Bringing Molecular Prognosis and Prediction to the Clinic

translational

medicine

Bringing Molecular Prognosis and Prediction to the Clinic Mariantonietta Colozza,1 Fatima Cardoso,2 Christos Sotiriou,2 Denis Larsimont,2 Martine J. Piccart2 Abstract In the past 30 years, important advances have been made in the knowledge of breast cancer biology and in the treatment of the disease. However, the translation of these advances into clinical practice has been slow. With the advent of molecular-based medicine, it is hoped that the bridge between the bench and the bedside will continue to be shortened. Because breast cancer is a heterogeneous disease with wide-ranging subsets of patients who have different prognoses and who respond differently to treatments, the identification of patients who need treatment and the definition of the best therapy for an individual have become the priorities in breast cancer care. This article will review the crucial role of prognostic and predictive factors in achieving these goals. A critical review of classical and newer individual molecular markers, such as hormone receptors, HER2, urokinase-type plasminogen activator and plasminogen activator inhibitor 1, cyclin E, topoisomerase II, and p53, was performed, and the preliminary results obtained using the new gene expression profiling technology are described along with their potential clinical implications. Clinical Breast Cancer, Vol. 6, No. 1, 61-76, 2005 Key words: Cyclins, Molecular biology, Plasminogen activator, Predictive factors, Prognostic factors

Introduction Breast cancer is the most common cancer among women and the second leading cause of death in developed countries. Overall mortality rates, although still high, have shown a decrease in 3.2% of patients with breast cancer from 1995 to 1999,1 but various factors contributing to this decrease remain to be defined. Adjuvant systemic therapies (chemotherapy and endocrine therapy [ET]) that aim at the eradication of micrometastases are certainly fueling this progress; they have been shown to reduce the risk of relapse and death in operable breast cancer in all subgroups of patients. However, the absolute risk reduction is correlated with the risk of relapse (on average, patients with node-negative disease derive lesser absolute benefits from adjuvant therapy than those with node-positive disease).2-4 Converse1S.C. Oncologia Medica, Azienda Ospedaliera, Perugia, Italy 2Jules Bordet Institute, Cancéropôle de l’Université, Libre de Bruxells,

Belgium Submitted: May 4, 2004; Revised: Jul 1 2004; Accepted: Jul 1, 2004 Address for correspondence: Martine J. Piccart, MD, PhD, Jules Bordet Institute, Boulevard de Waterloo 215, 1000 Brussels, Belgium Fax: 32-2538-0858; e-mail: [email protected]

ly, we have learned that there can be marked heterogeneity in treatment effects. Some patients derived benefit from therapy in view of the extreme sensitivity of their tumors whereas others did not, as a result of resistant tumors. Therefore, the determination of accurate prognostic and predictive markers is of utmost importance. Prognostic factors are those that predict the risk of recurrence of breast cancer or death from breast cancer independent of the administered treatment. Predictive factors are those that help distinguish patients who are more or less likely to exhibit a response to a given therapy. Prognostic and predictive factors have been extensively studied, but few have been technically and clinically validated. After > 20 years of research, the accepted prognostic factors for routine clinical use are still the classical ones: lymph node status, tumor size, hormone receptor (HR) status, histologic grade, and patient age.5-7 However, the only accepted biologic predictive factors are HR status to select ET and, recently, HER2 status for the use of trastuzumab in metastatic disease.8 The availability of only a few clinically usable prognostic and predictive factors is rather disappointing in view of the huge diversity in molecular pathways dissected by basic scientists that are relevant to breast cancer biology. As we enter the era of molecular-

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Clinical Breast Cancer April 2005 • 61

Clinical Use of Prognostic and Predictive Factors Figure 1 Worldwide Expert Opinions for Treating Small, Endocrine-Unresponsive Tumors 50 Physicians (%)

48 40 30 25

20

15

10

4

0 None

CMF × 6

AC × 4

Tamoxifen

8 Other FAC/FEC ×6

Questionnaires were sent to 48 experts in breast cancer (24 from Europe, 11 from the United States, and 13 from Canada and Australia), and, as shown, there is no consensus. Abbreviation: AC = doxorubicin/cyclophosphamide From Piccart MJ. Proceedings of the American Society of Clinical Oncology Educational Book, 2002:138-143.

based medicine, it is becoming clear that, because breast cancer is an extremely heterogeneous disease, the evaluation of a few tumor genes or proteins, until now, has been of limited clinical use in identifying subgroups of patients with different prognoses or different responsiveness to available systemic treatments. The development of new technologies and, in particular, the use of complementary DNA (cDNA) microarrays, which allow the simultaneous analysis of thousands of genes, could reveal distinct molecular profiles corresponding to different biologic entities of breast cancer. Through the design and conduct of innovative clinical trials, clinicians might learn about the prognostic and predictive value of these profiles and improve treatment tailoring.

Identification of Patients Who Need Treatment: Why Are New Prognostic Tools Necessary? Three important initiatives have been undertaken to analyze and interpret the growing amount of data generated by randomized adjuvant clinical trials: the Oxford Overview, the National Institutes of Health Consensus Conference, and the St. Gallen Consensus Conference.2-7,9,10 In addition, since 1996, the American Society of Clinical Oncology has regularly published evidence-based, clinical practice guidelines for the use of prognostic and predictive factors.8 The most important prognostic factor used in clinical trials for risk assessment has been node status. According to the 2003 St. Gallen Consensus Conference, patients with node-negative disease can be classified as endocrine unresponsive or endocrine responsive based on their HR status (HR positive > 1% stained cells). Endocrine-responsive patients can be further classified into low and average/high risk according to

62 • Clinical Breast Cancer April 2005

tumor size, histologic grade, and age. With the use of traditional clinical/pathologic factors, there remains a great deal of discomfort in treatment decision-making for small cancers, especially in the selection of chemotherapy. Figure 1 represents the highly divergent opinions of 48 worldwide experts in breast cancer for recommending chemotherapy or simple follow-up for a postmenopausal woman diagnosed with a small estrogen receptor (ER)–negative tumor. In recent years, 3 new and potentially useful prognostic tools for node-negative disease have been developed: urokinase-type plasminogen activator (uPA) and its inhibitor plasminogen activator inhibitor 1 (PAI-1); cyclin E; and gene expression profiling.

