Annals of Oncology Advance Access originally published online on May 21, 2007
Annals of Oncology 2007 18(9):1477-1483; doi:10.1093/annonc/mdm209
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© 2007 European Society for Medical Oncology
breast cancer |
Breast cancer molecular subclassification and estrogen receptor expression to predict efficacy of adjuvant anthracyclines-based chemotherapy: a biomarker study from two randomized trials
1 Translational research unit, Unite Propre de Recherche de l'enseignement supérieur, équipe d'accueil 03535
2 Biostatistics, and Epidemiology Unit
3 Department of Pathology
4 Department of Radiation Oncology
5 Department of Medicine, Institut Gustave Roussy, Villejuif, France
* Correspondence to: Dr F. Andre, Breast Cancer Unit, Institut Gustave Roussy, 39 rue Camille Desmoulins, 94805 Villejuif, France. Tel: +33-1-42114371; Fax: +33-1-42115274; E-mail. fandre{at}igr.fr
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Abstract |
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Background: The purpose of this study was to determine the predictive value of breast cancer molecular subclassification regarding the benefit of adjuvant anthracycline-based chemotherapy.
Patients and methods: Tumor samples from 823 patients included in two randomized trials that compared an anthracycline-based chemotherapy with no treatment were used to construct a tissue array. Estrogen receptor (ER), Her2, epidermal growth factor receptor, cytokeratine 5/6 expressions were determined by immunohistochemistry (IHC). The potential predictive factors of treatment effect on disease-free survival (DFS) were assessed by interaction tests and multivariate analysis.
Results: Sixty-four (8%), 98 (12%), 109 (14%) and 527 (66%) patients presented a Her2+/ER–, basal-like, Her2–/ER–/nonbasal and luminal-like breast cancer. ER expression, when assessed by IHC, was an independent predictive factor for the benefit of chemotherapy on DFS (test for interaction, P = 0.0015). The molecular subclassification significantly predicted the efficacy of chemotherapy (test for interaction, P = 0.01), but had no significant added value (P = 0.32) as compared to the ER by treatment interaction. Adjuvant chemotherapy was associated with an adjusted hazard ratio for relapse or death of 0.42 [95% confidence interval (CI): 0.17–1.05], 0.54 (95% CI: 0.27–1.08), 0.35 (95% CI: 0.18–0.68), 1.07 (95% CI: 0.81–1.41) for patients with Her2+/ER–, basal-like, Her2–/ER–/nonbasal and luminal-like tumors, respectively.
Conclusion: The breast cancer molecular subclassification was predictive for chemotherapy efficacy in adjuvant setting, but did not provide significant additional information to ER.
Key words: adjuvant chemotherapy, basal like, breast cancer, estrogen receptor, molecular subclassification
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introduction |
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TopAbstractintroductionpatients and methodsresultsdiscussionAcknowledgementsReferences |
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Adjuvant chemotherapy decreases the relapse rates of patients with breast cancer [1]. The Oxford meta-analysis has shown that anthracyclines provide a significant benefit in patients with early breast cancer. Based on this, anthracycline-based chemotherapy, associated or not with taxanes [2], has become a standard treatment in patients with intermediate and high-risk early breast cancer [3]. However, a large proportion of treated patients do not benefit from this treatment, and the need has emerged to identify predictive biomarkers [4].
