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Estimating the penetrances of breast and Estimating the penetrances of breast and ovarian cancer in the carriers of ovarian cancer in the carriers of
BRCA1/2 mutationsBRCA1/2 mutations
Silvano PresciuttiniSilvano PresciuttiniUniversity of Pisa, ItalyUniversity of Pisa, Italy
• Accurate estimates of breast and ovarian cancer penetrance in BRCA1/2 mutation carriers are crucial in genetic counseling.
• We estimated the penetrances of breast and ovarian cancers in carriers of BRCA1/2 mutations in 568 Italian families screened for germline mutations.
• Our approach could lead to country-customized versions of the BRCAPRO software by providing appropriate population-specific estimates.
Content of the presentationIntroduction:
1) Hereditary cancer2) BRCA1 and BRCA2
The problem:1) Predicting the presence of a germline mutation in a proband2) Performances of extant predictive models
How to improve predictions1) Our results2) Comparison with previous penetrance estimates3) Consequences at the population level
Sporadic vs hereditary tumorsIn most cases, cancer-causing mutations in somatic cells occur by chance, or as a result In most cases, cancer-causing mutations in somatic cells occur by chance, or as a result of damage to DNA by environmental factors such as chemicals in cigarette smoke, or of damage to DNA by environmental factors such as chemicals in cigarette smoke, or UV radiation in sunlight. Cancer in these cases is said to be UV radiation in sunlight. Cancer in these cases is said to be sporadicsporadic..
However, a small percentage However, a small percentage of cancers of cancers arise in families that show a very strong, arise in families that show a very strong, hereditary susceptibilityhereditary susceptibility to a particular to a particular type of cancer.type of cancer.The cancer-susceptibility in these The cancer-susceptibility in these families is usually families is usually highly penetranthighly penetrant.. Affected individuals in these families Affected individuals in these families carry a germ-line (i.e. inherited) mutation carry a germ-line (i.e. inherited) mutation - which is therefore present in every cell - which is therefore present in every cell of their body - that makes it much more of their body - that makes it much more likely that their somatic cells will likely that their somatic cells will become cancerous.become cancerous.
BRCA1 and BRCA2 Mutations in the two genes Mutations in the two genes BRCA1 BRCA1 andand BRCA2 BRCA2 account account
for 30–40% of the familiesfor 30–40% of the families with multiple breast cancer with multiple breast cancer cases and for the vast majority ofcases and for the vast majority of families with multiple families with multiple breast and ovarian cancers cases.breast and ovarian cancers cases.
Taken together, these genesTaken together, these genes may be responsible for 5–may be responsible for 5–10% of10% of early-onset breast cancers and about 10% of all early-onset breast cancers and about 10% of all ovarianovarian cancers.cancers.
Initial studies of multiple-case families with four or moreInitial studies of multiple-case families with four or more cancer cases suggested that the lifetime risk cancer cases suggested that the lifetime risk (penetrance) (penetrance) of breast cancerof breast cancer in in BRCA1 BRCA1 mutation mutation carriers was 71–85%, and that ofcarriers was 71–85%, and that of ovarian cancer was ovarian cancer was 42–63% at age 70.42–63% at age 70.
Similarly, earlySimilarly, early penetrancepenetrance evaluations in evaluations in BRCA2 BRCA2 led to led to an 84% risk ofan 84% risk of breast cancer and 27% for ovarian breast cancer and 27% for ovarian cancer at age 70.cancer at age 70.
How can the presence of a germline mutation predicted in a proband?
In other words, the questions are:1.Given a proband, what is the probability that a mutation in BRCA1/2 is present? 2.What is the chance of the DNA laboratory finding a mutation?
A rather complicated problem...
General population
Affectedindividuals
5%
Non-affectedsubjects
95%
Geneticcases
10%
Sporadiccases
90%
}“simplex” families:genetic 2.5%sporadic 82.1%
“duplex”families:genetic 5.0%sporadic 7.7%
}“multiplex” families:genetic 2.5%sporadic 0.2%
}Total families 100.0%
Affectedindividuals
A substantial proportion (60%) of familial cases are “sporadic”
A minority only (1/4) of all genetic cases are selected through stringent criteria
A significant proportion (3%) of non-familial cases are genetic
Next generationGeneral population
Affectedindividuals
5%
Non-affectedsubjects
95%
Geneticcases
10%
Sporadiccases
90%
}“simplex” families:genetic 2.5%sporadic 82.1%
“duplex”families:genetic 5.0%sporadic 7.7%
}“multiplex” families:genetic 2.5%sporadic 0.2%
}
“simplex” families:genetic 2.5%sporadic 82.1%
“duplex”families:genetic 5.0%sporadic 7.7%
}“multiplex” families:genetic 2.5%sporadic 0.2%
}Total families 100.0%
Affectedindividuals
A substantial proportion (60%) of familial cases are “sporadic”
A minority only (1/4) of all genetic cases are selected through stringent criteria
A significant proportion (3%) of non-familial cases are genetic
Next generation
Two well-known predictive models
TThe he MyriadMyriad mutationmutation prevalence tablesprevalence tables display the proportion of probands, stratified display the proportion of probands, stratified in 42 possiblein 42 possible groups, with identified groups, with identified mutations in BRCA1 ormutations in BRCA1 or BRCA2 in theBRCA2 in the analyses analyses performed at Myriadperformed at Myriad,, which include more which include more than 10than 10,,000 tests000 tests