Urokinase-Type Plasminogen Activator and Plasminogen Activator Inhibitor 1 When measured by quality-assured enzyme-linked immunosorbent assay (ELISA), the 2 molecular markers of invasiveness, uPA and PAI-1, have shown strong prognostic power in early-stage breast cancer under a variety of demographic conditions (in Europe, the United States, and Japan), reaching level 1 evidence, particularly for patients with node-negative disease. Patients with high levels of uPA and/or PAI-1 in their primary tumors have statistically significant shorter disease-free survival (DFS) and overall survival (OS) times than patients with low levels.11-15 Additionally, it has been shown that the clinical relevance of uPA and PAI-1 is greatest when used in combination (markers low vs. high).16 The prognostic impact of these 2 markers on DFS and OS for node-negative breast cancer has been prospectively and independently confirmed.14,17 Moreover, a pooled analysis comprising > 8000 patients with breast cancer has substantiated their independent prognostic value.18 Nonetheless, the wide acceptance of these 2 new markers in clinical practice is limited mainly by their evaluation method, which, although robust, reproducible, and quality-assured, requires a substantial amount of frozen tissue. An additional problem is the suboptimal 10-year outcomes of patients with low uPA/PAI-1 levels in metaanalysis (77% relapse-free survival [RFS]).18 Notwithstanding these problems, although waiting for the mature results from the Chemo N0 trial,14 it appears that uPA/PAI-1 can reliably identify a subset of women with a 90% probability of 5-year RFS.

Cyclin E Cyclin E is an important regulator of S phase entry in the cell cycle and is frequently deregulated in breast tumors. It is overexpressed in 27% of breast carcinoma cases. Cyclin E exists in 2 isoforms with high homology: designed cyclin E1 (formerly called cyclin E) and cyclin E2. Recently, cyclin E1 and its low molecular weight forms, evaluated by Western blot analysis, were reported to be very powerful prognostic factors in stage I-III breast cancer.19 In this study, the hazard ratio for death as a result of breast cancer in patients with high levels of cyclin E was higher than the hazard ratio

Mariantonietta Colozza et al Figure 2 EORTC-TRANSBIG Node-Negative Breast Cancer MINDACT Trial

Adequately Processed Core Biopsy

Risk Evaluation

R A N D O M I Z E

Clinical/ Pathologic Arm

Low Risk

Average/ High Risk Genomic Arm

Chemotherapy

Endocrine Therapy or No Treatment (Look at event rate at 1 and 3 years by IDMC)

Low Risk

This is the design of the MINDACT trial, a planned large prospective trial that will enroll 5000 patients with node-negative breast cancer. Patients will be randomized between risk assessment using common clinical/pathologic criteria or the 70-gene expression signature. The low-risk patients in both arms will receive no further treatment or tamoxifen, but the average/high–risk patients will receive chemotherapy. The MINDACT trial is the first project of TRANSBIG, the recently created network for translational research. Abbreviation: IDMC = independent data monitoring committee

associated with any other biologic marker examined, and it was > 7 times as high as the hazard ratio associated with lymph node metastases. All patients with node-negative disease (12 of 114) with high levels of cyclin E died of breast cancer, whereas all patients with node-negative disease with low levels of cyclin E were alive at a median follow-up of 6.4 years. However, this study has some weaknesses: (1) it is a relatively small retrospective study that included 395 patients; (2) the patients had different stages of disease (I-IV); (3) a large proportion of patients were treated with adjuvant therapy; (4) and the Western blot analysis was used, a method that requires a relatively large amount of fresh tissue.20 Although quite provocative, these results need to be validated in a larger independent study, particularly in view of the fact that other studies of the prognostic value of cyclin E, which mainly used immunohistochemistry (IHC) as the evaluation method, did not generate consistent results.21-29

Gene Expression Profiling The ability to interrogate 10,000-30,000 genes simultaneously using microarray technology has significantly changed our approach to the analysis of expression profiles. Such comprehensive technologies permit the assessment not of individual genes but of clusters of genes that are coordinately expressed to generate “fingerprints” of biologic states of cells of origin. With cDNA- or oligonucleotide-based microarray analysis, it has been possible to identify new classes in breast cancer according to their gene expression patterns and to correlate them with distinct clinical outcomes. Interestingly, the ER status of the tumor is the most important discriminator of expression subtypes, and this finding has been consistently reported by several groups.30-34 Sorlie et al refined this classification: first they showed that the 2 major subgroups of tumors based on ER status correlated well with luminal (ER-positive) and basal (ER-negative) characteristics.35 Furthermore, ER-positive tumors (luminal type) could be separated into 3 expression groups that ultimately were associated with the frequency of TP53 muta-

tions (A, B, and C), whereas the ER-negative group was further divided into HER2-overexpressing, HER2-negative, or basal-like groups. The basal-like and HER2-overexpressing subgroups had a worse prognosis than did the luminal A subgroup. Other subgroups had prognoses between these extremes. Very similar observations were made by Sotiriou et al.36 With DNA microarray analysis, van’t Veer et al reported some impressive, although still preliminary, results, suggesting that a 70-gene signature was able to predict RFS in 78 untreated women with sporadic node-negative tumors.37 Patients were classified in low-risk and high-risk groups on the basis of their prognosis profile, with genes involved in cell cycle, invasion and metastasis, angiogenesis, and signal transduction significantly upregulated in the poor-prognosis signature (for example, cyclin E2, MCM6, matrix metalloproteinase 9 and metalloproteinase 1, RAB6B, PK 428, ESM1, and the vascular endothelial growth factor receptor FLT1). Forty-four patients remained free of disease after their initial diagnosis for an interval of ≥ 5 years (good-prognosis group), and 34 patients developed distant metastases within 5 years (poor-prognosis group). This new prognostic tool was then compared with the St. Gallen criteria as a way to assist the clinician in treatment decision making. Both methods performed well in identifying those patients with an early relapse who needed treatment. However, the St. Gallen criteria classified 70% of the relapse-free patients into an average/high–risk group requiring therapy, whereas the gene prognosis signature did so for only 27%, implying the potential for marked reduction in overtreatment. Also, van de Vijver’s group published the results of a confirmatory study performed on a larger set of 295 patients with node-negative and node-positive breast cancer, a number of whom had received adjuvant systemic therapy.38 At a median follow-up of 6.7 years, the 70gene prognosis signature clearly separated a subgroup with an excellent 10-year survival rate from one with a high mortality rate; in addition, on multivariate analysis, the poorprognosis signature was the strongest predictor of the likelihood of distant metastases, with an overall hazard ratio of

Clinical Breast Cancer April 2005 • 63

Clinical Use of Prognostic and Predictive Factors Figure 3 Pregenomic Era: Heterogeneity in Magnitude of Benefit Seen in a “Classic” Randomized Trial Comparing 2 Treatments Treatement A Found To Be Superior to Treatment B Scenario 1

Scenario 2

Whole population benefits

Whole population benefits

= Subpopulation α benefits

+

α Subgroup

β Subgroup

Subpopulation β benefits

Treatment Selection for the Individual: New Predictive Tools = Subpopulation α benefits

+ Subpopulation β benefits

Detrimental Effect If treatment A is superior to treatment B in its global treatment effect (A is better than B), this is compatible with different scenarios: an acceptable one (center of figure) where all subpopulations derive a benefit; another one (scenario 1) where 1 subpopulation derives a benefit and another only a negligible one, despite being exposed to the side effects of the treatment; and, third, a more worrisome one (scenario 2), where one subpopulation derives a large benefit and another is detrimentally affected (A < B).

