- Email: [email protected]
Characterization of breast cancer subtypes by quantitative assessment of biological parameters: Relationship with clinicopathological characteristics, biological features and prognosis
European Journal of Obstetrics & Gynecology and Reproductive Biology 141 (2008) 147–152
Contents lists available at ScienceDirect
European Journal of Obstetrics & Gynecology and Reproductive Biology journal homepage: www.elsevier.com/locate/ejogrb
Characterization of breast cancer subtypes by quantitative assessment of biological parameters: Relationship with clinicopathological characteristics, biological features and prognosis J.M. Del Casar a,b,c, A. Martı´n a, C. Garcı´a a, M.D. Corte a, A. Alvarez d, S. Junquera a, ˜ iz f, M.T. Allende c,d, F. Vizoso a,b,c,* L.O. Gonza´lez a,c,e, M. Bongera a, J.L. Garcı´a-Mun a
Unidad de Investigacio´n, Hospital de Jove, Gijo´n, Spain Servicio de Cirugı´a General, Hospital de Jove, Gijo´n, Spain c Instituto Universitario de Oncologı´a del Principado de Asturias, Oviedo, Spain d Servicio de Medicina Nuclear, Hospital Central de Asturias, Oviedo, Spain e Servicio de Anatomı´a Patolo´gica, Hospital de Jove, Gijo´n, Spain f Servicio de Cirugı´a General, Hospital Central de Asturias, Oviedo, Spain b
A R T I C L E I N F O
A B S T R A C T
Article history: Received 6 July 2007 Received in revised form 10 April 2008 Accepted 11 July 2008
Objectives: Gene expression analysis has identified several breast cancer subtypes, including luminal, epidermal growth factor receptor-2 positive (HER2+), and basal-like. To determine if our proposed molecular taxonomy correlates with biological and clinical behavior. This is based on four biological markers: estrogen and progesterone receptors (ER and PR, respectively), HER2 and the epidermal growth factor receptor-1 (HER1), all of them being determined by quantitative assays. Study design: The biological parameters were examined by enzyme immunoassay, radioligand-binding assay or ELISA, in tumors from 787 patients with invasive breast cancer. Patients were prospectively evaluated over a median follow-up period of 50 months. Subtype definitions were as follows: luminal (ER+), HER2+ (HER2+, ER , PgR ) and basal-like (HER2 , ER , PgR ). In addition, we divided basal tumors into two groups based on their HER1 status. Results: A 55.8% of tumors were of luminal type, 11.9% basal-like HER1+, 10.7 basal-like HER1 , and the remainder 21.6% HER2+. Both HER2+ and basal-like subtypes were more frequent in younger and premenopausal women, showing a higher percentage of cases of poorly differentiated tumors and higher S-phase fraction, when compared with those of luminal subtype. Multivariate analysis demonstrated that the subtype of tumor was related to both relapse and overall survival, being those of luminal subtype associated with the best prognosis. Conclusions: Through the classification of breast tumors in four groups, according to their ER, PgR, HER2 and HER1 status, it is possible to obtain a major division of breast tumors associated with significant differences in biological features and clinical behavior. ß 2008 Elsevier Ireland Ltd. All rights reserved.
Keywords: Breast cancer Epidermal growth factor receptor HER1 HER2 Prognosis
1. Introduction With the increasing use of breast cancer screening programs, more early-stage tumors are being diagnosed, thus creating a need for new prognostic and therapy-directing tools and therefore avoiding under- and over-treatment of large patient cohorts. There is some difficulty in determining the prognosis of these women
* Corresponding author at: Hospital de Jove, Servicio de Cirugı´a General, Avda. Eduardo Castro s/n, Apartado 385, 33290 Gijo´n, Spain. Tel.: +34 985315710. E-mail address: [email protected] (F. Vizoso). 0301-2115/$ – see front matter ß 2008 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.ejogrb.2008.07.021
since breast cancer is a heterogeneous disease encompassing a wide range of clinical behaviors, even in patient groups that appear to be clinically similar. Despite a number of classical prognostic variables such as nodal status, tumor size, age and hormone receptor status, additional and predictive factors need to be identified in order to improve risk classification and thereby develop a more rational management of breast cancer patients. Currently available tumor classification systems rely on classical histopathology findings; however, although the grade of malignancy is a prognostic indicator, it is evident that the molecular heterogeneity of these tumors is not reflected only by their histological appearance.
J.M. Del Casar et al. / European Journal of Obstetrics & Gynecology and Reproductive Biology 141 (2008) 147–152
148
Recent DNA microarray profiling studies on frozen breast cancer samples have identified distinct subtypes of breast carcinomas associated with different clinical outcomes [1–3]. Using an intrinsic set of 534 genes, Sorlie et al. analyzed the expression profiles of 115 independent breast tumors samples and categorized breast tumors into four different groups: luminal (estrogen receptor positive (ER+)), HER2 overexpressing, normal breast-like and basal-like. In addition, several studies have shown the potential clinical value of this classification. Breast cancers of the basal-like subtype comprise about 19% of tumors and have a poor prognosis as assessed by relapse-free survival [2,4,5]. This seems to indicate that large-scale molecular techniques such as DNA microarrays contribute to the understanding of the molecular complexity of breast cancer [3]. Nevertheless, the cost, complexity, and interpretation of DNA microarrays make them currently unsuitable for routine use in standard clinical settings. Additional opportunities to identify and/ or validate molecular signatures are provided by the molecular profiling of breast cancer using a limited number of protein biomarkers, since basal epithelial cells can be stained with antibodies to keratins 5/6, whereas luminal epithelial cells stain with antibodies against keratins 8/18 [6–8]. Recent immunohistochemical studies on formalin-fixed paraffin-embedded tumor archives have validated this classification as well as the prevalence and poor prognosis of basal-like breast cancers [6,7,9,10]. However, at present there are no studies on the possible clinical value of quantitative assays in classifying subtypes of breast carcinomas.
