Download 18.30 Modern classification of breast cancer

Molecular Pathology of Breast Cancer
Ian Ellis
Molecular Medical Sciences, University of Nottingham
Departments of Histopathology, Nottingham City Hospital NHS Trust
Time
Prognosis
Intrinsic
Time
Prognosis
How long the
tumour has been
there
Stage
Intrinsic
The nature of
the tumour
Biology
Nottingham Prognostic Index
Grade + LN Stage + (0.2 x Size)
1-3
1-3
cm
Nottingham Prognostic Index
100
Age matched
% Survival
80
GPG
(2.1=3.4)
60
MPG
(3.41-5.4)
40
20
PPG
(>5.4)
0
0
635
1040
316
2
4
6
237
357
39
8
10
12
14
46
63
7
GPG
MPG
PPG
16
18
Years
Histological Grade in Breast Carcinoma
Consistency and Reproducibility
Poor
Cutler et al
1966
Stenkvist et al
1979
Delides et al
1980
Gilchrist et al
1985
Histological Grade
in Breast Cancer
Tubule formation
Majority of tumour
Moderate degree
Little or none
(>75%)
(10-75%)
(<10%)
Nuclear pleomorphism
Small, regular uniform cells
Moderate increase in size and
variability
Marked variation
Mitotic counts
Dependent on microscope field area
- 1 point
- 2 points
- 3 points
- 1 point
- 2 points
- 3 points
1 - 3 points
Histological Grade
Microscope
Leitz
Nikon
Ortholux
Labophot
X25
X40
Objective
Field diameter
Field area
0.44 mm
0.63 mm
0.274 mm2 0.152 mm2 0.312 mm2
1 point
Count*
0.59 mm
Leitz
Diaplan
X40
0-9
0-5
0-11
2 points
10-19
6-10
12-22
3 points
>20
>11
>23
* Assessed as number of mitoses per 10 fields at the tumour periphery
Nottingham Method for
Histological Grade in Breast
Carcinoma
Consistency and Reproducibility
Satisfactory
Dalton et al
1984
Frierson et al
1985
Robbins et al
1995
Nottingham Method for
Histological Grade in Breast
Carcinoma
Recommended by:
RCPath
NHSBSP
EU
AJCC
UICC
WHO
Cox Multivariate
Analysis
Size
Grade
Tumour type
LN Stage
Vascular Invasion
???
0.19
0.64
0.29
0.76
0.18
Z values > 1.96 significant at p=0.05 level
Z
4.86
6.69
3.47
11.18
3.18
Cum. Survival
N P I
1
.8
EPG
GPG
.6
MPG I
MPG II
.4
.2
PPG
Chi-Square
899.005
DF P-Value
4 <.0001
0
0
48
96
144
192
240
288
Time
Traditional Prognostic
Factors
•
•
•
•
•
Histological grade
Histological type
Lymph node stage
Tumour size
Vascular invasion
Cox Multivariate Analysis
Size
Grade
LN Stage
Tumour type
Vascular Invasion
ER
C-erb-B2
DNA Index
Proliferation Index
?
0.17
0.86
0.81
0.31
0.19
0.001
0.02
0.28
0.17
Z values > 1.96 significant at p=0.05 level
?Z
2.93
5.64
6.96
1.46
1.78
1.21
0.11
1.27
1.26
Cox Multivariate Analysis
Size
Grade
LN Stage
Tumour type
Vascular Invasion
ER
C-erb-B2
DNA Index
Proliferation Index
?
0.17
0.86
0.81
0.31
0.19
0.001
0.02
0.28
0.17
Z values > 1.96 significant at p=0.05 level
?Z
2.93
5.64
6.96
1.46
1.78
1.21
0.11
1.27
1.26
Prognostic Factors
but eliminated by multivariate analysis
Receptors & related
ER
PR
Bcl-2
Liv-1
PS2
Cap D
Histological
Angiogenesis
LVI
Type
Nucleolar Organisers
Cell Antigens
Lectins
CEA
Epithelial memb. Ag
Growth Factors
EGFR
Cerb-B2/3&4
Proliferation Markers
Mib1
Ki67
TK
S-Phase
Oncogenes
C-myc
Suppressor genes
P53
Adhesion molecules
E-Cadherin
Catenins
Integrins
Cell Antigens
Do we really need prognostic
factors for breast carcinoma?