4.6 (95% CI, 2.3-9.2; P < 0.001). Although very impressive and provocative, this work has some weaknesses such as the retrospective nature of the study, the relatively small sample size, and the selection of a group of young women (all < 52 years of age) all treated in one hospital, making extrapolations to other age groups and other countries difficult. Therefore, before this new prognostic tool can be successfully used in clinical practice, it needs to be validated in an independent population from other countries and by independent laboratories. Ultimately, the best way to confirm the prognostic value of this signature is through a large, highly powered, independent prospective trial looking at its clinical utility.

New Prospective Prognostic Trials A large study with this design is in progress in the TRANSBIG consortium, partly supported by a generous grant from the European Commission under the Framework Programme VI. This research project includes an initial validation/standardization phase, followed by a large, prospective, randomized study, the Microarray for Node-Negative Disease May Avoid Chemptherapy (MINDACT) trial, which will be coordinated by the European Organization for Research and Treatment of Cancer (EROTC; Figure 2). Although clinical outcome is expected to be similar in the 2 groups, it is postulated that the prescription of adjuvant chemotherapy will be reduced by approximately 15%-20% in the group treated according to the tumor gene expression

64 • Clinical Breast Cancer April 2005

profile. Because ongoing research may show that gene expression arrays are of value in selecting optimal treatment at the time of relapse, the plan is to offer this technology to all women participating in the trial but with a delayed potential use in the control group. It is hoped that this project will confirm that this new prognostic tool outperforms traditional clinical/pathologic criteria for risk assessment and adjuvant systemic treatment decision making.

Chemotherapy Among the systemic treatment modalities available to treat early-stage breast cancer, chemotherapy has the worst reputation in terms of side effects and suffers from poor “tailoring” in view of lack of evidence-based predictive molecular markers. So far, from the numerous randomized trials comparing different regimens, we have learned that the 2 most active classes of cytotoxic agents available for advanced breast cancer treatment are the anthracyclines and the taxanes. Adjuvant anthracycline-based regimens (CAF [cyclophosphamide/doxorubicin/5-fluorouracil (5-FU)], CEF [cyclophosphamide/epirubicin/5-FU], or CMF [cyclophosphamide/ methotrexate/5-FU]) provide a modest but significant impact on breast cancer survival rates in node-negative and node-positive disease in comparison with classic CMF or CMF-like regimens, as shown by randomized trials39-42 and metaanalysis.4 Because of similar or superior efficacy of taxanes compared with anthracyclines in the treatment of advanced disease and the absence of cross-resistance, this class of agents has been subjected to extensive testing in the adjuvant setting. So far, 2 adjuvant trials43,44 have shown an improvement in DFS in node-positive breast cancer, and one also showed a modest advantage in OS, with regimens giving anthracyclines and paclitaxel in sequence (doxorubicin/cyclophosphamide followed by paclitaxel).44 A third trial has reported an increase in DFS and OS by using the TAC (docetaxel/doxorubicin/cyclophosphamide) regimen in comparison with CAF.45 Recently, interesting results have been obtained with a dose-dense taxane-based regimen. In 2005 patients with nodepositive breast cancer were randomized to receive the same drugs (doxorubicin, cyclophosphamide, and paclitaxel), at the same cumulative doses in 2 different schedules (concurrent or sequential), and at 2 different intervals (every 3 weeks or every 2 weeks with granulocyte colony-stimulating factor support).46 At a relatively short follow-up (36 months), the dosedense regimens (concurrent and sequential) showed improved DFS and OS, whereas no difference in outcome between the concurrent and sequential schedules was observed. Although these trials clearly demonstrate progress in breast cancer adjuvant therapy, they promote the use of increasingly more expensive drugs but do not provide reliable information on the subset of women who truly benefit from the incorporation of the newer agents in the treatment strategy.

Mariantonietta Colozza et al Table 1

Hormonal Receptors as Predictive Markers for Response to Neoadjuvant Chemotherapy48-56

Study

Makris et al48

Mauriac et al49

Kuerer et al50

Petit et al51

Method of Evaluation

Type of Study

Number of Evaluable Patients

Stage

Chemotherapy

Predictive of Response

Level of Evidence*

ICA Antibody monoclonal H222 and KD68

Retrospective

77 for ER and 78 for PgR

T1-T4 N0-2

Mostly 2-3MT regimen for 4 courses

No

IV

Retrospective

134/126 for ER/PgR by DCC; 126/124 for ER/PgR by IHC

T2 < 2 cm to T3 N0/1

EVM for 3 courses → MTV for 3 courses

Yes for cOR (ER negative by IHC) on multivariate analysis

IV

233

LABC

Doxorubicin-based for 4 courses

Yes for pCR (ER negative) on multivariate analysis

III

99

II/III (noninflammatory)

FEC 100 for 6 courses

Yes for cCR (ER negative and PgR negative) on multivariate analysis

IV

Median, 4 cycles FAC/FEC

Yes for cOR Correlation (ER negative and PgR negative)

III

DCC, IHC

NR

IHC

Retrospective

Retrospective

Pierga et al52

Quantitative radio immunoassay

Retrospective

936

T2-T3 N0/1

Buzdar et al53

NR

Retrospective

1018

NR

Anthracyclinebased, with or without taxanes

Yes for pCR (ER negative)

III

Different regimens

Yes for pCR on multivariate analysis (ER/PgR absent)

III

AT → CMF

Yes for pCR on multivariate analysis (ER/PgR absent)

