Comprehensive molecular analysis of several prognostic signatures using molecular indices... to hallmarks of breast cancer: proliferation index appears to be...

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Comprehensive molecular analysis of several prognostic signatures using molecular indices related
to hallmarks of breast cancer: proliferation index appears to be the most significant component of all signatures
Christos Sotiriou1,2, Benjamin Haibe-Kains1,2,3, Christine Desmedt1,2, Pratyaksha Wirapati4, Virginie Durbecq1, Adrian Harris5, Denis Larsimont1,
Gianluca Bontempi3, Marc Buyse6, Mauro Delorenzi4, and Martine Piccart1,3.
1Jules Bordet Institute, 2National Foundation of Cancer Research,3Free University of Brussels, 4Swiss Institute of Bioinformatics, Lausanne, 5John Radcliff Hospital, Oxford, UK, 6IDDI,Brussels
Defining Molecular Indices
Introduction
Survival Analysis DMFS (original data sets)
(Sotiriou et al. ASCO 2006)
Although the development of high-throughput gene expression
technologies has led to the identification of several “molecular
signatures” predicting clinical outcome, no attempt has yet been made
to perform a comprehensive analysis integrating well characterized
biological processes and gene expression data. Here we aim to
elucidate the relationship of gene expression patterns defined by
several biologically relevant indices with previously reported prognostic
signatures and their interaction with prognosis
Van’t veer et al. Nature 2002, 70 genes
Chang et al. Plos Biology 2004, wound, 573 genes
Representative genes
ESR1 = Basal/luminal
2 Published datasets
Van de Vijver et al.
NEJM, 2002
+
Wang et al.
Lancet, 2005
ERBB2 = Her2-neu
gene X1
+
.
.
.
.
Materials & Methods
Agilent
N=295
Affymetrix
N=251
STK6 = proliferation/GGI
+
gene X40000
Wang et al. Lancet 2005, 76 genes
Sotiriou et al. JNCI 2006, genomic grade, 97 genes
PLAU = Stroma/invasion
+
STAT1 = immune response
•Selection of prototype genes related to several biological processes in
breast cancer (hallmarks of cancer) such as basal/luminal phenotype,
ERBB2, proliferation, fully captured by the gene expression grade index,
stroma/invasion, angiogenesis, apoptosis and immune response (Sotiriou et
al ASCO 2006)
A model selection procedure is fitted to
estimate the contribution of each
prototype for the prediction of the
expression of each gene on the arrays
Hallmarks of breast cancer
Proliferation
genes (GGI)
+
VEGF = angiogenesis
+
CASP3 = apoptosis
Miller at al. PNAS 2005, p53, 32 genes
Dissecting Gene Expression
Prognostic Signatures
HER-2
70 genes
76 genes
Van’t veer et
al. Nature
2002
Wang et al.
Lancet 2005
P53
(32 genes)
Miller at al.
PNAS 2005
Wound
(573 genes)
Chang et al.
Plos Biology
2004
Genomic grade
(97 genes)
Sotiriou et al.
JNCI 2006
Recurence
Score
(21 genes)
Pail et al.
NEJM 2004
ESR1
(lumina/basal)
73%
(10%)
38%
(3%)
88%
(34%)
42%
(4%)
73%
(1%)
69%
(19%)
ERBB2
60%
(0%)
35%
(0%)
53%
(0%)
30%
(0%)
37%
(2%)
44%
(6%)
STK6
(proliferation)
63%
(14%)
55%
(16%)
53%
(16%)
52%
(13%)
99%
(54%)
69%
(13%)
•Use of a model selection procedure based on cross-validation error
estimation in order to select the genes that are able to predict
significantly et specifically one of the prototypes (molecular indices)
PLAU
(stroma/invasion)
47%
(3%)
42%
(5%)
47%
(0%)
39%
(3%)
64%
(0%)
38%
(6%)
VEGF
(angiogenesis)
43%
(0%)
26%
(1%)
28%
(0%)
35%
(1%)
43%
(0%)
25%
(0%)
•Application to several previously reported prognostic signatures (70gene, 76-gene, wound healing, p53, genomic grade and recurrence score)
STAT1
(immune response)
29%
(1%)
30%
(0%)
19%
(3%)
30%
(0%)
43%
(0%)
25%
(0%)
CASP3
(apoptosis)
60%
(0%)
16%
(1%)
38%
(0%)
40%
(3%)
30%
(0%)
38%
(0%)
ER/luminal/bas
al
Immune
Response
uPA/PAI
VEGF
Hanahan D, Weinberg R, Cell 2000
•Characterization of dependency patterns between these indices for
each prognostic signature and their impact on survival using several
microarray datasets
% of genes related to each prototype; % of genes specific for each prototype
Paik et al. NEJM 2004, recurence score, 21 genes
Survival Analysis DMFS, TRANSBIG VALIDATION N=198
Van’t veer et al.
Wang et al.
Sotiriou et al.
Conclusions
Proliferation seems to be the
common denominator of many
existing prognostic gene
signatures, recapitulating their
prognostic power.
Acknowledgments
FNRS, Medic Foundation,
Breast Cancer Research Foundation
(Evelyne Lauder)
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