elio riboli md, mph, scm head, nutrition, hormones and cancer group i.a.r.c.-w.h.o. international...
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Elio Riboli MD, MPH, ScM
Head, Nutrition, Hormones and Cancer
Group
I.A.R.C.-W.H.O.
International Agency for
Research on CancerWorld Health Organization
Lyon, France
LYON
PARIS
FLORENCE
MILAN
RAGUSA
TURIN
NAPLESBARCELONA
OVIEDO
GRANADAMURCIA
PAMPLONA
SAN SEBASTIAN
CAMBRIDGE
OXFORD BILTHOVEN
UTRECHT
ATHENS
HEIDELBERG
POTSDAM
MALMÖ
UMEÅ
AARHUS
COPENHAGEN
TROMSØ
Collaborating centres and cohort subjects
Subjects includedQuestionnaire Q + Blood
France 74 524 21 053Italy 47 749 47 725Spain 41 440 39 579UK 87 942 43 141Netherlands 40 072 36 318Greece 28 555 28 483Germany 53 091 50 678Sweden 53 826 53 781Denmark 57 054 56 131Norway 37 215 11 000All 521 468 387 889
EPIC
LONDON
BASELINE•Subjects recruitment •Questionnaires data•Anthropometry data•Blood/DNA collection•Data Base & Biorepository
1993…………………………..…….1999………… 2000…….2002……………………2005
EPIC Time Table
SpainNor
way
France
Italy
UKNeth
erlan
d
sGer
man
y
Greec
e
FOLLOW-UP:• Cancer diagnosis• Vital status • Causes of death• Changes in Lifestyle
Development of common/standardized Nutrient and lifestyle Data BasesSetting up of lab facilities for sample handling / DNA extraction etc
ETIOLOGICAL STUDIES
Swed
en
DK
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 !
“Westernization” of lifestyle and cancer.
• Final size of the database : over 100 giga bytes.
• 90 screens have been developed to
facilitate thetransfer, standardization,control andexportof the data
• 521.000 subjects x about 2000 common variables over 1 billions values stored
EPIC Database
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)(yellow straws)– buffy coat 4 (blue straws)– RBC 4 (green straws)
28 aliquots x 300.000 subjects =
8.4 Million biological aliquots
EPIC
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)
Working groups on risk factors, end-points other than cancer, methodological issues: Coordinators:
EPIC-Elderly-EC (Aging)EPIC-Elderly-EC (Aging) Antonia Trichopoulou (Athens Univ.)
EPIC-Heart-EC (M.I.)EPIC-Heart-EC (M.I.) John Danesh (Cambridge Univ.)
EPIC-DiabetesEPIC-Diabetes Nick Wareham (MRC Cambridge)
Anthropometry Anthropometry Heiner Boeing (DIFE-
Potsdam)
Total MortalityTotal Mortality Kim Overvad (Aaarhus Univ.)
Dietary PatternsDietary Patterns Nadia Slimani
(IARC)
PhytoestrogensPhytoestrogens Petra Peeters (U.
Utrecht)
EPIC Steering Committee
EPIC: Organizational Structure
IARC Scientific Council, 2005
Follow-up of EPIC subjects, 1994-2003
Breast 220 720 845 797 386 607 2844 557 285 56 7317
Lung 41 224 450 233 154 116 127 92 81 42 1560
Ovary 59 87 94 123 38 59 165 58 47 15 745
Corpus uteri 32 106 129 101 38 65 270 81 58 11 591
Cervix uteri 18 241 29 241 63 32 23 34 40 7 728
Upper GI Tract 2 72 125 99 57 35 . 27 33 2 452
Pancreas 4 101 86 99 54 32 . 26 23 11 406
Kidney 9 73 76 61 78 38 . 49 32 7 423
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
Nor Swe Den UK Ger NL Fra Ita Spa Gre EPIC
cancer incidence (28,000 incident cancer cases)
2003: 1st Funded Project:
Cohort Consortium on Hormone Metabolizing Gene
Variants and Breast and Prostate cancer risk
2000: NCI Cohort Studies Consortium
on gene environment interaction
1999-2000: NCI Bypass programme “Exceptional Opportunities” for research in the Area of Gene-Environment interaction studies
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
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.