II

Colleoni et al54

IHC

Retrospective

399

T2-T4d, N0-2

Gianni et al55

IHC

Prospective

448

T2-T3 N0/1

levels of evidence for grading clinical utility of ER and/or PgR follow those reported by Hyes et al.56 Abbreviations: AT = doxorubicin/paclitaxel; cCR = clinical complete response; cOR = clinical overall response; DCC = dextran-coated charcoal; EVM = epirubicin/vincristine/methotrexate; FAC = cyclophosphamide/doxorubicin/5-fluorouracil; FEC = cyclophosphamide/epirubicin/5-fluorouracil; ICA = immunocychemical analysis; LABC = locally advanced breast cancer; MTV = mitomycin C/thiotepa/vindesine; NR = not reported; pCR = pathologic complete response; PgR = progesterone receptor; 2-3 MT = mitoxantrone/methotrexate plus tamoxifen (with or without mitomycin C) *The

All the aforementioned large randomized clinical trials, performed in patients who were not selected for their tumor biologic characteristics, tell us, for example, that treatment A is superior to treatment B, a result that will guide treatment for future patients (ie, treatment A will be registered and approved for use, and all future patients will receive treatment A).47 However, in a very heterogeneous disease such as breast cancer, this global treatment effect—A is better than B—might be compatible with different scenarios (Figure 3). Therefore, considering the potential side effects of these new drugs and regimens and their high cost, it is a high priority to discriminate subgroups of patients who truly benefit from the more toxic and expensive regimens.

Individual Predictive Markers of Chemotherapy Effectiveness Hormone Receptor Status Hormone receptor negativity has been shown to predict for chemotherapy responsiveness in several trials of primary chemotherapy for operable or locally advanced breast cancer48-55 (Table 148-56). In parallel to the demonstration through gene expression profiling that ER-positive and ERnegative breast cancers are two different diseases, we are becoming aware of the modest chemotherapy effects in the former group and its more striking results in the latter. Supporting this statement is the observation that very young women (< 35 years) with ER-positive tumors receiving adjuvant CMF as the sole treatment modality fare poor-

Clinical Breast Cancer April 2005 • 65

Clinical Use of Prognostic and Predictive Factors Figure 4 Predictive Value of HER2 Overexpression for Anthracycline-Based Adjuvant Chemotherapy NSABP-B11 PAF > PF

NSABP-B15 AC > CMF

NCI-C-CTG CEF > CMF

ITALIAN BELGIAN EC > CMF CMF →A ≅ CMF 1.22

Hazard Ratio for Relapse

1.21

1.0

Interaction Test

1.04

0.96

0.89 0.83

0.83 0.64

0.60

0.37

P = 0.02 P = 0.14

P = 0.23

No HER2 Overexpression

P = 0.10

P = 0.25

HER2 Overexpression

Relapse rates obtained by retrospectively analyzing HER2 overexpression in patients enrolled in 5 randomized adjuvant trials that have compared anthracycline-based versus CMF or alkylating agent–based regimens. There is a trend for reduced risk of relapse in the anthracycline arms in 4 trials and a statistically significant difference in only one. Abbreviations: A = doxorubicin; CEF = cyclophosphamide/epirubicin, 5-FU; EC = epirubicin/cyclophosphamide; PAF = L-phenylalanine mustard/5-FU/doxorubicin; PF = L-phenylalanine mustard/5-FU

ly. This strong interaction between ER status, age, and chemotherapy effectiveness, shown retrospectively in 3700 pre- and postmenopausal patients,57 was reinforced by the observation that no difference in outcome between younger and older premenopausal patients was detected if the tumors were ER-negative. This has led to the hypothesis that endocrine effects of adjuvant chemotherapy (through ovarian suppression) greatly contribute to outcome in young women with endocrine-responsive breast cancer; these indirect endocrine effects, of course, are lacking in very young women who retain intact ovarian function despite chemotherapy.

HER2 Status Another example of differential efficacy of chemotherapy in specific subgroups of patients is related to HER2 overexpression and/or amplification. The first study that showed an interaction between the overexpression of HER2 and adjuvant therapy with doxorubicin-containing regimens was a US trial in patients with node-positive breast cancer; a better outcome was obtained with a dose-intensive regimen containing anthracyclines (ie, FAC [5-FU/doxorubicin/cyclophosphamide) in patients with high expression of HER2.58 Since then, other retrospective studies using IHC but different antibodies and cutoff values have similarly reported better results with anthracycline-based regimens than with CMF-like regimens when HER2 is overexpressed.59-65 However, statistical significance was reached in only 1 trial.60 The results in terms of relapse rate of some trials are shown in Figure 4. A

66 • Clinical Breast Cancer April 2005

dose-intense regimen with epirubicin was not superior to the standard dose in HER2-overexpressing disease,66 whereas the opposite was shown in a recently reported trial comparing dose-dense FEC (5-FU/epirubicin/cyclophosphamide) to standard-dose FEC.67 Moreover, in a randomized study comparing high-dose chemotherapy with hematopoietic stem-cell rescue versus conventionaldose chemotherapy in high-risk node-positive breast cancer (≥ 4 lymph nodes) after induction chemotherapy with an anthracycline-based regimen, a significant advantage in 5-year RFS with high-dose chemotherapy was found only in patients without HER2 overexpression (unplanned subgroup analysis).68 Regarding CMF and CMF-like regimens, the majority of trials69-72 suggested that HER2 overexpression is associated with a lower likelihood of response, except for 1 trial that did not support this finding.73 The role of HER2 as a predictor of response to taxane-based therapy has been evaluated retrospectively in metastatic and neoadjuvant trials, with some trials suggesting that HER2-overexpressing tumors are more responsive to taxane-based regimens than anthracycline-based regimes,74,75 whereas others have drawn opposite conclusions.76 A retrospective evaluation of HER2 by fluorescence in situ hybridization (FISH) was conducted in a phase III trial comparing epirubicin/cyclophosphamide to epirubicin/paclitaxel in the metastatic setting.77 In this trial, a better response rate (RR), progression-free survival, and OS were seen in patients with HER2-overexpressing tumors receiving taxanes. Until now, only 1 adjuvant trial has evaluated the clinical outcome of node-positive disease treated with an anthracycline-based regimen with or without docetaxel in relation to HER2 overexpression45; the TAC (docetaxel/doxorubicin/cyclophosphamide) regimen was superior to the FAC regimen in all patients, and this advantage was even more striking for HER2-overexpressing disease in comparison with cases without HER2 overexpression.

