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

, phary

nx, la

rynx

Naso

phary

nx

Oeso

phagus

Lung

Sto

mach

Pancr

eas

Gallbla

dder

Liv

er

Colo

rect

um

7

Bre

ast

pre

menopause

Bre

ast

post

menopause

Ovary

Endom

etr

ium

Pro

state

Kid

ney

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

Coffee

Beta-carotene6

Physical activity

Body fatness

Adult attained height

Greater birth weight

Lactation

Alcoholic drinks5

Convincing decreased risk

Probable decreased risk

Probable increased risk

Convincing increased riskSubstantial effect on risk unlikely

Continuous Update

Project matrix of

strong evidence

Continuous Update Project – strong evidenceEarly 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

MottledMottled

Slightly

MottledYellow

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

2002 -20030y

20074y

20063.5y

20085.5y

20096.5y

20129.5y

GOCS IIGOCS I

2500-4500grn= 14330

n= 1196

n= 313

n= 1050n= 1196

Growth and Obesity Cohort Study (GOCS):

1200 Chilean children born in 2002 attending nursery schools in 2006

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

Growth and Obesity Cohort Study is a concurrent cohort of

mothers-children in Chile

Body Mass Index Z score 0-84 months by Body Mass Index status at 7 years (n=1096)

BA

Z;

WH

O 2

00

6

Adjusted for current age and sex

Points connected for ease of reading

Age (months)

BAZ ;WHO 2006-7

BAZ ≥2

1≤ BAZ <2

-1≤ BAZ <1

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

10.5

18.9

22.6

48.1

27.7

25.0

38.7

8.6

24.8

52.7

1.7

20.7

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

BAZ =>2

1<=BAZ <2

Body Mass Index

Z-scores

WHO 2007

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

Early Determinants of Fruit and

Vegetable AcceptanceCatherine A. Forestell, PhD, Julie A.

Mennella, PhD Monell Chemical Senses

Center, Philadelphia, Pennsylvania

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

AdolescenceInfancy andChildhood

Genetic susceptibility to Cancer

Older ages

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

SESMother’sNutrition

CarcinogenExposures

Fetal Growthbirth weight

Genetic susceptibility to Cancer

Cumulativeincidence

Preventable risk

Established adult risky behaviours

Diet/Physical activity. Tobacco.

Alcohol. Carcinogens

OBESITY

Biological risks

Socioeconomic status

Environmental conditions

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

@wcrfint

facebook.com/wcrfint

www.wcrf.org

Professor Ricardo Uauy

University of Chile

London School of Hygiene and Tropical Medicine

druauy@gmail.com