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Multigentests wurden entwickelt, um Krankheitsverlauf und Ansprechen der Chemotherapie beim primären Mammakarzinom vorherzusagen. Sie erfassen unterschiedliche Genmuster, die mit Hormonempfindlichkeit, Proliferation und Tumoraggressivität assoziiert sind, und geben Informationen über das Risiko für frühe oder späte Rezidive. Einige Tests erlauben auch eine Abschätzung des Chemotherapienutzens in den unterschiedlichen Risikogruppen. Derzeit werden v. a. 4 Tests (Endopredict®, Mammaprint®, Oncotype DX®, Prosigna™) in Deutschland eingesetzt, die alle bisher nur retrospektiv validiert sind. Die Ergebnisse prospektiver internationaler Validierungsstudien werden für Mammaprint (MINDACT) und Oncotype DX (TAILORx, RXPONDER) nicht vor 2016 erwartet. In Deutschland hat die WSG-PlanB-Studie gerade erstmals prospektive Überlebensdaten für Oncotype-DX-Risikogruppen gezeigt; diese Daten bestätigen ein exzellentes 3-Jahres-Überleben für Niedrigrisikopatientinnen mit bis zu drei befallenen Lymphknoten. Die WSG-ADAPT-Studie evaluiert derzeit die Kombination von Oncotype DX und Proliferationsansprechen nach präoperativer endokriner Kurzzeittherapie, um die optimale adjuvante Therapie bei mittleren Risiko festzulegen. Multigentests geben klinisch relevante Informationen beim primären Mammakarzinom. Wenn histopathologische Faktoren keine optimale Einschätzung der Tumorbiologie erlauben, helfen sie, Übertherapie durch (neo-)adjuvante Chemotherapie bei Niedrigrisikopatientinnen, aber auch Untertherapie zu vermeiden. Auch wenn einzelne Tests umfassendere Daten haben, besteht die beste Datenlage für den klinischen Nutzen von Multigentests bei postmenopausalen Patientinnen mit hormonrezeptorpositiven, HER2-negativen, nodalnegativen Mammakarzinomen. Multigene tests were developed to predict outcome and chemotherapy response in early breast cancer (eBC). These tests assess different gene panels mostly associated with endocrine responsiveness, proliferation, and tumor cell aggressiveness. They provide clinicians with information on risk for early, late locoregional, and distant relapses. Some of the tests even allow an estimate of chemotherapy benefits in the different risk groups. In Germany four tests, i.e. Endopredict®, Mammaprint®, Oncotype DX®, and Prosigna™, are currently commercially available and used. So far, all of them have only been validated retrospectively. Results of prospective international validation studies are pending for Mammaprint (MINDACT) and Oncotype DX (TAILORx and RXPONDER) and not expected before 2016. In Germany, the WSG-PlanB study has recently provided initial prospective outcome data for Oncotype DX risk groups confirming excellent short-term outcome for low-risk patients with up to three involved lymph nodes. The WSG-ADAPT study is currently evaluating a combination of Oncotype DX and dynamic proliferation response to short-term preoperative endocrine treatment for optimal therapy of the intermediate-risk group. In general, multigene assays provide clinically useful information in eBC. They may help to avoid overtreatment by (neo)adjuvant chemotherapy in low-risk patients and also to avoid undertreatment when established prognostic factors do not allow optimal assessment of tumor aggressiveness. Even though the data for broader clinical situations are available for some of these tests, the clinical usefulness has been best demonstrated in hormone receptor-positive HER2-negative disease for postmenopausal patients with node-negative primary breast cancer.

Tripelnegative Mammakarzinome (TNBC) sind durch das Fehlen therapeutisch nutzbarer Zielstrukturen definiert — der Abwesenheit von Hormonrezeptoren und HER2. Sie sind eine Hochrisikoerkrankung mit einem heterogenen Erscheinungsbild. Klinisch ist — neben der Lokaltherapie — eine Chemotherapie die Therapie der Wahl. Eine spezifische Chemotherapie oder zielgerichtete Therapie gibt es leider (noch) nicht. Aktuelle Studienkonzepte beim TNBC versuchen, die Chemotherapie zu optimieren, Prädiktoren für das Ansprechen zu finden, aber auch vielversprechende neue zielgerichtete Substanzen zu evaluieren.