Topoisomerase IIα Topoisomerase IIα (topo IIα) is another molecular marker reported to be predictive of response to specific chemotherapeutic agents in patients with breast cancer. Topo IIα is a key enzyme in DNA metabolism that plays an important role in DNA replication, cell cycle progression, chromosome recombination, and segregation.78 The regulation of topo IIα expression in solid tumors is still not understood completely, and some preliminary data suggest that the correlation between topo IIα gene amplification and protein overexpression evaluated by IHC is seen in only approximately 60% of cases.79-81 This suggests that protein expression is regulated at different levels, including posttranscription and posttranslation steps. Because topo IIα is the molecular target of anthracyclines, its overexpression may render the cells more sensitive to topo IIα inhibitors.82,83 The topo IIα gene is located close to the HER2 gene on the long arm of chromosome 17; this is thought to be the reason why topo IIα aberrations are very rare in the absence of HER2 amplification

Mariantonietta Colozza et al (8% of tumors according to one study84). The observation that topo IIα amplification occurs almost exclusively with concurrent HER2 amplification led to the hypothesis that the predictive value of HER2 regarding anthracycline-based chemotherapy could be explained by the concomitant amplification of the topo IIα gene.82,85-88 Preclinical data also indicate that intratumoral topo IIα levels may explain some forms of resistance to anthracyclines observed in in vitro systems.89 Some retrospective studies have investigated the role of topo IIα as a predictive factor of response to anthracycline-based therapy in all stages of disease,80,84,90 and they seem to suggest an interaction between topo IIα and response to anthracyclines; however, several methodologic weaknesses characterize these retrospective studies. To overcome this problem, a metaanalysis of 4 major adjuvant studies comparing anthracycline-based regimens with CMFlike regimens is ongoing with central reevaluation of HER2 amplification as well as additional determination of topo IIα.

p53 Many experimental and clinical studies have shown that most anticancer agents achieve their cytotoxic effect through apoptosis,91,92 and p53 is a key regulatory gene in the apoptotic pathway. The response to anthracyclines seems to depend on p53 status,93-95 because tumors with normal p53 respond better to these drugs than those with mutated p53; additionally, a study suggested that only specific p53 mutations confer resistance to anthracyclines.96 Conversely, most in vitro and in vivo studies have shown that p53 status does not affect response to taxanes,97-104 because these agents induce apoptosis in a p53-independent way. In a clinical trial of neoadjuvant chemotherapy, tumors with mutated p53 showed a high RR when treated with taxanes but a low RR when treated with anthracyclines.105 This and other in vitro and in vivo studies have raised the hypothesis that tumors with mutated p53 might be less sensitive to anthracyclines while retaining sensitivity to taxanes. Different p53 assessment methods have been used. The risk of false-positive and false-negative results is higher with IHC than with the sequencing method.106,107 A functional assay for p53 in yeast that tests its transcriptional competence has been devised,108,109 because normal p53 activates transcription, whereas mutations abolish this function. This test can detect biologically important mutations and is an attractive alternative to full gene sequencing.

Urokinase-Type Plasminogen Activator and Plasminogen Activator Inhibitor 1 The predictive role of uPA and/or PAI-1 was also retrospectively evaluated, with results suggesting that high levels may predict for enhanced benefit from adjuvant chemotherapy.14,110 These results prompted the launch of a relatively large, prospective, multicenter, randomized adjuvant trial in node-negative breast cancer (the Chemo N0 trial) in which patients were stratified according to tumor levels of uPA/PAI-1. The results of its first interim analysis support

the prognostic and the predictive value of uPA/PAI-1 regarding adjuvant CMF.14 However, because high levels of uPA/PAI-1 indicate greater potential benefit from chemotherapy, low levels are also associated with a clinically relevant chemotherapy benefit;110 therefore, the predictive use of these markers remains controversial.

Multiple Predictive Markers Gene Expression Profiling The prediction of drug sensitivity in the clinic is particularly challenging, because drug response not only reflects properties intrinsic to the target cells but also reflects complex interactions between tumor cells, stromal cells, and host metabolic properties. Tumor response to chemotherapy depends on multiple cellular events, and therefore multiple gene markers generated by profiling hold more promise in terms of ability to predict response to chemotherapy than single genes. Primary systemic therapy (PST) is a very attractive model for analyzing molecular markers, because it is possible to obtain tumor specimens before, during, and at the end of treatment. Complementary DNA microarray technology was used to examine gene expression profiles obtained from fine needle aspiration (FNA) in 10 patients treated with neoadjuvant doxorubicin/cyclophosphamide chemotherapy. The results showed the feasibility of obtaining representative array profiles from FNA of breast carcinomas, as well as the possibility of identifying a gene expression profile and its changes after 1 cycle of chemotherapy that correlate with response to treatment. With 37 genes, the expression was most significantly different between good and poor responders as they were identified. These discriminator genes are involved in a variety of cellular functions.111 Interestingly, a correlation has been reported between gene expression profiles and response to PST using docetaxel in a very small study of 24 patients. A set of 92 genes was identified that allowed for the differentiation of docetaxelsensitive and docetaxel-resistant tumors.112 Docetaxel-sensitive tumors had a higher expression of genes involved in cell cycle, cytoskeleton, adhesion, protein transport, protein modification, transcription, stress, and apoptosis, whereas resistant tumors showed increased expression of some transcriptional and signal transduction genes. This 92-gene predictor had positive and negative predictive values for response to docetaxel of 92% and 83%, respectively. If confirmed and validated, this molecular profile could be useful for the development of a clinical test for docetaxel sensitivity, thereby allowing clinicians to better select patients most likely to respond to this drug. In another small study, a multigene model with 74 markers was built using data from 24 patients (discovery set) treated with a PST regimen consisting of sequential weekly paclitaxel and FAC as a predictor of pathologic complete response (pCR). This model was then tested on a validation set of 18 patients treated with the same chemotherapy and showed a high positive predictive value of 100% (95% CI,

Clinical Breast Cancer April 2005 • 67

Clinical Use of Prognostic and Predictive Factors Figure 6 The BIG-EORTC p53 Trial

Figure 5 The TOP Trial (Jules Bordet Institute) Large operable tumors ER-negative Epirubicin 100 mg/m2 × 4

N = 360

Incisional biopsy

Large tumors

Snap-frozen sample

RANDOMIZE

HER2/topo IIα FISH analysis

Surgery : pCR

Microarray gene profiling

FEC 100 or Canadian CEF

Incisional biopsy

Snap-frozen sample

N = 1300

Docetaxel × 3

p53 anaylsis (functional assay)

Microarray gene profiling

ED × 3

pCR in HER2/topo IIα coamplified tumors pCR in HER2-/basal-like 1 tumors → → →

Hypothesis:

→ → →

Radiation therapy with or without hormonal therapy

Molecular signature of anthracycline’s response

Disease-free survival

Hypothesis:

Molecular signature of taxane’s benefit

→

Docetaxel × 4

DFS at 3 years by 5% in p53– and 20% in p53+

The objective of this trial is to prospectively test topo IIα gene amplification or protein overexpression as potential strong predictive markers for anthracyclinebased chemotherapy and their interaction with HER2 amplification. Patients with large operable ER-negative breast tumors receive epirubicin for 4 courses. After surgery, responsive patients receive docetaxel for 4 courses, radiation therapy, and hormone therapy if PgR positive.

