The impact of the genomic imbalances on the clinical outcomeof 34 patients with lymph-node positive high-risk breast cancer (HRBC) was investigated using comparative genomic hybridization. All of the patients were uniformly treated with high-dose chemotherapy and autologous stem cell transplantation. The average number of chromosomal imbalances per tumor was 11 (range, 2–24), including DNA overrepresentation on chromosomes 1q (59%), 17q (38%), 8q and 16p (35% each), 20q (32%), and 19p (26%), and genomic losses involving 9p and 18q (41%), 8p, 11q, and 18p (38%), 17p (32%), 4p and Xq (29%), and 16q (26%). The most significant association among genomic changes and clinical-pathological features was the correlation of the loss of 8p with progesterone receptor positivity (P < 0.005). With a median follow-up time of 74 months, 15 patients (44%) have relapsed. In the univariate analysis, patients with gain/amplification of 17q including the HER-2/neu gene locus had a longer disease-free survival (P = 0.02), whereas those with genomic loss of 18p had a higher probability of relapse (P = 0.003). In multivariate analysis, the loss of 18p was the only parameter correlated with shorter disease-free survival (relative risk, 4.8; 95% confidence interval, 1.57–14.8; P = 0.006). In summary, our data indicate that the tumoral genomic profile may represent a valuable marker for predicting the clinical outcome in HRBC. Furthermore, the genomic loss of 18p may identify a poor prognostic subgroup of patients with HRBC.

The presence of axillary lymph nodes affected at diagnosis is the most significant factor in overall survival of breast cancer patients (1). Adjuvant chemotherapy has been demonstrated to improve outcome of these patients, but it is still controversial whether the use of HDC3 followed by ASCT may be beneficial (2, 3, 4, 5). Little is known about the impact of the tumor genetic changes on the outcome of patients with lymph node-positive HRBC. Most studies have evaluated single genetic markers that in some cases have been associated with increased risk of relapse (6, 7, 8, 9). Despite these efforts, based on current knowledge it is not possible to predict the outcome of patients with HRBC after intensive therapy.

Using CGH, tumors can be screened for DNA copy number variation genome-wide (10). This technique has revealed typical aberrant genomic profiles that include amplification and deletion sites unknown previously in most cancer categories (11, 12). In breast carcinomas, distinct patterns of genomic imbalances have been described in the different clinical-pathological subgroups (13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27). However, the correlation of the CGH data with patient survival has been scarce. Isola et al.(14) reported that genetic aberrations detected by CGH predict outcome in lymph node-negative breast cancer. In a recent report, genomic profiles were valuable prognostic parameters in patients with HRBC (21). The identification of recurrent genomic changes associated with the outcome of patients with HRBC would reveal novel clinically useful markers.

We report on the CGH analysis of a group of patients with lymph node-positive HRBC treated with a uniform protocol. Our aims were to define the pattern of genomic imbalances in this cohort, to correlate CGH findings with clinical-pathological features, and to identify possible genetic aberrations that might influence in patient outcome.

Tumor Samples.

Breast tumor samples obtained at diagnosis from 34 patients were studied. They were consecutively diagnosed at HRBC stages II or III. Those with >10 lymph nodes affected at diagnosis (n = 24) received six courses of FAC/FEC (5-fluorouracyl 600 mg/m2/day and doxorubicin/epirubicin 50/75 mg/m2/day, respectively, and cyclophosphamide 600 mg/m2/day), whereas patients with 4–10 lymph nodes affected (n = 10) received induction chemotherapy (four courses of FEC 75), followed by breast resection and two additional courses of FEC 75. Subsequently, all of them received pretransplant conditioning chemotherapy regimen (STAMP-V or CEM) followed by ASCT. Median follow-up time after diagnosis was 74 months (range, 18–96). The clinical and pathological characteristics of the patients are shown in Table 1.

CGH.

DNA was extracted from frozen and paraffin-embedded tumor tissues using standard procedures. CGH analysis was performed as described previously (28). Chromosomal imbalances were interpreted as genomic gains when DNA tumor:test ratio exceeded 1.2, genomic losses when the ratio was <0.8, and gene amplifications when the ratio was >1.5. The Imaging Software QUIPS XL Workstation (Vysis, Downers Grove, IL) was used for analysis interpretation.

FISH, Western Blot, and IHC Analyses.

These procedures were performed to evaluate gene amplification and/or overexpression of HER-2/neu gene in the tumor samples. FISH methods have been reported previously (29). The PathVysion HER-2 DNA Probe kit (Vysis) was used on paraffin-fixed tissues following manufacturer’s instructions. IHC studies were performed on paraffin-embedded tissue blocks using the HercepTest (DAKO, Oslo, Norway). For immunoblotting analysis, protein extraction and blotting were performed as reported (30). The anti-HER-2/neu monoclonal antibody clone CB11 (Biogenex, San Carlos, CA) was used.

Statistical Analyses.