The presence of isolated tumor cells in the bone marrow (ITC-BM) of breast cancer patients is an independent prognostic parameter, indicating hematogenous tumor cell dissemination. While the HER2 status of breast cancer tissue has predictive value for the efficacy of different therapies, its prognostic relevance is controversial. To investigate the relationship between HER2 and ITC-BM, we retrospectively analyzed tumor tissues of 327 patients who underwent bone marrow aspiration at primary diagnosis or during the disease-free interval. Screening for ITC-BM was performed immunocytochemically, using the anti-cytokeratin antibody A45 B/B3. HER2 was determined by immunohistochemistry (IHC) with the antibody CB 11 (n= 277) and by fluorescence in situ hybridization (FISH, PathVision, Vysis, n= 206). ITC-BM were found in 83 of 327 patients (25.4%), with a median of 2.0 per 2 × 106mononuclear cells. HER2 positivity (2+/3+) was demonstrated in 18.8% of the tumors, amplification by FISH in 56 of 206 cases (27.2%). Established pathological parameters,tiviathological parameters, such as tumor size (p= 0.15), lymph node status (p= 0.93) and HER2 did not predict the presence of ITC-BM. After a median follow-up of 49months (1–255), the presence of ITC-BM was a significant prognostic factor for distant disease free and overall survival, as well in univariate (log-rank-test, p= 0.024) as in multivariate analysis (cox-regression, p= 0.033 ). This also was confirmed in subgroups of patients by aease free survival (p= 0.013) and local recurrence (p= 0.003). The detection of ITC-BM is superior in predicting overall survival, compared to the HER2 status of the primary tumor. The direct identification of HER2 on ITC-BM is the aim of ongoing research, potentially synergizing the prognostic relevance of ITC-BM and the predictive value of the HER2 status.

AbstractHuman kallikrein 5 (hK5; encoded by the KLK5 gene) is a secreted serine protease expressed in hormonally regulated tissues, including the breast and ovary. We have previously reported regulation of the KLK5 gene by estrogens and progestins and its clinical value as a marker of poor prognosis in breast and ovarian cancers. We thus hypothesized that hK5 may represent a potential biomarker for ovarian carcinomas, at the protein level. Using a newly developed ELISA, hK5 levels were quantified (nanograms per milligram of total protein) in 22 low malignant potential (LMP) and 132 epithelial ovarian tumors and correlated with various clinicopathological variables and outcome [progression-free survival (PFS), overall survival (OS)]. hK5 concentration in LMP tumors ranged from 0 to 2.3 ng/mg (mean = 0.24) and from 0 to 220 ng/mg (mean = 3.35) in ovarian tumor cytosols (p = 0.002). Using a cutoff value of 0.15 ng/mg, 60% of ovarian tumors were categorized as hK5 positive. We found a strong correlation between patients with hK5-positive tumors and disease stages III/IV and grade 3 tumors (all p < 0.05). Univariate survival analysis revealed that hK5-positive patients had a significantly shorter PFS and OS (p < 0.05). Kaplan-Meier survival curves further confirmed an increased risk of relapse and death in women with hK5-positive tumors (p = 0.015 and p = 0.019, respectively). Multivariate analysis indicated that the prognostic value of hK5 was not independent from other parameters in the entire group of patients. When stratified by tumor grade (G1/2 vs. G3) and debulking success (optimal vs. suboptimal), univariate and multivariate analyses demonstrated that hK5 was an independent indicator of poor prognosis for patients with grade 3 tumors and with optimal debulking (p < 0.05). In patients with disease stage I/II versus III/IV, hK5 positivity was independently associated with a shorter PFS (p = 0.046) and marginally decreased OS (p = 0.08), in multivariate analysis. Lastly, we observed a fairly weak, positive, but statistically significant correlation between the expression levels of tissue hK5 and tissue CA125 (rs = 0.297; p < 0.001). Our findings provide evidence for an association between hK5 and more aggressive forms of epithelial ovarian cancer.Copyright © 2003 S. Karger AG, Basel