Patients with locally advanced/inflammatory or large operable breast cancer are randomized to an anthracycline-based regimen (FEC 100 or CEF) or to a taxane plus anthracycline regimen (docetaxel x 3 cycles and epirubicin and docetaxel x 3 cycles). An evaluation of p53 status and gene profile expression will be performed in all patients and correlated with responses to the 2 treatment arms. Abbreviations: ED = epirubicin/docetaxel; FEC = 5-fluorouracil/doxorubicin/cyclophosphamide

29%-100%) and high specificity, whereas the sensitivity rate was 43% (95% CI, 10%-82%).113 All patients had undergone pretreatment FNA biopsy to obtain RNA from the tumors for transcriptional profiling using cDNA microarrays. These data are intriguing but still preliminary and need to be optimized in a larger series of patients. In the not-too-distant future it should be possible to obtain gene expression profiles from individual tumors predicting for response to different regimens.

Because of some preclinical and early clinical data suggesting that mutations of the p53 gene may compromise the efficacy of anthracyclines,94,96 p53 gene mutations will be evaluated in the TOP trial to test the hypothesis that the greatest efficacy of anthracyclines can be observed in topo IIα-positive tumors carrying a wild-type p53 gene. In addition, for all patients, a pretreatment and a surgical tumor sample will be evaluated by cDNA microarray (affymetrix platform) to identify a gene signature predictive of response to epirubicin. A large prospective multicenter trial is ongoing that is powered to prospectively assess the potential predictive value of p53 using a functional assay in yeast in patients with locally advanced/inflammatory or large operable breast cancer (Figure 6). The 2 principal objectives of this study are to test a treatment effect by comparing the 2 regimens in patients whose tumors have normal or mutated p53 and to test an interaction effect between p53 status and chemotherapy regimen (with or without taxanes). An evaluation of gene expression profiles will also be performed in a subset of patients with the hope of identifying a molecular signature predicting response to anthracyclines or taxanes.

New Prospective Prediction Trials in Chemotherapy Optimization Innovative trials designed to prospectively evaluate the predictive value of some molecular markers in order to improve our understanding of the heterogeneity in chemotherapy benefit are a high priority as we enter the era of molecular medicine. A few such trials are open to patient recruitment. A neoadjuvant trial for patients with operable ERnegative breast cancer aiming to test prospectively whether topo IIα gene amplification or protein overexpression can be a strong predictive marker for anthracycline-based chemotherapy has been activated (Trial of Principle [TOP]; Figure 5). Importantly, this trial is strictly confined to ERnegative breast tumors, which means that it will not suffer from confounding indirect endocrine effects generated by chemotherapy in young women. The expected results of the TOP trial are as follows: in the cohort of HER2-amplified tumors, there will be a 3-fold increase in the rate of pCR when the topo IIα-amplified subgroup is compared with the topo IIα-nonamplified subgroup; and in the cohort of HER2-nonamplified tumors, the socalled basal-like subset of topo IIα protein overexpression will be associated with a 2.5-fold increase in the pCR rate.

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Endocrine Therapy Recent Progress and the Move Toward New Standards of Care Tamoxifen has been the most widely used treatment for breast cancer and the gold standard endocrine therapy in the metastatic and adjuvant settings for decades. Tamoxifen administered for 5 years to women with ER-positive tumors in the adjuvant setting reduces the risk of recurrences by 47% and the risk of mortality by 26% based on the most recently published Oxford metaanalysis.2 These benefits are seen re-

Mariantonietta Colozza et al gardless of patient age, menopausal status, axillary node status, and use of adjuvant chemotherapy, and they persist beyond the 5-year period that the drug is given. In the past few years, tamoxifen supremacy has been challenged by the third-generation aromatase inhibitors/inactivators (AIs), first in advanced disease114-120 and now in earlystage breast cancer.121-123 Preliminary results of a large adjuvant trial have shown that DFS is superior in patients randomized to receive anastrozole in comparison with tamoxifen alone or a combination of the 2 drugs, with different toxicity profiles.121 More recently, another adjuvant study was reported, at a relatively short follow-up, with a better DFS for patients randomized to receive letrozole for 5 years instead of placebo after 5 years of tamoxifen.122 Finally, a third phase III randomized double-blind study with a follow-up of 30.6 months showed a significant improvement in DFS when exemestane was given sequentially after 2 or 3 years of tamoxifen (total duration of 5 years) in comparison with tamoxifen alone for 5 years.123 Long-term data on the efficacy and toxicity of AIs are still lacking, and this will be important to collect. The convergence of these positive results with 3 different AIs used according to 3 different strategies makes it likely that AIs will be important components in tomorrow’s adjuvant ET. Critical, underdetermined elements include the optimal duration of treatment, the superior modality of administration (alone or in sequence with an antiestrogen), and the accurate selection of patients who benefit most from incorporating these costly new agents into the adjuvant treatment scheme.

Predictive Role of Hormone Receptors Hormone receptor status and in particular ER, which mediates the effects of estrogen on the development and progression of breast cancer, was the first molecular predictive marker able to select tumors that are likely to respond to ET. In the adjuvant setting, data from randomized trials and from the Oxford metaanalysis clearly show that patients with ER-positive tumors derive a significant benefit from 5 years of tamoxifen in terms of RFS than OS,2 whereas ER-negative tumors do not. A correlation between the levels of ER and the efficacy of tamoxifen has also been reported.124,125 However, a substantial number of patients with ER-positive disease do not respond to ET, and therefore other predictive markers are necessary.