Studies on gene expression profiles have revealed that breast cancer can be considered a heterogeneous entity [5–7], and three large molecular subgroups have been proposed: (i) Her2-overexpressing/Estrogen receptor (ER)-negative tumors, (ii) basal-like and (iii) luminal-like breast cancers. More recently, several efforts have been made to classify breast cancers according to immunohistochemistry (IHC) expression [8, 9]. Basal-like breast cancers are characterized by (i) the lack of ER, progesterone receptor (PgR) and Her2 expressions and (ii) cytokeratine (CK) 5/6 and/or epidermal growth factor receptor (EGFr) expressions [5–9]. The luminal subtype is characterized by ER expression [10]. Several studies have investigated whether some subclass-related biomarkers could be associated with chemotherapy efficacy. ER expression has been reported as predictive factor for the efficacy of an adjuvant methotrexate- or paclitaxel-based chemotherapy [11, 12]. In addition to these studies that did not evaluate efficacy of anthracyclines, several papers have reported that ER expression correlates with resistance to preoperative anthracycline-based chemotherapy [13, 14]. Nevertheless, there is no compelling evidence that ER expression could be predictive for the efficacy of adjuvant anthracycline-based chemotherapy [1], while this drug family is routinely used. Several studies have investigated the predictive value of Her2 status for the efficacy of anthracyclines [15–18]. In two out of four studies, Her2 expression was found to be predictive for the benefit of anthracyclines in terms of disease-free survival (DFS) [16, 18]. Until now, no study has evaluated the predictive value of the molecular subclassification regarding the benefit of adjuvant chemotherapy. One study reported a good correlation between the molecular subclassification (determined by DNA microarray) and the efficacy of preoperative anthracycline-based chemotherapy [19].
In the present study, we planned to evaluate the predictive values of ER expression, Her2 status and the molecular subclassification regarding the benefit of adjuvant anthracycline-based chemotherapy. In addition, since most of the trials that did not report any predictive value for ER expression used a ligand-binding assay, we compared the value of ER status by IHC and ligand-binding assay to predict efficacy of adjuvant chemotherapy.
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patients and methods |
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TopAbstractintroductionpatients and methodsresultsdiscussionAcknowledgementsReferences |
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patients
Two French multicentric randomized trials compared adjuvant anthracycline-based chemotherapy with no chemotherapy in pre- and postmenopausal early breast cancer patients and included a total of 1146 patients, between 1989 and 1995. Nine hundred and thirty-five patients (83% of the trials) were included at the Institut Gustave Roussy (IGR). Inclusion criteria and results of these trials were reported elsewhere [20]. Of the 935 patients, 688 were postmenopausal and presented either with histologically confirmed positive axillary lymph nodes or with negative lymph nodes, but with a tumor grade II or III. The remaining 247 patients were premenopausal and presented with negative axillary nodes, but with a tumor grade II or III. Tumor grade was defined according to a modified Scarff-Bloom-Richardson classification [21]. In the two trials, ER and PgR status were defined according to ligand-binding assay. The cut-off for positivity was defined as 10 fmol/mg protein.
tissue array and immunostaining
Primary tumors from 823 (88%) out of the 935 patients included at the IGR were used to build a tissue array [22]. The tissue array contained three spots of each primary tumor. Each slide was stained with anti-Her2 (DA485, Dako, Glostrub, Denmark), anti-ER (clone 6F11, Novocastra, Newcastle, UK), anti-CK 5/6 (D5/16B4, Zymed, Cergy Pontoise, France) and anti-EGFr (3C6, Ventana, Illkirch, France) antibodies according to manufacturer recommendations. Her2 staining was considered positive when an intense complete membrane staining was observed in >10% of tumor cells. ER staining was considered positive when >10% of tumor cells were stained. CK 5/6 and EGFr stainings were considered positive when observed in at least one tumor cell as previously reported [8]. A staining was also carried out using anti-CK 18 antibody (DC-10, Zymed). CK 18 staining was considered positive when an intense staining was observed in >50% of tumor cells, as used by Abd El-Rehim et al. [10]. In this latter study, authors indicated that luminal tumors had a higher percentage of stained tumor cells as compared with other subtypes. When a discrepancy was observed between the three spots, the definitive score was the one observed in two out of three spots, except for CK 5/6 and EGFr for which a staining was considered positive if one tumor cell was stained in at least one spot.
breast cancer molecular subclassification
Breast tumors were classified into four subclasses according to Her2, ER, CK 5/6 and EGFr expressions. The algorithm for subclassification is summarized in Figure 1 and is derived from Nielsen et al. [8] to classify basal-like tumors. In addition to the Her2+/ER–, basal-like and luminal subclasses, another subclass emerged from this subclassification, i.e. Her2–/ER–/nonbasal tumors. This latter subclass was defined by the lack of Her2/ER/CK 5/6 and EGFr expressions IHC. Illustrative stainings are shown in Figure 2.