There are at least three situations in which
prognostic factors could be helpful
• To identify patients whose prognosis is so good that adjuvant
therapy after local surgery would not be cost beneficial
•
To identify patients whose prognosis is so poor that a more
aggressive adjuvant approach would be warranted
•
To identify patients likely to be responsive or resistant to
particular forms of therapy
Clark GM. Breast Cancer Res Treat. 1994;30:117-26
Cum. Survival
N P I
1
.8
EPG
GPG
.6
MPG I
MPG II
.4
.2
PPG
Chi-Square
899.005
DF P-Value
4 <.0001
0
0
48
96
144
192
240
288
Time
Do we really need prognostic
factors for breast carcinoma?
There are at least three situations in which
prognostic factors could be helpful
• To identify patients whose prognosis is so good that adjuvant
therapy after local surgery would not be cost beneficial
•
To identify patients whose prognosis is so poor that a more
aggressive adjuvant approach would be warranted
•
To identify patients likely to be responsive or resistant to
particular forms of therapy
Clark GM. Breast Cancer Res Treat. 1994;30:117-26
Prognostic Factor:
Altered natural history
Predictive Factor:
Resistance or sensitivity to therapy
ER Immunohistology
Cut off points for treatment
Score
treatment
Effect of Endocrine
0
2–3
4–6
7–8
No effect
Small (20%) chance
Even (50%) chance
Good (75%) chance
Leake et al. J Clin Path 2000; 53: 634-635
Herceptin
®
humanised anti-HER2 monoclonal
antibody
EGFR / HER2 signalling
Membrane
p21ras
P
Raf
P
p38 MAPK
pp90rsk
Mek
Nucleus
E2/Tam
ER ER
P
P
AIB1 CBP
Hormone-dependent growth
MAPK
c-jun c-fos
Cell proliferation
Prognostic Factors
but eliminated by multivariate analysis
Receptors & related
ER
PR
Bcl-2
Liv-1
PS2
Cap D
Histological
Angiogenesis
LVI
Type
Nucleolar Organisers
Cell Antigens
Lectins
CEA
Epithelial memb. Ag
Growth Factors
EGFR
Cerb-B2/3&4
Proliferation Markers
Mib1
Ki67
TK
S-Phase
Oncogenes
C-myc
Suppressor genes
P53
Adhesion molecules
E-Cadherin
Catenins
Integrins
Cell Antigens
Improved knowledge of
cancer biology
?
New therapy targets
Time
Prognosis
How long the
tumour has been
there
No
Intrinsic
The nature of
the tumour
Yes
Cum. Survival
N P I
1
.8
EPG
GPG
.6
MPG I
.4
MPG II
.2
Chi-Square
899.005
DF P-Value
4 <.0001
PPG
0
0
48
96
144
192
240
288
Time
ER neg
ER pos
Sorlie, et
al.
PNAS 2001
Subtypes and Prognosis
SURVIVAL
DISEASE-FREE SURVIVAL
Sorlie T et al, PNAS 2001
cDNA expression patterns
• Gene expression patterns of breast cancer
• Patterns in two tumour samples from the
same individuals were always more similar to
each other than either was to any other
sample
? i) (Either) tumour is very homogenous,
? ii) (Or) Most of gene expression relates to
a person’s DNA rather than the tumours
• Patterns distinguish subclasses
• Subclasses carry clinical implications
Perou et al, Nature; 2000: 747-752
Sorlie et al PNAS 2001: 10868 - 74
cDNA expression patterns
• Patterns distinguish subclasses
• Subclasses carry clinical implications
Perou et al, Nature; 2000: 747-752
Sorlie et al PNAS 2001: 10868 - 74
Breast Cancer is a Family
of Diseases
• Convergence of clinical and genomic data
• Unclear how many distinct members of this
family
• At a minimum:
–
–
–
–
HER-2 +
Basal-like or triple negative
ER + (luminal A)
ER + (luminal B)
“Basal-like”
HER2-positive
ER/PR-negative
HER2-negative
ER-positive
Luminal B
ER-positive
Luminal A
Luminal / ER positive/ basal negative group [group 1]
Basal positive luminal /ER negative [group 5]
Choice of Markers
1- involved in breast carcinogenesis
Predisposing
genes
Normal breast
Hormones & their receptors
Cell proliferation
Atypical cell proliferation
Growth factors
Genetic alterations
Oncogenes
Tumour suppressor genes
Carcinoma insitu
Cell adhesion
molecules
Invasive carcinoma
2- cDNA microarray studies
3- Have prognostic and predictive power
4- Related to tumor histogenesis and cellular lineage evolution
5- Related to special morphological types
24 well characterized tumor markers selected
Luminal and basal differentiation [ck 7/8, 18, 19, 5/6, 14, actin and p63],
Hormone receptors markers [ER, PgR and AR],
EGFR family markers [EGFR, c-erbB-2, c-erbB-3 and c-erbB-4],
Tumor suppressor gene products [p53, BRCA1 and Fhit],
Adhesion molecule markers [E-cad and P-cad],
Mucins muc 1, muc 2,
Neuroendocrine differentiation chromogranin and synaptophysin
Apocrine differentiation GCDFP-15.