Consequently, our aim is to determine if our proposed molecular taxonomy correlates with biological and clinical behavior. This is based on four biological markers: estrogen and progesterone receptors (ER and PR, respectively), HER2 and the epidermal growth factor receptor-1 (HER1), all of them being determined by quantitative assays. 2. Materials and methods 2.1. Patient characteristics and tissue specimen handling This study is comprised of 787 consecutive women with a histologically confirmed diagnosis of invasive breast cancer, who were treated at Hospital de Jove (Gijo´n, Spain) and at Hospital Central de Asturias (Oviedo, Spain), between 1990 and 2002. The median age was 59 years (range, 30–92 years). None of them had undergone any neoadjuvant therapy nor shown evidence of any other malignant tumors or distant metastases at the time of diagnosis. Patient characteristics with respect to age, menopausal status, clinical tumor stage, histopathology, proliferative and biological parameters are listed in Table 1. Histological grade was determined according to criteria reported by Bloom and Richardson [11], whereas nodal status was assessed histopathologically. Women were treated according to the guidelines used in our institution. All patients were followed for disease recurrence and survival status by clinical and biological studies every 3 months for
Table 1 Relationship between patient characteristics and breast cancer subtypes in 787 patients Patient and tumor characteristics
N (%) Luminal
Basal-like HER1+
Basal-like HER1
HER2+
Total
439 (55.7)
94 (11.94)
84 (10.67)
170 (21.6)
Tumor size T1 T2 T3 T4
181 201 35 22
34 39 13 8
34 38 4 8
Age (years) <59 >59
191 (43.5) 248 (56.5)
57 (60.6) 37 (39.4)
54 (64.3) 30 (35.7)
103 (60.6) 67 (39.4)
Menopausal status Premenopausal Postmenopausal
112 (25.5) 327 (74.5)
35 (37.2) 59 (62.8)
35 (41.7) 49 (58.3)
64 (37.6) 106 (62.4)
Histological type Ductal Lobular Others
388 (88.4) 27 (6.2) 24 (5.5)
81 (86.2) 7 (7.4) 6 (6.4)
68 (81) 7 (8.3) 9 (10.7)
155 (91.2) 10 (5.9) 5 (2.9)
Histological gradea I II III Unknown
127 225 66 21
14 41 33 6
23 32 21 8
Nodal status Negative Positive
242 (55.1) 197 (44.9)
52 (55.3) 42 (44.7)
39 (46.4) 45 (53.6)
92 (54.1) 78 (45.9)
Ploidy Diploid Aneuploid Unknown
107 (24.4) 157 (35.8) 175 (39.9)
18 (19.1) 34 (36.2) 42 (44.7)
27 (32.1) 20 (23.8) 37 (41.7)
35 (20.6) 73 (42.9) 62 (36.5)
S-phase <7.69b >7.69b Unknown
159 (36.2) 119 (27.1) 161 (36.7)
21 (22.3) 32 (34) 41 (43.6)
22 (26.2) 27 (32.1) 35 (41.7)
43 (25.3) 67 (39.4) 60 (35.3)
a b
Scarff–Bloom–Richardson criteria. Median S-phase fraction value.
p
0.290 (41.2) (45.8) (8) (5)
(36.2) (41.5) (13.8) (8.5)
(40.5) (45.2) (4.8) (9.5)
75 71 11 13
(44.1) (41.8) (6.5) (7.6) 0.0001
0.001
0.26
0.0001 (28.9) (51.3) (15) (4.8)
(14.9) (43.6) (35.1) (6.4)
(27.4) (38.1) (25) (9.5)
39 70 54 7
(22.9) (41.2) (31.8) (4.1) 0.52
0.027
0.03
J.M. Del Casar et al. / European Journal of Obstetrics & Gynecology and Reproductive Biology 141 (2008) 147–152
the first 2 years and then yearly. Radiological studies were performed yearly or when considered necessary. The median follow-up period was 54 months (range, 6–288 months). The endpoint was death secondary to tumor progression. The median follow-up period in surviving patients was 58 months. One hundred and ninety five patients developed tumor recurrence and 102 (52.3%) died as a consequence of tumor progression. The study adhered to national regulations and was approved by our institution’s Ethics and Investigation Committee. 2.2. Tissue processing and assays Breast carcinoma tissue samples were obtained at the time of surgery from 787 patients. Immediately after surgical resection, samples were processed for pathological examination while the remainder of the tissue was washed with cold saline solution, divided into aliquots, rapidly transported on ice to the laboratory and stored at 70 8C pending biochemical studies. The tumor tissue samples were obtained with informed consent from the patients. The specimens obtained from neoplastic tissues were pulverized with a microdismembrator (Braun Biotech International, Melsungen, Germany) at 70 8C and homogenized in TRIS– hydrochloride buffer (10 mM of TRIS, 1.5 mM of EDTA, 10% glycerol, 0.1% of monothioglycerol). Homogenates, kept at 4 8C, were centrifuged at low speed (800 g for 10 min, at 4 8C), and the supernatant was ultracentrifuged at 100,000 g for 60 min, at 4 8C. The protein content was quantified by the Bradford method [12], using bovine albumin as the standard (Sigma Chemical Co., St. Louis, USA) and the Bio-Rad Protein Assay Dye Reagent Concentrate (Bio-Rad Laboratories, Munich, Germany). 2.3. Flow cytometry DNA content was evaluated by flow cytometry in all tumors (Bectron Dickinson, San Jose´, CA, USA), on nuclei stained with propidium iodide. DNA ploidy was expressed as DNA-index. Tumors were considered diploid when the DNA-index obtained was 1.0, and aneuploid for any diverging value, including tetraploid tumors, with a DNA-index of 2.0. Proliferative activity was expressed as the fraction of cells in the ‘‘S’’ phase of the cell cycle and calculated with the CellFit software program (Bectron Dickinson), according to the DNA Cytometry Consensus Conference recommendations [13]. Median S-phase fraction value was used as the cut-off point. Tumors were also divided into those with a high or a low S-phase fraction. 2.4. Assays ER and PR receptor measurements were performed on cytosol extracts by using a solid-phase enzyme immunoassay based on the ‘‘sandwich’’ principle (ER-EIA and PR-EIA from Abbot Laboratories, Diagnostics Division, Wiesbaden, Germany). ER and PR values were expressed as femtomols per milligram of protein. HER-1 was expressed as fmol/mg protein. HER2 was analyzed in membranous samples by an ELISA (Oncogene Research Products, Boston, MA, USA). Samples found to contain greater than 1200 NHU/mg of protein homogenate (i.e., outside the range of the standard curve) were diluted with sample diluents, so that the HER2 concentration would fall within the range spanned by the standard curve and assayed again. 2.5. Definition of breast cancer subtypes Although breast cancer subtypes were originally identified by gene expression analysis using DNA microarrays [1–3] and
149
immunohistochemical markers had been verified against gene expression profiles to estimate the prevalence of the intrinsic subtypes in large populations [6,7,9,10], large-scale subtyping using quantitative assessment of biological markers is not currently feasible. For this reason, we investigated the prognostic interest of these classification criteria by measuring some key biological markers, such as ER, HER2 and HER1, by enzyme immunoassay, radioligand-binding assay and ELISA, respectively. We established the following subtypes: luminal (ER+), HER2+ (HER2+, ER , PR ) and basal-like (ER , PR , HER2 ). In addition, we recategorized basal tumors into two groups based on their HER1 status, since this division was designed as an alternative criteria for classifying tumors of basal-like subtype [7,14–16]. For data analysis, a value higher than 10 fmol/mg total protein was considered as positive for ER and PR, whereas a value of 1200 NHU/ mg protein for HER2 and the median value for HER1, were taken, respectively, as cut-off points in consideration of their clinical value as reported in previous studies [17,18]. 