[The modification of the prephase of coagulation with dextran 150 in vitro].
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Adult↗
Biomedical subjects
H Graeff
Publications and source records attributed to H Graeff.
The importance of early laboratory screening methods for maternal and fetal outcome in cases of HELLP syndrome.
Over a period of 5 years and 3 months 50 patients with HELLP syndrome were treated at our hospitals. All of these patients fulfilled the criteria of this syndrome described by Weinstein. Pre-eclampsia with HELLP syndrome was either diagnosed correctly by the referring doctor or on admission by the obstetrician on the basis of the laboratory findings. The median time interval between admission and delivery was 3 hours (range: 0.5-40 hours). In 49 patients, Caesarean section was performed, one patient developed a HELLP syndrome 18 hours after vaginal delivery. The median gestational age at delivery was 35 weeks (range: 26-40). Only three of 51 infants died before delivery, and there was one neonatal death, resulting in a perinatal mortality of 7.8%. Apgar scores below 7 occurred in 15 of the newborns after 1 min and in only 2 after 5 min. In 47 cases, Caesarean section and hospital course were free of complications; in three patients postoperative hemorrhages required relaparotomy, in two of these patients puerperal hysterectomy had to be performed. In our experience, the relevant laboratory parameters should be determined in any pregnant women with right upper quadrant pain independent of the severity of pre-eclampsia in order to diagnose HELLP syndrome as soon as possible. Both early control and follow-up of the laboratory parameters and immediate delivery--by Caesarean section, if necessary--may lead to a reduction of maternal mortality and morbidity and to an improvement of perinatal results.
Adult↗
Tumor-biological factors uPA and PAI-1 as stratification criteria of a multicenter adjuvant chemotherapy trial in node-negative breast cancer.
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.
Biomarkers, Tumor↗
Long-term follow-up confirms prognostic impact of PAI-1 and cathepsin D and L in primary breast cancer.
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.
Adult↗
A new approach to phenotyping disseminated tumor cells: methodological advances and clinical implications.
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.
Biomarkers, Tumor↗
Neural network analysis of follow-up data in primary breast cancer.
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.
Adult↗
Inhibition of the interaction of urokinase-type plasminogen activator (uPA) with its receptor (uPAR) by synthetic peptides.
Focusing of the serine protease urokinase-type plasminogen activator (uPA) to the cell surface via interaction with its specific receptor (uPAR, CD87) is an important step for tumor cell invasion and metastasis. The ability of a synthetic peptide derived from the uPAR-binding region of uPA (comprising amino acids 16-32 of uPA; uPA(16-32)) to inhibit binding of fluorescently labeled uPA to uPAR on human promyeloid U937 cells was assessed by quantitative flow cytofluorometric analysis (FACS) and compared to the inhibitory capacities of other synthetic peptides known to interfere with uPA/uPAR-interaction. An about 3000-fold molar excess of uPA(16-32) resulted in 50% inhibition of pro-uPA binding to cell surface-associated uPAR. Using a solid-phase uPA-ligand binding assay employing recombinant soluble uPAR coated to microtiter plates, the minimal binding region of wild-type uPA was determined. The linear peptide uPA(19-31) and its more stable disulfide-bridged cyclic form (cyclo(19,31)uPA(19-31)) displayed uPAR-binding activity whereas other peptides such as uPA(18-30), uPA(20-32) or uPA(20-30) did not react with uPAR. Cyclic peptide derivatives of cyclo(19,31)uPA(19-31) in which certain amino acids were deleted and/or replaced by other amino acids as well as uPAR-derived wild-type peptides did also not inhibit uPA/uPAR-interaction. Therefore, the present investigations identified cyclo(19,31)uPA(19-31) as a potential lead structure for the development of uPA-peptide analogues to block uPA/uPAR-interaction.
Amino Acid Sequence↗
Detection of micrometastases in sentinel lymph nodes of the breast applying monoclonal antibodies AE1/AE3 to pancytokeratins.
Sentinel lymph node excision in breast cancer is a minimally invasive diagnostic procedure for accurate staging of the axilla and for avoiding unnecessary axillary dissection. In patients with palpable breast cancer we injected microcolloidal particles of human serum albumin labelled with technetium-99m the day before surgery. The sentinel node was detected intraoperatively with a handheld gammaprobe and then removed. Complete axillary dissection was performed and the nodes inspected by routine histological examination. The axillary lymph node status was correctly predicted by the sentinel node technique in 32 of 33 breast cancer patients. Two cases of micrometastases escaped routine histopathological detection but were identified by immunohistochemical analysis applying the antibody AE1/AE3 to pancytokeratins. Immunohistochemical examination of the sentinel node improves the diagnostic security of patients with breast carcinoma by detection of micrometastases.
