Genetics and Risk of Breast Cancer

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Genetics and Risk of Breast Cancer

• What is the Evidence

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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

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What is the likelihood of finding a mutation ?
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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

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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.

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Determining Probability of Being a Gene Carrier

• Empirical data
• Logistic Regression Analysis
• Bayes calculation

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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).

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Peto et.al. 1999

• BRCA1 and BRCA2 Mutation Analysis
• Status Mutation detected
• BRCA1 BRCA2
• Affected lt 35 9/254 6/254
• Affected 36-45 7/363 8/363
• Affected lt45, mother breast cancer 2/54
  1/54
• Affected lt45, 1o with breast CAlt60 3/52
  1/52
• Affected lt45, 1o with ovarian CA 3/5 0/5
• Affected 36-45, 2X 1o with breast lt60 1/8
  3/8

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Schattuck Eidens et.al. 1997

• BRCA1 and BRCA2 Mutation Analysis
• Status Mutation detected
• BRCA1 BRCA2
• Affected lt 35 5
• Affected 36 - 45 1-2
• Affected lt45, mother breast cancer 2
• Affected lt45, 1o with breast CAlt60 2
• Affected lt45, 1o with ovarian CA 6
• Affected 35, 1o relative with breast
  ovarian 20
• Affected 35, Bilateral Breast Cancer 20

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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

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CASH data Ford data
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Likelihood of identifying a mutation

• BRCA1 and BRCA2 Mutation Detection
• Status Cyrillic Peto
• (BRCAPro)
• BRCA1 BRCA2 BRCA1 BRCA2
• Affected lt 35 2 0.3 4 2
• Affected lt45, 1o with breast CAlt60 4 2 6 2
• Affected lt45, 1o with ovarian CA 22 1.6 60 0
• Affected lt45 2X1o relative with breast
  lt60 21 10 13 38

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Population Specific Mutations

• Ashkenazi Jewish Population Over 2 of population
• BRCA1 185delAG
• 5382insC
• BRCA2 6174delT
• Icelandic population 0.6 of population
• BRCA2 999del5

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Mutation Detection with Askenazi Jewish descent

• Lalloo et.al. 1998
• Breast cancer lt60 1/4
• 2 X Breast cancer lt70 3/10
• BCLC criteria 5/5
• Schattuck-Eidens et.al. 1997
• Affected age 40 12
• Affected at 40 1o relative breast 20
• Affected at 40 1o relative ovarian 35

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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

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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 ltage 45 with 1o ovarian cancer

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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.

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Conclusions

• Testing for the common Ashkenazi Jewish mutations
  may be relevant,
• In the presence of modest family history.
• with isolated young onset disease.

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What is the Risk to Mutation Carriers ?
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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

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Risk To Mutation Carriers ()

• Easton et.al. Ford et.al.
  Struewing Steinum ISD
• BRCA1 BRCA2 BRCA12 BRCA2
  (Population)
• Br Ov Br Ov Br Ov Br
  Ov Br O v
• By age 40 19 0.6 12 0.0 -
  - - - - -
• By age 50 50 22 28 0.4 33 7
  15 - - -
• By age 60 54 30 48 7.4 -
  - - - - -
• By age 65 - - - -
  - - - - 5.5 0.9
• By age 70 85 63 84 27 56 16
  35 - - -
• By age 75 - - - -
  - - - - 7.9
  1.5

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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.

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Modifying Risk to Gene Carriers
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Modifying Risk

• Screening Breast examination
• Mammography
• Ovarian Ultrasound
• Hormonal Manipulation Tamoxifen
• Surgical Intervention Mastectomy
• Oophorectomy

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Screening / Mammography

• Proven benefit when age gt 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

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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
• 1259 women with a lifetime risk of breast cancer
  gt 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

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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

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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.

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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.)

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Conclusions

• The benefits of prophylactic tamoxifen remain
  unproven.
• Family history of breast cancer is not
  necessarily a contraindication for HRT.
• More studies are needed

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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.

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Conclusions

• Screening of high risk patients can be effective
  in detecting breast cancer.
• Overall benefit of screening remains to be
  demonstrated.

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Presenting Risk
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Lifetime Absolute Risk

• Your lifetime risk of dying is 100

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Relative Risk

• Your Risk of dying is 1X that of the population

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Absolute Risk over Time

• Your risk of dying over the next 10 years is
• 2

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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)

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How Can Risk be Estimated from Family History ?
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Risk Analysis - Situation A

• Mother and Sister Affected with Breast Cancer

60
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Risk Analysis - Situation B

• Three Relatives Affected with Breast Cancer

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Risk Analysis - Situation C

• Mother Affected with Ovarian Cancer and Sister
  with Breast Cancer

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Risk Analysis - Situation D

• Mother affected with bilateral breast cancer

40/55
40
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Risk Analysis - Situation E

• Two second degree relatives with breast cancer lt
  age 60

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Risk Analysis - Situation F

• Mother affected with breast cancer age 45 and
  ovarian age 65

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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 2,852 cases of breast cancer
• Linkage/Computer Analysis
• Cyrillic (Uses CASH data)

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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

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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 RR 5.9 (3.9-8.9)
• Two sisters affected RR 3.6 (2.1-6.1)
• One mother, 2 sisters RR 17 (9.4-31)

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Meta-AnalysisPharoah et.al.1997

• Applicable to limited situations
• Affected 1o relative RR 2.1 (2.0-2.2)
• Mother and sister RR 3.6 (2.5-5.0)
• Sister affected lt50 RR 2.7 (2.4-3.2)
• Mother affected lt50 RR 2.0 (1.7-2.4)

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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

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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

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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)

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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

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So Which is Best ?
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20 Year Risk Comparison
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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.

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Where do we start screening ?
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Current Guidelines

• SIGN Guideline - 3 times population risk
• 1o relative with bilateral breast cancer
• 1o relative with breast cancer lt40
• 1o male relative with breast cancer
• 1o relative with breast and ovarian
• 2 first or second degree relatives with breast
  cancer lt 60
• 3 first or second degree relatives with breast
  cancer

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Bilateral breast cancer in 1o 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 lt45
• 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

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10 Year Risk Estimates
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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

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Future Research

• Validation of risk estimation
• Detailed comparison of methods of risk analysis
• Application to pedigrees with known outcome
• (A retrospective-prospective study !)

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Future Research

• Validation of screening protocols for high risk
  individuals.

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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.