Significant correlation between the genomic imbalances with themselves and with clinical-pathological parameters were analyzed through 2 × 2 contingency tables using Pearson’s χ2 test unless there was an inadequate number of observations, in which case a Fisher’s exact test was used. All of the resulting Ps were two-tailed. DFS time was calculated according to the Kaplan-Meier survival curves and Ps with the log-rank test. Multivariate analysis using the Cox regression model was performed only on the variables with a P <0.05 in the univariate analyses. Both backward and forward analyses removed the same nonsignificant variables. Finally, the factors were removed one at time, based on the Wald test that was used to determine the level of significance; only statistically significant factors remained (P < 0.05). All of the clinical variables included in statistical analysis were dichotomized, i.e., estrogen and progesterone receptors were considered positive or negative when protein level were higher or lower than 10 fmol/mg, or age that was considered as ≤50 or >50 years. The statistical analyses were carried out using SPSS 10.0 software for Windows 98.

All 34 of the tumors showed genomic changes (Fig. 1). The average number of chromosomal imbalances per tumor was 11 (range, 2–24), including 5 gains (0–11) and 6 losses (0–15). A variable spectrum of genomic aberrations occurring across the entire genome was observed, including DNA overrepresentation on chromosomes 1q (59%), 17q (38%), 8q (35%), 16p (35%), 20q (32%), 19p (26%), and 11q (24%), and chromosomal losses involving 9p (41%), 18q (41%), 18p (38%), 8p (38%), 11q (38%), 17p (32%), Xq (29%), 4p (29%), 16q (26%), 4q (24%), and 22q (24%). In addition, three amplification events were observed in 6q21-q22, 8q24, and 20q13.

A number of associations among the most common genomic changes were detected: the loss of chromosome 8p and gain of 8q (P = 0.002), possibly as a consequence of an isochromosome 8q; losses of 18p and 9p (P = 0.01) or 4q (P = 0.002); losses of 18q and 9p (P = 0.005); and loss of 18q and gain of 20q (P = 0.002; Table 2). Significant correlations between recurrent genetic changes and clinical-pathological characteristics were investigated. Loss of 8p was significantly correlated with progesterone receptor positivity (P < 0.005). In addition, gain on chromosome 8q was detected in 73% of tumors and was correlated with stage III, whereas all of the samples with 19p gain corresponded with tumors in stage II; however, the few tumors in the study prevented us to adequately perform the χ2 test. There was no relationship between any other single chromosomal abnormality and the clinical-pathological variables, including changes occurred at high frequency such as gains of 1q, 17q, 16p, and 20q, and losses of 11q and 17p.

With a median follow-up from diagnosis of 74 months (range, 18–96), 19 patients (56%) are alive, and disease-free and 15 patients (44%) have relapsed. DFS for the whole series is shown in Fig. 2. Clinical-pathological features and genomic imbalances were evaluated in Kaplan-Meier survival curves to identify factors associated with DFS after diagnosis. There was no correlation between the total number of genomic imbalances and the outcome of patients. However, the number of genomic losses was associated with inferior outcome: patients with tumors containing <4 losses had a better DFS than those with ≥4 (P = 0.03; Fig. 3,A). When individual genomic imbalances were analyzed separately, two different associations were found. Gain of chromosomal material on 17q was correlated with a lower risk of relapse (P = 0.02), whereas patients with tumors displaying losses of chromosome 18p showed higher risk of relapse (P = 0,003; Fig. 3, B and C). No other association between chromosomal aberrations and DFS was found. A multivariate analysis (Cox model) was applied to analyze those parameters previously found statistically significant in the univariate analysis. Both backward and forward analyses retained only the loss of 18p associated with increased risk of relapse (RR = 4.8; 95% CI, 1.57–14.8; P = 0.006). The correlation of gain of 17q with superior DFS retained a borderline significance (RR = 3.24; 95% CI, 0.87–12.10; P = 0.06) in the multivariate analysis, whereas the number of genomic losses was not statistically significant (P = 0.146)

Because the HER-2/neu gene is located in band 17q12, we evaluated the status of this gene in the patients. All but one of the samples with genomic gain of 17q showed amplification of HER-2/neu gene documented by FISH and/or augmented protein expression according to immunoblotting or IHC. Among the 21 remaining tumors without genomic abnormalities of 17q, 5 had HER-2/neu alteration (data not shown). No differences in DFS were observed when patients with and without HER-2/neu abnormality detected by FISH, immunoblotting, or IHC were compared.

Patients with lymph node-positive breast cancer have markedly different clinical courses and treatment responses from those without. In this cohort, the use of HDC and ASCT is currently being assessed (2, 3, 4, 5, 6). Within this subgroup, whether genetic changes may have an impact on patient survival is unknown. We report here that the pattern of genomic imbalances may be correlated with different clinical outcome in patients with lymph node-positive HRBC treated with HDC and ASCT. Our results also show that the median number of genomic aberrations per tumor was higher than in other CGH studies of breast tumors (see Table 2 for references). This may reflect the advanced clinical stage and the aggressive histological grade (II and III) of most patients studied herein, with subgroups reported to show more genomic changes than other categories (18, 21).