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treatment and follow-up
The chemotherapy regimen consisted of six courses of 5-fluorouracil 500 mg/m2, doxorubicin or epirubicin 50 mg/m2 and cyclophosphamide 500 mg/m2, administered i.v. on day 1 (Day 0 = Day 28). Locoregional treatment, endocrine therapy and follow-up have been reported elsewhere [19].
statistical analysis
The primary end point was DFS, defined as the time between the date of randomization and the date of the last follow-up or the date of the best available evidence for the first event: locoregional recurrence, distant metastasis, contralateral breast tumor or death. Survival rates were estimated using the Kaplan–Meier method. The median follow-up was calculated by use of the inverted Kaplan–Meier method [23]. Chi-square tests were used to compare the distribution of clinical characteristics across the five molecular subgroups. We used a Cox model [24] stratified by trial and adjusted for the significant clinical prognostic variables: histological grade (I, II or III), lymph node status (positive or negative) and age (six classes as reported in Table 1). The predictive value of the binary variables ER and Her2 status, and the four-class molecular subclassification were studied by testing the interaction between the relevant variables and the attributed treatment (chemotherapy or no chemotherapy) in the same Cox model. The added predictive value of the Her2 status as opposed to ER status alone was tested adding the Her2 x treatment interaction into the adjusted Cox model with the ER x treatment interaction and applying a likelihood ratio test (test with 1 degrees of freedom). This was done analogously for the four-classes subclassification and its interaction with treatment (test with 4 degrees of freedom). The proportional hazard assumptions were verified by tests for interactions between time and the covariates; the data confirmed the proportionality assumption. Two-sided P values of P < 0.05, and of <0.01 for the interaction tests, were considered statistically significant. All analyses were carried out using SAS software, version 8.2 (SAS Institute Inc., Cary, NC).
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TopAbstractintroductionpatients and methodsresultsdiscussionAcknowledgementsReferences |
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patient characteristics
Immunostainings were carried out in the 823 tumors that were retrieved from the 935 patients included in the two randomized trials at IGR. The patients corresponding to the 112 nonretrieved tumors were a bit younger than those corresponding to the 823 retrieved tumors (mean age 54 versus 56, P = 0.02), less postmenopausal (63% versus 75%, P = 0.01) and less progesteron receptor+ (ligand-binding assay, 54% versus 76%, P < 0.001). There was no evidence for a selection bias based on the stage of the disease, tumor grade or ER positivity (ligand-binding assay). The tumor could be successfully classified into the four molecular subclasses for 798 patients. This accounts for 97% of the tumors collected, 85% of the patients included in the trials at the IGR and 70% of the overall population included in the trial. The study flowchart is shown in Figure 1 and patient characteristics are reported in Table 1. Four hundred (51%) patients were randomized to receive adjuvant anthracycline-based chemotherapy that included epirubicine 50 mg/m2 in 91% of treated patients.
correlation between molecular subclassification and clinical characteristics
ER and Her2 were expressed in 527 (66%) and 103 (13%) tumors, respectively. Sixty-four (8%), 98 (12%), 109 (14%) and 527 (66%) tumors were classified as Her2+/ER–, basal-like, Her2–/ER–/nonbasal and luminal-like (i.e. ER+) breast cancers, respectively. Breast cancer molecular subclassification is correlated with several clinical characteristics (Table 1). There was a significantly different percentage of grade III tumors across the four classes (P < 0.0001, chi-square test). As expected, luminal-like tumors were characterized by a high frequency (99%) of ER expression by ligand-binding assay. On the other hand, basal-like tumors were found to be ER+ by ligand-binding assay in only 35% of cases. Surprisingly, while reported to be ER– by IHC, the Her2–/ER–/nonbasal subgroup was found to be ER+ by biochemistry in 91% of cases. PgR (assessed by ligand-binding assay) was expressed in 82% of Her2–/ER–/nonbasal tumors as compared with 35% of basal-like tumors. Since these data gave rise to the hypothesis that the Her2–/ER–/nonbasal tumors could exhibit a luminal origin, we compared the CK 18 expression between basal-like tumors and Her2–/ER–/nonbasal tumors. CK 18 was expressed in 87 of 107 evaluable Her2–/ER–/nonbasal tumors (81%) and in 28 of 96 evaluable basal-like tumors (29%).