2.6. Statistical analysis Patients were subdivided into groups based on the definition of breast cancer subtypes. Differences in percentages were calculated with the chi-square test. Differences between curves were evaluated with the log rank test. Cox’s regression model was also used to examine several combinations and interactions of different prognostic factors in a multivariate analysis. In the multivariate analysis, only parameters that achieve statistical significance for relapse-free survival or overall survival in the log rank test were included. The SPSS 11.5 program (SPSS Inc., Chicago, USA) was used for all calculations. Statistical significance was considered at 5% probability level (p 0.05). 3. Results A total of 439 tumors (55.8%) were of the luminal type, 94 (11.9%) were basal-like HER1+, 84 (10.7%) basal-like HER1 , and the remainder 170 (21.6%) were HER2+. Table 1 shows the clinicopathological characteristics of these four groups. Statistical analysis showed that there were significant differences in the distribution of breast cancer subtypes in relation to age, menopausal status and histological tumor grade. Thus, the percentage of luminal subtype of tumors was higher in older and postmenopausal patients, whereas the remainder of the tumor subtypes were more frequent among younger and premenopausal women. The luminal subtype showed a higher percentage of cases with well-differentiated tumors, whereas the percentage of poorly differentiated tumors was higher in the other types of tumors. Likewise, as Table 1 shows, luminal tumors showed a significantly lower S-phase fraction when compared with the other subtypes of breast cancer. The potential relationship between the different subtypes of breast carcinomas and both relapse-free survival and overall survival was evaluated in all of the patients included in the present study. Fig. 1A and B shows both relapse-free survival and overall survival curves, respectively, considering the already mentioned three groups of patients. Statistical analysis demonstrated significant differences between these survival curves (p = 0.02 and 0.05, respectively). The luminal subtype of tumors was associated with a better prognosis, whereas HER2+ tumors had a poor prognosis. Survival analyses were also performed separately in the different subgroups of patients stratified according to the nodal status. Thus, significant and similar differences with regard to the subtypes of breast carcinomas were found in the nodenegative subgroup, whereas only significant differences were
150
J.M. Del Casar et al. / European Journal of Obstetrics & Gynecology and Reproductive Biology 141 (2008) 147–152 Table 2 Multivariate analysis of the association between different clinicopathological parameters and relapse-free survival and overall survival Tumor characteristics
found for relapse-free survival in the subgroup of patients with node-positive tumors (Fig. 2). We also looked into the possible prognostic value of classifying the luminal type of tumors into luminal A (ER+, HER2 ) and luminal B (ER+, HER2+) subtypes, but significant differences between both subgroups were not found (data not shown). On the other hand, our data did not show significant differences in both relapse-free and overall survival curves between HER1+ and HER1 tumors, when only basal-like tumors were considered (data not shown). Multivariate analysis demonstrated that tumor size, nodal status and tumor subtype were all associated with both relapse and overall survival in the group of patients as a whole. Likewise, the histological grade was also related with relapse-free survival (Table 2). 4. Discussion Currently, there are few data on the possible clinical value of quantitative assays to classify subtypes of breast carcinomas. In the present work, we established a classification based on criteria of cancer subtypes and considering four biological markers: ER, PR, HER2 and HER1, which were assessed by quantitative techniques (enzyme immunoassay, radioligand-binding assay and ELISA). Our results demonstrated that this definition of breast cancer subtypes allows the identification of breast carcinomas displaying different tumor behavior. We consider it remarkable that these subtypes vary significantly in terms of age (p = 0.0001), menopausal status (p = 0.003), tumor grade (p = 0.0001), and S-phase fraction
Overall survival
RR
RR
CI (95%)
1 3.8
– 2.3–6.3
1 1.4 1.1 2.3
– 0.7–2.7 0.5–2.2 1.4–3.7
1 1.6 1.5 3.4
– 0.9–2.7 0.7–3.5 1.7–6.7
CI (95%)
Nodal status N N+
1 2.5
– 1.7–3.5
Tumor groups Luminal Basal-like HER1+ Basal-like HER1 HER2+
1 1.1 1.2 1.9
– 0.7–1.8 0.7–2.1 1.3–2.7
Tumor size T1 T2 T3 T4
1 1.6 1.8 2.4
– 1.1–2.3 1.0–3.1 1.4–4.1
Histological gradea I II III
1 1.8 1.8
– 1.2–2.8 1.1–3.
a
Fig. 1. Probability of overall survival (A) and relapse-free survival (B) in the 787 patients.
Relapse-free survival p 0.0001
p 0.0001
0.003
0.004
0.004
0.004
0.011
– – – –
– – –
Scarff–Bloom–Richardson criteria.
(p = 0.0001), but surprisingly there was little difference in lymphnode metastases (p = 0.6), which has also been described by other authors [19]. Thus, since both HER2+ and basal-like breast cancers carried a poorer prognosis, it is possible that these tumor subtypes could be associated with a predominantly hematogenous pattern of dissemination, rather than lymphatic. Our results demonstrated a distribution of breast cancer subtypes similar to that reported by other immunohistochemical studies [7]. In addition, our data are in accordance with previous reports indicating the higher prevalence of both HER2+ and basallike tumors and the lower prevalence of luminal tumors among younger and/or premenopausal women [19,20]. Likewise, our results are in line with the aforementioned studies demonstrating that luminal tumors (ER+) are associated with clinicopathological and biological parameters indicative of low tumor aggressiveness and a more favorable outcome. In contrast, and similar to the findings observed in some immunohistochemical studies [6,7,9,10], HER2+ tumors and basal-like tumors were associated with parameters indicative of tumor aggressiveness as well as a more unfavorable outcome in our study population. These findings were expected given the high expression of the cluster proliferation of genes in microarray analyses of basal-like and HER2+ subtype tumors [1,2,21,22]. It has recently been reported that the majority of ER /PR / HER2 cancers express cytokeratin CK5/6 and therefore belong to the basal subtype of breast carcinomas [16]. These cancers represent a poorly characterized subtype of tumor without a validated clinical assay able to identify them; therefore, and considering that half of the tumors of basal-like phenotype show an over-expression of HER1 [7,14–16,23], in the present study we recategorized this subtype with regard to their HER1 content. Thus, among these basallike, HER1+ tumors, there was a higher percentage of poorly differentiated tumors as compared with basal-like HER1 , suggesting biological differences between them. HER1 (EGFR or ErbB1) is a glycoprotein consisting of an extracellular domain that binds to different ligands, a short lypophilic transmembrane domain and an intracellular domain carrying tyrosine kinase activity [24]. The receptors belonging to this family, which also includes HER2, HER3 and HER4, are activated by dimerization, either between identical receptors (homodimerization) or between different members of the same family (heterodimerization) [25]. Several lines of research
J.M. Del Casar et al. / European Journal of Obstetrics & Gynecology and Reproductive Biology 141 (2008) 147–152
151
Fig. 2. Probability of overall survival and relapse-free survival in the patients with nodal status negative (A) and nodal status positive (B).