Results
Six groups Have been identified
1
2
3
4
Cluster Tree [Dendrogram]
5
6
Groups 1 & 2
336 (31.2%)
180 (16.7%)
Luminal epithelial markers, MUC1 and hormone receptor positive
HER2 and p53 negative
Differences in c-erbB-3, c-erbB-4 and BRCA1 expression
Group 3
234 (21.7%)
Luminal epithelial markers, MUC1 and HER2 positive
Hormone receptor E Cadherin negative or weakly expressing
Group 4
4 (0.4%)
BRCA1, p53 EGFR and P-cadherin positive
Hormone receptor negative
Group 5
183 (17%)
p53 protein, basal epithelial markers positive
Luminal epithelial marker, hormone receptor expression, HER2
and BRCA1 low or negative.
Group 6
139 (12.9%)
Luminal epithelial markers, HER2, E Cadherin positive
Hormone receptor, MUC1 negative or weakly expressing
El-Rehim et al Int. J Cancer 2005;116: 340 -350
Groups 1 & 2
336 (31.2%)
180 (16.7%)
Luminal epithelial markers, MUC1 and hormone receptor positive
HER2 and p53 negative
Differences in c-erbB-3, c-erbB-4 and BRCA1 expression
Group 3
234 (21.7%)
Luminal epithelial markers, MUC1 and HER2 positive
Hormone receptor E Cadherin negative or weakly expressing
Group 4
4 (0.4%)
BRCA1, p53 EGFR and P-cadherin positive
Hormone receptor negative
Group 5
183 (17%)
p53 protein, basal epithelial markers positive
Luminal epithelial marker, hormone receptor expression, HER2
and BRCA1 low or negative.
Group 6
139 (12.9%)
Luminal epithelial markers, HER2, E Cadherin positive
Hormone receptor, MUC1 negative or weakly expressing
El-Rehim et al Int. J Cancer 2005;116: 340 -350
Relationship with histological grade
400
300
200
No of cases
GRADE
100
3.00
2.00
0
1.00
p6
ou
Gr
p5
ou
Gr
p4
ou
Gr
p3
ou
Gr
P<0.001
p2
ou
Gr
p1
ou
Gr
GROUP
Group distribution among different tumour types
700
GROUP
No of cases
600
500
6.00
400
5.00
300
4.00
200
3.00
100
2.00
0
1.00
us
eo
an
all
lty
sc
cia
Mi
pe
&s
ST
dN
typ
ial
ixe
M
ec
sp
on
m
m
co
Un
lar
bu
Lo
d
ixe
m
T
NS
y
ar
ul
ed
M
lar
bu
Tu
ive
as
Inv
Histological tumour types
Highly significant association with
patient outcome
1.0
G4 n=4
G1 n=328
G2 n=180
.9
G6 n=138
G3 n=231
Probability
.8
G5 n=177
.7
0
20
40
Survival in months
Log Rank p<0.0001
60
80
100
120
140
160
Conclusions
Distinct sub classes of breast cancer can be identified
by expression of proteins of known relevance in breast
cancer
These sub classes are comparable to those identified by
cDNA expression array technology
Conclusions
Molecular classification of breast cancer based on
protein expression potentially offers further refinement
of traditional methods of classification
A modern clinically relevant breast cancer classification
based on molecular genetic, phenotypic and
morphological characteristics appears realistic
Breast Cancer Classes
Luminal classes
Class 1
Class 2
Class 6
n=202
n=153
n=80
Discriminators
Luminal cytokeratins
ER and PgR
HER3 and HER4
Muc1
HER2 class
Class 3
n=77
Discriminators
HER2
ER/PgR
Basal classes
Class 4
Class 5
n=82
n=69
Discriminators
Basal cytokeratins
ER, PgR, HER2
p53
Significant associations with pathology
Luminal tumour classes
Class 1 and 2: good prognostic factors including smaller
tumour size, grade 1 tumours, node-negative and tubular
mixed carcinomas
Class 6: Poorer prognostic factors such as larger tumour size,
higher stage and grade.