benefit of adjuvant chemotherapy in the overall population
At the date of analysis (December 2005), the median follow-up time was equal to 10 years. During this time, 376 patients (40%) developed a relapse and 236 patients (25%) died. The adjusted hazard ratio of relapse or death for patients treated with adjuvant chemotherapy was 0.83 (95% CI: 0.68–1.02) (P = 0.08). Ten-year DFS rates were 64% (95% CI: 59–68) and 59% (95% CI: 54–64) in patients treated or not with adjuvant chemotherapy.
predictive value of ER expression regarding the benefit of adjuvant chemotherapy
As shown in Table 2, ER status, when determined by IHC, was found to be predictive for the benefit of adjuvant chemotherapy in DFS (test for interaction, P = 0.0015). Adjuvant chemotherapy was associated with an adjusted hazard ratio for relapse or death of 0.50 (95% CI: 0.34–0.73) in ER-negative patients and of 1.07 (95% CI: 0.81–1.40) in those with ER-positive disease. The 10-year DFS rates were 69% (95% CI: 61–77) and 49% (95% CI: 40–58) for patients with ER-negative tumors treated or not with adjuvant chemotherapy, respectively (Figure 3A). On the other hand, the 10-year DFS rates were 62% (95% CI: 56–68) and 64% (95% CI: 57–70) for patients with ER-positive disease treated or not with adjuvant chemotherapy (Figure 3B).
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It is of note that ER expression was not predictive for the efficacy of adjuvant chemotherapy in the Oxford Overview [1]. In this latter report, ER positivity was defined either as an ER expression >1% by IHC or >10 fmol/mg by ligand-binding assay. We hypothesized that the apparent discrepancy between Oxford meta-analysis and our results could be due to differences in the methods and cut-off used to define ER positivity. We therefore compared predictive values of ER expression when assessed by ligand-binding assay (10 fmol/mg protein cut-off) and by IHC (10% cut-off) in patients for whom both expressions were available (n = 702). As reported in Table 3, while ER expression by IHC was predictive in this population (test for interaction, P = 0.002), ER expression assessed by ligand-binding assay was not predictive for the efficacy of adjuvant chemotherapy (test for interaction, P = 0.20). The performance of adjuvant chemotherapy was associated with hazard ratio for relapse or death at 1.10 (95% CI: 0.82–1.47) and 0.89 (95% CI: 0.69–1.14) in patients with ER+ disease defined by IHC and ligand-binding assay, respectively.
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predictive value of Her2 status and of molecular subclasses regarding the benefit of adjuvant chemotherapy
As reported in Table 2, Her2 status was not predictive for the benefit of adjuvant anthracyclines-based chemotherapy for DFS (test for interaction, P = 0.37). The performance of chemotherapy was associated with an adjusted hazard ratio for relapse or death of 0.64 (95% CI: 0.35–1.17) for patients with Her2-expressing tumors and 0.86 (95% CI: 0.68–1.10) for patients whose tumor did not express Her2. When included in a Cox model adjusted for the clinical characteristics and the ER by treatment interaction, the Her2 by treatment interaction was not significant, indicating that Her2 did not significantly add a predictive value to that provided by the ER status for DFS (P = 0.89).
As reported in Table 2, the breast cancer molecular subclassification significantly predicted the efficacy of chemotherapy (test for interaction, P = 0.01). The performance of adjuvant chemotherapy was associated with an adjusted hazard ratio for relapse or death of 0.42 (95% CI: 0.17–1.05) for patients with Her2+/ER– tumors, 0.54 (95% CI: 0.27–1.08) for those with basal-like tumors, 0.35 (95% CI: 0.18–0.68) for patients with Her2–/ER–/nonbasal tumors and 1.07 (95% CI: 0.81–1.41) for patients with luminal-like tumors. Nevertheless, when included in a Cox model adjusted for the clinical characteristics and the ER by treatment interaction, the molecular subclassification did not significantly add a predictive value to that provided by the ER status for DFS (P = 0.32).