Progesterone Receptor Because progesterone receptor (PgR) is an ER-regulated protein, its expression indicates a functional ER pathway, and therefore it is thought that PgR determination might contribute to the prediction of endocrine responsiveness. In several adjuvant studies, the presence of ER and PgR is a marker of a greater probability of benefit than ER alone,126-128 whereas in the Oxford overview, the reduction of recurrence for patients with ER-positive/PgR-negative tumors after adjuvant tamoxifen is similar to the corresponding reduction among patients with ER-positive/PgR-

positive tumors.2 This discordance could be a result of technical difficulties in measuring PgR in some of the earlier trials included in the metaanalysis.129 Also in the metastatic setting, it has been shown that women whose tumors are ER- and PgR-negative have approximately a 5% chance of responding to any ET, whereas those whose tumors are ER- and PgR-positive have a > 70% chance of response to this approach.130,131 Interestingly, in the Adjuvant Tamoxifen Alone or in Combination trial, which compared tamoxifen with anastrozole, a better outcome was observed with anastrozole in the subgroup of patients with ER-positive and PgR-negative tumors, whereas no difference between the 2 agents was seen in ER-positive and PgR-positive tumors.132 However, no difference has been reported yet in these different subgroups of patients with the sequential adjuvant therapy of tamoxifen and exemestane.123 Human PgR proteins exist in 2 isoforms, PgR-α and PgR-β, which are transcribed from the same gene under the control of separate promoters but seem to have different functions, as shown by in vitro and in vivo data.133-135 Recently, a high ratio between the 2 isoforms (PgR-α/PgR-β) has been found to identify a subgroup of patients with node-positive disease with ER- and PgR-positive tumors that are unresponsive to tamoxifen.136 These data, which need to be confirmed, are interesting, because approximately 30% of ER- and PgRpositive cases do not respond to hormonal therapy; therefore, there is great interest in the identification of additional biologic/molecular markers that could better define endocrine responsiveness and possibly function as therapeutic targets.

Estrogen Receptors α and β The action of estrogen in breast cancer is mediated through the activation of 2 related ERs: ERα and ERβ. The latter ER was identified in 1996, and several variants have been described. In particular, the presence of ERα correlates with a better prognosis and a higher response to ET. There is also a suggestion of ERα involvement in breast cancer initiation as well as progression, whereas at present the role of ERβ in these processes is still unclear. Estrogen receptor β is abundant in healthy mammary glands and its loss of expression in some breast tumors as well as its antiproliferative and anti-invasive properties in vitro suggest that ERβ could function as a tumor suppressor. The loss of ERβ in cancers seems to be an epigenetic event caused by the silencing of the ERβ gene by methylation. Its prognostic and predictive role is not yet defined; however, overexpression of ERβ messenger (RNA) was seen in tumors from patients considered resistant to tamoxifen and in tumors without ERα and PgR, which represent a category usually unresponsive to hormone therapy.137,138 Several studies are under way to evaluate the expression of wild-type ERβ or its variant isoforms as potential predictors of clinical response to endocrine agents.139 Also of key importance has been the increasing knowledge regarding the intense cross-

Clinical Breast Cancer April 2005 • 69

Clinical Use of Prognostic and Predictive Factors Figure 7 Intense Crosstalk Between Estrogen Receptor and Growth Factor Pathways IGFR

G Growth Factors

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There is an intense crosstalk between ER and the growth factor signaling pathways, and therefore any aberration in this pathway can dramatically influence/circumvent the action of estrogen and endocrine agents. Some examples include (1) estrogens stimulate positive elements of growth factor signaling pathways such as epidermal growth factor (EGF) and its receptor, EGFR, insulin growth factor (IGF) and its receptor, IGFR; (2) estrogens directly stimulate the tyrosine kinase activities of EGFR and HER2, thus activating the mitogen-activated protein kinase (MAPK) pathway and cell proliferation; (3) activated MAPK leads to phosphorylation of ER and formation of activator protein 1 (AP-1) complex; (4) several growth factors (EGF, IGF-I) directly phosphorylate and activate ER; and (5) estrogens and growth factor signaling pathways influence common growth regulatory genes (basal transcriptional machinery), G1 cyclins, and their kinases and inhibitors. Abbreviation: ERK = extracellular signal–related kinase; P13-K = phosphatidylinositol-3 kinase; SOS = son of sevenless

talk between the ER and the growth factor signaling pathways (Figure 7).140,141 Activators of this cross-talk are good candidates for predictive markers of endocrine resistance.

Bcl-2 The Bcl-2 protooncogene, which encodes for a protein that inhibits programmed cell death (apoptosis), has been associated with high levels of ER and PgR in breast cancers142-145 and has been proposed as a predictor of efficacy of ET in 2 retrospective trials.146,147 In a third retrospective study, the interaction between Bcl-2 and response to tamoxifen was evaluated in 289 patients with ER- and/or PgR-positive early-stage breast cancer previously enrolled in a randomized adjuvant chemotherapy trial.148 This is the only study in which a control group of patients who did not receive treatment with tamoxifen exists;, although, the assignment to each group was not randomized. Despite the relatively small number of patients in each subgroup, there was a trend toward a greater benefit from tamoxifen in ERpositive/Bcl-2–positive cases, as opposed to ER-positive/Bcl2–negative cases.

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Epidermal Growth Factor Receptor and HER2 Increased expression or amplification of epidermal growth factor receptor (EGFR) and HER2 has been associated with endocrine resistance in ER-positive tumors.149-155 To some degree, this association may be explained by the inverse relationship between EGFR/HER2 and ER, but there also seems to be a direct involvement of the HER family pathway in endocrine resistance. Mitogen-activated protein kinase provides one link, because its increased activation has been associated with tamoxifen resistance and reduced OS in ER-positive tumors.149 Another important link currently under intense investigation is the activator protein–1 (AP-1) complex (including Jun and Fos components). Studies have shown significant associations of elevated Fos protein and AP-1 DNA binding to endocrine resistance.156-158 In ER-positive breast tumors, after prolonged tamoxifen exposure, tamoxifen may act as an agonist through the stimulation of AP-1.159,160 Furthermore, high levels of ER coactivators and/or low levels of ER corepressors reduce tamoxifen antagonist activity.161 Preclinical data suggest that HER2 overexpression may be associated with decreased efficacy of tamoxifen, potentially even with detrimental effect.123,162,163 Sever-

Mariantonietta Colozza et al al trials have addressed the issue of clinical resistance to hormonal therapy, particularly tamoxifen therapy, in patients with metastatic disease whose tumors overexpressed HER2.154,164-167 A metaanalysis based on 12 studies and 2371 patients has shown a high correlation between HER2 overexpression retrospectively assessed and endocrine treatment failure, with a relative risk for disease progression of 1.41, which is even higher if the few ER-negative cases are excluded.167 In addition, in all trials of first-line hormonal therapy, the time to progression has been < 6 months.168 However, conflicting results have been reported in the adjuvant setting.169-174 In a neoadjuvant trial comparing letrozole with tamoxifen, a strikingly better RR was observed with letrozole in a very small subgroup of patients with disease overexpressing HER1 and/or HER2.128 Similar results were reported in another neoadjuvant trial comparing anastrozole with tamoxifen, even though the difference was not statistically significant.175 Further strengthening this hypothesis, preclinical studies have demonstrated that adding trastuzumab to hormonal therapy results in greater antitumor activity than is seen with either agent alone,176 and clinical trials exploring this combination in HER2-overexpressing disease are ongoing.