The pattern of genomic aberrations found in our study did not differ significantly from other CGH data reported previously (13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27). The most common regions of genomic gain were 1q, 17q, 8q, 20q, and 16p. These aberrations occurred in the majority of reports independently from the clinical-pathological features, possibly indicating that these gains occurred at all stages of tumor development. However, the pattern of genomic losses was more variable than in series reported previously. Some of the common deletions observed in our study (9p, 18q, and 18p) were rarely seen in other reports, reflecting that they may develop primarily in patients with advanced or aggressive disease. A summary of the genomic imbalances reported in previous CGH analyses of breast cancer is shown in Table 3. Despite the few patients in the series, we found some associations among genetic changes and clinical-pathological characteristics. The loss of 8p was correlated with positive progesterone receptors. This association showed a small P (<0.005) in the Fisher’s exact test, therefore supporting that it is not coincidental. Other correlation included the gain of 8q that was frequent in tumors in stage III. This alteration has been associated with tumor progression (14, 20) and is present not only in the majority of breast tumors but also in other malignancies (11). On the contrary, gain of 19p was characteristic of tumors in stage II. However, in the associations among the gains of 8q and 19p with tumors in stage III or II, respectively, we cannot exclude a coincidence because of random sampling because of the few patients. The association between 8p loss and 8q gain as a consequence of an isochromosome 8q formation was already known (14, 21).

The number of genomic aberrations did not influence the clinical outcome of patients. In contrast, Isola et al.(14) reported that relapsed patients with lymph node-negative breast cancer had a greater number of genomic changes than those that were disease free. However, in our series, the number of genomic losses was associated with higher risk of relapse, confirming previous studies of breast tumors (14) and of other malignancies (12). This finding supports the hypothesis that the loss of genomic material affecting tumor suppressor gene loci may play a critical role in tumor progression.

In a univariate analysis, gain in 17q was associated with favorable patient outcome. The long arm of chromosome 17 at 17q12 is the locus of HER-2/neu gene. This oncogene is activated in 20–30% of breast tumors through amplification and overexpression. HER-2/neu positivity is associated with adverse prognostic factors and shorter survival of breast cancer patients (26, 31). Nieto et al.(6) reported that HER-2/neu overexpression was an independent negative predictor of relapse in HRBC treated with HDC and ASCT. In contrast, in other reports HER-2/neu overexpression seemed to increase tumor sensitivity to intensive chemotherapy regimens containing doxorubicin or paclitaxel (7, 8, 9, 32). In agreement with these studies, we report here that the gain of 17q including the HER-2/neu gene locus is associated with a superior DFS in HRBC treated with intensive chemotherapy including doxorubicin. However, in our series, when HER-2/neu status was evaluated by FISH, Western blotting, or IHC, it did not influence patient outcome. Therefore, according to our data it is the genomic gain of 17q and not the HER-2/neu alteration that the predictive parameter correlated with prolonged survival in HRBC. In 17q, two different regions of amplification have been reported. These loci harbor a number of additional genes that are also amplified in breast tumors and may be critical in the pathogenesis of the disease: RAD51C, S6K, PAT1, and TBX2 in 17q23, and GRB7, MLN64 and TopoIIα in the HER-2/neu amplicon in 17q12 (33, 34, 35, 36, 37). TopoIIα gene amplification is associated frequently with frequently amplification. It has been postulated that the increased gene dosage of TopoIIα may relate to an increased sensitivity to TopoII inhibitors such as doxorubicin in patients with breast cancer (35, 36, 37). Whether the amplification of other genes in the 17q12 amplicon, in addition to frequently and TopoIIα, may be of clinical significance in HRBC is at present unknown.

Despite the results of the univariate analysis, the only parameter correlated with shorter DFS in the multivariate analysis was the loss of 18p, whereas the association of the gain of 17q with superior DFS had a borderline significance. For the multivariate analysis, ∼10 events per independent variable (in our case, tumor relapses) are required to produce a statistical model of reasonable accuracy (38). As it was not possible in our series, results of the multivariate analysis should be interpreted carefully. Nevertheless, in our series the status of 18p was the only significant predictive factor for clinical outcome, and it was independent from other genomic changes. Thus, loss of 18p may be an important indicator of adverse outcome in HRBC. The status of 17q was a marginally significant indicator of response to the treatment and seems to show trends to favorable clinical outcome; this is probably related to the few patients included in the series and to the P of 0.02 in the univariate analysis. On the contrary, in the multivariate analysis the 18p loss retained its statistically significance because of the lower P (0.003) observed for this specific correlation in the univariate analysis. Nevertheless, because of the limited number of patients, these results should be confirmed in larger trials.

The deletion of 18p has not been reported as a frequent change in previous CGH studies of breast cancer patients (13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27), but it was a common event in breast tumor cell lines (39). Loss of heterozygosity on 18p was detected in patients with breast tumors (40, 41, 42). In one report, the allelic loss on 18p11.3 occurred early in ductal carcinoma in situ(40). This genomic loss is also common in other malignancies (12, 41). The association of the genomic loss of 18p and shorter DFS has not been reported previously in breast cancer. Our results suggest the presence of one or more tumor suppressor gene(s) on 18p with a role in breast cancer progression.