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discussion |
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TopAbstractintroductionpatients and methodsresultsdiscussionAcknowledgementsReferences |
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Based on data reported in DNA array [5–7] and IHC [8–10] studies, we used four biomarkers i.e. ER, Her2, EGFr and CK 5/6 to define molecular subclasses. Several issues could be discussed regarding this definition. First, EGFr and CK 5/6 stainings, but not PgR, were used to classify basal-like tumors. We applied the approach from Nielsen et al. [8] who showed, based on DNA array and immunostainings, that four biomarkers i.e. Her2, ER, EGFr and CK 5/6 may accurately classify basal-like tumors. The second issue is the emergence of a subclass defined as Her2–/ER–/nonbasal tumors. This tumor subclass, while ER– by IHC, exhibits both luminal features (including CK 18 expression) and characteristics of aggressiveness, such as younger age and higher tumor grade, as compared to luminal-like tumors. Studies that focused on breast cancer classification using large-scale genomic analyses have already reported that some luminal-like breast cancers, i.e. luminal type B [7], could present a more aggressive phenotype including high tumor grade [5–7].
We found that ER expression was a strong and independent predictive biomarker for the benefit of adjuvant chemotherapy (Table 2). Although the concept that chemotherapy is less effective in ER-positive disease has become popular, there is actually no reported solid evidence based on interaction tests that ER expression is truly predictive of the benefit of adjuvant anthracycline-based chemotherapy. For instance, in the last published Oxford meta-analysis, the test for heterogeneity was not significant [1]. In addition, several randomized trials have reported recently that chemotherapy could improve outcome in ER-positive disease [25, 26]. However, it must be emphasized that ER determination in most of the previously cited trials were based on either ligand-binding assay with a conventional cut-off at 10 fmol/mg or a 1% cut-off for IHC positivity, while a number of teams currently use a 10% cut-off in their daily practice for decision making. In our study, while ER expression determined by IHC (10% cut-off) was predictive (P = 0.002), ER expression determined by ligand-binding assay in the same patient subset was not (P = 0.20). This data indicated that the apparent discrepancy between Oxford meta-analysis and present results could be due to difference in technologies and cut-off. This finding, if confirmed in further studies, may have some implications regarding the selection of patients for adjuvant chemotherapy in the future.
Several studies have reported that Her2 status, when determined by IHC, could be predictive for the benefit of adjuvant anthracycline-based chemotherapy [15–18]. Our study found that the P value for interaction between Her2 expression and benefit of chemotherapy was 0.37, and showed that Her2 did not add predictive information to that provided by the ER status. Several hypotheses can be put forward to explain this apparent discrepancy. The first explanation may be related to the limited statistical power of our study, which does not allow excluding a potential interaction with a higher number of events. A second explanation could be related to the tested hypothesis in the trial design. Studies that reported a positive interaction compared an adjuvant anthracycline-based regimen [15, 18] with another chemotherapy, while our study compared an anthracycline-based chemotherapy with no treatment. Since it has been reported that erbb2 gene coamplifies with TOP2A gene [27], the target of anthracyclines, one could hypothesize that Her2 status predicts more specifically the benefit of anthracyclines over another chemotherapy regimen, while ER status could predict more adequately the benefit of chemotherapy over a no-treatment arm.
We analyzed then whether a new molecular subclassification could be predictive for the effect of adjuvant chemotherapy. It has been reported previously that molecular subclassification was associated with efficacy of preoperative chemotherapy [19]. Nevertheless, when compared with conventional predictors (ER and tumor grade), the molecular subclassification added little information to predict the pathological complete response rates. In the present study, while the molecular subclassification was predictive for the efficacy of chemotherapy (test for interaction, P = 0.01, Table 2), its determination did not add significant information to the predictive value provided by the ER status (P = 0.32).
