the genetic epidemiology of common hormonal cancers

The genetic epidemiology of common hormonal cancers

Deborah ThompsonCentre for Cancer Genetic Epidemiology

The 15 Most Common Cancers, UK 2011 (Cancer Research UK)

Fam RR~2

2-3

~2

3-4

The 20 Most Common Cancers, UK 2011 (Cancer Research UK)

Account for 32% of UK cancers

0.000001 0.00001 0.0001 0.001 0.01 0.11

10

Allele frequency

Rela

tive

Risk

BRCA1

BRCA2TP53

? ATM ?

PTEN

Example: The landscape for breast genetics in 1997

0.000001 0.00001 0.0001 0.001 0.01 0.1 11

10

Allele frequency

Rela

tive

Risk

BRCA1

BRCA2TP53

PALB2

CHEK2 ATM

CDH1

STK11

PTEN

Risk SNPs

Example: The landscape for breast genetics in 2014

International Consortia in which CCGE plays a key roleCancer site Consortium No. studies CCGE involvement

Breast BCAC 90 SEARCH study, SIBS study;Genetic + phenotypic data management, QC + statistical analyses, website

Prostate PRACTICAL 78 SEARCH study;Genetic + phenotypic data management, QC + statistical analyses, website

BRCA1/2 carriers CIMBA 65 EMBRACE study, UKFOCR study; Genetic + phenotypic data management, QC + statistical analyses, website

Ovarian OCAC 50 SEARCH study, UKFOCR study, RMH study;Genetic data management, QC + statistical analyses, website

Endometrial ECAC 16 SEARCH study; QC + statistical analyses

+ computing / bioinformatics + laboratory resources

The Collaborative Oncological Gene-environment Study (COGS)

• GWAS follow-up• fine-mapping• candidate variants

211,115 SNPs

SNP selection:BCAC

OCAC

PRACTICAL

CIMBA

“Common”

Genotyped in >200,000 samples:• cancer cases/ctrls • BRCA1/2 carriers

March 2013: 13 iCOGS papers, >70 new cancer loci

Unexplained: 50%

BRCA1BRCA2CHEK2

ATMPALB2BRIP1XRCC2

TP53PTENLKB1

SNPs pre-iCOGS

(GWAS)

Proportional of the Familial RR of Breast Cancer Explained

iCOGSSNPs

Other iCOGSestimated

9%5%

14%

Michailidou et al 2014

Proportional of the Familial RRs of:

Unexplained: 54%

BRCA1BRCA240%

GWAS3%

iCOGS 1% RAD51C

RAD51DBRIP12%

Ovarian Cancer

Unexplained: 65%

BRCA1BRCA2HOXB13MMRNBS1CHEK25%

GWAS25%

iCOGS5%

Prostate Cancer

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.10

20 25 30 35 40 45 50 55 60 65

10 y

r bre

ast c

ance

r ris

k

Age (years)

Lowest risk quintile

Quintile 2

Quintile 3

Quintile 4

Highest risk quintile

Reference

Ten year breast cancer risk based on 77 SNP profile

70

BOADICEA is a polygenic risk prediction model for familial breast and ovarian cancer. Based on cancer family-history it computes:

• age-specific risks of breast and ovarian cancer

• BRCA1 and BRCA2 mutation carrier probabilities

The user-friendly BOADICEA web application allows researchers, clinicians and members of the public to estimate risks

The web application has ~3,800 registered users worldwide

Recommended as a risk assessment tool in NICE clinical guidelines and internationally (e.g. American Cancer Society, Ontario BSP).

Using our findings: the BOADICEA model

http://ccge.medschl.cam.ac.uk/boadicea/

GAME-ON OncoArray

OncoChip600K

beadtypes

GWAS Backbone

250KIllumina Core

Common Content – 40K Fine-mapping of common cancer susceptibility loci

Ancestry Informative MarkersCross-Site meta analysis

Pharmacogenetic components Quantitative traits

Other cancers published GWAS variantsChromosome X and mitochondrial DNA variants

Cancer Specific Variants ~320k

ProstateBreast

OvarianLung

BRCA1/2 carriersColon

What next?

DISCOVERY: OncoArraySequencing (targeted, whole-

genome)

FINE-MAPPING: looking at GWAS/iCOGS risk loci in more detailedmultiple independent variables

within loci?linking epidemiological and

functional evidence

APPLICATION: extension of BOADICEA developing risk-prediction

models for other cancers

Acknowledgements