In summary, using CGH we have identified a subgroup of patients with HRBC with 17q gain or with 18p loss who have a significantly different clinical outcome after HDC and ASCT. The biological importance of these two regions and their definite clinical relevance warrants additional evaluation in a larger series of patients. Our results indicate that HRBC patients with genomic loss of 18p have an adverse clinical outcome and may benefit from more intensive or novel experimental therapies. Future studies using large-scale CGH to microarrays and gene expression profiling will help in the identification of genes at these regions targeted by gene amplification and deletion.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

1

Supported by grants from Spanish Association Against Cancer (AECC-1999) and Spanish Ministry of Health (FIS 01/0040-01) and Aventis Pharma. M. J. G-B. is supported by a grant from Spanish Ministry of Education (MEC AP99)

3

The abbreviations used are: HDC, high-dose chemotherapy; ASCT, autologous stem cell transplantation; HRBC, high-risk breast cancer; CGH, comparative genomic hybridization; FISH, fluorescence in situ hybridization; IHC, immunohistochemical; DFS, disease-free survival; RR, relative risk; CI, confidence interval.

Fig. 1.

Summary of chromosomal imbalances in 34 patients with HRBC. Lines on the left of the ideograms indicate loss of chromosomal material, lines on the right indicate gain of chromosomal material, and thick bars represent high-level amplified regions. A total of 383 genomic imbalances were found, corresponding to 150 gains, 230 losses, and 3 gene amplification events. Genomic imbalances found in nonrelapsed patients are shown in black, whereas those observed in relapsed patients are shown in gray.

Fig. 1.

Summary of chromosomal imbalances in 34 patients with HRBC. Lines on the left of the ideograms indicate loss of chromosomal material, lines on the right indicate gain of chromosomal material, and thick bars represent high-level amplified regions. A total of 383 genomic imbalances were found, corresponding to 150 gains, 230 losses, and 3 gene amplification events. Genomic imbalances found in nonrelapsed patients are shown in black, whereas those observed in relapsed patients are shown in gray.

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Fig. 2.

DFS of 34 HRBC patients. The median follow-up time from diagnosis was 74 months.

Fig. 2.

DFS of 34 HRBC patients. The median follow-up time from diagnosis was 74 months.

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Fig. 3.

DFS of HRBC patients according to the pattern of genomic imbalances in the tumors. A, comparison of tumors with ≥4 genomic losses versus tumors with <4 losses. B, tumors with gain in 17q chromosomal region versus tumors without this genomic gain. C, tumors with 18p genomic loss versus tumors without this genomic loss. D, tumors with genomic gain in 17q and without 18p loss versus the remaining tumors.

Fig. 3.

DFS of HRBC patients according to the pattern of genomic imbalances in the tumors. A, comparison of tumors with ≥4 genomic losses versus tumors with <4 losses. B, tumors with gain in 17q chromosomal region versus tumors without this genomic gain. C, tumors with 18p genomic loss versus tumors without this genomic loss. D, tumors with genomic gain in 17q and without 18p loss versus the remaining tumors.

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Table 1

Clinicopathological characteristics

Patients n = 34
Median age (years) (range) 50 (36–62)  
 ≤50 yr 16 47% 
 >50 yr 18 53% 
Hormonal status   
 Premenopausal 16 47% 
 Postmenopausal 16 47% 
 Perimenopausal 6% 
Lymph nodes affected   
 4–9 10 30% 
 10–15 17 50% 
 16–20 9% 
 >20 11% 
Stage   
 II 20 59% 
 IIIA 11 32% 
 IIIB 9% 
Estrogen receptor   
 Positive 17 50% 
 Negative 10 29% 
 Unknown 21% 
Progesterone receptor   
 Positive 14 41% 
 Negative 13 38% 
 Unknown 21% 
Histologic grade   
 I 12% 
 II 16 47% 
 III 23% 
 Unknown 18% 
Histologic type   
 Ductal 29 85% 
 Lobular 12% 
 Tubular 3% 
Patient survival status   
 Relapsed 15 44% 
 Disease free 19 56% 
Patients n = 34
Median age (years) (range) 50 (36–62)  
 ≤50 yr 16 47% 
 >50 yr 18 53% 
Hormonal status   
 Premenopausal 16 47% 
 Postmenopausal 16 47% 
 Perimenopausal 6% 
Lymph nodes affected   
 4–9 10 30% 
 10–15 17 50% 
 16–20 9% 
 >20 11% 
Stage   
 II 20 59% 
 IIIA 11 32% 
 IIIB 9% 
Estrogen receptor   
 Positive 17 50% 
 Negative 10 29% 
 Unknown 21% 
Progesterone receptor   
 Positive 14 41% 
 Negative 13 38% 
 Unknown 21% 
Histologic grade   
 I 12% 
 II 16 47% 
 III 23% 
 Unknown 18% 
Histologic type   
 Ductal 29 85% 
 Lobular 12% 
 Tubular 3% 
Patient survival status   
 Relapsed 15 44% 
 Disease free 19 56% 
Table 2

Correlation among the frequent genomic imbalances

4q Loss8q Gain20q Gain9p Loss
 n  12  11  14  
8p loss 13 – nsa P = 0.002b – ns – ns 
18q loss 14 – ns – ns P = 0.002 10 P = 0.005 
18p loss 13 P = 0.002 – ns – ns P = 0.01 
4q Loss8q Gain20q Gain9p Loss
 n  12  11  14  
8p loss 13 – nsa P = 0.002b – ns – ns 
18q loss 14 – ns – ns P = 0.002 10 P = 0.005 
18p loss 13 P = 0.002 – ns – ns P = 0.01 
a

ns, not significant.

b

Ps were obtained by Fisher’s exact test. Genomic imbalances are entered into statistical model as binari variables for which presence of gain/loss was considered positive (= 1) and absence was considered negative (= 0).