have established that HER1 acts as a cellular oncogene. Thus, it has been showed that the introduction of high levels of HER1 into cultured cells confers a malignant phenotype [26,27]. It has also been demonstrated that HER1 and its various ligands (EGF, TGF-a, amphiregulin, heparin-binding (HB)-EGF, heregulin, betacellulin) play an important role not only in cell proliferation, but also in a number of diverse processes likely to be significant during tumor progression, such as cell motility, cell adhesion, tissue invasion, cell survival, and angiogenesis [28]. More importantly, HER1 is also a target for several recently developed drugs, such as therapeutic antibodies (cetuximab) and small-molecule tyrosine kinase inhibitors (gefitinib or erlotinib). It has been shown that the molecular subtype and prognostic expression profile of a primary breast tumor are maintained throughout its metastatic process [29]. Therefore, future treatment decisions based on the expression profile of a primary tumor is a rational approach towards preventing the outgrowth of metastases. Accordingly, it has been suggested that the different breast tumor subtypes represent biologically distinct disease entities and may require different therapeutic strategies [30]. The luminal subtype of tumor is characterized by high expression of ER and genes regulated by estrogens, showing a high response rate to hormone-therapy. Likewise, it has been reported that therapies targeting the ER or HER2 oncogene would not be effective on basallike breast cancers because this subtype typically expresses neither of these proteins. Although there is no published data on how the different molecular classes of breast cancer respond to chemother-
apy, they have been associated with differences in pathologic response to neoadjuvant chemotherapy [31,32]. In addition, the HER2+ subtype has been associated with a relative resistance to some chemotherapeutic agents (CMF) and tamoxifen [33]. However, in the present study, we did not find a predictive value of the breast cancer subtype with regard to response to adjuvant systemic therapy (data not shown). Nevertheless, this study was not specifically designed for that purpose. In addition, breast cancer cases in this study were not treated with the anti-HER2 monoclonal antibody trastuzumab. In summary, we have been able to verify that by classifying breast tumors into four groups according to their ER, PR, HER2 and HER1 status, it is possible to obtain a major division of these tumors associated with differences in biological features and clinical behavior. Further researches are necessary to confirm these findings in other patient populations and to evaluate the predictive value of these classification criteria. References [1] Sorlie T, Perou CM, Tibshirani R, et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci USA 2001;98:10869–74. [2] Sorlie T, Tibshirani R, Parker J, et al. Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc Natl Acad Sci USA 2003;100:8418–23. [3] Bertucci F, Viens P, Hingamp P, Nasser V, Houlgatte R, Birnbaum D. Breast cancer revisited using DNA array-based gene expression profiling. Int J Cancer 2003;103:565–71.
152
J.M. Del Casar et al. / European Journal of Obstetrics & Gynecology and Reproductive Biology 141 (2008) 147–152
[4] van’t Veer LJ, Dai H, van de Vijver MJ, et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature 2002;415:530–6. [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 USA 2003;100:10393–8. [6] van de Rijn M, Perou CM, Tibshirani R, et al. Expression of cytokeratins 17 and 5 identifies a group of breast carcinomas with poor clinical outcome. Am J Pathol 2002;161:1991–6. [7] 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;10:5367–74. [8] Matos I, Dufloth R, Alvarenga M, Zeferino LC, Schmitt F. p63, cytokeratin 5, and P-cadherin: three molecular markers to distinguish basal phenotype in breast carcinomas. Virchows Arch 2005;447:688–94. [9] Callagy G, Cattaneo E, Daigo Y, et al. Molecular classification of breast carcinomas using tissue microarrays. Diagn Mol Pathol 2003;12:27–34. [10] Jacquemier J, Ginestier C, Rougemont J, et al. Protein expression profiling identifies subclasses of breast cancer and predicts prognosis. Cancer Res 2005;65:767–79. [11] Bloom HJ, Richardson WW. Histological grading and prognosis in breast cancer; a study of 1409 cases of which 359 have been followed for 15 years. Br J Cancer 1957;11:359–77. [12] Bradford MM. A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein–dye binding. Anal Biochem 1976;72:248–54. [13] Hedley DW, Shankey TV, Wheeless LL. DNA cytometry consensus conference. Cytometry 1993;14:471. [14] Korsching E, Packeisen J, Agelopoulos K, et al. Cytogenetic alterations and cytokeratin expression patterns in breast cancer: integrating a new model of breast differentiation into cytogenetic pathways of breast carcinogenesis. Lab Invest 2002;82:1525–33. [15] Livasy CA, Karaca G, Nanda R, et al. Phenotypic evaluation of the basal-like subtype of invasive breast carcinoma. Mod Pathol 2006;19:264–71. [16] Siziopikou KP, Cobleigh M. The basal subtype of breast carcinomas may represent the group of breast tumors that could benefit from EGFR-targeted therapies. Breast 2007;16:104–7. [17] Corte MD, Rodil JA, Vazquez J, et al. Clinical significance of the quantitative assessment of the cytosolic concentration of HER-2/neu protein in breast cancer by immunoenzymatic assay (ELISA). J Cancer Res Clin Oncol 2005;131:701–14.
[18] Quintela I, Corte MD, Allende MT, et al. Expression and prognostic value of EGFR in invasive breast cancer. Oncol Rep 2005;14:1655–63. [19] Calza S, Hall P, Auer G, et al. Intrinsic molecular signature of breast cancer in a population-based cohort of 412 patients. Breast Cancer Res 2006;8:R34. [20] Carey LA, Perou CM, Livasy CA, et al. Race, breast cancer subtypes, and survival in the Carolina Breast Cancer Study. JAMA 2006;295:2492–502. [21] Perou CM, Sorlie T, Eisen MB, et al. Molecular portraits of human breast tumours. Nature 2000;406:747–52. [22] Whitfield ML, Sherlock G, Saldanha AJ, et al. Identification of genes periodically expressed in the human cell cycle and their expression in tumors. Mol Biol Cell 2002;13:1977–2000. [23] Reis-Filho JS, Milanezi F, Steele D, et al. Metaplastic breast carcinomas are basal-like tumours. Histopathology 2006;49:10–21. [24] Ullrich A, Schlessinger J. Signal transduction by receptors with tyrosine kinase activity. Cell 1990;61:203–12. [25] Lemmon MA, Schlessinger J. Regulation of signal transduction and signal diversity by receptor oligomerization. Trends Biochem Sci 1994;19:459–63. [26] Velu T, Beguinot L, Vass W, et al. Epidermal-growth-factor-dependent transformation by a human EGF receptor proto-oncogene. Science 1987;238:1408– 10. [27] Di Marco E, Pierce J, Fleming T, et al. Autocrine interaction between TGF alpha and the EGF-receptor: quantitative requirements for induction of the malignant phenotype. Oncogene 1989;4:831–8. [28] Woodburn JR. The epidermal growth factor receptor and its inhibition in cancer therapy. Pharmacol Ther 1999;82:241–50. [29] Weigelt B, Hu Z, He X, et al. Molecular portraits and 70-gene prognosis signature are preserved throughout the metastatic process of breast cancer. Cancer Res 2005;65:9155–8. [30] Sorlie T, Wang Y, Xiao C, et al. Distinct molecular mechanisms underlying clinically relevant subtypes of breast cancer: gene expression analyses across three different platforms. BMC Genomics 2006;7:127. [31] Rouzier R, Perou CM, Symmans WF, et al. Breast cancer molecular subtypes respond differently to preoperative chemotherapy. Clin Cancer Res 2005;11: 5678–85. [32] Bertucci F, Finetti P, Rougemont J, et al. Gene expression profiling identifies molecular subtypes of inflammatory breast cancer. Cancer Res 2005;65: 2170–8. [33] Burstein HJ. The distinctive nature of HER2-positive breast cancers. N Engl J Med 2005;353:1652–4.
