Genetics and Risk of Breast
Cancer
What is the Evidence
Questions
•
•
•
•
•
What is the role of mutation testing
What is the risk to mutation carriers
What is the evidence for intervention
How does family history predict risk
What lines of future research are required
What is the likelihood of finding
a mutation ?
BRCA1 and BRCA2
• Mutations confer an autosomal dominant susceptibility to
Breast and Ovarian cancer with high penetrance
• In some populations there are common mutations
• These are not the only genes involved
BRCA1 and BRCA2
• Population frequency (British Cases)
BRCA1 0.11%
BRCA2 0.12%
(Peto et.al. 1999)
• Estimate 16% of hereditary breast cancer susceptibility
is caused by these genes in UK.
Determining
Probability of Being a Gene Carrier
• Empirical data
• Logistic Regression Analysis
• Bayes calculation
Ford et.al. 1997, Narod et.al. 1995
• 84% of BCLC families showed evidence of
linkage to BRCA1 or BRCA2. (4 affected
members).
• 76% of breast-ovarian families linked to
BRCA1 (3 affected members, one ovarian).
Peto et.al. 1999
• BRCA1 and BRCA2 Mutation Analysis
Status
Mutation detected
BRCA1
BRCA2
Affected < 35
Affected 36-45
Affected <45, mother breast cancer
Affected <45, 1o with breast CA<60
*Affected <45, 1o with ovarian CA
*Affected 36-45, 2X 1o with breast <60
9/254
7/363
2/54
3/52
3/5
1/8
6/254
8/363
1/54
1/52
0/5
3/8
Schattuck Eidens et.al. 1997
• BRCA1 and BRCA2 Mutation Analysis
Status
Affected < 35
Affected 36 - 45
Affected <45, mother breast cancer
Affected <45, 1o with breast CA<60
Affected <45, 1o with ovarian CA
Mutation detected
BRCA1
BRCA2
~5%
1-2%
~2%
~2%
~6%
Affected 35, 1o relative with breast + ovarian
Affected 35, Bilateral Breast Cancer
20%
20%
Parmigiani et.al.1998
• Bayes Risk Calculation
–
–
–
–
–
Uses population frequency of mutation
Uses penetrance data for gene mutation
Takes family structure into account
Assumes all non BRCA1/BRCA2 cancer is sporadic
Has been computerised
CASH data
Ford data
Likelihood of identifying a mutation
BRCA1 and BRCA2 Mutation Detection
Status
Cyrillic
Peto
(BRCAPro)
Affected < 35
Affected <45, 1o with breast CA<60
Affected <45, 1o with ovarian CA
Affected <45 2X1o relative with breast <60
BRCA1
BRCA2
BRCA1
BRCA2
2%
4%
22%
21%
0.3%
2%
1.6%
10%
4%
6%
60%
13%
2%
2%
0%
38%
Population Specific Mutations
Ashkenazi Jewish Population
BRCA1
BRCA2
185delAG
5382insC
6174delT
Icelandic population
BRCA2
Over 2% of population
999del5
0.6% of population
Mutation Detection with
Askenazi Jewish descent
• Lalloo et.al. 1998
– Breast cancer <60
– 2 X Breast cancer <70
– BCLC criteria
1/4
3/10
5/5
–
• Schattuck-Eidens et.al. 1997
– Affected age 40
– Affected at 40 + 1o relative breast
– Affected at 40 + 1o relative ovarian
~12%
~20%
~35%
Male Breast Cancer
Friedman et.al. 1997 (Californian Male Cases)
• 2/54 cases of male breast cancer had BRCA2 mutations
• 17% had a 1o family history of breast cancer
Conclusions
In a small proportion of cases, mutation
testing for BRCA1 and BRCA2 would be
expected to have a high pickup rate.
Eg.
4 family members with breast cancer
Breast cancer <age 45 with 1o ovarian cancer
Conclusions
• Different systems exist to predict likelihood
of detecting a mutation.
– BRCApro
– Logistic regression curves
• Not all of these have been validated in
clinical practice.
Conclusions
• Testing for the common Ashkenazi Jewish
mutations may be relevant,
– In the presence of modest family history.
– with isolated young onset disease.
What is the Risk to Mutation
Carriers ?
Risk to Mutation Carriers
• Derived from Linkage
– Easton et.al. 1993
– Ford et.al. 1994,1998
• Empirical data from common mutations
– Struewing et.al. 1997
– Steinumn et.al. 1998
Risk To Mutation Carriers (%)
Easton et.al.
By age 40
By age 50
By age 60
By age 65
By age 70
By age 75
Ford et.al.
Struewing
Steinum
BRCA1
BRCA2
BRCA1+2
BRCA2
(Population)
Br Ov
Br
Br
Br Ov
Br O v
19
50
54
85
-
12 0.0
28 0.4
48 7.4
84 27
-
15
35
-
5.5
7.9
0.6
22
30
63
-
Ov
33
56
-
Ov
7
16
-
-
ISD
0.9
1.5
Conclusions
• BRCA1 and BRCA2 mutations confer a
high risk of breast and ovarian cancer.