Table 3

Comparison between frequent genomic imbalances found in previous CGH studies of breast cancer and in the present study

Genomic abnormalities shown in descending order of frequency are those seen in more than 20% of tumor samples.

ReferenceTumor samplesGainsLossesGenomic imbalances
Median (Range)
Seute et al. (2001)21 44 HRBC 17q, 1q, 8q, 20q, 6p 13q, 11q, 5q, 6q, 9p, 18q 5 (1–18) 
Richard et al. (2000)19 105 Primary breast carcinomas 1q, 8q, 11q, 16p, 17q, 19 1p, 4p, 4q, 6q, 11q, 13q, 16q, 17p, 18q n.a.a 
Loveday et al. (2000)24 52 Infiltrating carcinomas 13q, 8q, 5q, 1q, 4q, 6q, 12q 17p, 1p, 8p, 22q, 19q n.a. 
Buerguer et al. (1999)22 77 Invasive breast cancer 1q, 3q, 8q, 17q, 20q 8p, 13q, 16q 6.7 (0–22) 
Buerguer et al. (1999)23 33 Ductal carcinoma in situ 1q, 17q, 8q 16q, 11q, 8p, 13q, 14q 5.6 (0–17) 
Moore et al. (1999)17 23 High-grade ductal carcinoma in situ 11q, 16p, 17q, 6p, 20q, 1q 1p, 19, 22q n.a. 
Isola et al. (1999)26 33 Invasive ductal carcinomas 1q, 8q, 17q, 20q, 16p 18q, 13q, 3p, Xq n.a. 
Tirkkonen et al. (1998)27 55 Unselected primary breast cancer 1q, 8q, 16p, 5p, 19q 16q, 8p, 13q, 17p, Xq 5.0 (1–22) 
Hermsen et al. (1998)16 53 Lymph node-negative breast cancer 8q, 1q, Xq, 5q, 4q 19p, 1p, 17p, 22q 9.1 (1–29) 
Nishizaki et al. (1997)17 33 Infiltrating carcinomas 1q, 8q, 17q, 20q, 11q 16q, 17p, 13q, Xq, 6q, 18q, 4q, 4p n.a. 
James et al. (1997)15 9 Ductal carcinoma in situ 1q, 17q, 19q, 20p, 20q 13q, 14q, 17p, 16q, 22q n.a. 
Present study 34 HRBC 1q, 17q, 8q, 16p, 20q, 19p, 11q 9p, 18q, 18p, 8p, 11q, 17p, Xq, 4p, 16q, 4q, 22q 11 (2–24) 
ReferenceTumor samplesGainsLossesGenomic imbalances
Median (Range)
Seute et al. (2001)21 44 HRBC 17q, 1q, 8q, 20q, 6p 13q, 11q, 5q, 6q, 9p, 18q 5 (1–18) 
Richard et al. (2000)19 105 Primary breast carcinomas 1q, 8q, 11q, 16p, 17q, 19 1p, 4p, 4q, 6q, 11q, 13q, 16q, 17p, 18q n.a.a 
Loveday et al. (2000)24 52 Infiltrating carcinomas 13q, 8q, 5q, 1q, 4q, 6q, 12q 17p, 1p, 8p, 22q, 19q n.a. 
Buerguer et al. (1999)22 77 Invasive breast cancer 1q, 3q, 8q, 17q, 20q 8p, 13q, 16q 6.7 (0–22) 
Buerguer et al. (1999)23 33 Ductal carcinoma in situ 1q, 17q, 8q 16q, 11q, 8p, 13q, 14q 5.6 (0–17) 
Moore et al. (1999)17 23 High-grade ductal carcinoma in situ 11q, 16p, 17q, 6p, 20q, 1q 1p, 19, 22q n.a. 
Isola et al. (1999)26 33 Invasive ductal carcinomas 1q, 8q, 17q, 20q, 16p 18q, 13q, 3p, Xq n.a. 
Tirkkonen et al. (1998)27 55 Unselected primary breast cancer 1q, 8q, 16p, 5p, 19q 16q, 8p, 13q, 17p, Xq 5.0 (1–22) 
Hermsen et al. (1998)16 53 Lymph node-negative breast cancer 8q, 1q, Xq, 5q, 4q 19p, 1p, 17p, 22q 9.1 (1–29) 
Nishizaki et al. (1997)17 33 Infiltrating carcinomas 1q, 8q, 17q, 20q, 11q 16q, 17p, 13q, Xq, 6q, 18q, 4q, 4p n.a. 
James et al. (1997)15 9 Ductal carcinoma in situ 1q, 17q, 19q, 20p, 20q 13q, 14q, 17p, 16q, 22q n.a. 
Present study 34 HRBC 1q, 17q, 8q, 16p, 20q, 19p, 11q 9p, 18q, 18p, 8p, 11q, 17p, Xq, 4p, 16q, 4q, 22q 11 (2–24) 
a

n.a., not available.