Contents lists available at ScienceDirect
European Journal of Obstetrics & Gynecology and Reproductive Biology journal homepage: www.elsevier.com/locate/ejogrb
Characterization of breast cancer subtypes by quantitative assessment of biological parameters: Relationship with clinicopathological characteristics, biological features and prognosis J.M. Del Casar a,b,c, A. Martı´n a, C. Garcı´a a, M.D. Corte a, A. Alvarez d, S. Junquera a, ˜ iz f, M.T. Allende c,d, F. Vizoso a,b,c,* L.O. Gonza´lez a,c,e, M. Bongera a, J.L. Garcı´a-Mun a
Unidad de Investigacio´n, Hospital de Jove, Gijo´n, Spain Servicio de Cirugı´a General, Hospital de Jove, Gijo´n, Spain c Instituto Universitario de Oncologı´a del Principado de Asturias, Oviedo, Spain d Servicio de Medicina Nuclear, Hospital Central de Asturias, Oviedo, Spain e Servicio de Anatomı´a Patolo´gica, Hospital de Jove, Gijo´n, Spain f Servicio de Cirugı´a General, Hospital Central de Asturias, Oviedo, Spain b
A R T I C L E I N F O
A B S T R A C T
Article history: Received 6 July 2007 Received in revised form 10 April 2008 Accepted 11 July 2008
Objectives: Gene expression analysis has identified several breast cancer subtypes, including luminal, epidermal growth factor receptor-2 positive (HER2+), and basal-like. To determine if our proposed molecular taxonomy correlates with biological and clinical behavior. This is based on four biological markers: estrogen and progesterone receptors (ER and PR, respectively), HER2 and the epidermal growth factor receptor-1 (HER1), all of them being determined by quantitative assays. Study design: The biological parameters were examined by enzyme immunoassay, radioligand-binding assay or ELISA, in tumors from 787 patients with invasive breast cancer. Patients were prospectively evaluated over a median follow-up period of 50 months. Subtype definitions were as follows: luminal (ER+), HER2+ (HER2+, ER , PgR ) and basal-like (HER2 , ER , PgR ). In addition, we divided basal tumors into two groups based on their HER1 status. Results: A 55.8% of tumors were of luminal type, 11.9% basal-like HER1+, 10.7 basal-like HER1 , and the remainder 21.6% HER2+. Both HER2+ and basal-like subtypes were more frequent in younger and premenopausal women, showing a higher percentage of cases of poorly differentiated tumors and higher S-phase fraction, when compared with those of luminal subtype. Multivariate analysis demonstrated that the subtype of tumor was related to both relapse and overall survival, being those of luminal subtype associated with the best prognosis. Conclusions: Through the classification of breast tumors in four groups, according to their ER, PgR, HER2 and HER1 status, it is possible to obtain a major division of breast tumors associated with significant differences in biological features and clinical behavior. ß 2008 Elsevier Ireland Ltd. All rights reserved.
Keywords: Breast cancer Epidermal growth factor receptor HER1 HER2 Prognosis
1. Introduction With the increasing use of breast cancer screening programs, more early-stage tumors are being diagnosed, thus creating a need for new prognostic and therapy-directing tools and therefore avoiding under- and over-treatment of large patient cohorts. There is some difficulty in determining the prognosis of these women
* Corresponding author at: Hospital de Jove, Servicio de Cirugı´a General, Avda. Eduardo Castro s/n, Apartado 385, 33290 Gijo´n, Spain. Tel.: +34 985315710. E-mail address: [email protected] (F. Vizoso). 0301-2115/$ – see front matter ß 2008 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.ejogrb.2008.07.021
since breast cancer is a heterogeneous disease encompassing a wide range of clinical behaviors, even in patient groups that appear to be clinically similar. Despite a number of classical prognostic variables such as nodal status, tumor size, age and hormone receptor status, additional and predictive factors need to be identified in order to improve risk classification and thereby develop a more rational management of breast cancer patients. Currently available tumor classification systems rely on classical histopathology findings; however, although the grade of malignancy is a prognostic indicator, it is evident that the molecular heterogeneity of these tumors is not reflected only by their histological appearance.
J.M. Del Casar et al. / European Journal of Obstetrics & Gynecology and Reproductive Biology 141 (2008) 147–152
148
Recent DNA microarray profiling studies on frozen breast cancer samples have identified distinct subtypes of breast carcinomas associated with different clinical outcomes [1–3]. Using an intrinsic set of 534 genes, Sorlie et al. analyzed the expression profiles of 115 independent breast tumors samples and categorized breast tumors into four different groups: luminal (estrogen receptor positive (ER+)), HER2 overexpressing, normal breast-like and basal-like. In addition, several studies have shown the potential clinical value of this classification. Breast cancers of the basal-like subtype comprise about 19% of tumors and have a poor prognosis as assessed by relapse-free survival [2,4,5]. This seems to indicate that large-scale molecular techniques such as DNA microarrays contribute to the understanding of the molecular complexity of breast cancer [3]. Nevertheless, the cost, complexity, and interpretation of DNA microarrays make them currently unsuitable for routine use in standard clinical settings. Additional opportunities to identify and/ or validate molecular signatures are provided by the molecular profiling of breast cancer using a limited number of protein biomarkers, since basal epithelial cells can be stained with antibodies to keratins 5/6, whereas luminal epithelial cells stain with antibodies against keratins 8/18 [6–8]. Recent immunohistochemical studies on formalin-fixed paraffin-embedded tumor archives have validated this classification as well as the prevalence and poor prognosis of basal-like breast cancers [6,7,9,10]. However, at present there are no studies on the possible clinical value of quantitative assays in classifying subtypes of breast carcinomas.
