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What is the epidemiological evidence linking early life 
events and cancer risk and what are the potential critical 
windows for cancer prevention? 
World Cancer Congress, Saturday 6 December 2014 
Professor Ricardo Uauy 
University of Chile 
London School of Hygiene and Tropical Medicine
Outline 
 
Life course and cancer prevention 
 
The evidence linking early life exposures to cancer 
 
Mechanisms 
 
Example; early life exposures and breast cancer 
 
Data from a Chilean cohort 
 
Conclusions
A life course approach is key in cancer prevention 
 Cancer process takes decades; there may be as much as 40 years 
between exposure to carcinogen and diagnosis 
 Cancer occurrence may be determined in very early life by: 
 Maternal hormones & vaginal cancer in offspring 
 Early diet and carcinogen exposure 
 Birth weight 
 Early growth 
 Dietary preferences 
 Attained height 
 Obesity 
 Breast feeding 
 Adult diet and physical activity behaviors are established in early life 
 Early life is most sensitive to cancer inducing processes (eg relatively 
high cancer risk in under tens exposed to radiation or carcinogens; 
smoking in adolescence)
Annual cancer rates 1970-2006 in all races (rates per 100,000)
Mouth, pharynx, larynx 
Nasopharynx 
Oesophagus 
Lung 
Stomach 
Pancreas 
Gallbladder 
Liver 
Colorectum7 
Breast premenopause 
Breast postmenopause 
Ovary 
Endometrium 
Prostate 
Kidney 
Skin 
Foods containing dietary fibre 
Aflatoxins 
Non-starchy vegetables1 
Allium vegetables 
Garlic 
Fruits2 
Foods containing lycopene 
Food containing selenium3 
Red meat 
Processed meat 
Cantonese-style salted fish 
Diets high in calcium4 
Salt, salted and salty foods 
Glycaemic load 
Arsenic in drinking water 
Maté 
Alcoholic drinks5 
Coffee 
Beta-carotene6 
Physical activity 
Body fatness 
Adult attained height 
Greater birth weight 
Lactation 
Convincing decreased risk 
Probable decreased risk 
Probable increased risk 
Convincing increased risk 
Substantial effect on risk unlikely 
Continuous Update 
Project matrix of 
strong evidence
Continuous Update Project – strong evidence 
Early life exposures and cancer risk 
Prostate 
cancer 
(total) 
Pancreatic 
cancer 
Colorectal 
cancer 
Premenopausal 
breast cancer 
Postmenopausal 
breast cancer 
Ovarian 
cancer 
Adult 
attained 
height 
Per 5 cm 
Probable 
RR = 1.04 
(1.03-1.05) 
Probable 
RR = 1.07 
(1.03-1.12) 
Convincing 
RR = 1.05 
(1.03-1.08) 
Probable 
RR = 1.09 
(1.05-1.12) 
Convincing 
RR = 1.10 
(1.07-1.13) 
Convincin 
g 
RR = 1.08 
(1.05-1.10) 
Greater 
birth 
weight 
- - - Probable - - 
Lactation - - - Convincing Convincing - 
Increased risk 
Decreased risk
Effect of in vitro culture media of human embryos on 
birth weight of newborns 
Human Reproduction, Vol.25, No.3 pp. 605–612, 2010
Nutritionally induced epigenetic imprinting 
Isogenic Avy/a animals, the five 
coat colors used to classify 
phenotype. Avy mutation results 
from the insertion of a murine LTR 
retrotransposon into an exon of the 
agouti gene 
Pseudo 
agouti 
Heavily 
Mottled 
Mottled 
Slightly 
Mottled 
Yellow 
betaine 
choline 
Folic ac 
vit B12. 
Waterland and Jirtle Nutrition 20:1 2004 
Avy alleles of yellow mice are 
hypo-methylated, allowing 
maximal agouti expression. 
Avy hyper-methylation silences 
ectopic agouti expression in 
pseudo -agouti animals, 
recapitulating the agouti 
phenotype.
Dutch Hunger Winter 
 Individuals prenatally exposed to famine during the Dutch Hunger 
Winter in 1944–45 had, 6 decades later, less DNA methylation of 
the imprinted IGF2 gene compared with their unexposed, same-sex 
siblings 
 The association was specific for peri conceptional exposure, 
reinforcing that very early development is a crucial period for 
establishing epigenetic marks 
 These data are the first to contribute empirical support for the 
hypothesis that early-life environmental conditions can cause 
epigenetic changes in humans that persist throughout life 
Heijmansa BT et al PNAS 105:17046–17049 2008