After long-term follow-up, the prognostic impact of the following proteolytic factors associated with tumor invasion and metastasis was evaluated in 276 primary breast cancer patients: uPA (urokinase-type plasminogen activator), PAI-1 (uPA inhibitor type 1), and cathepsins B, D and L. The median follow-up of patients still alive at the time of analysis was 109 months. To date 119 patients (43%) have relapsed and 117 (42%) have died. Antigen levels of uPA and PAI-1 were determined by ELISA in detergent extracts; cathepsin B, D, and L content was determined in cytosol fractions of the primary tumor: cathepsin D by ELSA and cathepsin B and L by ELISA.In multivariate analysis (Cox model) for disease-free survival (DFS), lymph node status (p<0.001; RR=3.8), cathepsin L (p<0.001; RR=2.6) and PAI-1 (p=0.027; RR=1.7) were significant factors in all patients. In addition to these factors, grading was significant for overall survival (OS). In another multivariate approach, CART (Classification And Regression Trees) analysis, lymph node status (p<0.001) turned out to be the strongest discriminator for patients at high risk of relapse. In the node-negative patient subset, PAI-1 was the strongest risk group discriminator (p<0.001): in this subset, patients with low levels of both PAI-1 and cathepsin D had a very low relapse rate of only 3.2% compared to 39% in the remaining node-negative patients. In node-positive patients cathepsin L gave the best risk group assessment (p=0.001).In conclusion, tumor-associated PAI-1 and cathepsins D and L provide significant, statistically independent prognostic information for DFS and OS in primary breast cancer, even after a median follow-up period of almost 10 years.

In axillary node-negative primary breast cancer, 70% of the patients will be cured by locoregional treatment alone. Therefore, adjuvant systemic therapy is only needed for those 30% of node-negative patients who will relapse after primary therapy and eventually die of metastases. Traditional histomorphological and clinical factors do not provide sufficient information to allow accurate risk group assessment in order to identify node-negative patients who might benefit from adjuvant systemic therapy. In the last decade various groups have reported a strong and statistically independent prognostic impact of the serine protease uPA (urokinase-type plasminogen activator) and its inhibitor PAI-1 (plasminogen activator inhibitor type 1) in node-negative breast cancer patients. Based on these data, a prospective multicenter therapy trial in node-negative breast cancer patients was started in Germany in June 1993, supported by the German Research Association (DFG). Axillary node-negative breast cancer patients with high levels of either or both proteolytic factors in the tumor tissue were randomized to adjuvant CMF chemotherapy versus observation only. Recruitment was continued until the end of 1998, by which time 684 patients had been enrolled. Since then, patients have been followed up in order to assess the value of uPA and PAI-1 determination as an adequate selection criterion for adjuvant chemotherapy in node-negative breast cancer patients. This paper reports on the rationale and design of this prospective multicenter clinical trial, which may have an impact on future policies in prognosis-oriented treatment strategies.

At the time of primary therapy (surgery, systemic chemotherapy and/or radiation), disseminated tumor cells in the bone marrow can be found in almost one-third of patients with cancer of the breast, ovary, esophagus, stomach, colon, and other solid tumors. Whereas the prognostic impact of the mere presence of these cells is still a matter of debate, it has been shown that expression of tumor-associated antigens in disseminated tumor cells is linked to more aggressive disease. Therefore, further characterization of disseminated tumor cells at the protein and gene level has become increasingly important. To date, the most common detection method for disseminated tumor cells in the bone marrow is an immunocytochemical approach using cytokeratin-directed antibodies for detection of epithelial cells and the APAAP system for their visualization. We have established a new double immunofluorescence technique enabling simultaneous detection, phenotyping, and antigen quantification of disseminated tumor cells. Mononuclear cells from bone marrow are enriched by Ficoll gradient centrifugation and cytospins are prepared. Double immunofluorescence is performed using antibodies against cytokeratins 8/18/19 (mAb A45B/B3) and the uPA receptor CD87 (pAb HU277). CD87 expression is recorded by confocal laser scanning microscopy (CLSM) using fluorescence labeled latex beads as the reference; staining intensities of all the scans are then summed and quantified (extended focus). This protocol, originally designed for disseminated tumor cells in bone marrow, can also be applied to disseminated tumor cells in blood, to leukapheresis cells or to cells present in malignant ascites or other malignant effusions. The tumor cells detected may be used for gene and mRNA analyses. Furthermore, disseminated tumor cells also represent interesting targets for clinical studies on patient prognosis or prediction of therapy response as well as for specific tumor-biological therapies.