Consequently, our aim is to determine if our proposed molecular taxonomy correlates with biological and clinical behavior. This is based on four biological markers: estrogen and progesterone receptors (ER and PR, respectively), HER2 and the epidermal growth factor receptor-1 (HER1), all of them being determined by quantitative assays. 2. Materials and methods 2.1. Patient characteristics and tissue specimen handling This study is comprised of 787 consecutive women with a histologically confirmed diagnosis of invasive breast cancer, who were treated at Hospital de Jove (Gijo´n, Spain) and at Hospital Central de Asturias (Oviedo, Spain), between 1990 and 2002. The median age was 59 years (range, 30–92 years). None of them had undergone any neoadjuvant therapy nor shown evidence of any other malignant tumors or distant metastases at the time of diagnosis. Patient characteristics with respect to age, menopausal status, clinical tumor stage, histopathology, proliferative and biological parameters are listed in Table 1. Histological grade was determined according to criteria reported by Bloom and Richardson [11], whereas nodal status was assessed histopathologically. Women were treated according to the guidelines used in our institution. All patients were followed for disease recurrence and survival status by clinical and biological studies every 3 months for
Table 1 Relationship between patient characteristics and breast cancer subtypes in 787 patients Patient and tumor characteristics
N (%) Luminal
Basal-like HER1+
Basal-like HER1
HER2+
Total
439 (55.7)
94 (11.94)
84 (10.67)
170 (21.6)
Tumor size T1 T2 T3 T4
181 201 35 22
34 39 13 8
34 38 4 8
Age (years) <59 >59
191 (43.5) 248 (56.5)
57 (60.6) 37 (39.4)
54 (64.3) 30 (35.7)
103 (60.6) 67 (39.4)
Menopausal status Premenopausal Postmenopausal
112 (25.5) 327 (74.5)
35 (37.2) 59 (62.8)
35 (41.7) 49 (58.3)
64 (37.6) 106 (62.4)
Histological type Ductal Lobular Others
388 (88.4) 27 (6.2) 24 (5.5)
81 (86.2) 7 (7.4) 6 (6.4)
68 (81) 7 (8.3) 9 (10.7)
155 (91.2) 10 (5.9) 5 (2.9)
Histological gradea I II III Unknown
127 225 66 21
14 41 33 6
23 32 21 8
Nodal status Negative Positive
242 (55.1) 197 (44.9)
52 (55.3) 42 (44.7)
39 (46.4) 45 (53.6)
92 (54.1) 78 (45.9)
Ploidy Diploid Aneuploid Unknown
107 (24.4) 157 (35.8) 175 (39.9)
18 (19.1) 34 (36.2) 42 (44.7)
27 (32.1) 20 (23.8) 37 (41.7)
35 (20.6) 73 (42.9) 62 (36.5)
S-phase <7.69b >7.69b Unknown
159 (36.2) 119 (27.1) 161 (36.7)
21 (22.3) 32 (34) 41 (43.6)
22 (26.2) 27 (32.1) 35 (41.7)
43 (25.3) 67 (39.4) 60 (35.3)
a b
Scarff–Bloom–Richardson criteria. Median S-phase fraction value.
p
0.290 (41.2) (45.8) (8) (5)
(36.2) (41.5) (13.8) (8.5)
(40.5) (45.2) (4.8) (9.5)
75 71 11 13
(44.1) (41.8) (6.5) (7.6) 0.0001
0.001
0.26
0.0001 (28.9) (51.3) (15) (4.8)
(14.9) (43.6) (35.1) (6.4)
(27.4) (38.1) (25) (9.5)
39 70 54 7
(22.9) (41.2) (31.8) (4.1) 0.52
0.027
0.03
J.M. Del Casar et al. / European Journal of Obstetrics & Gynecology and Reproductive Biology 141 (2008) 147–152
the first 2 years and then yearly. Radiological studies were performed yearly or when considered necessary. The median follow-up period was 54 months (range, 6–288 months). The endpoint was death secondary to tumor progression. The median follow-up period in surviving patients was 58 months. One hundred and ninety five patients developed tumor recurrence and 102 (52.3%) died as a consequence of tumor progression. The study adhered to national regulations and was approved by our institution’s Ethics and Investigation Committee. 2.2. Tissue processing and assays Breast carcinoma tissue samples were obtained at the time of surgery from 787 patients. Immediately after surgical resection, samples were processed for pathological examination while the remainder of the tissue was washed with cold saline solution, divided into aliquots, rapidly transported on ice to the laboratory and stored at 70 8C pending biochemical studies. The tumor tissue samples were obtained with informed consent from the patients. The specimens obtained from neoplastic tissues were pulverized with a microdismembrator (Braun Biotech International, Melsungen, Germany) at 70 8C and homogenized in TRIS– hydrochloride buffer (10 mM of TRIS, 1.5 mM of EDTA, 10% glycerol, 0.1% of monothioglycerol). Homogenates, kept at 4 8C, were centrifuged at low speed (800 g for 10 min, at 4 8C), and the supernatant was ultracentrifuged at 100,000 g for 60 min, at 4 8C. The protein content was quantified by the Bradford method [12], using bovine albumin as the standard (Sigma Chemical Co., St. Louis, USA) and the Bio-Rad Protein Assay Dye Reagent Concentrate (Bio-Rad Laboratories, Munich, Germany). 2.3. Flow cytometry DNA content was evaluated by flow cytometry in all tumors (Bectron Dickinson, San Jose´, CA, USA), on nuclei stained with propidium iodide. DNA ploidy was expressed as DNA-index. Tumors were considered diploid when the DNA-index obtained was 1.0, and aneuploid for any diverging value, including tetraploid tumors, with a DNA-index of 2.0. Proliferative activity was expressed as the fraction of cells in the ‘‘S’’ phase of the cell cycle and calculated with the CellFit software program (Bectron Dickinson), according to the DNA Cytometry Consensus Conference recommendations [13]. Median S-phase fraction value was used as the cut-off point. Tumors were also divided into those with a high or a low S-phase fraction. 2.4. Assays ER and PR receptor measurements were performed on cytosol extracts by using a solid-phase enzyme immunoassay based on the ‘‘sandwich’’ principle (ER-EIA and PR-EIA from Abbot Laboratories, Diagnostics Division, Wiesbaden, Germany). ER and PR values were expressed as femtomols per milligram of protein. HER-1 was expressed as fmol/mg protein. HER2 was analyzed in membranous samples by an ELISA (Oncogene Research Products, Boston, MA, USA). Samples found to contain greater than 1200 NHU/mg of protein homogenate (i.e., outside the range of the standard curve) were diluted with sample diluents, so that the HER2 concentration would fall within the range spanned by the standard curve and assayed again. 2.5. Definition of breast cancer subtypes Although breast cancer subtypes were originally identified by gene expression analysis using DNA microarrays [1–3] and
149
immunohistochemical markers had been verified against gene expression profiles to estimate the prevalence of the intrinsic subtypes in large populations [6,7,9,10], large-scale subtyping using quantitative assessment of biological markers is not currently feasible. For this reason, we investigated the prognostic interest of these classification criteria by measuring some key biological markers, such as ER, HER2 and HER1, by enzyme immunoassay, radioligand-binding assay and ELISA, respectively. We established the following subtypes: luminal (ER+), HER2+ (HER2+, ER , PR ) and basal-like (ER , PR , HER2 ). In addition, we recategorized basal tumors into two groups based on their HER1 status, since this division was designed as an alternative criteria for classifying tumors of basal-like subtype [7,14–16]. For data analysis, a value higher than 10 fmol/mg total protein was considered as positive for ER and PR, whereas a value of 1200 NHU/ mg protein for HER2 and the median value for HER1, were taken, respectively, as cut-off points in consideration of their clinical value as reported in previous studies [17,18]. 