Basal tumour classes
Poor prognostic factors including grade 3 tumours, larger size,
higher stage, ductal NST and medullary carcinomas.
Class 4 patients (altered p53) younger than Class 5 patients
(normal p53)
Breast Cancer Specific Survival
Luminal classes
Basal classes
p<0.001
HER2 class
p<0.001
Highly significant association with patient outcome
Nottingham Prognostic Index
Class divisions are providing additional information to NPI
Breast Cancer Phenotypic
Classes
Breast
Cancer
Luminal CKs+
ER+
HER2+
ER-
Basal CKs+
ER-
Luminal
HER2
Class
HER23
Basal
HER3HER4-
HER3+
HER4+
PgR+
PgR+
PgR-
Class 2
Luminal
N
Class 1
Luminal
A
Class 6
Luminal
B
Mixed Class
p53+
p53-
Class 4
Basal –
p53 altered
Class 5
Basal –
p53 normal
Classes of Breast
Cancer
• Gene & protein expression patterns of
breast cancers similar
• Patterns distinguish subclasses
• Subclasses carry clinical implications
Complex epithelium
Expression markers
Simple epithelial CKs:
Superficial cells
Basal cells
CK7, CK8, CK18 and CK19
Basal / high molecular weight CKs:
CK5 and CK14
Cell type
marker
Luminal cells
CK7, CK8, CK18, and CK19, MUC1
alpha-6 intergrin and EP CAM
Myoepithelial cells
basal CKs + SMA, SM myosin
heavy chain, calponin, caldesmon,
p63, CD10, maspin, 14-3-3sigma
and S100
Basal cells
CK5, CK14, CK17
? Stem cells
CK5 without CK8 / CK18 or SMA
Luminal Subtypes
• Luminal A/B – generally carry a good prognosis (1)
• Luminal A better prognosis than B (1)
• Is this in part due to better response to ET in luminal
A cf B
• Expect better response to ET in luminal subtypes
• Poorer response (pCR) to Anthracycline &/or Taxane
chemotherapy (2)
• Recurrence score - Multi gene predictor of distant
relapse in ER(+) LN(-)ve Txs treated with tamoxifen(3)
(1)
Sorlie et al PNAS 2003: 100: 8418 – 23,
(2)
Rouzier et al Human Cancer Biology 2005; 11: 5678-85 ,
(3)
Paik et al NEJM 2004; 23: Abstr 512
Luminal Subtypes
• Luminal A/B – generally carry a good
prognosis (1)
• Luminal A better prognosis than B (1)
• Expect better response to ET in luminal
subtypes
(1)
Sorlie et al PNAS 2003: 100: 8418 – 23,
(2)
Rouzier et al Human Cancer Biology 2005; 11: 5678-85 ,
Luminal Subtypes
Questions
• Do patients with luminal A tumours need
chemotherapy ?
• Do luminal B tumours respond to tamoxifen ?
• Should patients with luminal B tumours receive an
AI ?
These seem familiar questions related to ER & PgR !
Will arrays provide a better answer ?
A Multigene Assay to
Predict Recurrence of
Tamoxifen -Treated,
Node - Negative Breast Cancer
• NSABP B-14 trial - node-negative, tamoxifen-treated
• 675 cases (668 assessable) paraffin-embedded tumor
tissue
• RT-PCR assay of 21 genes (16 cancer related & 5 ref
genes
• End point - distant recurrence
• Prospectively defined algorithm to determine risk
groups (low, intermediate, or high)
S Paik et al N Engl J Med 2004;351:2817-26.
