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Elio Riboli MD, MPH, ScM Head, Nutrition, Hormones and Cancer Group I.A.R.C.-W.H.O.

Elio Riboli MD, MPH, ScM Head, Nutrition, Hormones and Cancer Group I.A.R.C.-W.H.O. International Agency for Research on Cancer World Health Organization Lyon, France. TROMS Ø. UMEÅ. AARHUS. MALM Ö. COPENHAGEN. UTRECHT. CAMBRIDGE. POTSDAM. BILTHOVEN. OXFORD. HEIDELBERG. PARIS.

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Elio Riboli MD, MPH, ScM Head, Nutrition, Hormones and Cancer Group I.A.R.C.-W.H.O.

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  1. Elio Riboli MD, MPH, ScM Head, Nutrition, Hormones and Cancer Group I.A.R.C.-W.H.O. International Agency for Research on Cancer World Health Organization Lyon, France

  2. TROMSØ UMEÅ AARHUS MALMÖ COPENHAGEN UTRECHT CAMBRIDGE POTSDAM BILTHOVEN OXFORD HEIDELBERG PARIS MILAN LYON TURIN OVIEDO FLORENCE SAN SEBASTIAN PAMPLONA BARCELONA NAPLES ATHENS MURCIA RAGUSA GRANADA EPIC Collaborating centres and cohort subjects LONDON

  3. ETIOLOGICAL STUDIES • FOLLOW-UP: • Cancer diagnosis • Vital status • Causes of death • Changes in Lifestyle EPIC Time Table • BASELINE • Subjects recruitment • Questionnaires data • Anthropometry data • Blood/DNA collection • Data Base & Biorepository Sweden Netherlands Germany Norway Greece Italy DK France Spain UK 1993…………………………..…….1999………… 2000…….2002……………………2005 Development of common/standardized Nutrient and lifestyle Data Bases Setting up of lab facilities for sample handling / DNA extraction etc

  4. “Westernization” of lifestyle and cancer. • Western Lifestyle: • Energy dense diet, rich in • - fat, • - refined carbohydrates • - animal protein • - Low physical activity • - Smoking and drinking • Consequences: • - Greater adult body height • - Early menarche • - Obesity • - Diabetes • - Cardiovascular disease • - Hypertension …and cancer !

  5. EPIC Database • Final size of the database : over 100giga bytes. • 90 screens have been developed to facilitate the transfer, standardization, control and export of the data • 521.000 subjects x about 2000 common variables  over 1 billions values stored

  6. EPIC Blood Collection and Storage (1993-1998) • 30 ml venous blood: • 20 ml citrated +10 ml dry • 28 aliquots of 500 l : • plasma 12(red straws) • serum 8(yellow straws) • buffy coat 4(blue straws) • RBC 4(green straws) • 28 aliquots x 300.000 subjects = • 8.4 Million biological aliquots

  7. IARC Scientific Council, 2005 EPIC: Organizational Structure EPIC Steering Committee IARC E. Riboli, N. Slimani, R. Kaaks, R.Saracci Danemark A.Tjonneland (DK Cancer Soc.), K. Overvad (U. Aarhus) France F. Clavel, MC Boutron (I.G.R-INSERM, Paris) Greece A. Trichopoulou, D. Trochopoulos (U. Athens/Harvard) Germany J. Linseisen (DKFZ), H. Boeing (DIFE) Italy F. Berrino (INT), P.Vineis, D. Palli, S.Panico, R.Tumino, Netherlands P. Peeters (U. Utrecht), B. Bueno de Mesquita (RIVM) Norway E. Lund (U. Tromso) Spain C. Gonzalez (I.C.O.), C. Martinez, C. Navarro, M. Doronsoro Sweden G. Berglund (U. Lund), G. Hallmans (U.Umea) UK S. Bingham, K-T Khaw (U.Cambridge), T. Key (CRUK Oxford)

  8. EPIC: Organizational Structure EPIC Steering Committee Working groups on risk factors, end-points other than cancer, methodological issues: Coordinators: EPIC-Elderly-EC (Aging) Antonia Trichopoulou (Athens Univ.) EPIC-Heart-EC (M.I.) John Danesh (Cambridge Univ.) EPIC-Diabetes Nick Wareham (MRC Cambridge) Anthropometry Heiner Boeing (DIFE-Potsdam) Total Mortality Kim Overvad (Aaarhus Univ.) Dietary Patterns Nadia Slimani (IARC) Phytoestrogens Petra Peeters (U. Utrecht)