Although this study showed strong evidence that ER IHC with a 10% cut-off is predictive for the benefit of anthracycline-based chemotherapy, it suffers from some limitations that hamper a transfer into clinical practice. First, the ER determination was based on tissue array and not on conventional tissue sections. While the correlation between tissue array and tissue sections has been reported to be excellent [28], a validation using the daily technology may still be required. Secondly, the chemotherapy regimen used in our study included moderate doses of epirubicin in most of the patients. Since it has been shown that higher doses of epirubicin improves outcome [29], we cannot recommend withholding adjuvant anthracyclines based on our data. Thirdly, although there is a significant interaction between ER expression and benefit of adjuvant anthracycline-based chemotherapy, our study does not have the statistical power to exclude a potential moderate benefit for adjuvant chemotherapy in patients with ER-positive disease.
In conclusion, our study indicates that ER expression strongly predicts the efficacy of adjuvant chemotherapy, but did not show that Her2 or molecular subclassification provide additional information as compared with ER status to predict efficacy of adjuvant chemotherapy over a no-treatment arm.
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Acknowledgements |
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RC was supported by a fellowship from European Society of Medical Oncology. FA was supported by grants from Lilly Fondation, Fondation de France, Ligue Nationale Contre le Cancer and Career Development Award from American Society of Clinical Oncology.
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Footnotes |
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These authors contributed equally to this work. 
Received for publication April 24, 2007. Accepted for publication April 25, 2007.
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References |
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1. Early Breast Cancer Trialists' Collaborative Group (EBCTCG). Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomised trials. Lancet (2005) 365:1687–1717.[CrossRef][Web of Science][Medline]
2. Hamilton A, Hortobagyi G. Chemotherapy: what progress in the last 5 years? J Clin Oncol (2005) 23:1760–1775.
3. Goldhirsch A, Wood WC, Gelber RD, et al. Meeting highlights: updated international expert consensus on the primary therapy of early breast cancer. J Clin Oncol (2003) 21:3357–3365.
4. Hamilton A, Piccart M. The contribution of molecular markers to the prediction of response in the treatment of breast cancer: a review of the literature on HER-2, p53 and BCL-2. Ann Oncol (2000) 11:647–663.
5. Sotiriou C, Neo SY, McShane LM, et al. Breast cancer classification and prognosis based on gene expression profiles from a population-based study. Proc Natl Acad Sci U S A (2003) 100:10393–10398.
6. Sorlie T, Perou CM, Tibshirani R, et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci U S A (2001) 98:10869–10874.
7. Perou CM, Sorlie T, Eisen MB, et al. Molecular portraits of human breast tumours. Nature (2000) 406:747–752.[CrossRef][Medline]
8. Nielsen TO, Hsu FD, Jensen K, et al. Immunohistochemical and clinical characterization of the basal-like subtype of invasive breast carcinoma. Clin Cancer Res (2004) 10:5367–5374.
9. Brenton JD, Carey LA, Ahmed AA, Caldas C. Molecular classification and molecular forecasting of breast cancer: ready for clinical application? J Clin Oncol (2005) 23:7350–7360.
10. Abd El-Rehim DM, Ball G, Pinder SE, et al. High-throughput protein expression analysis using tissue microarray technology of a large well-characterised series identifies biologically distinct classes of breast cancer confirming recent cDNA expression analyses. Int J Cancer (2005) 116:340–350.[CrossRef][Web of Science][Medline]
11. International Breast Cancer Study Group. Endocrine responsiveness and tailoring adjuvant therapy for postmenopausal lymph node-negative breast cancer: a randomized trial. J Natl Cancer Inst (2002) 94:1054–1065.
12. Berry DA, Cirrincione C, Henderson IC, et al. Estrogen-receptor status and outcomes of modern chemotherapy for patients with node-positive breast cancer. JAMA (2006) 295:1658–1667.
13. Penault-Llorca F, Cayre A, Bouchet Mishellany F, et al. Induction chemotherapy for breast carcinoma: predictive markers and relation with outcome. Int J Oncol (2003) 22:1319–1325.[Web of Science][Medline]
14. Rouzier R, Pusztai L, Delaloge S, et al. Nomograms to predict pathologic complete response and metastasis-free survival after preoperative chemotherapy for breast cancer. J Clin Oncol (2005) 23:8331–8339.