21 Genes Panel (Oncotype)
Estrogen
ER
PGR
BCL2
SCUBE2
HER2
GRB7
HER2
Proliferation
Ki67
STK15
Survivin
CCNB1 (cyclin
B1)
MYBL2
BAG1
GSTM1
CD68
Invasion
MMP11 (stromolysin 3)
CTSL2 (cathepsin L2)
Reference
ACTB (b-actin)
GAPDH
RPLPO
GUS
TFRC
S Paik et al N Engl J Med 2004;351:2817-26.
A Multigene Assay to Predict
Recurrence of
Tamoxifen-Treated, NodeNegative Breast Cancer
Distant recurrence at 10 years
low
Int
high
(51% cases)
(22% cases)
(27% cases)
6.8%
14.3%
30.5%
(4.0 - 9.6)
(8.3 - 20.3)
(23.6 - 37.4)
•Low-risk group v high-risk group (P<0.001).
•Multivariate - independent of age and tumor size
•Predictive of overall survival (P<0.001)
•Can use as a continuous function to predict distant recurrence in individual
patients.
S Paik et al N Engl J Med 2004;351:2817-26.
DCIS
Allelic imbalance analysis suggests that low grade &
high grade carcinomas follow different genetic
pathways
Roylance et al. J Pathol 2002; 196:32-36
?Common
Precursor
Other candidates:
E Cadherin
Lobular Carcinoma
LOH 16q
Low Grade Carcinoma
C-erbB-2
& p53
High Grade Carcinoma
BRCA 1 17q
BRCA 2 13q
1q 3p 11q 13q 17q
Medullary
Tub & Lob
Tubular
E Cadherin
?Common
Precursor
Lobular Carcinoma
Lobular
Ductal
LOH 16q
Low Grade Carcinoma
C-erbB-2
& p53
High Grade Carcinoma
E Cadherin
Lobular Carcinoma
16q
?Common
Precursor
LOH 16q
Low Grade Carcinoma
C-erbB-2
& p53
High Grade Carcinoma
17q
Class 1
E Cadherin
Lobular Carcinoma
16q
?Common
Precursor
LOH 16q
Low Grade Carcinoma
Class 2
C-erbB-2
& p53
High Grade Carcinoma
17q
Luminal Type A lesions
•Luminal ck
•ER rich
•HER2 neg
•16q del
CCLs
Low Grade
DCIS
LN
LOW GRADE
NEOPLASIA FAMILY
TUBULAR
TUBULOLOBULAR
ILC
Complex epithelium
Expression markers
Simple epithelial CKs:
Superficial cells
Basal cells
CK7, CK8, CK18 and CK19
Basal / high molecular weight CKs:
CK5 and CK14
Basal Breast Cancer
• The concept of BP has been known for some
time
• First described using electron microscopy
>30 years age
• Its potential poor survival first reported by
Dairkee et al in 1987
Recently, topical following:
- Its recognition as the worst prognostic group in the
high profile cDNA expression analysis
- High frequency in BRCA1 gene mutation carriers
However, previous studies:
- Have not focused on routine identification of the BP
- Were not of sufficient size to examine its clinical
relevance
- Dissimilar results in the different subgroups
For example:
All: Independent marker of poor prog in BC as a whole
- van de Rijn et al: in LN neg but not in LN pos
- Nielsen et al: in LN pos but not in the LN neg
Most studies have defined BP by expression of basal CKs
- Nielsen et al: CK5/6, ER, EGFR and HER-2
- Matos et al: CK5, P-cadherin and p63
- Lakhini et al: basal CKs, EGFR and osteonectin
Basal Phenotype
•
Grade 3
•
Duct/NST, Medullary like carcinoma, adenoid cystic carcinoma
•
High mitotic count, lack of tubule formation, comedo necrosis
and salivary gland type adenoid cystic change
•
Larger size, LN disease, poorer NPI, DM and recurrence
•
High rate of liver, lung, and brain mets, less bone mets
•
Not with VI or with age
Basal Phenotype
Negative
- ER, PgR and AR
- LA CKs
- FHIT protein
- MUC1
- HER2
- BRCA1
Positive
- P-cadherin
- p53
- EGFR
- E-cadherin
P 53
ER
CK 14
HER-2
Basal Breast Cancer
1)
Group1: tumours with basal phenotype (CK5/6 and/or
CK14) [18.6% of total]
Was further subdivided into two subgroups;
- A) dominant basal pattern (> 50% of cells +ve) [8.6%]
- B) basal characteristics (10 - 50% of cells +ve) [10%].