BRCAPROBRCAPRO is a Mendelian model that is a Mendelian model that incorporates mutated allele frequencies and incorporates mutated allele frequencies and cancer specificcancer specific penetrances derived from penetrances derived from published published studiesstudies and uses and uses Bayesian updating Bayesian updating methods to compute carrier probabilitiesmethods to compute carrier probabilities in in pedigreespedigrees
Evaluating model performances
BRCAPRO:(sensitivity of molecular techniques set to 70%)
Myriad Tables:
Probability (mut+)
Total no. of families analyzed
Total no. of mutations
identified
Predicted no. of
mutations <20% 194 25 6.5
20-40% 36 10 7.5 40-60% 29 7 10.0 60-80% 22 10 10.5 >80% 50 29 32.3 Total 331 81 66.8
Probability (mut+)
Total no. of families analyzed
Total no. of mutations
identified
Predicted no. of
mutations <15% 188 28 14.8
15-20% 68 17 13.1 20-30% 17 5 4.1 30-40% 27 13 9.7 >40% 31 18 16.2 Total 331 81 57.8
Including five other models in the analysis
0
0.1
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0.4
0.5
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0.7
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
Expected proportion of mutations
Ob
se
rve
d p
rop
ort
ion
of
mu
tati
on
s
BRCAPRO
Finnish model
ICHBOC
Myriad-1
Myriad Tables
Penn model
Spanish model
For each model, For each model, pprobands were robands were stratified by risk in stratified by risk in three groups: <10%, three groups: <10%, 10-40%, and >40%10-40%, and >40%
The figure shows, for The figure shows, for each model, a plot of each model, a plot of the proportion of the proportion of expected expected vsvs observed observed proportion of proportion of mutations mutations in the three groups.in the three groups.
All models show a All models show a similar pattern, similar pattern, underestimating underestimating mutation detection mutation detection probability at lower probability at lower risks (<10%), and risks (<10%), and overestimating overestimating it it at at higher risks. higher risks.
How to improve predictions We estimated cancer- and gene-specific penetrances in a We estimated cancer- and gene-specific penetrances in a
large sample of Italian families (568) screened for both large sample of Italian families (568) screened for both genes, 83 harboring a BRCA1 mutation, and 50 a BRCA2 genes, 83 harboring a BRCA1 mutation, and 50 a BRCA2 mutation.mutation.
We used the software BRCAPRO as a probability We used the software BRCAPRO as a probability calculation tool. Since the prediction made by this calculation tool. Since the prediction made by this program is based on a specific genetic model (the set of program is based on a specific genetic model (the set of parameter values, allele frequencies and penetrances that parameter values, allele frequencies and penetrances that define the risk of disease in the population), it is possible define the risk of disease in the population), it is possible to reverse the approach, that is, estimating some of the to reverse the approach, that is, estimating some of the parameters from the family data.parameters from the family data.
This is accomplished by iteratively exploring new This is accomplished by iteratively exploring new parameter values until the best genetic model is found, for parameter values until the best genetic model is found, for which the prediction made by BRCAPRO is more accurate. which the prediction made by BRCAPRO is more accurate.
STUDY DESIGNSTUDY DESIGN
GENETIC MODEL
Stop when convergencecriteria are met
Individual prediction for all families
Calculationof totallog-likelihood
Explore new Parameter values
MODIFIED MODEL
Re-calculationof totallog-likelihood
Comparelog-likelihoods
Accept/Reject modifiedmodel
The new penetrance curves
Performance of the modified model
Observed and expected number of mutations inObserved and expected number of mutations in the the families stratified by cancer profile, consideringfamilies stratified by cancer profile, considering BRCA1 and BRCA2 togetherBRCA1 and BRCA2 togetherHBC: hereditary breast cancer. HBOC: hereditary breast-HBC: hereditary breast cancer. HBOC: hereditary breast-ovarianovarian cancer. HOC: hereditary ovarian cancer. MBC: male cancer. HOC: hereditary ovarian cancer. MBC: male breast cancer.breast cancer.
Risk of disease for women with BRCA1 or BRCA2 mutations
Cancer Cancer specific specific penetrances penetrances translate into translate into cumulative cumulative risks of being risks of being affected by affected by either diseaseeither disease0
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0.7
20 30 40 50 60 70 80
Age
Pro
po
rtio
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wo
men
aff
ecte
d f
rom
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reas
t o
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vari
an c
ance
r at
ag
e x
BRCA1
BRCA2
Proportion of breast cancers occurring in carriers
The fraction of The fraction of breast cancers breast cancers occurring in occurring in gene carriers gene carriers can be can be computed computed either by five-either by five-year intervals year intervals or as or as cumulative cumulative proportionproportion
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20 30 40 50 60 70 80
Age
Pro
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f g
enet
ic c
ases
Age-specif icfraction
Cumulativefraction
Conclusions
Our new penetrance functions are appropriate Our new penetrance functions are appropriate for predicting breast cancer risk, and forfor predicting breast cancer risk, and for determining the probability of carrying determining the probability of carrying BRCA1/2 BRCA1/2 mutations, in people who are mutations, in people who are presently referred topresently referred to genetic counseling in genetic counseling in Italy.Italy.
Our approach could lead to country-customized Our approach could lead to country-customized versions of the BRCAPROversions of the BRCAPRO software by providing software by providing appropriate population-specific estimates.appropriate population-specific estimates.