We thank Dra. Maria J. Terol (Department of Hematology, Hospital Clìnìco Universìtarìo, Valencia, Spain) and Prof. Francisco Martinez (Department of Statistics, University of Valencia, Valencia, Spain) for their help with the statistical analysis, and Dr. Samuel Navarro (Department of Pathology, University of Valencia) for IHC analysis. We also thank Dr. Jose Palacios (Centro Nacional de Investìgacìon Oncologìca, Madrid, Spain) for histological evaluation of tumors and Dr. M. J. S. Dyer (Department of Haematology, University of Leicester, UK) for critical reviews of the manuscript.

1
Carter C. L., Allen C., Henson D. E. Relation of tumor size, lymph node status, and survival in 24.740 breast cancer.
Cancer (Phila.)
,
63
:
181
-187,  
1989
.
2
Bonadonna G., Valagussa P., Moliterni A., Zambetti M., Brambilla C. Adjuvant cyclophosphamide, methotrexate, and fluorouracil in node-positive breast cancer: the results of 20 years of follow-up.
N. Engl. J. Med.
,
332
:
901
-906,  
1995
.
3
Rodenhuis S., Bontenbal M., Beex L. V. A. M., van der Wall E., D. J., Richel M. A., Nooij E. E., Voest P., Hupperets A. M., Westermann O. B., Dalesio E. G. E. de Vries randomized phase III study of high-dose chemotherapy with cyclophosphamide, thiotepa and carboplatin in operable breast cancer with 4 or more axillary lymph nodes.
Proc. ASCO
,
19
:
286
2000
.
4
Gianni A., Gianni B. Five-year results of the randomized clinical trial comparing standard versus high-dose myeloablative chemotherapy in the adjuvant treatment of breast cancer with > 3 positive nodes (LN+).
Proc. ASCO
,
20
:
80
2001
.
5
Peters W. P., Rosner G., Vredenburgh J., Shpall E. J., Crump M., Marks L., Cirrincione C., Hurd D., Norton L. Updated results of a prospective, randomized comparison of two doses of combination alkyating agents (AA) as consolidation after CAF in high-risk primary breast cancer involving ten or more axillary lymph nodes (LN): CALGB 9082/SWOG 9114/NCIC Ma-13.
Proc. ASCO
,
20
:
81
2001
.
6
Nieto Y., Cagnoni P. J., Nawaz S., Shpall E. J., Yerushalmi R., Cook B., Russell P., McDermit J., Murphy J., Bearman S. I., Jones R. B. Evaluation of the predictive value of Her-2/neu overexpression and p53 mutations in high-risk primary breast cancer patients treated with high-dose.
J. Clin. Oncol.
,
18
:
2070
-2080,  
2000
.
7
Muss H. B., Thor A. D., Berry D. A., Kute T., Liu E. T., Koerner F., Cirrincione C. T., Budman D. R., Wood W. C., Barcos M. c-erbB-2 expression and response to adjuvant therapy in women with node-positive early breast cancer.
N. Engl. J. Med.
,
330
:
1260
-1266,  
1994
.
8
Paik S., Bryant J., Park C., Fisher B., Tan-Chiu E., Hyams D., Fisher E. R., Lippman M. E., Wickerham D. L., Wolmark N. erbB-2 and response to doxorubicin in patients with axillary lymph node-positive, hormone receptor-negative breast cancer.
J. Natl. Cancer Inst.
,
90
:
1361
-1370,  
1998
.
9
Berry D. A., Muss H. B., Thor A. D., Dressler L., Liu E. T., Broadwater G., Budman D. R., Henderson I. C., Barcos M., Hayes D., Norton L. HER-2/neu and p53 expression versus tamoxifen resistance in estrogen receptor-positive, node-positive breast cancer.
J. Clin. Oncol.
,
18
:
3471
-3479,  
2000
.
10
Kallioniemi A., Kallioniemi O. P., Sudar D., Rutovitz D., Gray J. W., Waldman F., Pinkel D. Comparative genomic hybridization for molecular cytogenetic analysis of solid tumors.
Science (Wash. DC)
,
258
:
818
-821,  
1992
.
11
Knuutila S., Bjorkqvist A. M., Autio K., Tarkkanen M., Wolf M., Monni O., Szymanska J., Larramendy M. L., Tapper J., Pere H., El-Rifai W., Hemmer S., Wasenius V. M., Vidgren V., Zhu Y. DNA copy number amplifications in human neoplasms: review of comparative genomic hybridization studies.
Am. J. Pathol.
,
152
:
1107
-1123,  
1998
.
12
Knuutila S., Aalto Y., Autio K., Bjorkqvist A. M., El-Rifai W., Hemmer S., Huhta T., Kettunen E., Kiuru-Kuhlefelt S., Larramendy M. L., Lushnikova T., Monni O., Pere H., Tapper J., Tarkkanen M., Varis A., Wasenius V. M., Wolf M., Zhu Y. DNA copy number losses in human neoplasms.