  9. IARC Scientific Council, 2005 Nor Swe Den UK Ger NL Fra Ita Spa Gre EPIC Follow-up of EPIC subjects, 1994-2003 cancer incidence (28,000 incident cancer cases) Breast 220 720 845 797 386 607 2844 557 285 56 7317 Colon-rectum 68 342 453 403 197 205 218 168 139 30 2223 Prostate . 650 329 311 235 35 . 66 105 14 1746 Stomach 5 67 54 63 55 37 17 64 38 19 421 Lung 41 224 450 233 154 116 127 92 81 42 1560 Kidney 9 73 76 61 78 38 . 49 32 7 423 Pancreas 4 101 86 99 54 32 . 26 23 11 406 Upper GI Tract 2 72 125 99 57 35 . 27 33 2 452 Cervix uteri 18 241 29 241 63 32 23 34 40 7 728 Corpus uteri 32 106 129 101 38 65 270 81 58 11 591 Ovary 59 87 94 123 38 59 165 58 47 15 745

  10. 1999-2000: NCI Bypass programme “Exceptional Opportunities” for research in the Area of Gene-Environment interaction studies 2003: 1st Funded Project:Cohort Consortium on Hormone Metabolizing Gene Variants and Breast and Prostate cancer risk 2000: NCI Cohort Studies Consortiumon gene environment interaction

  11. HORMONE METABOLIZING GENE VARIANTS AND BREAST AND PROSTATE CANCER RISK • OBJECTIVES: • to study the role in the etiology of breast and prostate cancer of genetic variations in the: • steroid hormone pathway, • insulin-like growth factor (IGF) pathway, • associated receptor and transport proteins

  12. HORMONE METABOLIZING GENE VARIANTS AND BREAST AND PROSTATE CANCER RISK • UNDERLYING HYPOTHESIS: • 1- Hormones can modulate cancer risk by: • 1.1 increasing the rate of cell division and/or • 1.2 suppressing apoptosis in the target tissues; • 2- Relatively common genetic polymorphisms could affect • cancer risk by determining: • 2.1 the rate of hormone synthesis or breakdown, • 2.2 the activity of hormones secreted by the hypotalamus- • pituitary axis that regulate steroidogenesis • 2.3 the amount or effectiveness of binding proteins that • regulate bioavailability • 2.4 the magnitude of the cellular response to hormonal • stimulation via membrane and intracellular receptors.

  13. Estrogens levels and subsequent breast cancer risk; pooled cohort study Endogenous Hormones and Breast Cancer Collaborative Group, JNCI, 2002; 94: 606

  14. P trend 0.0002 0.001 <0.0001 0.0004 <0.0001 0.004 <0.0001 <0.0001 RR 1.00 DHEAS 1.28 1.06 1.68 1.69 1.00 Androstenedione 1.47 1.35 1.70 1.73 Testosterone 1.00 1.14 1.33 1.56 1.85 1.00 Estrone 1.60 1.89 2.05 1.96 1.00 Estradiol 1.10 1.45 1.54 2.05 1.00 SHBG 0.98 0.72 0.87 0.61 Free testosterone 1.00 1.83 1.92 1.86 2.50 Free estradiol 1.00 1.30 1.34 1.71 2.00 0.5 1 2 Postmenopausal Serum Sex Steroids and Breast Cancer Risk The EPIC Study; (677 cases / 1309 controls) Kaaks et al., Endocr Relat Cancer, in press (2005)

  15. Premenopausal Serum Sex Steroids and Breast Cancer Risk The EPIC Study; (416 cases, 815 controls) Ptrend OR 1.00 Testosterone 0.02 1.33 1.36 1.58 1.00 SHBG 1.05 0.98 0.97 1.02 1.00 DHEAS 0.17 1.34 1.15 1.37 1.00 Androstenedione 0.01 1.11 1.14 1.64 1. 00 Estrone 0.76 1.13 0.73 1.22 1.00 Estradiol 0.75 0.76 0.96 0.99 1.00 Progesterone 1.16 0.07 1.07 0.63 Kaaks et al., JNCI (2005) 0.5 1 2