DIET 
ENVIRONMENT 
BODY FAT DISTRIBUTION AND 
CANCER RELATED OUTCOMES
Mechanisms of breast cancer development
1200 Chilean children born in 2002 attending nursery schools in 2006 
2002 -2003 
0y 
Growth and Obesity Cohort Study (GOCS): 
2007 
4y 
2006 
3.5y 
2008 
5.5y 
2009 
6.5y 
2012 
9.5y 
GOCS I GOCS II 
2500-4500gr 
n= 14330 
n= 1196 
n= 313 
n= 1196 n= 1050
Growth and Obesity Cohort Study is a concurrent cohort of 
mothers-children in Chile 
Socio-economic status = low-middle 
Maternal height = 156.3 ± 5.6 cm 
Pre-pregnancy BMI = 24.2 ± 4.3 kgm2 
Pregnancy weight gain = 12.4 ± 4.8 kg 
Smoking during pregnancy = 15% 
Diabetes during pregnancy = ~ 5% (20-40%) 
Preeclampsia = 9.1% 
Breastfeeding* at 4 mo = 64% 
* Exclusive or predominant
Body Mass Index Z score 0-84 months by Body Mass 
Index status at 7 years (n=1096) 
BAZ; WHO 2006 
Age (months) 
Adjusted for current age and sex 
Points connected for ease of reading 
BAZ ≥2 
1≤ BAZ <2 
-1≤ BAZ <1 
BAZ ;WHO 2006-7
Timing of adiposity rebound in 805 Chilean children born in 2002, by Body 
Mass Index status at 7 years 
% 
Timing of Adiposity Rebound 
<2y 
2-4y 
4-5y 
5-7y 
Body Mass Index Z-scores based on WHO 2007 
18.9 
10.5 
48.1 
22.6 
27.7 
38.7 
25.0 
8.6 
52.7 
24.8 
20.7 
1.7 
Body Mass Index 
g/m2 
Age (months) 
BAZ >2 
1 <=BAZ <=2 
BAZ <1
Ultrasound bone age in 936 Chilean children categorized by 
Body Mass Index status at 7 years of age 
Months 
BAZ <1 
1<=BAZ <2 
BAZ =>2 
Body Mass Index 
Z-scores 
WHO 2007
Early Determinants of Fruit and 
Vegetable Acceptance 
Catherine A. Forestell, PhD, Julie A. 
Mennella, PhD Monell Chemical Senses 
Center, Philadelphia, Pennsylvania 
Examples of types of facial 
expressions displayed during the 
first 2 minutes of feeding: brow 
lowerer (A), inner brow raise (B), 
squint (C), nose wrinkle (D), upper-lip 
raise (E), and gape (F). 
www.pediatrics.org/cgi/doi/10.1542/ 
peds.2007-0858 doi:10.1542/peds.2007-0858
What is “healthy growth”? 
 Growth standards reflect nutrition and feeding practices of a given 
community where reference data was obtained (none measure long term 
health) 
 Global growth standards are based on current (breast feeding + weaning 
nutrition) guidelines 
 Paradigm of “bigger” or “taller” is better has never been tested critically 
(benefits vs potential risks). 
 “Healthy” growth should be validated relative to measures that are 
predictors of long term health… such as cancer risk
Cancer prevention : a Life Course Approach 
Age 
Fetal 
Life 
Adult Life 
Infancy and Adolescence 
Childhood 
Older ages 
Established adult risky behaviours 
Diet/Physical activity. Tobacco. 
Alcohol. Carcinogens 
OBESITY 
Biological risks 
Socioeconomic status 
Environmental conditions 
Cumulative 
incidence 
Genetic susceptibility to Cancer 
Breast Feeding 
SES 
Infections/PEM 
Micronutrients 
Contaminants 
(air. food. water.) 
Growth rate 
Stature 
Physical Activity 
Food and Play 
Behaviours 
Smoking 
Contaminants 
(air. food. water.) 
Time of Puberty 
Obesity 
Exercise and 
Physical activity 
Inactivity 
SES 
Mother’s 
Nutrition 
Carcinogen 
Exposures 
Fetal 
Growth 
birth weight 
susceptibility to Preventable 
risk
Conclusions 
 There is increasing evidence that early life exposures 
are associated with cancer risk 
 Need long term cohort follow up studies, including 
randomized controlled interventions that confirm 
putative associations 
 Understanding the mechanisms that control cell biology 
and influence the cancer process will help us to better 
target cancer preventive strategies related to early life 
 Need to identify optimal growth standards for cancer 
prevention
For further information 
Professor Ricardo Uauy 
University of Chile 
London School of Hygiene and Tropical Medicine 
druauy@gmail.com 
@wcrfint 
facebook.com/wcrfint 
www.wcrf.org

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What is the epidemiological evidence linking early life events and cancer risk and what are the potential critical windows for cancer prevention?