2) Group2: tumours with myoepithelial phenotype (SMA
and/or p63) [13.7%]
Basal Breast Cancer
[LR 22.54, p<0.001]
Basal Phenotype criteria
Total 1872 cases after excluding uninformative
•
•
•
•
347 cases (18.6%) showed expression of CK5/6 and/or
CK14 in >10% of tumour cells (defined as BP)
Combined basal CKs +ve and ER -ve: 228 (12%)
also HER-2 -ve: 170 (9%)
Basal CKs +ve, ER -ve and EGFR +ve: 81 (4%)
Routine practice: BP defined as expression of basal CKs
Basal phenotype
LN negative, grade 3 tumours
[510 cases, 27% of total cases]
Familial Breast Cancer
• BRCA 1 Prediction
• BRCA 1 – basal phenotype
– Ck 5/6&14 +ve - 44% of all BRCA 1 carriers
– Ck 5/6&14 +ve – < 2% sporadic cancers
Lakhani Clin Cancer Res 2005 11 5175
Breast Cancer Subtypes,
Race and Age
N
Basal
HER2+
Luminal
A
Luminal
B
Unclass
Premenopausal
African-American
97
39%
9%
36%
9%
6%
Postmenopausal
African-American
99
14%
7%
59%
16%
4%
Premenopausal
non African-American
164
16%
6%
51%
18%
10%
Postmenopausal
non African-American
136
16%
6%
58%
16%
4%
TOTAL 496
20%
7%
51%
16%
6%
Adapted from Carey LA et al, ASCO 04
P=0.0001
Basal-like Breast Cancer and
Chemotherapy (MDACC)
Gene expression array subtyping and pathologic complete
response to neoadjuvant chemotherapy with T-FAC (n=83)
Molecular
classification
Luminal
Normal breast
HER2+
Basal subtype
Residual Pathologic complete
Disease
response
93% [78-99]
7% [1-22]
100% [29-100]
0% [0-31]
55% [32-77]
45% [23 -68]
55% [32-76]
45% [24-68]
Chi square: P<0.001
Rouzier R et al, SABCS 2004
Basal-like Breast Cancer and
Neoadjuvant Chemotherapy
Clinical Response to AC
N=104
Basal-like
HER2+
Luminal
N
Overall RR
Clinical CR
Clinical PR
28
22
55
86%*
68%
60%
32%*
18%
5%
54%
50%
55%
Pathologic stage post-chemotherapy
Basal-like
HER2+
Luminal
N
0
I
II
III
27
22
55
30%
27%
13%
22%
14%
13%
26%
41%
36%
22%
18%
38%
*p < 0.05
Carey LA, SABCS 2004
Treatment Approaches
of Interest for Triple
Negative Disease
• Angiognesis
inhibitors
• EGFR inhibitors
• PARP inhibitors
(particularly in
setting of BRCA1
and 2 mutant
tumors)
• Platinum salts
– Take advantage of
inability of BLC to
repair double strand
DNA breaks
– Similarities between
sporadic basal-like
cancers and BRCA1
associated tumors
Time
Prognosis
How long the
tumour has been
there
Intrinsic
The nature of
the tumour
Cum. Survival
Tumour Size
1
0-9mm
10-14mm
15-19mm
20-24mm
.8
.6
.4
25mm or more
.2
Chi-Square
272.403
DF P-Value
4 <.0001
0
0
0
48
4
96
8
144
12
192
Time
16 Time (years)
Cum. Survival
Lymph Node Stage
1
.8
Stage 1 - LN Neg
.6
.4
Stage 2 - Up to 3 low
axillary LN +, or internal
mammary LN + alone
.2
Chi-Square
553.146
0
0
48
0
Stage 3: 4 or more axillary LN +, apical LN +,
or low axillary AND internal mammary +
DF P-Value
2 <.0001
96
4
144
8
192
12
240
Time
16
20
Time (years)
Lymph Node Involvement
Sentinel node biopsy
Vascular Invasion
Prognostic significance
Close correlation with loco-regional lymph node status –
Rosen et al, 1983; Davis et al, 1985; Orbo et al, 1990; Pinder et al,
1994; Yiangou et al, 1999
Correlates with early recurrence in lymph node negative
patients –
Rosen et al, 1983; Bettelheim et al, 1984; Neville et al, 1992
Vascular Invasion
Prognostic significance
Predicts for long term survival, independent of nodal status
Roses et al, 1982; Pinder et al, 1994
Predicts for local recurrence following breast conserving
surgery
Fourquet et al, 1989; Borger et al, 1994; Pinder et al, 1994; Sundquist
et al, 2000
Predicts for local recurrence after mastectomy
O’Rourke et al, 1994; Sundquist et al, 2000
Progress to systemic
metastatic disease
•
•
•
•
•
•
173 women who developed metastatic disease
after a previous breast cancer.