• All studies have potential sources of bias,
the true risk will depend on the population
and mutation type.
Modifying Risk to Gene Carriers
Modifying Risk
Screening
Breast examination
Mammography
Ovarian Ultrasound
Hormonal Manipulation
Tamoxifen
Surgical Intervention
Mastectomy
Oophorectomy
Screening / Mammography
• Proven benefit when age > 50 in individuals at population risk
– Meta-analysis, Kerlikowske JAMA 1995
• Conflicting Evidence for population screening ages 40 to 49
– Some studies for, some against
• High Risk Screening
– Uncontrolled longitudinal follow up of high risk cohort
Screening / Mammography
• Chart et.al. 1997 - Canadian High Risk Programme
–
–
–
–
1044 women categorised as high, moderate or low risk
6 year follow up, mammography and breast examination
in high risk group 7/381 had tumours at presentation
5/381 high risk developed tumours on follow up
• Lalloo et.al. 1998 - Manchester high risk breast clinic
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–
–
–
1259 women with a lifetime risk of breast cancer > 1 in 6
7 tumours prevalent (4 were in situ), 9 tumours incident
2 tumours were detected by self examination between screens
6 of incident tumours were palpable
Tamoxifen prevention Studies
The Breast Cancer Prevention Trial (P1)
–
–
–
–
Women at “increased Risk”, 13388 cases, 5 year follow up
Tamoxifen reduced breast cancer risk (RR 0.5)
Increased endometrial cancer and pulmonary embolus + cataract
Overall mortality not significantly lower
Royal Marsden Chemoprevention Trial
– 8 year follow up of 2471 women, power 90% for 50% effect
– No detectable effect on breast cancer
Hormone Replacement Therapy
• No study has looked at HRT in BRCA mutation carriers
• Generally, HRT confers a small increased risk of breast cancer.
• HRT decreases cardiovascular and osteoporotic events.
• In one large meta-analysis (anonymous 1997) positive family history
did not show a significantly increased risk of breast cancer in HRT
users as opposed to non-users. Numbers analysed were small.
• Breast cancer in BRCA1 carriers is often oestrogen receptor negative.
Prophylactic Surgery
• Mastectomy
– Various modelling approaches looking at cost/benefit
– Hartmann et.al. 1999 Retrospective study
• Estimated 90% reduction in breast cancer incidence
• Did not take other post-operative morbidity into account
• Oophorectomy
– Rebbeck et.al. 1998 (ASHG abstract)
• reduction in breast cancer in BRCA1 mutation carriers
– Papillary serous carcinoma of peritoneum may arise in BRCA1
carriers after oophorectomy. (Schorge et.al.1998, Piver et.al. 1993.)
Conclusions
• The benefits of prophylactic tamoxifen remain unproven.
• Family history of breast cancer is not necessarily a
contraindication for HRT.
• More studies are needed
Conclusions
• Prophylactic mastectomy can have a role in
patients at high risk of breast cancer.
• Prophylactic oophorectomy may reduce risk
of ovarian cancer and breast cancer.
Peritoneal tumours may still arise.
Conclusions
• Screening of high risk patients can be
effective in detecting breast cancer.
• Overall benefit of screening remains to be
demonstrated.
Presenting Risk
Lifetime Absolute Risk
• Your lifetime risk of dying is 100%
Relative Risk
• Your Risk of dying is 1X that of the population
Absolute Risk over Time
• Your risk of dying over the next 10 years is
2%
Presenting Risk
• Absolute Risk over a given time is
– Easy to understand
– Easy to base decisions upon
• Relative Risk can be converted to absolute risk
– Assuming relative risk is constant over time
– Assuming individual belongs to the population studied
• (Dupont and Plumber 1996)
How Can Risk be Estimated from
Family History ?