  • 1. What is the epidemiological evidence linking early life events and cancer risk and what are the potential critical windows for cancer prevention? World Cancer Congress, Saturday 6 December 2014 Professor Ricardo Uauy University of Chile London School of Hygiene and Tropical Medicine
  • 2. Outline  Life course and cancer prevention  The evidence linking early life exposures to cancer  Mechanisms  Example; early life exposures and breast cancer  Data from a Chilean cohort  Conclusions
  • 3. A life course approach is key in cancer prevention  Cancer process takes decades; there may be as much as 40 years between exposure to carcinogen and diagnosis  Cancer occurrence may be determined in very early life by:  Maternal hormones & vaginal cancer in offspring  Early diet and carcinogen exposure  Birth weight  Early growth  Dietary preferences  Attained height  Obesity  Breast feeding  Adult diet and physical activity behaviors are established in early life  Early life is most sensitive to cancer inducing processes (eg relatively high cancer risk in under tens exposed to radiation or carcinogens; smoking in adolescence)
  • 4. Annual cancer rates 1970-2006 in all races (rates per 100,000)
  • 5. Mouth, pharynx, larynx Nasopharynx Oesophagus Lung Stomach Pancreas Gallbladder Liver Colorectum7 Breast premenopause Breast postmenopause Ovary Endometrium Prostate Kidney Skin Foods containing dietary fibre Aflatoxins Non-starchy vegetables1 Allium vegetables Garlic Fruits2 Foods containing lycopene Food containing selenium3 Red meat Processed meat Cantonese-style salted fish Diets high in calcium4 Salt, salted and salty foods Glycaemic load Arsenic in drinking water Maté Alcoholic drinks5 Coffee Beta-carotene6 Physical activity Body fatness Adult attained height Greater birth weight Lactation Convincing decreased risk Probable decreased risk Probable increased risk Convincing increased risk Substantial effect on risk unlikely Continuous Update Project matrix of strong evidence
  • 6. Continuous Update Project – strong evidence Early life exposures and cancer risk Prostate cancer (total) Pancreatic cancer Colorectal cancer Premenopausal breast cancer Postmenopausal breast cancer Ovarian cancer Adult attained height Per 5 cm Probable RR = 1.04 (1.03-1.05) Probable RR = 1.07 (1.03-1.12) Convincing RR = 1.05 (1.03-1.08) Probable RR = 1.09 (1.05-1.12) Convincing RR = 1.10 (1.07-1.13) Convincin g RR = 1.08 (1.05-1.10) Greater birth weight - - - Probable - - Lactation - - - Convincing Convincing - Increased risk Decreased risk
  • 7. Effect of in vitro culture media of human embryos on birth weight of newborns Human Reproduction, Vol.25, No.3 pp. 605–612, 2010
  • 8. Nutritionally induced epigenetic imprinting Isogenic Avy/a animals, the five coat colors used to classify phenotype. Avy mutation results from the insertion of a murine LTR retrotransposon into an exon of the agouti gene Pseudo agouti Heavily Mottled Mottled Slightly Mottled Yellow betaine choline Folic ac vit B12. Waterland and Jirtle Nutrition 20:1 2004 Avy alleles of yellow mice are hypo-methylated, allowing maximal agouti expression. Avy hyper-methylation silences ectopic agouti expression in pseudo -agouti animals, recapitulating the agouti phenotype.
  • 9. Dutch Hunger Winter  Individuals prenatally exposed to famine during the Dutch Hunger Winter in 1944–45 had, 6 decades later, less DNA methylation of the imprinted IGF2 gene compared with their unexposed, same-sex siblings  The association was specific for peri conceptional exposure, reinforcing that very early development is a crucial period for establishing epigenetic marks  These data are the first to contribute empirical support for the hypothesis that early-life environmental conditions can cause epigenetic changes in humans that persist throughout life Heijmansa BT et al PNAS 105:17046–17049 2008
