BOP breast course Nov 2010
Biology of disease
Who is at risk for what type of breast cancer
and how does type affect outcome
Laura J. Van ‘t Veer
Helen Diller Family Comprehensive Cancer Center
University of California, San Francisco
Breast Cancer - Survival
Kaplan-Meier Survival Curves
Who gets what type of breast cancer?
Which breast cancers return?
Disease Biology
• Genetic make-up of individual
• Biology of screen-detected cancers and of interval
cancers
• Biology informs need for systemic treatment
- who is at risk for what type of disease
- does type affect outcome
- how can type of detection inform management
Who is at risk for what type of disease
Opportunities for prevention
Opportunities for management
Breast cancer susceptibility loci
rs number
Gene
Chromosome
MAF
Per allele
OR
P (trend
test)
rs1045485
CASP8
2q
0.13
0.88
1.1 x 10–7
rs2981582
FGFR2
10q
0.38
1.23
2.0 x 10–76
rs1219648
FGFR2
10q
0.39
Familial aggregation
of 1.32
breast cancer1.1 x 10–10
rs10941679 Multiple low-penetrance 5p12
rs3803662
alleles (polygenic model)
TNRC9
16q
5%(?) CHEK2 1100delC*
0.24
1.19
2.9 x 10–11
0.25
1.20
10–36
0.27
1.28 4.7% SNPs
5 x 10–19
rs13387042
2q34
25% BRCA1/2
0.50
1.20
1.3 x 10–13
rs13281615
8q24
0.40
1.08
5 x 10–12
MAP3K1
5p
0.28
1.13
7 x 10–20
LSP1
11p
0.30
1.07
3 x 10–9
rs889312
rs3817198
Recent breast cancer susceptibility loci - SNPs
rs number
Gene
Chromosome
MAF
Per allele
OR
P (trend
test)
rs1045485
CASP8
2q
0.13
0.88
1.1 x 10–7
rs2981582
FGFR2
10q
0.38
1.23
2.0 x 10–76
rs1219648
FGFR2
10q
0.39
1.32
1.1 x 10–10
5p12
0.24
1.19
2.9 x 10–11
16q
0.25
1.20
10–36
0.27
1.28
5 x 10–19
rs10941679
rs3803662
TNRC9
rs13387042
2q35
0.50
1.20
1.3 x 10–13
rs13281615
8q24
0.40
1.08
5 x 10–12
MAP3K1
5p
0.28
1.13
7 x 10–20
LSP1
11p
0.30
1.07
3 x 10–9
rs889312
rs3817198
Easton et al; Cox et al; Stacey et al; Hunter et al
Association of 10 susceptibility loci with tumor subtypes
ER+PR+Her2+
ER+PR+Her2-
Triple negative
negative
(prevents)
positive association
(increases)
Broeks et al, BCAC, submitted
Breast cancer outcome: Example rs3803662 in TNRC9
Second Breast Cancer Risk
in BOSOM breast
cancer series
Variant allele
(homozygous
carriers)
Adjusted HR (95% CI)
2.7 (1.7-4.3)
rs3803662 in TNRC9:
increase of contralateral
breast cancer risk
Ongoing:
Validation in BCAC
series (studies with
follow-up data)
Same analyses for other
breast cancer riskrelated SNPs
N total = 1370
Breast cancer outcome: MDM2 SNP309 *TP53 R72P
in BCAC breast
cancer series
MDM2 SNP309 (G = variant allele)
GG
TP53 R72P
‘wildtype’
GT
TT
SNP-SNP interaction effect on survival:
MDM2 SNP309 and TP53 R72P variants
combined: 7% worse survival (p<0.05)
TP53 R72P
‘variant allele’
also if adjusted for known prognostic
factors
N total =3739
Schmidt et al Cancer Res 2007
Breast cancer outcome: CHEK2 1100delC
CHEK2 1100del C carrier:
worse breast cancer
outcome
in BOSOM breast
cancer series
Contralateral breast cancer risk
HR (95%CI) 2.1 (1.0-4.3)
Treatment interaction?
Interaction with SNPs?
Tumor characteristics?
Ongoing data collection
and analyses in BOSOM
and pooled BCAC series
Recurrence-free survival
HR (95%CI) 1.7 (1.2-2.4)
Breast cancer-specific survival
HR (95%CI) 1.4 (1.0-2.1)
Schmidt et al. JCO 2007
Biology informs need of systemic treatment
Opportunities to reduce over- and undertreatment
Effect on morbidity
Breast Cancer - Survival
Kaplan-Meier Survival Curves
Which breast cancers return?
Of 100 women with breast cancer
(stage 1/2)
…………~25% will develop a recurrence
………..75% of all patients is treated
with chemotherapy
So, overall 50% of patients receive toxic chemotherapy
of which they do not benefit,
but may suffer the toxic side-effects
Can we do better?
Development of
70 gene
MammaPrint
Tumor samples of known
clinical outcome
Unbiased full genome
gene expression
analysis
Prognosis reporter genes
Distant metastases
group
No distant metastases
group
70 prognosis genes
Nature, 2002
Metastases: white=+
Tumor samples
b
Multi Gene Expression Profiles
in Clinical Practice
Clinical Utility MammaPrint
Prospective study implementing MammaPrint, 2003-2006
PIs Sabine Linn, Marc van de Vijver
Sponsor: Dutch Health Insurance Council
Bueno et al, Lancet Oncol, 2007, Knauer et al, SABCS 2008 #1084
Discordant cases MammaPrint signature versus
Guidelines The Netherlands and Adjuvant-on-line
~30 % discordant cases led in
~20% to adapted treatment advise
Bueno et al, Lancet Oncol, 2007, Knauer et al, SABCS 2008 #1084
Biology of screen detected cancers
Method of detection may inform management
US general population screening data from SEER 1973-2005
Age-adjusted incidence breast cancer by Stage at diagnosis
-> Screening era
Localized
Regional
In Situ
Distant
70 Gene Prognosis Signature
Supervised analysis on n=78 tumors, >96% adjuvantly untreated
70 significant prognosis genes
Tumor samples
ultra-low
threshold 2
van´t Veer et al., Nature 415, p. 530-536, 2002
Nature, (2002)
threshold set with 0% false negatives
Biology of Screen-detected Cancers
Age 49-60
0.7
30%
MammaPrint
0.6
0.5
0.4
12%
Pre-screening
0.3
Screened RASTER
0.2
0.1
0
High
Medium-low
Ultra-low
P<0.001
 Screen detected cancers show increase in ultra-low risk cancers
Pre-screening n=143, sreen-detected n=73