2.6. Statistical analysis Patients were subdivided into groups based on the definition of breast cancer subtypes. Differences in percentages were calculated with the chi-square test. Differences between curves were evaluated with the log rank test. Cox’s regression model was also used to examine several combinations and interactions of different prognostic factors in a multivariate analysis. In the multivariate analysis, only parameters that achieve statistical significance for relapse-free survival or overall survival in the log rank test were included. The SPSS 11.5 program (SPSS Inc., Chicago, USA) was used for all calculations. Statistical significance was considered at 5% probability level (p 0.05). 3. Results A total of 439 tumors (55.8%) were of the luminal type, 94 (11.9%) were basal-like HER1+, 84 (10.7%) basal-like HER1 , and the remainder 170 (21.6%) were HER2+. Table 1 shows the clinicopathological characteristics of these four groups. Statistical analysis showed that there were significant differences in the distribution of breast cancer subtypes in relation to age, menopausal status and histological tumor grade. Thus, the percentage of luminal subtype of tumors was higher in older and postmenopausal patients, whereas the remainder of the tumor subtypes were more frequent among younger and premenopausal women. The luminal subtype showed a higher percentage of cases with well-differentiated tumors, whereas the percentage of poorly differentiated tumors was higher in the other types of tumors. Likewise, as Table 1 shows, luminal tumors showed a significantly lower S-phase fraction when compared with the other subtypes of breast cancer. The potential relationship between the different subtypes of breast carcinomas and both relapse-free survival and overall survival was evaluated in all of the patients included in the present study. Fig. 1A and B shows both relapse-free survival and overall survival curves, respectively, considering the already mentioned three groups of patients. Statistical analysis demonstrated significant differences between these survival curves (p = 0.02 and 0.05, respectively). The luminal subtype of tumors was associated with a better prognosis, whereas HER2+ tumors had a poor prognosis. Survival analyses were also performed separately in the different subgroups of patients stratified according to the nodal status. Thus, significant and similar differences with regard to the subtypes of breast carcinomas were found in the nodenegative subgroup, whereas only significant differences were
150
J.M. Del Casar et al. / European Journal of Obstetrics & Gynecology and Reproductive Biology 141 (2008) 147–152 Table 2 Multivariate analysis of the association between different clinicopathological parameters and relapse-free survival and overall survival Tumor characteristics
found for relapse-free survival in the subgroup of patients with node-positive tumors (Fig. 2). We also looked into the possible prognostic value of classifying the luminal type of tumors into luminal A (ER+, HER2 ) and luminal B (ER+, HER2+) subtypes, but significant differences between both subgroups were not found (data not shown). On the other hand, our data did not show significant differences in both relapse-free and overall survival curves between HER1+ and HER1 tumors, when only basal-like tumors were considered (data not shown). Multivariate analysis demonstrated that tumor size, nodal status and tumor subtype were all associated with both relapse and overall survival in the group of patients as a whole. Likewise, the histological grade was also related with relapse-free survival (Table 2). 4. Discussion Currently, there are few data on the possible clinical value of quantitative assays to classify subtypes of breast carcinomas. In the present work, we established a classification based on criteria of cancer subtypes and considering four biological markers: ER, PR, HER2 and HER1, which were assessed by quantitative techniques (enzyme immunoassay, radioligand-binding assay and ELISA). Our results demonstrated that this definition of breast cancer subtypes allows the identification of breast carcinomas displaying different tumor behavior. We consider it remarkable that these subtypes vary significantly in terms of age (p = 0.0001), menopausal status (p = 0.003), tumor grade (p = 0.0001), and S-phase fraction
Overall survival
RR
RR
CI (95%)
1 3.8
– 2.3–6.3
1 1.4 1.1 2.3
– 0.7–2.7 0.5–2.2 1.4–3.7
1 1.6 1.5 3.4
– 0.9–2.7 0.7–3.5 1.7–6.7
CI (95%)
Nodal status N N+
1 2.5
– 1.7–3.5
Tumor groups Luminal Basal-like HER1+ Basal-like HER1 HER2+
1 1.1 1.2 1.9
– 0.7–1.8 0.7–2.1 1.3–2.7
Tumor size T1 T2 T3 T4
1 1.6 1.8 2.4
– 1.1–2.3 1.0–3.1 1.4–4.1
Histological gradea I II III
1 1.8 1.8
– 1.2–2.8 1.1–3.
a
Fig. 1. Probability of overall survival (A) and relapse-free survival (B) in the 787 patients.
Relapse-free survival p 0.0001
p 0.0001
0.003
0.004
0.004
0.004
0.011
– – – –
– – –
Scarff–Bloom–Richardson criteria.
(p = 0.0001), but surprisingly there was little difference in lymphnode metastases (p = 0.6), which has also been described by other authors [19]. Thus, since both HER2+ and basal-like breast cancers carried a poorer prognosis, it is possible that these tumor subtypes could be associated with a predominantly hematogenous pattern of dissemination, rather than lymphatic. Our results demonstrated a distribution of breast cancer subtypes similar to that reported by other immunohistochemical studies [7]. In addition, our data are in accordance with previous reports indicating the higher prevalence of both HER2+ and basallike tumors and the lower prevalence of luminal tumors among younger and/or premenopausal women [19,20]. Likewise, our results are in line with the aforementioned studies demonstrating that luminal tumors (ER+) are associated with clinicopathological and biological parameters indicative of low tumor aggressiveness and a more favorable outcome. In contrast, and similar to the findings observed in some immunohistochemical studies [6,7,9,10], HER2+ tumors and basal-like tumors were associated with parameters indicative of tumor aggressiveness as well as a more unfavorable outcome in our study population. These findings were expected given the high expression of the cluster proliferation of genes in microarray analyses of basal-like and HER2+ subtype tumors [1,2,21,22]. It has recently been reported that the majority of ER /PR / HER2 cancers express cytokeratin CK5/6 and therefore belong to the basal subtype of breast carcinomas [16]. These cancers represent a poorly characterized subtype of tumor without a validated clinical assay able to identify them; therefore, and considering that half of the tumors of basal-like phenotype show an over-expression of HER1 [7,14–16,23], in the present study we recategorized this subtype with regard to their HER1 content. Thus, among these basallike, HER1+ tumors, there was a higher percentage of poorly differentiated tumors as compared with basal-like HER1 , suggesting biological differences between them. HER1 (EGFR or ErbB1) is a glycoprotein consisting of an extracellular domain that binds to different ligands, a short lypophilic transmembrane domain and an intracellular domain carrying tyrosine kinase activity [24]. The receptors belonging to this family, which also includes HER2, HER3 and HER4, are activated by dimerization, either between identical receptors (homodimerization) or between different members of the same family (heterodimerization) [25]. Several lines of research
J.M. Del Casar et al. / European Journal of Obstetrics & Gynecology and Reproductive Biology 141 (2008) 147–152
151
Fig. 2. Probability of overall survival and relapse-free survival in the patients with nodal status negative (A) and nodal status positive (B).