  • 10. DIET ENVIRONMENT BODY FAT DISTRIBUTION AND CANCER RELATED OUTCOMES
  • 11. Mechanisms of breast cancer development
  • 12. 1200 Chilean children born in 2002 attending nursery schools in 2006 2002 -2003 0y Growth and Obesity Cohort Study (GOCS): 2007 4y 2006 3.5y 2008 5.5y 2009 6.5y 2012 9.5y GOCS I GOCS II 2500-4500gr n= 14330 n= 1196 n= 313 n= 1196 n= 1050
  • 13. Growth and Obesity Cohort Study is a concurrent cohort of mothers-children in Chile Socio-economic status = low-middle Maternal height = 156.3 ± 5.6 cm Pre-pregnancy BMI = 24.2 ± 4.3 kgm2 Pregnancy weight gain = 12.4 ± 4.8 kg Smoking during pregnancy = 15% Diabetes during pregnancy = ~ 5% (20-40%) Preeclampsia = 9.1% Breastfeeding* at 4 mo = 64% * Exclusive or predominant
  • 14. Body Mass Index Z score 0-84 months by Body Mass Index status at 7 years (n=1096) BAZ; WHO 2006 Age (months) Adjusted for current age and sex Points connected for ease of reading BAZ ≥2 1≤ BAZ <2 -1≤ BAZ <1 BAZ ;WHO 2006-7
  • 15. Timing of adiposity rebound in 805 Chilean children born in 2002, by Body Mass Index status at 7 years % Timing of Adiposity Rebound <2y 2-4y 4-5y 5-7y Body Mass Index Z-scores based on WHO 2007 18.9 10.5 48.1 22.6 27.7 38.7 25.0 8.6 52.7 24.8 20.7 1.7 Body Mass Index g/m2 Age (months) BAZ >2 1 <=BAZ <=2 BAZ <1
  • 16.
  • 17. Ultrasound bone age in 936 Chilean children categorized by Body Mass Index status at 7 years of age Months BAZ <1 1<=BAZ <2 BAZ =>2 Body Mass Index Z-scores WHO 2007
  • 18. Early Determinants of Fruit and Vegetable Acceptance Catherine A. Forestell, PhD, Julie A. Mennella, PhD Monell Chemical Senses Center, Philadelphia, Pennsylvania Examples of types of facial expressions displayed during the first 2 minutes of feeding: brow lowerer (A), inner brow raise (B), squint (C), nose wrinkle (D), upper-lip raise (E), and gape (F). www.pediatrics.org/cgi/doi/10.1542/ peds.2007-0858 doi:10.1542/peds.2007-0858
  • 19. What is “healthy growth”?  Growth standards reflect nutrition and feeding practices of a given community where reference data was obtained (none measure long term health)  Global growth standards are based on current (breast feeding + weaning nutrition) guidelines  Paradigm of “bigger” or “taller” is better has never been tested critically (benefits vs potential risks).  “Healthy” growth should be validated relative to measures that are predictors of long term health… such as cancer risk
  • 20. Cancer prevention : a Life Course Approach Age Fetal Life Adult Life Infancy and Adolescence Childhood Older ages Established adult risky behaviours Diet/Physical activity. Tobacco. Alcohol. Carcinogens OBESITY Biological risks Socioeconomic status Environmental conditions Cumulative incidence Genetic susceptibility to Cancer Breast Feeding SES Infections/PEM Micronutrients Contaminants (air. food. water.) Growth rate Stature Physical Activity Food and Play Behaviours Smoking Contaminants (air. food. water.) Time of Puberty Obesity Exercise and Physical activity Inactivity SES Mother’s Nutrition Carcinogen Exposures Fetal Growth birth weight susceptibility to Preventable risk
  • 21. Conclusions  There is increasing evidence that early life exposures are associated with cancer risk  Need long term cohort follow up studies, including randomized controlled interventions that confirm putative associations  Understanding the mechanisms that control cell biology and influence the cancer process will help us to better target cancer preventive strategies related to early life  Need to identify optimal growth standards for cancer prevention
  • 22. For further information Professor Ricardo Uauy University of Chile London School of Hygiene and Tropical Medicine druauy@gmail.com @wcrfint facebook.com/wcrfint www.wcrf.org