72% had nodal metastases
59% had definite vascular invasion
84% had either lymph node metastases or
vascular invasion or both.
Consistently present whatever the histological
grade of the primary tumour.
Absence of VI and nodal involvement indicated
a low risk of subsequent metastatic disease.
(Evans 2001)
LVI contribution and nodal status
contribution to hazard
Cumulative Proportion Surviving (Kaplan-Meier)
Complete
Censored
1.0
LVI+
TWO
P
=0.511
P
=0.920
LN-
0.9
Cumulative Proportion Surviving
ONE
LVI+
LN-
0.8
ONE
0.7
TWO
0.6
0.5
0.4
0.3
0.2
0.1
0
40
20
80
60
120
100
160
140
Time
200
180
240
220
280
260
300
LVInegLNneg
LVIposLNneg
one
two
three
fourplus
P
=0.563
Prognostic Factor:
Altered natural history
Predictive Factor:
Resistance or sensitivity to therapy
Predictive assays
Luminal / ER +ve
ER PR
HER 2
Overexpression HER2
protein
Gene amplification
Basal
“Triple negative”
Gene expression
Basal phenotype
CK’s, EGFR
ER Immunohistology
Cut off points for treatment
Score
treatment
Effect of Endocrine
0
2–3
4–6
7–8
No effect
Small (20%) chance
Even (50%) chance
Good (75%) chance
Leake et al. J Clin Path 2000; 53: 634-635
Herceptin
®
humanised anti-HER2 monoclonal
antibody
Her-2 status
0
Normal
1+
Normal
2+
3+
Low amplification High amplification
IHC Images courtesy of MJ Kornstein, MD, Medical College of Virginia
Breast cancer
is heterogeneous
The goal is…
Move away from “one size fits all”
strategy ? individualize therapy
… to tailor treatment
ER/PR - important in breast cancer
biology & treatment selection
• ER/PR are key markers to classify subtypes
of breast cancer with different treatment needs
(St. Gallen 2005)
Phenotype
Incidence
(%)
Response to Tamoxifen
(%)
ER+/PR+
58
77
ER+/PR–
23
27
ER–/PR+
4
46
ER–/PR–
15
11
Allred et al. Mod Pathol 1998;11:155-168
Goldhirsch et al. Ann Oncol 2005;16:1569-1583
ER/PR status defines different
treatment needs in breast
cancer
Endocrine
non-responsive
Negative
Endocrine
Response
Uncertain
Low Positive
Endocrine
Responsive
Positive
Chemotherapy
alone
No benefit from
endocrine therapy
Endocrine therapy
benefit from
adding
chemotherapy
Endocrine therapy
alone
Less benefit from
chemotherapy
ER/PR status defines different
treatment needs in breast cancer
Endocrine
responsive*
Basic
Definition
Additional
Features
Main
Therapy
Strong
ER expression
Some
PR expression
Endocrine
Therapy
Endocrine Therapy
(upfront AI**?) with
possible chemotherapy
and Herceptin depending
on risk level & menopausal
status
Chemotherapy
Endocrine
Response
Uncertain*
Low
ER expression
No detectable
PR expression or
HER2
overexpression
Endocrine
Non-Responsive
No detectable
ER or PR
expression
–
•Exact boundary between “endocrine responsive” and “endocrine response uncertain” is
undecided ** Aromatase Inhibitor
•Adapted from AdjuvantOnline.com and Goldhirsch et al. Ann Oncol 2005;16:1569-1583
Oestrogen Receptor (ER): Run 65
IDC: 90 –95%
Intensity: High
IDC: 50 –75%
Intensity: Medium
Slide courtesy of
Merdol Ibraham, UK NEQAS
IDC: 0%
Intensity: Negative
NEQAS RUN 65 ‘ER’ Results
UK NEQAS Sections
Scores >12/20 116 (36%)
Scores 10-12/20 77 (23%)
Scores <10/20 132 (41%)
'In House' Sections
Scores > 12/20 253(78%)
Scores 10-12/20 53(17%)
Scores <10/20 17( 5%)
ANTIGEN RETRIEVAL: main factor responsible for weak staining
(Rhodes et al Am J Clin Pathol 2001; 115: 44–58)
Slide courtesy of
