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Clinical Cancer Research Vol. 12, 3319-3328, June 1, 2006
© 2006 American Association for Cancer Research

Imaging, Diagnosis, Prognosis

Which Cyclin E Prevails as Prognostic Marker for Breast Cancer? Results from a Retrospective Study Involving 635 Lymph Node–Negative Breast Cancer Patients

Anieta M. Sieuwerts, Maxime P. Look, Marion E. Meijer-van Gelder, Mieke Timmermans, Anita M.A.C. Trapman, Roberto Rodriguez Garcia, Miranda Arnold, Anneke J.W. Goedheer, Vanja de Weerd, Henk Portengen, Jan G.M. Klijn and John A. Foekens

Authors' Affiliation: Department of Medical Oncology, Erasmus MC, Rotterdam, the Netherlands

Requests for reprints: Anieta M. Sieuwerts, Erasmus MC, Josephine Nefkens Institute, Room Be 400, P.O. Box 1738, 3000 DR Rotterdam, the Netherlands. Phone: 31-10-408-8372; Fax: 31-10-408-8377; E-mail: a.sieuwerts{at}erasmusmc.nl.


   Abstract
Top
 Abstract
Patients and Methods
 Results
 Discussion
 References
 
Purpose: To evaluate the prognostic value of cyclin E with a quantitative method for lymph node–negative primary breast cancer patients.

Patients and Methods: mRNA transcripts of full-length and splice variants of cyclin E1 (CCNE1) and cyclin E2 (CCNE2) were measured by real-time PCR in frozen tumor samples from 635 lymph node–negative breast cancer patients who had not received neoadjuvant or adjuvant systemic therapy.

Results: None of the PCR assays designed for the specific splice variants of the cyclins gave additional prognosis-related information compared with the common assays able to detect all variants. In Cox multivariate analysis, corrected for the traditional prognostic factors, high levels of cyclin E were independently associated with a short distant metastasis-free survival [hazard ratio (HR), 3.40; P < 0.001 for CCNE1 and HR, 1.76; P < 0.001 for CCNE2, respectively]. After dichotomizing the tumors at the median level of 70% tumor cells, the multivariate analysis showed particularly strong results for CCNE1 in the group of 433 patients with stroma-enriched primary tumors (HR, 5.12; P < 0.001). In these tumors, the worst prognosis was found for patients with estrogen receptor–negative tumors expressing high CCNE1 (HR, 9.89; P < 0.001) and for patients with small (T1) tumors expressing high CCNE1 (HR, 8.47; P < 0.001).

Conclusion: Our study shows that both CCNE1 and CCNE2 qualify as independent prognostic markers for lymph node–negative breast cancer patients, and that CCNE1 may provide additional information for specific subgroups of patients.

Dysregulation of the cyclin-dependent kinase-2 (CDK2)–bound cyclins plays an important role in the pathogenesis of cancer. High levels of cyclin E expression are found in many types of cancer, and elevated levels of the E1 cell cycle protein have been associated with a poor prognosis in primary breast cancer patients (reviewed by Yasmeen et al.; ref. 1). Although studies have mainly focused on cyclin E1, the human genome encodes two E-type cyclins: CCNE1 (formerly cyclin E) on chromosome 19q (2, 3) and CCNE2 on chromosome 8q (4–6). The encoded human cyclin E2 protein shares 47% overall similarity to cyclin E1 and contains a cyclin box motif that is characteristic of all cyclins (5). However, whereas a significantly increased expression of cyclin E2 is observed in breast cancers (7), its potential association with tumor aggressiveness is still unknown. Notwithstanding, CCNE2 and not CCNE1 overlapped between the 76-gene prediction signature from Wang et al. (8) and the 70-gene prediction signature from van't Veer et al. (9) for metastasis-free survival (MFS) of lymph node–negative patients. This suggested that at least for microarray techniques, and perhaps for all gene expression levels measuring methods, CCNE2 might be a better prognostic marker when compared with CCNE1.