  16. Total and bioavailable estradiol in relation to BMI:Post-menopausal women Key et al., Proc Nutr Soc 2001

  17. Pathways of steroid synthesis Cholesterol 17--OH- pregnenolone -5-androstenediol Pregnenolone DHEA 17--OH- progesterone -4-androstenedione Progesterone testosterone estrone estradiol Mineralo- corticoids Gluco- corticoids

  18. Genes encoding enzymes that are central to the synthesis, conversions and hydroxylation/methoxylation of sex steroids, or encoding steroid-binding proteins and receptors, Blood DHEA(S) 4A T E1 E2 SHBG Hypotha lamus GNRH Pituitary GNRHR CGA LHB FSHB POMC LH FSH ACTH Blood Ovary / Adrenal gland receptors: LHCGR, FSHR, ACTHR cholesterol STAR, CYP11A1, CYP17, HSD3B, pregnenolone, DHEA progesterone, 4A HSD17B Ovary & Adipose tissue TCYP19 estadiol, estrone Breast tissue steroid receptors: ESR1, ESR2, PGR, AR ----------------------------- 4A, T CYP19 E1E2 HSD17B1, HSD17B2 CYP1A1, CYP1B1, CYP3A4, COMT hydroxy / methoxy estrogens Liver SHBG

  19. Hypothalamus GHSR IGF1R + SST GHRH + - SSTR GHRHR - Ghrelin Growth GHSR + - + Target tissues: Breast Prostate Colorectum etc. IGF1+ IGFBP3+ IGFALS POU1F1 - GH Pituitary Circulation Circulation Liver Circulation Regulation of IGF1 and related molecules IGFBP3 GH + IGF1 GHR Ghrelin IGFALS Stomach

  20. Study Year started Subjects with blood samples Breast cancer cases Prostate cancer cases 1992 EPIC 397,256 2,050 900 39,000 ACS (CPS-II) 1998 500 1,450 20,500 ATBC 1991 - 1,000 20,000 - 1,500 PHS 1982 1989 NHS 32,826 945 - HPFS 1993 33,240 - 600 1993 WH 28,263 675 - Multi Ethnic 100,000 1,990 2,400 PLCO - 1,000 1993 75,000 Total 797,085 6,160 8,850 Cohort Consortium on Hormone Metabolizing Gene Variants and Breast and Prostate cancer risk Harvard

  21. Project flowchart Selection of candidate genes (53 genes involved in metabolism of IGF-I and steroid hormones) SNP discovery by gene resequencing (CEPH, WI-MIT) Haplotype tagging (CEPH, WI-MIT) Genotyping (IARC, Cambridge, Harvard, USC, Hawaii, NCI) Hormone measurement (IARC, Harvard) Statistical analysis main effects of SNPs and haplotypes, gene-environment interactions Breast at IARC Prostate at Harvard An

  22. Cohort Consortium Work Flow Chart Study planning and gene choice Gene Resequencing Haplotype determination Identification of ht-SNPs Steering Group and Secretariat Whitehead CEPH NCI PUBLIC ACCESS Web ht-SNP Database IARC & Cambridge Un. NCI Genotyping Centres USC & Honolulu Harvard Multiethnic Cohort Harvard Cohorts ACS PLCO ATBC EPIC Exposure Data Breast Cancer Database IARC Prostate Cancer Database Harvard Database consolidation Collaborative Statistical Analysis PUBLIC ACCESS Web and Journal Publications

  23. Harvard cohorts EPIC cohorts ACS cohort Multiethnic Cohort PLCO cohort ATBC cohort Whitehead Genome Center NCI Core Genotyping Facility STEERING COMMITTEE: Harvard David Hunter, Michael Gaziano, Julie Buring, Graham Colditz, Walter Willett EPIC,CEPH & Cambridge Elio Riboli, Rudolf Kaaks, Bruce Ponder, Gilles Thomas, ACS Michael Thun, Heather Feigelson, NCI Richard Hayes, Demetrius Albanes, Louise Brinton, Sandra Melnick MEC & Whitehead Brian Henderson, Laurence Kolonel, David Altshuler GENOMICS & GENOTYPING subgroup: David Altshuler Federico Canzian Steve Channock Alison Dunning Raju Kucherlapati David Kwiatkowski Gilles Thomas Chris Haiman STATISTICS subgroup: Doug Easton Jun Liu Dan Stram Duncan Thomas, Shalom Wacholder SECRETARIAT: David Hunter Elio Riboli

