Tumor markers in breast cancer - European Group on Tumor Markers recommendations

Recommendations are presented for the routine clinical use of serum and tissue-based markers in the diagnosis and management of patients with breast cancer. Their low sensitivity and specificity preclude the use of serum markers such as the MUC-1 mucin glycoproteins ( CA 15.3, BR 27.29) and carcinoembryonic antigen in the diagnosis of early breast cancer. However, serial measurement of these markers can result in the early detection of recurrent disease as well as indicate the efficacy of therapy. Of the tissue-based markers, measurement of estrogen and progesterone receptors is mandatory in the selection of patients for treatment with hormone therapy, while HER-2 is essential in selecting patients with advanced breast cancer for treatment with Herceptin ( trastuzumab). Urokinase plasminogen activator and plasminogen activator inhibitor 1 are recently validated prognostic markers for lymph node-negative breast cancer patients and thus may be of value in selecting node-negative patients that do not require adjuvant chemotherapy. Copyright (C) 2005 S. Karger AG, Basel

Serum CEA and CA 15-3 as prognostic factors in primary breast cancer

In the present study, we investigated the association of the serum levels of the tumour markers carcinoembryonic antigen and cancer antigen 15-3 with disease free survival and death from disease in 1046 women with breast cancer without metastases at the time of primary diagnosis in relation to age and the established prognostic factors tumour size, lymph node status, histological grading and hormone receptor status. We found that elevated pre-operative serum marker values were correlated with early relapse (cancer antigen 15-3; P=0.0003) and death from disease (carcinoembryonic antigen, cancer antigen 15-3; P=0.0001 both) in univariate analyses. By comparing pre- and post-operative values we found a decline in values post-surgery. In those patients where marker levels of carcinoembryonic antigen decreased more than 33%, a significantly higher risk for relapse and death from disease (both P=0.0001) in univariate analyses was observed. In multivariate analysis this decrease of carcinoembryonic antigen proved to be an independent prognostic factor. The results for cancer antigen 15-3 were comparable to carcinoembryonic antigen in univariate analyses but showed no significance in multivariate analysis. In this study the post-operative decrease of the serum tumour marker carcinoembryonic antigen was a strong independent prognostic factor for disease free survival and death from disease in breast cancer patients

Rationalization and Design of the Complementarity Determining Region Sequences in an Antibody-Antigen Recognition Interface

Protein-protein interactions are critical determinants in biological systems. Engineered proteins binding to specific areas on protein surfaces could lead to therapeutics or diagnostics for treating diseases in humans. But designing epitope-specific protein-protein interactions with computational atomistic interaction free energy remains a difficult challenge. Here we show that, with the antibody-VEGF (vascular endothelial growth factor) interaction as a model system, the experimentally observed amino acid preferences in the antibody-antigen interface can be rationalized with 3-dimensional distributions of interacting atoms derived from the database of protein structures. Machine learning models established on the rationalization can be generalized to design amino acid preferences in antibody-antigen interfaces, for which the experimental validations are tractable with current high throughput synthetic antibody display technologies. Leave-one-out cross validation on the benchmark system yielded the accuracy, precision, recall (sensitivity) and specificity of the overall binary predictions to be 0.69, 0.45, 0.63, and 0.71 respectively, and the overall Matthews correlation coefficient of the 20 amino acid types in the 24 interface CDR positions was 0.312. The structure-based computational antibody design methodology was further tested with other antibodies binding to VEGF. The results indicate that the methodology could provide alternatives to the current antibody technologies based on animal immune systems in engineering therapeutic and diagnostic antibodies against predetermined antigen epitopes

Mechanism and cellular function of Bud6 as an actin nucleation–promoting factor

Bud6 functions as an actin nucleation–promoting factor (NPF) for Bni1; thus formins can depend on NPFs like the Arp2/3 complex. Unexpected parallels exist between Bud6 and WASp. Bud6 is the first nonmetazoan example of formins pairing with actin monomer–binding proteins to stimulate nucleation, akin to Spire-Capu and APC-mDia