Adult↗
Identification of low-risk node-negative breast cancer patients by tumor biological factors PAI-1 and cathepsin L.
In node-negative breast cancer, 70% of patients are cured by surgery alone and thus should be spared the necessity of systemic adjuvant treatment. Histomorphological and tumor biological prognostic factors may be employed to assess the patient's risk profile with regard to disease recurrence and death. To evaluate the relationship between tumor biological factors and the metastatic potential of primary breast cancer, proteolytic factors uPA, PAI-1, and cathepsin L, which are associated with tumor invasion and metastasis, were determined in breast cancer tissue extracts by ELISA and the values assessed by uni- and multivariate analysis as well as CART (classification and regression trees) in comparison with traditional prognostic factors. Cysteine protease cathepsin L, serine protease uPA, and the protease inhibitor PAI-1 were determined by ELISA in extracts of primary tumors of 103 node-negative breast cancer patients and values assessed by univariate and multivariate analysis in comparison with traditional prognostic factors (tumor size, steroid hormone receptor status, grading, vessel invasion, menopausal status). Median follow-up of patients still alive at time of follow-up was 56.5 months (range 34-88). PAI-1, cathepsin L, tumor size, grading, and steroid hormone receptor status but not uPA, vessel invasion, and menopausal status were of prognostic relevance for disease-free survival (univariate analysis). Multivariate analysis of disease-free survival (Cox proportional hazards model) disclosed PAI-1 (relative risk of 8.6, p = 0.0001) to be the only strong and statistically independent prognostic factor. By CART-analysis, however, the combination of PAI-1 (< or = 14 ng/mg protein) and cathepsin L (< or = 1,100 ng/mg protein) allowed the identification of a subgroup comprising 68% of the node-negative breast cancer patients having a very low risk of disease recurrence (2/70; incidence of 0.8% per year) versus the high-risk group with PAI-1 (> 14 ng/mg protein) and cathepsin L (> 1,100 ng/mg protein) showing an increased recurrence rate (14/33; incidence of 8.6% per year). We conclude that by the combined determination of PAI-1 and cathepsin L tumor levels low-risk node-negative breast cancer patients may be identified. These patients most probably will not benefit from systemic adjuvant therapy.
Adult↗
Prognostic impact of tumor biological factors on survival in node-negative breast cancer.
Tumor biological factors uPA, PAI-1, cathepsin D, S-phase fraction (SPF), MIB1 (Ki-67), p53, and HER-2/neu were assessed in 100 node-negative breast cancer patients. Their prognostic impact on disease-free (DFS) as well as overall survival (OS) was compared to that of traditional factors tumor size, grading, and steroid hormone receptor status. Antigen levels of uPA, its inhibitor PAI-1, and cathepsin D were determined in tumor tissue extracts by immunoenzymatic methods. SPF was determined by flow cytofluorometry, MIB1, p53, and HER-2/neu by immunohistochemistry in adjacent routinely formalin-fixed paraffin sections. Median follow-up in all patients still alive at time of analysis was 76 months. Univariate analysis determined PAI-1 (p = 0.0001), uPA (p = 0.0437), MIB1 (p = 0.0214), and SPF (p = 0.0248) as statistically significant prognostic factors for DFS. In contrast, tumor size, steroid hormone receptor status, grading, p53, HER-2/neu, and cathepsin. D failed to be of prognostic value. In multivariate analysis, including the statistically significant prognostic factors PAI-1, uPA, MIB1, and SPF, only PAI-1 (p = 0.0003, relative risk: 4.7) proved to be of independent statistical significance for DFS. Regarding OS, PAI-1 was the only statistically significant prognostic factor in univariate (p = 0.0001) as well as multivariate analysis (p = 0.0000, relative risk: 7.1). Thus, factors describing the invasive and metastatic capacity of tumor cells (uPA, PAI-1) and factors related to their proliferative activity (SPF, MIB1) provide valuable prognostic information in node-negative breast cancer patients.
Biomarkers, Tumor↗