  24. EPIC components of BPC3 , 2003-2005 IARC Elio Riboli Rudolf Kaaks Coordination Pooled Bata Base for Breast Cancer Pooled statistical analyses Lab analyses of Endogenous Hormones IARC Federico Canzian Genotyping Breast Cancer Cases/Controls Genotyping QC Cambridge Univ Alison Dunning Paul Pharoah Genotyping Prostate Cancer Cases/Controls Oxford CRUK Tim Key Ruth Travis Naomi Allen Stat. analyses prostate data CEPH: Gilles Thomas Helene Blanche Gene Resequencing Haplotype determination Identification of ht-SNPs

  25. EPIC components of BPC3 , 2005-2007 Imperial College London Elio Riboli Scientific Coordination Statistical Methods and Analyses DKFZ, Heidelberg Federico Canzian Genotyping Breast Cancer Cases/Controls Genotyping QC Cambridge U. Alison Dunning Paul Pharoah Genotyping Prostate Cancer Cases/Controls Oxford CRUK Tim Key Stat. analyses prostate data IARC Rudolf Kaaks Pooled Data Base for Breast Cancer Pooled statistical analyses

  26. Elio Riboli MD, MPH, ScM Chair, Cancer Epidemiology and Prevention, Department of Epidemiology Faculty of Medicine Imperial College London e.riboli@imperial@ac.uk

  27. Cohort Consortium Work Flow Chart Study planning and gene choice Gene Resequencing Haplotype determination Identification of ht-SNPs Steering Group and Secretariat Whitehead CEPH NCI PUBLIC ACCESS Web ht-SNP Database DKFZ & Cambridge NCI Genotyping Centres USC & Honolulu Harvard Multiethnic Cohort Harvard Cohorts ACS PLCO ATBC EPIC Exposure Data Prostate Cancer Harvard Breast Cancer IARC-ICL Database consolidation and Statistical Analyses Collaborative Statistical Analysis PUBLIC ACCESS Web and Journal Publications

  28. THE END

  29. Hypothalamus GHSR IGF1R + SST GHRH + - SSTR GHRHR - Ghrelin Growth GHSR + - + Target tissues: Breast Prostate Colorectum etc. IGF1+ IGFBP3+ IGFALS POU1F1 - GH Pituitary Circulation Circulation Liver Circulation Regulation of IGF1 and related molecules IGFBP3 GH + IGF1 GHR Ghrelin IGFALS Stomach An

  30. Project flowchart Selection of candidate genes (53 genes involved in metabolism of IGF-I and steroid hormones) SNP discovery by gene resequencing (CEPH, WI-MIT) Haplotype tagging (CEPH, WI-MIT) Genotyping (IARC, Cambridge, Harvard, USC, Hawaii, NCI) Hormone measurement (IARC, Harvard) Statistical analysis main effects of SNPs and haplotypes, gene-environment interactions Breast at IARC Prostate at Harvard An

  31. Relation between Western Lifestyle, hormone metabolism, and cancer Increased IGF-I bio-activity Cancer of breast endometrium, ovary, or prostate Western Lifestyle; Overnutrition Alterations in steroid hormone metabolism Other cancers: colon/rectum, lung pancreas, Kaaks, IARC

  32. Insulin, IGF-I and cancer development (Unknown mechanisms) Diet / Low Physical activity Total Plasma IGF-I   Obesity, hyper-insulinemia IGF-I bio-activity  Cancer IGFBP-1  IGFBP-2  Kaaks, IARC

  33. Estradiolo 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 <0.001 Estrone < 0.001 < 0.001 Androstenedione < 0.001 Testosterone 0.5 1 2 4 Androgens levels and subsequent breast cancer relative risk:Pooled cohort study trend-p RR Endogenous Hormones and Breast Cancer Collaborative Group, JNCI, 2002; 94: 606

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