For both CCNE1 and CCNE2, alternatively spliced transcript variants, which encode distinct protein isoforms, have been reported (5, 10–13). Once translated in tumor cells, the protein products of such variants can give rise to constitutively active forms of the cyclin E containing complexes. To complicate matters, it has been shown that in breast cancer compared with normal cells and tissues, cyclin E1 protein is overexpressed and post-translationally cleaved by a protease into low molecular weight isoforms (14, 15). These low molecular weight forms of cyclin E1 show higher CDK2 kinase activity, and the low molecular weight cyclin E1/CDK2 complexes are more resistant to inhibitors and antiestrogens (16). Keyomarsi et al. showed that levels of total cyclin E1 and low molecular weight cyclin E1 in tumor tissue measured by Western blot assay correlated strongly with survival in patients with breast cancer (17). A complicating factor was that approximately two thirds of the patients included in this study received either adjuvant chemotherapy or hormonal therapy (18). Trials of adjuvant therapy in patients with breast cancer no longer include an untreated control group. Therefore, retrospective studies involving well-characterized tumor banks with tumors from untreated patients will be necessary to determine whether cyclin E is a pure prognostic factor instead of a predictor for the benefits of adjuvant systemic therapy. Our current study involves such a cohort of 635 tumors from lymph node–negative patients who did not receive any adjuvant systemic therapy.


   Patients and Methods
Top
 Abstract
 Patients and Methods
Results
 Discussion
 References
 
Patients. The study was approved by the institutional medical ethics committee (MEC 02·953). Tumor samples were originally submitted to our reference laboratory from 25 regional hospitals for measurements of steroid hormone receptors. Guidelines for primary treatment were similar for all hospitals. To avoid bias, selection of tumors from our tumor bank at the Erasmus Medical Center (Rotterdam, the Netherlands) was done by processing all available frozen tumor samples from female patients with lymph node–negative breast cancer who entered the clinic during 1979 to 1995 and from whom detailed clinical follow-up was available. Lymph node negativity and tumor size was based on pathologic examination by regional pathologists. Information on grade was extracted from the pathology records and reflects clinical practice during those years. Exclusion criteria were residual disease or distant spread diagnosed at or within 1 month after primary surgery, noninvasive breast cancer, neoadjuvant or adjuvant systemic therapy, a previous other cancer (except basal cell skin cancer or early-stage cervical cancer stage Ia/Ib), <100 mg frozen tissue available, evaluation of tumor content not reliable (2%), <30% tumor cell nuclei in the sample (15%), and poor RNA quality (8%). The thus remaining 635 eligible patients were treated either with breast-conserving surgery (54%) or with modified mastectomy (46%). Forty-one percent of the patients had T1 tumors. The median age of the patients at surgery was 56 years (range, 25-88 years). Three hundred eighty-seven patients (61%) received radiotherapy. Routine post-surgical follow-up and defining the date of MFS was as described (8). Thirty-seven patients presented with a relapse without signs of a distant metastasis. The median follow-up time was 95 months (range, 11-202 months) with 256 failures in the analysis of MFS and 226 failures in the analysis of overall survival. Other relevant clinicopathologic characteristics are listed in Table 1 .


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  		Table 1. Associations of CCNE1 and CCNE2 mRNA levels with clinicopathologic factors

 
Tissue processing. Tissue processing was done as described in detail before (19). In brief, 20 to 60 cryostat sections of 30 µm, corresponding to 30 to 100 mg, were cut from frozen tissues. Before, in between, and after cutting the sections for RNA isolation, 5-µm sections were cut for H&E staining to assess the amount of tumor cells relative to the amount of surrounding stromal cells. The amount of nuclei evidently of epithelial tumor cell origin relative to the amount of surrounding stromal cells was estimated with a 100-fold magnification in 10 different areas covering the area of each of the three H&E sections. Only specimen with at least 30% of the nuclei of epithelial tumor cell origin and distributed uniformly over at least 70% of the section area were included. Like done before (19), these estimates were used to dichotomize our tumor cohort at the median level of 70% tumor cell nuclei in stroma-rich (primary tumors containing ≥30% stromal components) and stroma-poor (primary tumors containing at least 70% tumor cells).

