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Journal Club
Cremona 24 Maggio 2008
Genomica e proteomica:
significato e utilità attuali
Alberto Ballestrero
Clinica di Medicina Interna a indirizzo Oncologico
DIMI - Università di Genova
Incorporation of genomic into breast
cancer management
Prognosis
Gene expression
analysis
Who treat?
Prediction
Which
therapy?
Classification/
Gene discovery
Improve biological
knowledge
Gene expression analysis assumptions
1) Expression analysis allows identifying the
tumour transcriptional features (transcriptoma)
2) Transcriptoma contains the information required
to predict tumour evolution and response to
treatments
Technologies used for high-throughput gene expression analysis
Marchionni, L. et. al. Ann Intern Med 2008;148:358-369
Netherlands signature
70 significant prognosis genes in N- patients
78 tumors
Good
signature
Poor
signature
Van’t Veer et al. Nature, 2002
Are results reproducible?
September 2006
Median coefficient of variation for:
within-laboratory replicates = 5-15%
between-laboratory replicates = 10-20%
Building a genomic classifier
Patients of
interest
Testing
set
Internal validation
Training
set
Classifier
Esternal validation:
• Retrospective
Classifier gene selection:
discriminant analysis linear or not
linear
• Prospective
Independent patients
70-gene prognostic signature
(“Netherlands signature”)
1st Validation Study
van de Vijver et al. N Engl J Med, 2002
Van’t Veer et al. Nature, 2002
Mammaprint Agendia
Netherlands signature: 151 N- patients
Van de Vijver MJ et al. N Engl J Med 347:1999-2009, 2002
Netherlands signature: 144 N+ patients
Van de Vijver MJ et al. N Engl J Med 347:1999-2009, 2002
Reclassify St. Gallen and NIH subgroups
according to 70-gene signature: 151 N- patients
Van de Vijver MJ et al. N Engl J Med 347:1999-2009, 2002
The gene-expression profile is a more powerful predictor of the
outcome of disease in young patients with breast cancer than standard
systems based on clinical and histologic criteria.
Risk assessments for metastases and
death: 70-gene signature vs Adjuvant
2nd Validation Study Buyse et al. J Natl Cancer Inst, 2006
N° of patients
in risk groups
Mts within 5 yrs
Deaths within 10 yrs
Risk
classification
High
Low
Sensitivity
Specificity
Sensitivity
Specificity
70-gene
signature
194
113
0.90
(0.78-0.95)
0.42
(0.36-0.48)
0.84
(0.73-0.92)
0.42
(0.36-0.48)
Adjuvant!
222
80
0.87
(0.75-0.94)
0.29
(0.24-0.35)
0.82
(0.71-0.90)
0.29
(0.23-0.35)
Both test correctly identify the high risk patients. Gene signature is superior in
correctly identifying the low risk patients.
90% (CI 85%-96%)
DMF
71% (CI 65%-78%)
30% discordant cases
between 70-gene
signature and Adjuvant
Buyse et al. J Natl Cancer Inst 2006
MINDACT trial
a testing hypotesis for a key question
Key question for use of 70-gene to decide on
chemotherapy.
Evaluate the risk of undertreating patients who would
otherwise get chemotherapy per clinical-pathological
criteria.
Testing hypotesis.
The patients who have a low risk gene prognosis signature
and high risk clinical-pathologic criteria, and who were
randomized to receive no chemotherapy has a 5-year
DMFS = 92% (null hypothesis).
EORTC-BIG MINDACT TRIAL DESIGN
6,000 Node negative women
Assess clinical risk and genomic risk
Clinical and
Genomic
BOTH HIGH RISK
DISCORDANT
Clinical and
Genomic Risks
Clinical and
Genomic
BOTH LOW RISK
RANDOMIZE
decision-making
Use clinical risk
High risk
Chemotherapy
High risk
Use genomic risk
Low risk
Low risk
No
chemotherapy
Oncotype DX® 21-Gene
Recurrence Score (RS) Assay
16 Cancer and 5 Reference Genes From 3 Studies
PROLIFERATION
Ki-67
STK15
Survivin
Cyclin B1
MYBL2
ESTROGEN RS =
ER
PR
Bcl2
SCUBE2
GSTM1
INVASION
Stromelysin 3
Cathepsin L2
HER2
GRB7
HER2
BAG1
CD68
REFERENCE
Beta-actin
GAPDH
RPLPO
GUS
TFRC
+ 0.47 x HER2 Group Score
- 0.34 x ER Group Score
+ 1.04 x Proliferation Group Score
+ 0.10 x Invasion Group Score
+ 0.05 x CD68
- 0.08 x GSTM1
- 0.07 x BAG1
Category
RS (0-100)
Low risk
RS <18
Int risk
RS ≥18 and <31
High risk
RS ≥31
Paik et al. N Engl J Med. 2004;351:2817-2826.
17
Prediction of recurrence in N0 ER positive
patients (TAM treated)
Paik et al. N Engl J Med.
2004;351:2817-2826
Prediction of chemotherapy benefit in
Node-negative, ER-positive breast cancer: NSABP B-20
(Paik S et al. JCO 2006)
TAM vs TAM + CT - 651 evaluable patients
Patient reclassification
Low risk
4.4 absolute benefit
from TAM+CT
RS
Intermediate risk
High risk
RS predicts chemotherapy benefit
Schema: TAILORx
Node-Neg, ER-Pos Breast Cancer
Oncotype DX® Assay
RS <10
Hormone
Therapy
RS 11-25
Randomize
Hormone
vs
Chemotherapy +
Hormone
RS >25
Chemotherapy
+
Hormone
Primary study group
To determine whether adjuvant hormonal therapy is not inferior to adjuvant
chemohormonal for patients in the “primary study group”
Oncologist treatment recommendations after RS:
N- ER+ patients
Others Genetic
Element of Interest
Chin L, Gray JW. Nature 2008
Why proteomic?
Cellular signaling events are driven by protein-protein
interactions, post-translational protein modifications and
enzymatic activities that cannot be predicted accurately or
described by transcriptional profiling methods alone.
Proteomic analysis of human breast cancer
J Proteome Res, 2008
EGFR family signaling, AKT/mTOR pathway activation, c-kit/abl growth factor
signaling and ERK pathway
Tumour as a system = organoid
Tumour stem
cells
Tumour cell
subpopulations
Microenvironment
Immune cells