Am. J. Pathol.
,
155
:
683
-694,  
1999
.
13
Kallioniemi A., Kallioniemi O. P., Piper J., Tanner M., Stokke T., Chen L., Smith H. S., Pinkel D., Gray J. W., Waldman F. M. Detection and mapping of amplified DNA sequences in breast cancer by comparative genomic hybridization.
Proc. Natl. Acad. Sci. USA
,
91
:
2156
-2160,  
1994
.
14
Isola J. J., Kallioniemi O. P., Chu L. W., Fuqua S. A., Hilsenbeck S. G., Osborne C. K., Waldman F. M. Genetic aberrations detected by comparative genomic hybridization predict outcome in node-negative breast cancer.
Am. J. Pathol.
,
147
:
905
-911,  
1995
.
15
James L. A., Mitchell E. L., Menasce L., Varley J. M. Comparative genomic hybridisation of ductal carcinoma in situ of the breast: identification of regions of DNA amplification and deletion in common with invasive breast carcinoma.
Oncogene
,
14
:
1059
-1065,  
1997
.
16
Hermsen M. A., Baak J. P., Meijer G. A., Weiss J. M., Walboomers J. W., Snijders P. J., van Diest P. J. Genetic analysis of 53 lymph node-negative breast carcinomas by CGH and relation to clinical, pathological, morphometric, and DNA cytometric prognostic factors.
J. Pathol.
,
186
:
356
-362,  
1998
.
17
Moore E., Magee H., Coyne J., Gorey T., Dervan P. A. Widespread chromosomal abnormalities in high-grade ductal carcinoma in situ of the breast. Comparative genomic hybridization study of pure high-grade DCIS.
J. Pathol.
,
187
:
403
-409,  
1999
.
18
Roylance R., Gorman P., Harris W., Liebmann R., Barnes D., Hanby A., Sheer D. Comparative genomic hybridization of breast tumors stratified by histological grade reveals new insights into the biological progression of breast cancer.
Cancer Res.
,
59
:
1433
-1436,  
1999
.
19
Richard F., Pacyna-Gengelbach M., Schl]uns K., Fleige B., Winzer K. J., Szymas J., Dietel M., Petersen I., Schwendel A. Patterns of chromosomal imbalances in invasive breast cancer.
Int. J. Cancer
,
89
:
305
-310,  
2000
.
20
Jain A. N., Chin K., Borresen-Dale A. L., Erikstein B. K., Eynstein Lonning P., Kaaresen R., Gray J. W. Quantitative analysis of chromosomal CGH in human breast tumors associates copy number abnormalities with p53 status and patient survival.
Proc. Natl. Acad. Sci. USA
,
98
:
7952
-7957,  
2001
.
21
Seute A., Sinn H. P., Schlenk R. F., Emig R., Wallwiener D., Grischke E. M., Hohaus S., Dohner H., Haas R., Bentz M. Clinical relevance of genomic aberrations in homogeneously treated high-risk stage II/III breast cancer patients.
Int. J. Cancer.
,
93
:
80
-84,  
2001
.
22
Buerger H., Otterbach F., Simon R., Schafer K. L., Poremba C., Diallo R., Brinkschmidt C., Dockhorn-Dworniczak B., Boecker W. Different genetic pathways in the evolution of invasive breast cancer are associated with distinct morphological subtypes.
J. Pathol.
,
189
:
521
-526,  
1999
.
23
Buerger H., Otterbach F., Simon R., Poremba C., Diallo R., Decker T., Riethdorf L., Brinkschmidt C., Dockhorn-Dworniczak B., Boecker W. Comparative genomic hybridization of ductal carcinoma in situ of the breast-evidence of multiplegenetic pathways.
J. Pathol.
,
187
:
396
-402,  
1999
.
24
Loveday R. L., Greenman J., Simcox D. L., Speirs V., Drew P. J., Monson J. R., Kerin M. J. Genetic changes in breast cancer detected by comparative genomic hybridisation.
Int. J. Cancer
,
86
:
494
-500,  
2000
.
25
Nishizaki T., Chew K., Chu L., Isola J., Kallioniemi A., Weidner N., Waldman F. M. Genetic alterations in lobular breast cancer by comparative genomic hybridization.
Int. J. Cancer
,
74
:
513
-517,  
1997
.
26
Isola J., Chu L., DeVries S., Matsumura K., Chew K., Ljung B. M., Waldman F. M. Genetic alterations in ERBB2-amplified breast carcinomas.
Clin. Cancer Res.
,
5
:
4140
-4145,  
1999
.
27
Tirkkonen M., Tanner M., Karhu R., Kallioniemi A., Isola J., Kallioniemi O. P. Molecular cytogenetics of primary breast cancer by CGH.
Genes Chromosomes Cancer
,
21
:
177
-184,  
1998
.
28