RNA isolation, cDNA synthesis, and quantification of specific mRNA species. RNA isolation, cDNA synthesis, quantification of specific mRNA species, and quality control checks were done as described in detail before (19). Real-time quantitative PCR was done in an ABI Prism 7700 Sequence Detection System (Applied Biosystems, Nieuwerkerk a/d IJssel, the Netherlands) and a Mx3000P Real-time PCR System (Stratagene, Amsterdam, the Netherlands) using both the Assay-on-Demand assays from Applied Biosystems and the intron-spanning forward and reverse primer combinations at the conditions shown in Table 2A . In our initial screening, we compared CCNE1 and CCNE2 mRNA transcript levels of the various variants in a set of 185 primary tumors from breast cancer patients and various cultured cell lines (Table 2B). Primer sequences for estrogen receptor-{alpha} (ER-{alpha}), PgR, and the housekeepers, as well as how PCR reactions and validations were done to ensure PCR specificity, have all been previously described (19). Levels of the target genes, expressed relative to our housekeeping set, which included the low abundance housekeeping gene porphobilinogen deaminase, the medium abundance housekeeping gene hypoxanthine-guanine phosphoribosyltransferase, and the high-abundance housekeeping gene ß2-microglobulin, were quantified as follows: mRNA target = 2(mean Ct housekeeping – mean Ct target).


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  		Table 2.

 
Statistics. Computations were done with the use of the STATA statistical package, release 8.2 (STATA Corp., College Station, TX). Differences in levels were assessed with the Mann-Whitney U test or Kruskal-Wallis test. In these tests, patient and tumor characteristics were used as grouping variables. The strengths of the associations between continuous variables were tested with the Spearman rank correlation (rs). Variables were either log transformed or Box-Cox transformed to reduce the skewness. The prognostic values of the clinical and biological variables, with MFS and overall survival as the end point in the univariate, multivariate, and interaction analyses, were investigated with the use of the Cox proportional hazards model. The hazard ratio (HR) and its 95% confidence interval were derived from these results. The proportionality assumption was investigated with a test based on the Schoenfeld residuals. Kaplan-Meier survival plots and log-rank tests were used to assess the differences in time to distant metastasis of the predicted high-risk and low-risk groups. All Ps are two sided, and P < 0.05 was considered statistically significant.


   Results
Top
 Abstract
 Patients and Methods
 Results
Discussion
 References
 
Correlation between real-time PCR and Affymetrix GeneChip array. Comparing our real-time PCR data for all CCNE1 and CCNE2 variants with expression data obtained after hybridizing the same total RNA samples on the Affymetrix oligonucleotide Human U133a GeneChips (8) showed significant correlations between our CCNE1 and CCNE2 real-time PCR assays and the CCNE1 213523_at and CCNE2 205034_at probe-based Affymetrix GeneChip array assays, which also recognize all variants of CCNE1 and CCNE2 (rs = 0.70 for CCNE1 and rs = 0.75 for CCNE2, respectively; P < 0.001, n = 248). The Spearman rank correlation between CCNE1 and CCNE2 was 0.40 (P < 0.001, n = 635) for the real-time PCR assays and 0.36 (P < 0.001, n = 248) for the probe sets. Relating the CCNE expression profiles to the subtypes of breast cancer as defined by global profiling (20) showed for both our real-time PCR and Affymetrix GeneChip array data significant (P < 0.05) differences in median CCNE mRNA levels between the subtypes. For both CCNE1 and CCNE2, levels ranked according to the major breast cancer subtype were luminal A (n = 94) > basal (n = 42) > normal (n = 48).