have established that HER1 acts as a cellular oncogene. Thus, it has been showed that the introduction of high levels of HER1 into cultured cells confers a malignant phenotype [26,27]. It has also been demonstrated that HER1 and its various ligands (EGF, TGF-a, amphiregulin, heparin-binding (HB)-EGF, heregulin, betacellulin) play an important role not only in cell proliferation, but also in a number of diverse processes likely to be significant during tumor progression, such as cell motility, cell adhesion, tissue invasion, cell survival, and angiogenesis [28]. More importantly, HER1 is also a target for several recently developed drugs, such as therapeutic antibodies (cetuximab) and small-molecule tyrosine kinase inhibitors (gefitinib or erlotinib). It has been shown that the molecular subtype and prognostic expression profile of a primary breast tumor are maintained throughout its metastatic process [29]. Therefore, future treatment decisions based on the expression profile of a primary tumor is a rational approach towards preventing the outgrowth of metastases. Accordingly, it has been suggested that the different breast tumor subtypes represent biologically distinct disease entities and may require different therapeutic strategies [30]. The luminal subtype of tumor is characterized by high expression of ER and genes regulated by estrogens, showing a high response rate to hormone-therapy. Likewise, it has been reported that therapies targeting the ER or HER2 oncogene would not be effective on basallike breast cancers because this subtype typically expresses neither of these proteins. Although there is no published data on how the different molecular classes of breast cancer respond to chemother-
apy, they have been associated with differences in pathologic response to neoadjuvant chemotherapy [31,32]. In addition, the HER2+ subtype has been associated with a relative resistance to some chemotherapeutic agents (CMF) and tamoxifen [33]. However, in the present study, we did not find a predictive value of the breast cancer subtype with regard to response to adjuvant systemic therapy (data not shown). Nevertheless, this study was not specifically designed for that purpose. In addition, breast cancer cases in this study were not treated with the anti-HER2 monoclonal antibody trastuzumab. In summary, we have been able to verify that by classifying breast tumors into four groups according to their ER, PR, HER2 and HER1 status, it is possible to obtain a major division of these tumors associated with differences in biological features and clinical behavior. Further researches are necessary to confirm these findings in other patient populations and to evaluate the predictive value of these classification criteria. References [1] Sorlie T, Perou CM, Tibshirani R, et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci USA 2001;98:10869–74. [2] Sorlie T, Tibshirani R, Parker J, et al. Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc Natl Acad Sci USA 2003;100:8418–23. [3] Bertucci F, Viens P, Hingamp P, Nasser V, Houlgatte R, Birnbaum D. Breast cancer revisited using DNA array-based gene expression profiling. Int J Cancer 2003;103:565–71.
152
J.M. Del Casar et al. / European Journal of Obstetrics & Gynecology and Reproductive Biology 141 (2008) 147–152
[4] van’t Veer LJ, Dai H, van de Vijver MJ, et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature 2002;415:530–6. [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 USA 2003;100:10393–8. [6] van de Rijn M, Perou CM, Tibshirani R, et al. Expression of cytokeratins 17 and 5 identifies a group of breast carcinomas with poor clinical outcome. Am J Pathol 2002;161:1991–6. [7] 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;10:5367–74. [8] Matos I, Dufloth R, Alvarenga M, Zeferino LC, Schmitt F. p63, cytokeratin 5, and P-cadherin: three molecular markers to distinguish basal phenotype in breast carcinomas. Virchows Arch 2005;447:688–94. [9] Callagy G, Cattaneo E, Daigo Y, et al. Molecular classification of breast carcinomas using tissue microarrays. Diagn Mol Pathol 2003;12:27–34. [10] Jacquemier J, Ginestier C, Rougemont J, et al. Protein expression profiling identifies subclasses of breast cancer and predicts prognosis. Cancer Res 2005;65:767–79. [11] Bloom HJ, Richardson WW. Histological grading and prognosis in breast cancer; a study of 1409 cases of which 359 have been followed for 15 years. Br J Cancer 1957;11:359–77. [12] Bradford MM. A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein–dye binding. Anal Biochem 1976;72:248–54. [13] Hedley DW, Shankey TV, Wheeless LL. DNA cytometry consensus conference. Cytometry 1993;14:471. [14] Korsching E, Packeisen J, Agelopoulos K, et al. Cytogenetic alterations and cytokeratin expression patterns in breast cancer: integrating a new model of breast differentiation into cytogenetic pathways of breast carcinogenesis. Lab Invest 2002;82:1525–33. [15] Livasy CA, Karaca G, Nanda R, et al. Phenotypic evaluation of the basal-like subtype of invasive breast carcinoma. Mod Pathol 2006;19:264–71. [16] Siziopikou KP, Cobleigh M. The basal subtype of breast carcinomas may represent the group of breast tumors that could benefit from EGFR-targeted therapies. Breast 2007;16:104–7. [17] Corte MD, Rodil JA, Vazquez J, et al. Clinical significance of the quantitative assessment of the cytosolic concentration of HER-2/neu protein in breast cancer by immunoenzymatic assay (ELISA). J Cancer Res Clin Oncol 2005;131:701–14.
[18] Quintela I, Corte MD, Allende MT, et al. Expression and prognostic value of EGFR in invasive breast cancer. Oncol Rep 2005;14:1655–63. [19] Calza S, Hall P, Auer G, et al. Intrinsic molecular signature of breast cancer in a population-based cohort of 412 patients. Breast Cancer Res 2006;8:R34. [20] Carey LA, Perou CM, Livasy CA, et al. Race, breast cancer subtypes, and survival in the Carolina Breast Cancer Study. JAMA 2006;295:2492–502. [21] Perou CM, Sorlie T, Eisen MB, et al. Molecular portraits of human breast tumours. Nature 2000;406:747–52. [22] Whitfield ML, Sherlock G, Saldanha AJ, et al. Identification of genes periodically expressed in the human cell cycle and their expression in tumors. Mol Biol Cell 2002;13:1977–2000. [23] Reis-Filho JS, Milanezi F, Steele D, et al. Metaplastic breast carcinomas are basal-like tumours. Histopathology 2006;49:10–21. [24] Ullrich A, Schlessinger J. Signal transduction by receptors with tyrosine kinase activity. Cell 1990;61:203–12. [25] Lemmon MA, Schlessinger J. Regulation of signal transduction and signal diversity by receptor oligomerization. Trends Biochem Sci 1994;19:459–63. [26] Velu T, Beguinot L, Vass W, et al. Epidermal-growth-factor-dependent transformation by a human EGF receptor proto-oncogene. Science 1987;238:1408– 10. [27] Di Marco E, Pierce J, Fleming T, et al. Autocrine interaction between TGF alpha and the EGF-receptor: quantitative requirements for induction of the malignant phenotype. Oncogene 1989;4:831–8. [28] Woodburn JR. The epidermal growth factor receptor and its inhibition in cancer therapy. Pharmacol Ther 1999;82:241–50. [29] Weigelt B, Hu Z, He X, et al. Molecular portraits and 70-gene prognosis signature are preserved throughout the metastatic process of breast cancer. Cancer Res 2005;65:9155–8. [30] Sorlie T, Wang Y, Xiao C, et al. Distinct molecular mechanisms underlying clinically relevant subtypes of breast cancer: gene expression analyses across three different platforms. BMC Genomics 2006;7:127. [31] Rouzier R, Perou CM, Symmans WF, et al. Breast cancer molecular subtypes respond differently to preoperative chemotherapy. Clin Cancer Res 2005;11: 5678–85. [32] Bertucci F, Finetti P, Rougemont J, et al. Gene expression profiling identifies molecular subtypes of inflammatory breast cancer. Cancer Res 2005;65: 2170–8. [33] Burstein HJ. The distinctive nature of HER2-positive breast cancers. N Engl J Med 2005;353:1652–4.