This paper reports on the performance of a recently developed neural network environment incorporating likelihood-based optimization and complexity reduction techniques in the analysis of breast cancer follow-up data with the goal of building up a clinical decision support system. The inputs to the neural network include classical factors such as grading, age, tumor size, estrogen and progesterone receptor measurements, as well as tumor biological markers such as PAI-1 and uPA. The network learns the structural relationship between these factors and the follow-up data. Examples of neural models for relapse-free survival are presented, which are based on data from 784 breast cancer patients who received their primary therapy at the Department of Obstetrics and Gynecology, Technische Universität München, Germany. The performance of the neural analysis as quantified by various indicators (likelihood, Kaplan-Meier curves, log-rank tests) was very high. For example, dividing the patients into two equally sized groups based on the neural score (i.e., cutoff = median score) leads to an estimated difference in relapse-free survival of 40% or better (80% vs. 40%) after 10 years in Kaplan-Meier analysis. Evidence for factor interactions as well as for time-varying impacts is presented. The neural network weights included in the models are significant at the 5% level. The use of neural network analysis and scoring in combination with strong tumor biological factors such as uPA and PAI-1 appears to result in a very effective risk group discrimination. Considerable additional comparison of data from different patient series will be required to establish the generalization capability more firmly. Nonetheless, the improvement of risk group discrimination represents an important step toward the use of neural networks for decision support in a clinical framework and in making the most of biological markers.

In breast cancer, several investigations have demonstrated that the tumour biological factors uPA urokinase-type plasminogen activator) and its inhibitor PAI-1 are statistically independent, strong prognostic factors for disease-free (DFS) and overall survival (OS). However, statistical analyses performed for varying follow-up periods suggested a time variation of prognostic strength. We therefore investigated the time-dependent prognostic power of uPA, PAI-1 and steroid hormone receptor status applying the time-varying coefficient model of Gray. uPA and PAI-1 were analysed by enzyme-linked immunosorbent assay in tumour tissue extracts from 314 breast cancer patients. Hormone receptors (oestrogen and progesterone) were determined by radioligand binding or by immunohistochemistry. Univariate and multivariate analyses (Cox proportional hazards model) of DFS and OS were performed for all patients, including 147 node-negative patients. Median follow-up of patients still alive at time of analysis (n = 232) was 58 months. Although initially of high prognostic impact, a continuous decrease over time in the prognostic power of hormone receptor status and uPA was observed. In contrast, the prognostic impact of PAI-1 increased over time and reached similar strength as the lymph node status. The time-dependent risk profile of prognostic factors may have important clinical implications in regard to follow-up and patients' individual risk situation. Evaluation of time dependency of prognostic factors may also give a more profound insight into the dynamics of breast cancer metastasis.

We examined bone marrow aspirates from 100 metastasis-free primary breast cancer patients. In 38/100 patients (38%), tumour cells were detected in the marrow using an immunocytochemical technique with a cocktail of two monoclonal antibodies: anti-EMA and anti-cytokeratin. Median follow-up was 34 months: 15/38 (39%) tumour cell-positive patients have since relapsed, but only 9/62 (15%) tumour cell-negative patients. The median interval between tumour cell detection and relapse was 11.4 months. No statistically significant correlation existed between tumour cell presence and 'established' prognostic factors. However, relapse-free survival was significantly shorter in tumour cell-positive patients. Multivariate analysis showed tumour cell presence as a strong, significant prognostic factor for relapse-free as well as overall survival. We conclude that screening for tumour cells in bone marrow of primary breast cancer patients identifies high-risk patients for early relapse. In particular, patients with node-negative tumours who have tumour cells in their bone marrow may require subsequent systemic therapy.

MIB1 proliferation rate (MIB1-PR) and total S-phase fraction (SPF) were retrospectively determined in formalin-fixed, paraffin-embedded sections of 90 primary node-negative breast carcinomas. None of the patients had received adjuvant systemic therapy. Median follow-up in patients still alive at the time of analysis was 37.5 months (16-72 months). Immunostaining of Ki-67 antigen was performed using the monoclonal antibody MIB1 and the APAAP technique. An adjacent 50-microm paraffin section was used for flow cytometric S-phase determination. Results were compared to established clinicopathological prognostic factors. MIB1-PR was significantly correlated to grading (P = 0.018); SPF was significantly correlated with tumour size (P = 0.041) and inversely with steroid hormone receptor status (P = 0.03). A significant correlation between MIB1-PR and SPF was found in aneuploid (P = 0.025) but not in diploid tumours (P = 0.164). In univariate analysis, both MIB1-PR (optimized cut-off of 25%) and SPF (optimized cut-off of 8%) were significant prognostic factors for disease-free survival (DFS) (MIB1-PR, P = 0.0224; SPF, P = 0.0028). In multivariate analysis, however, only SPF remained significant; it was the strongest prognostic factor for DFS (P = 0.0073), stronger than MIB1-PR or established clinicopathological prognostic factors. We thus conclude that MIB1-PR and SPF provide additional prognostic information in node-negative breast cancer. However, in our study, flow cytometrically determined SPF had the greater prognostic impact.

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