REVIEW ARTICLE
Int J Clin Oncol (2002) 7:245–253 © The Japan Society of Clinical Oncology 2002
Angelo Di Leo · Fatima Cardoso · Virginie Durbecq
Rosa Giuliani · Max Mano · Gul Atalay · Denis Larsimont
Christos Sotiriou · Laura Biganzoli · Martine J. Piccart
Predictive molecular markers in the adjuvant therapy of breast cancer:
state of the art in the year 2002
Received: February 28, 2002
A. Di Leo (*) · F. Cardoso · V. Durbecq · R. Giuliani · M. Mano ·
G. Atalay · C. Sotiriou · L. Biganzoli · M. J. Piccart
Department of Chemotherapy, Jules Bordet Institute, Brussels, rue
Heger-Bordet 1, 1000 Brussels, Belgium
Tel. +32-2-541-31-80; Fax +32-2-541-30-90
e-mail: Angelo.Dileo@bordet.be
D. Larsimont
Department of Pathology, Jules Bordet Institute, Brussels, Belgium
Abstract In the present article, an extensive review of the
current knowledge regarding predictive molecular markers
in breast cancer is presented. The main emphasis has been
given to the adjuvant therapy setting, because of the lack of
well-designed studies evaluating predictive markers in the
metastatic setting. In the first part of the article some gen-
eral concepts have been summarized, mainly to emphasize
the difference between prognostic and predictive markers.
In the second part of the article, studies evaluating mole-
cular markers with predictive value for the most commonly
used drugs or regimens (i.e., cyclophosphamide, metho-
trexate, 5-fluorouracil [CMF], anthracyclines, taxanes, and
herceptin) have been reviewed and discussed. An attempt
has been made to provide for each single predictive marker
the currently available level of evidence, to allow the reader
to have immediate information regarding the impact of the
evaluated marker in daily clinical practice. In the last part of
the article, the most important findings have been summa-
rized and future avenues of research have been outlined.
Key words Breast cancer · Adjuvant therapy · Molecular
markers · Predictive markers
Introduction
The results of important and large randomized clinical trials
and the conclusions of the Oxford meta-analysis have had a
major impact on treatment recommendations for patients
with early breast cancer
1–7
(R. Peto 2000, Fifth main meet-
ing of the Early Breast Cancer Trialist’s Collaborative
Group, unpublished work). Today, adjuvant medical
therapy is offered to the vast majority of patients with node-
negative breast cancer.
1,4–6
Indeed, the international panel
of experts on adjuvant therapy met again in St. Gallen in
February 2001, and concluded that only node-negative pa-
tients aged 35 years or more, with tumors of small size
(2 cm), well-differentiated (histological grade 1), and posi-
tive for both the estrogen (ER) and the progesterone (PgR)
receptors, might be spared adjuvant chemotherapy because
of their minimal risk of relapse. Adjuvant chemotherapy
should at least be offered to all other patients, particularly
those with endocrine non-responsive disease (i.e., ER- and
PgR-negative).
8
The Oxford 2000 overview, based on data
from 56 trials and 28 000 women, concluded that, after stan-
dardization for age and time since randomization, with the
use of polychemotherapy, proportional reductions in risk
of recurrence and death are similar for women with
node-negative and node-positive disease (R. Peto 2000,
unpublished).
According to these guidelines, most patients with early
breast cancer receive adjuvant treatment, and the main
challenge has become the identification of predictive factors
that may help in selecting the optimal therapeutic strategy
for individual patients. The accomplishment of this ambi-
tious aim could translate into a substantial increase in the
absolute benefit associated with adjuvant therapy.
Predictive factors: general concepts
The main differences between predictive and prognostic
factors are illustrated in Fig. 1. While a prognostic factor
influences disease outcome whichever adjuvant therapy is
used (Fig. 1A), a predictive factor will interfere with disease
outcome only when a specific treatment is given (Fig. 1B,C).
Figure 1B shows how the outcome of treatment A is
positively influenced by the predictive factor under study,
which, in contrast, has no impact on the efficacy of treat-
ment B. A predictive factor might also differentially influ-
ence the outcome of two different adjuvant therapies, as
described in Fig. 1C. This latter scenario would be the ideal