

  12. Susceptibility alleles for breast cancer defined by WGWAs

  13. Pharoah et al (2008) • 7 leading low penetrance genes. • Calculated absolute risk assuming a multiplicative risk – polygenic hypothesis. • 2187 distinct genotypes possible from these 7 genes

  14. Table of risk (Pharoah 2008)

  15. Other breast cancer studies

  16. Other Cancer studies • WGWAs on colorectal cancer (Houlston et al, 2007 Nature Genetics. • Prostate cancer (Lee et al, 2005 Nature Genetics). • Oesophageal cancer (Thomas et al, 2007 Nature Genetics)

  17. Clinical Relevance • Very early stage, relative risk based on having high risk alleles in a polygenic system. • Together the common low penetrance alleles identified so far may account for less than 5% of genetic risk. • Can’t screen individual patients at the moment until more genes are found and combined into a risk model. • Might prove useful for drug response

  18. References • Low penetrance susceptibility to breast cancer due to CHEK2 1100delC in non-carriers of BRCA1 or BRCA2 mutations Nat Gen 2002. 31:55-59. • CHEK2 1100delC and susceptiblity to breast cancer: a collaborative analysis involving 10,860 breast cnacer cases and 9065 controls from 10 studies. Am J. Hum Gen 2004, 74:1175-1182. • Weischer et al, 2007. Increased risk of breast cancer associated with CHEK2 1100delC. J. Clin. Oncol. 25: 57-63. • Einarsdottir et al, 2006. Comprehensive analysis of the ATM, CHEK2 and ERBB2 genese in relation to breast tumour characteristics and survival: a population-based case-control and follow up study. Breast cancer Res 8:R67. • Cybulski et al. A deletion in CHEK2 of 5395 bp predisposes to breast cancer in poland. Breast cancer Res Treat 2007, 102: 119-122. • Bernstein et al, 2006. Chek2 1100delC allelic variant and risk of breast cancer. Cancer Epidemiol Biomarkers Prev 15: 348-352.

  19. References • Thomas, G.; Jacobs, K. B.; Kraft, P.; Yeager, M.; Wacholder, S.; Cox, D. G.; Hankinson, S. E.; Hutchinson, A.; Wang, Z.; Yu, K.; Chatterjee, N.; Garcia-Closas, M.; and 36 others :A multistage genome-wide association study in breast cancer identifies two new risk alleles at 1p11.2 and 14q24.1 (RAD51L1). Nature Genet. 41: 579-584, 2009. • Hunter, D. J.; Kraft, P.; Jacobs, K. B.; Cox, D. G.; Yeager, M.; Hankinson, S. E.; Wacholder, S.; Wang, Z.; Welch, R..; Hutchinson, A.; Wang, J.; Yu, K.; and 18 others : A genome-wide association study identifies alleles in FGFR2 associated with risk of sporadic postmenopausal breast cancer. Nature Genet. 39: 870-874, 2007. 

  20. References • Stacey, S. N.; Manolescu, A.; Sulem, P.; Thorlacius, S.; Gudjonsson, S. A.; Jonsson, G. F.; Jakobsdottir, M.; Bergthorsson, J. T.; Gudmundsson, J.; Aben, K. K.; Strobbe, L. J.; Swinkels, D. W.; and 44 others :Common variants on chromosome 5p12 confer susceptibility to estrogen receptor-positive breast cancer. Nature Genet.40: 703-706, 2008.  • Stacey, S. N.; Manolescu, A.; Sulem, P.; Rafnar, T.; Gudmundsson, J.; Gudjonsson, S. A.; Masson, G.; Jakobsdottir, M.; Thorlacius, S.; Helgason, A.; Aben, K. K.; Strobbe, L. J.; and 41 others Common variants on chromosomes 2q35 and 16q12 confer susceptibility to estrogen receptor-positive breast cancer.Nature Genet. 39: 865-869, 2007. • Thomas, G.; Jacobs, K. B.; Kraft, P.; Yeager, M.; Wacholder, S.; Cox, D. G.; Hankinson, S. E.; Hutchinson, A.; Wang, Z.; Yu, K.; Chatterjee, N.; Garcia-Closas, M.; and 36 others :A multistage genome-wide association study in breast cancer identifies two new risk alleles at 1p11.2 and 14q24.1 (RAD51L1). Nature Genet. 41: 579-584, 2009. • Zheng, W.; Long, J.; Gao, Y.-T.; Li, C.; Zheng, Y.; Xiang, Y.-B.; Wen, W.; Levy, S.; Deming, S. L.; Haines, J. L.; Gu, K.; Fair, A. M.; Cai, Q.; Lu, W.; Shu, X.-O. :Genome-wide association study identifies a new breast cancer susceptibility locus at 6q25.1. Nature Genet. 41: 324-328,

  21. References • Design of Tag SNP Whole Genome Genotyping ArraysBy: Daniel A. Peiffer2  , Kevin L. Gunderson2. • Genetic mapping human disease. Altshuler and Daly and Lander. Science vol 322 881-888. • Clinical implications of low-penetrance breast cancer susceptibility alleles. Freisinger and Domchek. Cur Oncology reports 2009: 11 8-14