Associations with clinicopathologic factors. The associations of CCNE1 and CCNE2 mRNA expression levels with patient and tumor characteristics are shown in Table 1. Although based on a relatively small number of patients, the lowest median levels of the cyclins were found in the histologic subgroup of medullary tumors. CCNE1 and CCNE2 levels were both inversely related with age and steroid hormone receptors and higher in premenopausal patients and poor-grade tumors. Furthermore, CCNE1 and CCN2 levels were higher in larger tumors, although for CCNE2, this association was not statistically significant. To further explore the associations between the mRNA levels of the cyclins and steroid hormone receptor status, we correlated ER-{alpha} and PgR mRNA levels measured by quantitative real-time PCR with mRNA levels of the cyclins measured in the same preparations. Although at the mRNA level, a strong negative correlation was present between CCNE1 and ER-{alpha} and PgR (rs = –0.54 for ER-{alpha} and –0.54 for PgR, respectively; P < 0.001, n = 635), this was less striking for the correlation between the CCNE2 and ER and PgR mRNA levels (rs = –0.16 for ER-{alpha} and –0.23 for PgR, respectively).

Univariate and multivariate analysis. We first did Cox univariate analyses for MFS and overall survival as a function of continuous CCNE1 and CCNE2 mRNA levels. In these analyses, CCNE1 and CCNE2 were associated with a poor MFS (HR, 1.29 for CCNE1 and HR, 1.59 for CCNE2; both P < 0.001) and overall survival (HR, 1.24 for CCNE1 and HR, 1.45 for CCNE2: both P < 0.001). These significant relationships justified the search for a cut point to analyze CCNE1 and CCNE2 as dichotomized variables and to allow visualization of their prognostic value in Kaplan-Meier analysis. Because the proportional hazards assumption was violated for grade and PgR for the total follow-up time of 202 months (P < 0.05), we restricted our exploration of the relationships of the cyclins with MFS to the first 5 years of follow-up. In this analysis with 209 failures, the proportional hazards assumption was no longer violated (P > 0.1). The data of the Cox univariate and multivariate analyses are summarized in Table 3 for MFS during the first 5 years and in Table 4 for overall survival during the total follow-up period including all deaths. Both cyclins, either when analyzed at their median level (HR, 2.65 for CCNE1 and HR, 1.69 for CCNE2, respectively) or at their optimized cut point (HR, 3.40 for CCNE1 and HR, 1.76 for CCNE2, respectively), contributed significantly to the multivariate model for MFS (all P < 0.001; Table 3). Similar significant relationships were observed in the analysis for overall survival (Table 4). No statistically significant interactions were observed between the cyclins and the prognostic factors included in the base multivariate model, between the cyclins and adjuvant radiotherapy, and between the cyclins themselves. When CCNE1 and CCNE2 were added simultaneously to the base model, they both independently contributed to the MFS and overall survival models.


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  		Table 3. Cox univariate and multivariate analysis for 5 years MFS in 635 lymph node–negative patients

 

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  		Table 4. Cox univariate and multivariate analysis for overall survival in 635 lymph node–negative patients

 
ER status and tumor size. To specifically investigate the differences between the two cyclins with respect to the strength of their associations with steroid hormone receptor status and tumor size (see Table 1), we did Cox univariate analyses in the subgroups of ER-negative and ER-positive tumors, and in small (≤20 mm) and larger (>20 mm) tumors (Table 5 ). Although both cyclins were associated with a poor prognosis in the ER-positive subgroup (HR, 4.08 for CCNE1 and HR, 2.63 for CCNE2, respectively), only CCNE1 was informative for the ER-negative subgroup (HR, 5.04). With respect to tumor size, high levels of both cyclins were significantly associated with a poor MFS, both for patients with small tumors (HR, 5.36 for CCNE1 and HR, 3.75 for CCNE2) and patients with larger tumors (HR, 3.00 for CCNE1 and HR, 1.49 for CCNE2).