Risk Analysis - Situation A
• Mother and Sister Affected with Breast Cancer
60
Risk Analysis - Situation B
• Three Relatives Affected with Breast Cancer
Risk Analysis - Situation C
• Mother Affected with Ovarian Cancer and Sister with Breast Cancer
Risk Analysis - Situation D
• Mother affected with bilateral breast cancer
40/55
40
Risk Analysis - Situation E
• Two second degree relatives with breast cancer < age 60
Risk Analysis - Situation F
• Mother affected with breast cancer age 45 and ovarian age 65
Estimation of Risk
• Empirical Data Studies
– OPCS data set
3295 cases of breast cancer
– CASH data set
4730 cases of breast cancer
– Meta-analysis - Pharoah et.al. 74 published studies
• Modelling of Data
– CASH data
– Gail Model
• Linkage/Computer Analysis
– Cyrillic (Uses CASH data)
2,852 cases of breast cancer
Empirical Estimation of Risk
Advantages
– No model is assumed
– Information is directly applicable
Disadvantages
– Data is population specific
– Data only covers a small range of situations
– Large studies are needed for meaningful data
CASH data (Claus et.al. 1990)
• Kaplan-Meier estimates of cumulative risk
– By age of onset of breast cancer in 1o relative
• Hazard ratios for other family histories
– Sister and mother affected
– Two sisters affected
– One mother, 2 sisters
RR 5.9 (3.9-8.9)
RR 3.6 (2.1-6.1)
RR 17 (9.4-31)
Meta-Analysis
Pharoah et.al.1997
• Applicable to limited situations
–
–
–
–
Affected 1o relative
Mother and sister
Sister affected <50
Mother affected <50
RR 2.1 (2.0-2.2)
RR 3.6 (2.5-5.0)
RR 2.7 (2.4-3.2)
RR 2.0 (1.7-2.4)
Estimation of Risk Using Models
Advantages
– Data can be widened to a greater range of situations
Disadvantages
– Can generalise to situations where data is not applicable
– Risks are often based on a small number of data points
– Risks calculated are population specific
Modelling of Breast Cancer Risk
“Gail” Model (BCDDP data)
– Incorporates age at menarche, parity, and affected 1o relatives
– Curves given to estimate 10, 20 and 30 year risk
– No mode of inheritance assumed
CASH data model
– Using age of onset and first degree relative data only
– Segregation analysis suggests dominant major locus
– Give cumulative risk curves based on relatives and age of onset
Linkage/Computer Analysis
Likelihood of developing breast cancer
=
Likelihood of dominant mutation in family
+ Likelihood of carrying mutation
+ Likelihood of developing cancer if mutation carrier
(Mendel to determine LOD score, CASH data penetrance
figures/ current age)
Linkage/Computer Risk Analysis
• Advantages
– Generates a risk for a complex situation
• Uses age of onset
• Uses unaffected individuals
– Easy to apply
– Removes subjective element
• Disadvantages
– Assumes single dominantly inherited gene
– Assumes one set of penetrance values for a single gene
– Prone to “rubbish in, rubbish out” phenomena
– Essentially unvalidated
So Which is Best ?
20 Year Risk Comparison
Relative Risk
(Absrisk)
CASH
(Empirical)
GRAIL
Cyrillic 3
Situation
A (M+S)
13.7%
11%/21%*
8.5%
7.4%
Situation
B (3 relatives)
(12.6%)
(5.3%)
(4%)
8.1%
Situation
C (ov +Br)
-
14.4%
-
6.3%
Situation
D (Bilat. Br.)
9.7%/16.5
10%*
8.5%
10.3%
Situation
E (2X2o Br.)
6.7%
-
-
5.1%
Situation
F (Br/Ov)
-
14.4%
-
7.4%
Conclusions
• Different systems for risk estimation can
give different results.
• Empirical risk calculation systems can only
apply to well defined situations.
• Computerised risk assessment is based on
assumptions that are not necessarily valid.
Where do we start screening ?
Current Guidelines
• SIGN Guideline - 3 times population risk
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–
–
–
–
–
1o relative with bilateral breast cancer*
1o relative with breast cancer <40
1o male relative with breast cancer
1o relative with breast and ovarian
2 first or second degree relatives with breast cancer < 60
3 first or second degree relatives with breast cancer
Bilateral breast cancer in
o
1 relative
• 2-5% of breast cancer is bilateral
• CASH data (USA families)
– risk same as if unilaterally affected relative
• Tulinius et.al. 1992 (Icelandic families)
– RR 4.4* (3.39-6.49), RR 9 if first onset <45
• Houlston (British families, OPCS data)
– RR 4.78 (0.12 to 26.62) postmenopausal onset
– RR 7.78 (0.94 to 28.08) premenopausal onset
10 Year Risk Estimates
Relative
Risk
1
2
3
5
10
20
0.1
0.1
0.2
0.3
0.6
30
0.5
0.9
1.4
2.3
4.6
40
1.5
3.0
4.5
7.4
14
50
2.5
5.0
7.4
12
23
60
2.5
4.9
7.3
12
22
70
2.4
4.7
7.0
11
21
Age
Conclusions
• Setting the criteria for screening should depend on
– Estimation of absolute risk (age dependant)
– Effectiveness of screening (may be age specific)
– Resources available
– A sensible risk estimation system
Future Research
• Validation of risk estimation
– Detailed comparison of methods of risk analysis
– Application to pedigrees with known outcome
• (A retrospective-prospective study !)
Future Research
• Validation of screening protocols for high
risk individuals.
Future Research
(Long term)
• Audit of effectiveness of screening protocols
and accuracy of risks calculated.
• This will be greatly facilitated by an
effective computerised database.