Merdol Ibraham, UK NEQAS
Effective Feedback = Better Performance
ER pass rates 2003-2006
2003
Slide courtesy of
Merdol Ibraham, UK NEQAS
2006
ER/PR immunohistochemical results
are variable from lab to lab
ER false-negative results (n=172 labs)
strongly ER-positive cases
moderately ER-positive cases
weakly ER-positive cases
2000
5%
28%
44%
2002
7%
14%
29%
von Wasielewski et al. Am J Clin Pathol 2002;118:675-682
• Main reason for false-negative results:
inefficient heat-induced epitope retrieval
• Further reasons for variability: diverse primary antibodies,
dilutions, incubation temp/time, detection systems, methods of
scoring, arbitrary definition of positivity (cutpoint), reporting
of results
ER/PR immunohistochemical
results variable from lab to lab
Variable PR immunostaining using
different PR antibodies on a strongly
PR-positive breast carcinoma.
Press et al. Steroids 2002;67:799-813
No. Participants using a
Specific PR Clone: Run 75
46% 15% 11%
Allred Score
clinically validated
Her-2 status
0
Normal
1+
Normal
2+
3+
Low amplification High amplification
IHC Images courtesy of MJ Kornstein, MD, Medical College of Virginia
Negative
Low positive
No endocrine treatment?
Positive
Add chemotherapy?
too low sensitivity and/or too high cutpoint
‘False-negativity’
Negative
Low positive
Endocrine treatment?
Positive
No chemotherapy?
too high sensitivity and/or too low cutpoint
‘False-positivity’
Clinical validation means
demonstration of…
• Assay sensitivity
• Assay specificity
• Stability of reagents, no lot-to-lot variability
• Assay reproducibility
• Assay robustness
• Concordance between assay versus reference method*
• Correlation with patients’ clinical outcome (therapeutic response
and/or prognosis)
Clinical usefulness
* eg. Herceptin Clinical Trial Assay (HER2), Allred Procedure (ER, PR), ligand binding
assay (ER, PR), FISH (HER2)
Personalised
treatment of breast cancer
• Breast cancer is a heterogeneous disease.
• Accurate and reproducible measurement of ER, PR
and HER2 expression is critical for optimal care of
breast cancer patients.
• Validated standardised assays are required to
correctly classify breast cancer and optimize
treatment efficacy and safety.
Predictive assays
ER & PR
Presence of target protein
HER 2
Presence and overexpression TP
Gene amplification
EGFR
? Target protein
? Gene copy number
? Gene mutation
Leake et al. J Clin Path 2000; 53: 634-635
Future Classification
of Breast Cancer
Emerging classification system with clinical relevance
based on:
morphology
phenotype
molecular genetics
Routine provision of prognostic and predictive information
Identification of key therapeutic targets
Linked development of theranostics with drug development
Future Classification
of Breast Cancer
Translation of research techniques / methods to routine
clinical practice
Robust validated & standardised routine methods
Quality assurance integrated into service provision
Pathology has a central role - analytical & coordination
“From inability to let well alone; from too
much zeal for the new and contempt for what
is old: from putting knowledge before wisdom,
science before art, and cleverness before
common sense, from treating patients as
cases, and from making the cure of the
disease more grievous than the endurance of
the same, Good Lord, deliver us”
Robert Hutchison (BMJ 1953: I : 671)