15. Paik S, Bryant J, Park C, et al. erbB-2 and response to doxorubicin in patients with axillary lymph node-positive, hormone receptor-negative breast cancer. J Natl Cancer Inst (1998) 90:1361–1370.
16. Paik S, Bryant J, Tan-Chiu E, et al. HER2 and choice of adjuvant chemotherapy for invasive breast cancer: National Surgical Adjuvant Breast and Bowel Project Protocol B-15. J Natl Cancer Inst (2000) 92:1991–1998.
17. Moliterni A, Menard S, Valagussa P, et al. HER2 overexpression and doxorubicin in adjuvant chemotherapy for resectable breast cancer. J Clin Oncol (2003) 21:458–462.
18. Pritchard KI, Shepherd LE, O'Malley FP, et al. HER2 and responsiveness of breast cancer to adjuvant chemotherapy. N Engl J Med (2006) 354:2103–2111.
19. Rouzier R, Perou CM, Symmans WF, et al. Breast cancer molecular subtypes respond differently to preoperative chemotherapy. Clin Cancer Res (2005) 11:5678–5685.
20. Arriagada R, Spielmann M, Koscielny S, et al. Results of two randomized trials evaluating adjuvant anthracycline-based chemotherapy in 1146 patients with early breast cancer. Acta Oncol (2005) 44:458–466.[CrossRef][Web of Science][Medline]
21. Contesso G, Mouriesse H, Friedman S, et al. The importance of histologic grade in long-term prognosis of breast cancer: a study of 1,010 patients, uniformly treated at the Institut Gustave-Roussy. J Clin Oncol (1987) 5:1378–1386.
22. Hoos A, Cordon-Cardo C. Tissue microarray profiling of cancer specimens and cell lines: opportunities and limitations. Lab Invest (2001) 81:1331–1338.[Web of Science]
23. Schemper M, Smith TL. A note on quantifying follow-up in studies of failure time. Control Clin Trials (1996) 17:343–346.[CrossRef][Web of Science][Medline]
24. Cox JD. Regression models and life tables. J R Stat Soc (1972) 34:187–220.
25. Namer M, Fargeot P, Roche H, et al. Improved disease-free survival with epirubicin-based chemoendocrine adjuvant therapy compared with tamoxifen alone in one to three node-positive, estrogen-receptor-positive, postmenopausal breast cancer patients: results of French Adjuvant Study Group 02 and 07 trials. Ann Oncol (2006) 17:65–73.
26. Albain K, Green S, Ravdin P, et al. Adjuvant chemohormonal therapy for primary breast cancer should be sequential instead of concurrent: initial results from intergroup trial 0100 (SWOG-8814). Proc Am Soc Clin Oncol (2002) 21. (Abstr 143).
27. Hicks DG, Yoder BJ, Pettay J, et al. The incidence of topoisomerase II-alpha genomic alterations in adenocarcinoma of the breast and their relationship to human epidermal growth factor receptor-2 gene amplification: a fluorescence in situ hybridization study. Hum Pathol (2005) 36:348–356.[CrossRef][Web of Science][Medline]
28. Zhang D, Salto-Tellez M, Putti TC, et al. Reliability of tissue microarrays in detecting protein expression and gene amplification in breast cancer. Mod Pathol (2003) 16:79–84.[CrossRef][Web of Science][Medline]
29. French Adjuvant Study Group. Benefit of a high-dose epirubicin regimen in adjuvant chemotherapy for node positive breast cancer patients with poor-prognosis factors: 5-year follow-up results of French Adjuvant Study Group 05 randomized trial. J Clin Oncol (2001) 19:602–611.
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M. C.U. Cheang, D. Voduc, C. Bajdik, S. Leung, S. McKinney, S. K. Chia, C. M. Perou, and T. O. Nielsen Basal-Like Breast Cancer Defined by Five Biomarkers Has Superior Prognostic Value than Triple-Negative Phenotype Clin. Cancer Res., March 1, 2008; 14(5): 1368 - 1376. [Abstract] [Full Text] [PDF]
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