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  		Table 5. Cox univariate analysis for 5 years MFS in 635 adjuvant untreated lymph node–negative patients

 
Stroma-enriched versus stroma-poor tumors. Interaction analysis showed that patients with high levels of CCNE1 had an increased risk (P = 0.03) to develop a metastasis within 5 years if their primary tumor was stroma enriched compared with patients with a high level of CCNE1 combined with a stroma-poor primary tumor. Hence, a high CCNE1 level was a better predictor of poor prognosis in the group of 433 patients with stroma-rich tumors (HR, 5.38) compared with the group of 202 patients with stroma-poor tumors (HR, 2.39; Table 5). A high level of CCNE2 on the other hand was a better predictor for the group of 202 patients with stroma-poor tumors (HR, 2.77 compared with HR, 1.86 for stroma-rich tumors). Note that, whereas median CCNE2 mRNA levels did not differ between stroma-poor tumors (median level, 0.70; interquartile range, 0.89) and stroma-rich tumors (median level, 0.71; interquartile range, 0.80), median levels of CCNE1 were higher in the group of stroma-rich tumors (median level, 0.043; interquartile range, 0.066 for stroma-rich tumors and median level, 0.034; interquartile range, 0.059 for stroma-poor tumors; P = 0.01). In contrast to CCNE2, for CCNE1, the importance of discriminating between stromal content became even more evident in the subgroups of ER-negative tumors and small tumors. Especially for stroma-rich ER-negative tumors (HR, 9.89) and stroma-rich small tumors (HR, 8.47), a high level of CCNE1 was a strong factor predicting a poor prognosis (Table 5). The prognostic value of the cyclins in all patients and in the subgroups of tumors with a low and high proportion of tumor cells and separately analyzed for T1 tumors is visualized in Kaplan-Meier curves (Fig. 1 ).


Figure 1
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  		Fig. 1. MFS as a function of CCNE1 (A) and CCNE2 (B) in 635 lymph node–negative primary breast cancer patients before (1) and after (2-4) dichotomizing patients according to the percentage of tumor cells present in the primary tumor and tumor size. Patients at risk are indicated. Cut point used for CCNE1 is 0.03 and for CCNE2 is 1.16.

 
CCNE1 and its mRNA splice variants. The contributions of the various mRNA variants of CCNE (see also Table 2A and B) with respect to prognosis was studied in a subgroup of 562 patients. Spearman rank correlation revealed highly significant correlations among all CCNE1 variants studied (rs > 0.70, P < 0.001, n = 562). Irrespective of which splice variant was analyzed, increasing levels of CCNE1 predicted a poor prognosis. The assay used in this study aimed at detecting all variants of CCNE1 contributed similarly to MFS and overall survival compared with the various splice variants of CCNE1 investigated (data not shown).


   Discussion
Top
 Abstract
 Patients and Methods
 Results
 Discussion
References
 
Many research groups have investigated the link between immunochemically measured cyclin E1 protein and prognosis in breast cancer, although with conflicting results (1, 17, 21–28). These heterogeneous results have been attributed to differences in antibodies used to detect cyclin E1 (17) and to differences in the adjuvant treatment of patients (18, 29). In our present study, we aimed to overcome these pitfalls by using quantitative real-time PCR to evaluate the prognostic value of cyclin E mRNA levels in lymph node–negative breast cancer patients who did not receive adjuvant systemic therapy, which was common practice in the Netherlands in the time period from which we retrieved our primary tumor samples. We evaluated, in addition to various mRNA splice variants of CCNE1, the far less extensively studied CCNE2 member of the cyclin E family, and we are the first to present comprehensive data with respect to the prognostic value of cyclin E2.

The mRNA splice variants of CCNE1 did not add to the information we obtained from wild-type CCNE1. Although our study shows that both CCNE1 and CCNE2 are prognosticators for lymph node–negative breast cancer, differences were observed between the two genomic variants of cyclin E. In agreement with previous studies (22), we found that ER-negative tumors expressed significantly higher CCNE1 mRNA levels. Based on this observation, a potential role for cyclin E1 in mechanisms responsible for estrogen-independent tumor growth has already been suggested (22). We showed that, in contrast to CCNE1, median CCNE2 levels do not largely differ between ER-negative and ER-positive tumors. Furthermore, only CCNE1 was a significant prognostic factor in patients with ER-negative tumors.