HORMONE METABOLIZING GENE VARIANTS AND BREAST AND PROSTATE CANCER RISK
Estrogens levels and subsequent breast cancer risk; pooled cohort study
Endogenous Hormones and Breast Cancer Collaborative Group, JNCI, 2002; 94: 606
Postmenopausal Serum Sex Steroids and Breast Cancer RiskThe EPIC Study; (677 cases / 1309 controls)
DHEAS
Androstenedione
Testosterone
Estrone
Estradiol
SHBG
Freetestosterone
Freeestradiol
1.001.281.061.681.69
1.001.471.351.701.73
1.001.141.331.561.85
1.001.601.892.051.96
1.001.101.451.542.05
1.000.980.720.870.61
1.001.831.921.862.50
1.001.301.341.712.00
RR
0.5 1 2
P trend
0.0002
0.001
<0.0001
0.0004
<0.0001
0.004
<0.0001
<0.0001
Kaaks et al., Endocr Relat Cancer, in press (2005)
Premenopausal Serum Sex Steroids and Breast Cancer RiskThe EPIC Study; (416 cases, 815 controls)
Testosterone
SHBG
DHEAS
Androstenedione
Estrone
Estradiol
Progesterone
1.00 1.33 1.36 1.58
1.00 1.05 0.97 1.02
1.00 1.34 1.15 1.37
1.00 1.11 1.14 1.64
1.001.13 0.73 1.22
1.00 0.76 0.96 0.99
1.00 1.16 1.07 0.63
OR
0.5 1 2
Ptrend
0.02
0.98
0.17
0.01
0.76
0.75
0.07
Kaaks et al., JNCI (2005)
Total and bioavailable estradiol in relation to BMI:
Post-menopausal women
Key et al., Proc Nutr Soc 2001
Cholesterol
Pregnenolone 17--OH-pregnenolone
DHEA -5-androstenediol
Progesterone 17--OH-progesterone
-4-androstenedione testosterone
Mineralo-corticoids
Gluco-corticoids
estrone estradiol
Pathways of steroid synthesis
Hypothalamus
GNRH
Pituitary
GNRHRCGALHBFSHBPOMC
LH
FSH
ACTH
Blood Ovary / Adrenal gland
receptors: LHCGR, FSHR, ACTHR
cholesterol STAR, CYP11A1, CYP17, HSD3B,
pregnenolone, DHEAprogesterone, 4A
HSD17B
Ovary & Adipose tissue T CYP19
estadiol, estrone
Blood
DHEA(S)4ATE1E2
SHBG
Liver
SHBG
Breast tissue
steroid receptors: ESR1, ESR2, PGR, AR-----------------------------4A, T
CYP19
E1 E2
HSD17B1, HSD17B2
CYP1A1, CYP1B1, CYP3A4, COMT
hydroxy / methoxy estrogens
Genes encoding enzymes that are central to the synthesis, conversions and hydroxylation/methoxylation
of sex steroids, or encoding steroid-binding proteins and receptors,
Regulation of IGF1 and related moleculesRegulation of IGF1 and related molecules
Target tissues: Breast Prostate Colorectum etc.
IGF1RHypothalamus
SST GHRH
Stomach
Ghrelin
-
Pituitary
SSTR GHRHR -
-GH
- +POU1F1
GH
Circulation
Growth
+Ghrelin
Circulation
+
+
GHSR
GHSR
Liver
GHR + IGF1
IGFBP3
IGFALS
IGF1+IGFBP3+IGFALS
Circulation
Study Yearstarted
Subjects withblood samples
Breast cancercases
Prostate cancercases
EPIC 1992 397,256 2,050 900
ACS (CPS-II) 1998 39,000 500 1,450
Harvard
PHS 1982 20,000 - 1,500
NHS 1989 32,826 945 -
HPFS 1993 33,240 - 600
WH 1993 28,263 675 -
Multi Ethnic 100,000 1,990 2,400
PLCO 1993 75,000 - 1,000
Total 797,085 6,160 8,850
ATBC 1991 20,500 - 1,000
Cohort Consortium on Hormone Metabolizing Gene Variants and Breast and Prostate cancer
risk
Project flowchart
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 analysismain effects of SNPs and haplotypes,
gene-environment interactionsBreast at IARC
Prostate at Harvard
Selection of candidate genes(53 genes involved in metabolism of IGF-I and steroid hormones)
Whitehead
CEPH
Web ht-SNP Database
Study planning and gene choice
Gene Resequencing
Haplotype determination
Identification of ht-SNPs
Harvard USC & Honolulu
IARC & Cambridge
Un.