Martinez-Climent J. A., Vizcarra E., Sanchez D., Blesa D., Marugan I., Benet I., Sole F., Rubio-Moscardo F., Terol M. J., Climent J., Sarsotti E., Tormo M., Andreu E., Salido M., Ruiz M. A., Prosper F., Siebert R., Dyer M. J., Garcia-Conde J. Loss of a novel tumor suppressor gene locus at chromosome 8p is associated with leukemic mantle cell lymphoma.
Blood
,
98
:
3479
-3482,  
2001
.
29
Sanchez-Izquierdo D., Siebert R., Harder L., Marugan I., Gozzetti A., Price H. P., Gesk S., Hernandez-Rivas J. M., Benet I., Sole F., Sonoki T., Le Beau M. M., Schlegelberger B., Dyer M. J., Garcia-Conde J., Martinez-Climent J. A. Detection of translocations affecting the BCL6 locus in B cell non-Hodgkin’s lymphoma by interphase fluorescence in situ hybridization.
Leukemia (Baltimore)
,
15
:
1475
-1484,  
2001
.
30
Molina M. A., Saez R., Ramsey E. E., Garcia-Barchino M. J., Rojo F., Evans A. J., Albanell J., Keenan E. J., Lluch A., García-Conde J., Baselga J., Clinton G. M. NH2-terminal truncated HER-2 protein but not full-length receptor is associated with nodal metastasis in human breast cancer.
Clin. Cancer Res.
,
8
:
347
-353,  
2002
.
31
Mitchell M. S., Press M. F. The role of immunohistochemistry and fluorescence in situ hybridization for HER-2/neu in assessing the prognosis of breast cancer.
Semin. Oncol.
,
26
: (Suppl. 12)
108
-116,  
1999
.
32
Gianni L. Future directions of paclitaxel-based therapy of breast cancer.
Semin. Oncol.
,
24
: (Suppl. 17)
91
-96,  
1997
.
33
Kauraniemi P., Bärlund M., Monni O., Kallioniemi A. New amplified and highly expressed genes discovered in the ERB2 amplicon in breast cancer by cDNA microarrays.
Cancer Res.
,
61
:
8235
-8240,  
2001
.
34
Monni O., Barlund M., Mousses S., Kononen J., Sauter G., Heiskanen M., Paavola P., Avela K., Chen Y., Bittner M. L., Kallioniemi A. Comprehensive copy number and gene expression profiling of the 17q23 amplicon in human breast cancer.
Proc. Natl. Acad. Sci. USA
,
98
:
5711
-5716,  
2001
.
35
Jarvinen T. A., Tanner M., Rantanen V., Barlund M., Borg A., Grenman S., Isola J. Amplification and deletion of topoisomerase IIα associate with ErbB-2 amplification and affect sensitivity to topoisomerase II inhibitor doxorubicin in breast cancer.
Am. J. Pathol.
,
156
:
839
-847,  
2000
.
36
Harris L. N., Yang L., Liotcheva V., Pauli S., Iglehart J. D., Colvin O. M., Hsieh T. S. Induction of topoisomerase II activity after ErbB2 activation is associated with a differential response to breast cancer chemotherapy.
Clin. Cancer Res.
,
7
:
1497
-504,  
2001
.
37
Coon J. S., Marcus E., Gupta-Burt S., Seelig S., Jacobson K., Chen S., Renta V., Fronda G., Preisler H. D. Amplification and overexpression of topoisomerase IIα predict response to anthracycline-based therapy in locally advanced breast cancer.
Clin. Cancer Res.
,
8
:
1061
-1067,  
2002
.
38
Peduzzi P., Concato J., Feinstein A. R., Holford T. R. Importance of events per independent variable in proportional hazards regression analysis. II. Accuracy and precision of regression estimates.
J. Clin. Epidemiol.
,
48
:
1503
-1510,  
1995
.
39
Forozan F., Mahlamaki E. H., Monni O., Chen Y., Veldman R., Jiang Y., Gooden G. C., Ethier S. P., Kallioniemi A., Kallioniemi O. P. Comparative genomic hybridization analysis of 38 breast cancer cell lines: a basis for interpreting complementary DNA microarray data.
Cancer Res.
,
60
:
4519
-4525,  
2000
.
40
Kittiniyom K., Gorse K. M., Dalbegue F., Lichy J. H., Taubenberger J. K., Newsham I. F. Allelic loss on chromosome band 18p11.3 occurs early and reveals heterogeneity in breast cancer progression.
Breast Cancer Res. Treat.
,
3
:
192
-198,  
2001
.
41
Tran Y., Benbatoul K., Gorse K., Rempel S., Futreal A., Green M., Newsham I. Novel regions of allelic deletion on chromosome 18p in tumors of the lung, brain and breast.
Oncogene
,
17
:
3499
-505,  
1998
.
42
Osborne R. J., Hamshere M. G. A genome-wide map showing common regions of loss of heterozygosity/allelic imbalance in breast cancer.
Cancer Res.
,
60
:
3706
-3712,  
2000
.