Other dissimilarities between the two cyclin E members were observed. Only recently, we established that the predictive value of biological factors, among which ER-{alpha}, may be further refined by splitting tumor samples at the median level of 70% tumor cell nuclei in a cohort of stroma-poor tumors and a cohort of stroma-enriched tumors (19). Interaction analyses justified to perform a similar analysis for CCNE and showed that high CCNE1 was a better predictor of poor prognosis in the group of patients with stroma-enriched tumors compared with the group of patients with stroma-poor tumors. This strongly suggests a paracrine interaction between tumor cell derived cyclin E1 and a stromal cell–derived factor, resulting in a more aggressive tumor type with a very poor prognosis. High levels of CCNE2 were similarly associated with poor prognosis in tumors with high and tumors with a relatively low percentage of tumor cell nuclei. For CCNE2, such an interaction mechanism between tumor cells and stromal cells does, therefore, not seem to play a role. Profiling studies usually focus on tumors with a relatively high percentage of tumor cell nuclei. This, together with the already discussed differences associated with ER status, most likely explains why it was the more consistently informative CCNE2 variant and not the more susceptible to tissue heterogeneity CCNE1 variant that overlapped between the two gene expression profiles (8, 9).

Success in breast cancer treatment depends greatly upon early detection. More sensitive and specific indicators of prognosis are required to identify those patients at risk for disease progression. Great advantage will be gained with markers that are able to anticipate disease progress for patients with still small tumors, a group of patients for whom prediction of prognosis is especially difficult to assess. Trials of adjuvant therapy in patients with breast cancer no longer include an untreated control group. Therefore, available tumor banks are very helpful to address specific questions. We did a retrospective study using tumors from patients who had not received systemic adjuvant treatment to determine whether cyclin E is a pure prognostic factor. However, there are obvious limitations to a retrospective study on frozen material that must be acknowledged. The data in Table 1 describe clinicopathologic data that reflect common practice in those days and are not always as comprehensive as the data available nowadays. Due to the frozen nature of our material, (re)examination of histology, grade, proliferation index or, for example, HER-2/neu amplification by fluorescence in situ hybridization will not provide the same results as the current standardized methods used for paraffin-embedded material. Furthermore, because our tumor bank consists of frozen tumor material that was left after the biochemical and pathologic examinations, small-sized tumors of ≤1 cm are under represented in this study. Despite this limitation, high levels of CCNE1 and CCNE2 as measured by real-time PCR showed to be especially poor predictors of MFS for the 260 of 635 patients with small (T1) tumors.

Although gene expression profiling methods are definitely more comprehensive, and immunohistochemical methods are more informative with respect to localization of target molecules, real-time PCR is a sensitive, fast, quantitative, and cost-effective method suitable for high-throughput screening. In summary, PCR-based measurement of CCNE1 and CCNE2 fulfill the criteria of a clinically attractive biomarker to select early breast cancer patients at high risk for distant metastases.


   Acknowledgments
 
We thank the surgeons, pathologists, and internists of the St. Clara Hospital, Ikazia Hospital, St. Fransiscus Gasthuis, Erasmus MC at Rotterdam, and Ruwaard van Putten Hospital at Spijkenisse for their assistance in collecting the tumor tissues and patient's clinical follow-up data.


   Footnotes
 
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.

Received 1/31/06; revised 3/17/06; accepted 4/ 4/06.


   References
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 Abstract
 Patients and Methods
 Results
 Discussion
 References
 

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L. Harris, H. Fritsche, R. Mennel, L. Norton, P. Ravdin, S. Taube, M. R. Somerfield, D. F. Hayes, and R. C. Bast Jr
American Society of Clinical Oncology 2007 Update of Recommendations for the Use of Tumor Markers in Breast Cancer
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A. M. Sieuwerts, P. A. Usher, M. E. Meijer-van Gelder, M. Timmermans, J. W.M. Martens, N. Brunner, J. G.M. Klijn, H. Offenberg, and J. A. Foekens
Concentrations of TIMP1 mRNA Splice Variants and TIMP-1 Protein Are Differentially Associated with Prognosis in Primary Breast Cancer
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