NCI
HarvardCohorts
Multiethnic
Cohort
ACS
EPIC PLCO
ATBC
Breast Cancer
Database IARC
Collaborative Statistical Analysis
Web and Journal Publications
Exposure Data
Cohort Consortium Work Flow Chart
Prostate Cancer
DatabaseHarvard
Genotyping
Centres
Database consolidation
Steering Group and
Secretariat
PUBLIC ACCESS
PUBLIC ACCESS
NCI
STEERING COMMITTEE:Harvard David Hunter, Michael Gaziano, Julie Buring, Graham Colditz, Walter WillettEPIC,CEPH & Cambridge Elio Riboli, Rudolf Kaaks, Bruce Ponder, Gilles Thomas,ACS Michael Thun, Heather Feigelson, NCI Richard Hayes, Demetrius Albanes, Louise Brinton, Sandra MelnickMEC & Whitehead Brian Henderson, Laurence Kolonel, David Altshuler
SECRETARIAT:
David HunterElio Riboli
GENOMICS & GENOTYPING
subgroup:
David Altshuler Federico CanzianSteve ChannockAlison DunningRaju KucherlapatiDavid KwiatkowskiGilles ThomasChris Haiman
STATISTICS subgroup:
Doug EastonJun LiuDan StramDuncan Thomas, Shalom Wacholder
Harvard cohorts
ACS cohort
EPIC cohorts
Multiethnic Cohort
PLCO cohort
ATBC cohort
WhiteheadGenome Center
NCI Core Genotyping
Facility
CEPH:
Gilles Thomas Helene Blanche
Gene Resequencing
Haplotype determination
Identification of ht-SNPs
Cambridge Univ
Alison Dunning Paul Pharoah
Genotyping Prostate Cancer Cases/Controls
Oxford CRUKTim Key
Ruth TravisNaomi Allen
Stat. analyses prostate data
IARC
Federico Canzian
Genotyping Breast Cancer Cases/Controls
Genotyping QC
IARC
Elio RiboliRudolf Kaaks
Coordination
Pooled Bata Base for Breast Cancer
Pooled statistical analyses
Lab analyses of EndogenousHormones
EPIC components of BPC3 , 2003-2005
Imperial College London
Elio Riboli
Scientific Coordination
StatisticalMethods and Analyses
Cambridge U.
Alison Dunning Paul Pharoah
Genotyping Prostate Cancer Cases/Controls
Oxford CRUKTim Key
Stat. analyses prostate data
DKFZ, Heidelberg
Federico Canzian
Genotyping Breast Cancer Cases/Controls
Genotyping QC
IARC
Rudolf Kaaks
Pooled Data Base for Breast Cancer
Pooled statistical analyses
EPIC components of BPC3 , 2005-2007
Elio Riboli MD, MPH, ScM
Chair, Cancer Epidemiology and
Prevention,
Department of Epidemiology
Faculty of Medicine
Imperial College London
e.riboli@[email protected]
Whitehead
CEPH
Web ht-SNP Database
Study planning and gene choice
Gene Resequencing
Haplotype determination
Identification of ht-SNPs
Harvard USC & Honolulu
DKFZ & Cambridge
NCI
HarvardCohorts
Multiethnic
Cohort
ACS
EPIC PLCO
ATBC
Breast Cancer IARC-ICL
Collaborative Statistical Analysis
Web and Journal Publications
Exposure Data
Cohort Consortium Work Flow Chart
Prostate Cancer Harvard
Genotyping
Centres
Database consolidationand Statistical Analyses
Steering Group and
Secretariat
PUBLIC ACCESS
PUBLIC ACCESS
NCI
THE END
Regulation of IGF1 and related moleculesRegulation of IGF1 and related molecules
Target tissues: Breast Prostate Colorectum etc.
IGF1RHypothalamus
SST GHRH
Stomach
Ghrelin
-
Pituitary
SSTR GHRHR -
-GH
- +POU1F1
GH
Circulation
Growth
+Ghrelin
Circulation
+
+
GHSR
GHSR
Liver
GHR + IGF1
IGFBP3
IGFALS
IGF1+IGFBP3+IGFALS
Circulation
Project flowchart
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 analysismain effects of SNPs and haplotypes,
gene-environment interactionsBreast at IARC
Prostate at Harvard
Selection of candidate genes(53 genes involved in metabolism of IGF-I and steroid hormones)
Kaaks / IARC / 98
Available IGF-I
IGFBP1 in plasma, target-tissues
Plasma insulin
Insulin resistance
Plasma SHBG
Ovarian androgen production
Plasma testosterone
Estrogen binding to SHBG
Free estrogen
Regulation of plasma steroid hormones by insulin / IGF-I in women
Relation between Western Lifestyle, hormone metabolism, and cancer
Western Lifestyle;Overnutrition
Increased IGF-I
bio-activity
Alterations in steroid hormone metabolism
Cancer of breast
endometrium,ovary, or prostate
Kaaks, IARC
Other cancers:
colon/rectum, lung
pancreas,
Total Plasma IGF-I
IGF-I bio-activity
IGFBP-1
IGFBP-2
Diet / Low Physical activity
Obesity, hyper-insulinemia
(Unknown mechanisms)
Cancer
Insulin, IGF-I and cancer development
Kaaks, IARC
RR trend-p
< 0.001
< 0.001
< 0.001Testosterone
Androstenedione
Estrone
12345
12345
12345
12345
<0.001Estradiolo
0.5 1 2 4
Androgens levels and subsequent breast cancer relative risk:Pooled cohort study
Endogenous Hormones and Breast Cancer Collaborative Group, JNCI, 2002; 94: 606
Kaaks / IARC / 98
Available IGF-I
IGFBP1 in plasma, target-tissues
Plasma insulin
Insulin resistance
Plasma SHBG
Ovarian androgen production
Plasma testosterone
Estrogen binding to SHBG
Free estrogen
Regulation of plasma steroid hormones by insulin & IGF- I