Figure 8 The NSABP 21-Gene Predictor Profiling for Endocrine Responsiveness (Oncotype DX®) Published microarray experiments

16 cancer genes plus 5 reference genes selected

21-Gene Predictor Low

Recurrence score Intermediate High

NSABP Validation Studies Tamoxifen arm of NSABP-B14 675 of 2617 patients 21-gene predictor sucessfully predicts clinical outcome

Tested using RT-PCR on 3 patient populations including NSABP-B20 447 patients (Tamoxifen without chemotherapy, ER contamination)

M. D. Anderson Validation Study

Observation arm of NSAPBB14 ongoing

149 Untreated patients with node-negative disease followed for 18 years

Results pending

21-Gene predictor fails to predict clinical outcome

The development of the NSABP 21-gene predictor and the main results obtained in the NSABP-B14 and in the M. D. Anderson studies are summarized in this figure.

Amplified in Breast Cancer 1 The value of ER coregulators, including amplified in breast cancer 1 (AIB1), as predictive factors of tamoxifen responsiveness is being evaluated, and, so far, preliminary data have been reported regarding the predictive value of high levels of AIB1, a member of the steroid receptor coactivator family. In one study, high nuclear levels of AIB1 determined by IHC seemed to be correlated with hormonal response.177 In contrast, in another study involving tumors that also overexpress the HER2 receptor, high levels of AIB1 measured by Western blot analysis were associated with tamoxifen resistance.178

NCOR1 Corepressor By using reverse-transcriptase polymerase chain reaction (RT-PCR) to measure messenger RNA expression of coregulator genes in 99 postmenopausal patients with ERα-positive tumors treated with tamoxifen as the only adjuvant therapy, low levels of NCOR1, a corepressor, were associated with significantly shorter RFS in univariate and multivariate analysesin when compared with intermediate-high levels.179

Cyclin E The role of cyclin E1 as a predictive marker has been evaluated in only one study, which used quantitative RT-PCR.28 In 108 patients, high levels of cyclin E1 predicted resistance to adjuvant tamoxifen therapy. Data on the potential prognostic and/or predictive role of cyclin E2 in breast cancer are very scarce. Recently, our group assessed the prognostic and predictive value of cyclin E1 and E2 by using quantitative RT-PCR in a series of 230 cases of node-positive and node-

negative breast cancer untreated or treated with chemotherapy (n = 19) or tamoxifen (n = 151). High levels of cyclin E1 appear to have a predictive value of failure to tamoxifen treatment in ER-positive breast cancer.180

Gene Expression Profiling The pattern of genes expressed in ER-negative and ERpositive disease is clearly different, and because no continuum seems to exist between these 2 groups, it is improbable that ER-positive tumors could evolve into “true” negative tumors. Furthermore, preclinical studies have shown that ER-negative cell lines do not become ER-positive only through the transfection of the ER gene.181 Rather the occasional primary or acquired resistance to antiestrogens in ER-positive tumors could be associated with a specific ER environment or modifications of this environment. Recently, a new 21-gene predictor that uses standard RT-PCR to analyze RNA extracted from fixed paraffin-embedded tumor block has been shown to predict a 10-year risk of distant breast cancer recurrences with unprecedented accuracy in node-negative, ER-positive cases treated with tamoxifen. Three different patient populations, including 234 patients enrolled in the National Surgical Adjuvant Breast and Bowel Project (NSABP) B-20 trial and treated with tamoxifen without chemotherapy, were initially evaluated.182 A single multigene predictor containing 21 genes (16 cancer genes and 5 reference genes; Figure 8) was developed. This predictor classified patients in 3 categories according to a recurrence score based on a 0-100 scale of low, intermediate, and high. Subsequentially, the predictor was prospectively validated using 675 pathologically eligible patients enrolled

Clinical Breast Cancer April 2005 • 71

Clinical Use of Prognostic and Predictive Factors in the tamoxifen arm of the NSABP B-14 trial. The recurrence score at a median follow-up of 14.1 years provided accuracy and precision in predicting the likelihood of distant recurrence exceeded standard measures (such as age and tumor size) in prognostic power and reproducibility. However, this multigene model was not predictive of recurrence at a median follow-up of 15 years in another small retrospective study in which 149 patients with untreated nodenegative disease were evaluated.183 There are several potential explanations: (1) the recurrence predictor was developed in a group of patients treated with tamoxifen with or without chemotherapy, whereas this group received no adjuvant systemic treatment; (2) the study was small and retrospective; (3) the population included some patients with ER-negative tumors who did not fit the criteria for the assay (ER-positive only in 70% of patients); and (4) an unexpected association between high nuclear grade and improved outcome could have negatively impacted the performance of the gene predictor. In another retrospective study, a 40-gene set was found to be predictive of response to tamoxifen for 96% of 70 patients with metastatic breast cancer who had not received the drug in the adjuvant setting.184 This 40-gene set was then validated in an independent set of 15 tamoxifen-resistant tumors and correctly predicted the outcome in 80% of these cases. Further validation studies are necessary to prove the value of these gene sets in identifying the individual patients who benefit from tamoxifen treatment.

Prospective Predictive Trials A new trial is starting to prospectively evaluate gene profiling expression and some biologic markers by tissue arrays in patients receiving neoadjuvant ET with letrozole. Trials should also be designed to allow for a segregation of the endocrine-responsive breast cancer population into 3 subsets: a “tamoxifen highly sensitive” subset that might not need early introduction of AIs in the treatment plan; a “tamoxifen moderately sensitive” group that might be best served by a tamoxifen and AI sequence with a switch at 2 or 3 years; and an “AI highly sensitive” subset, for which AIs should be used as first-line treatment.

Conclusion As we move from empiric to molecular oncology, our classic large prospective trials comparing different regimens or strategies in unselected populations need to be replaced or complemented by new tailored studies asking biologically relevant questions. Multidisciplinary efforts and a close collaboration between basic scientists and clinical researchers are key to the success of the investigation of novel approaches that will make individual treatment tailoring the standard of care in breast cancer management in a not-toodistant future.

Acknowledgements The authors thank the Jean H. Lubrano Foundation, which invited Dr. M. Piccart to give a keynote lecture on the topic of this manuscript in July 2003, as well as C. Straehle for editing the manuscript.

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