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Untitled Document
CANCER GENOMICS & PROTEOMICS
Volume 2, Number
5, September-October 2005
| CONTENTS |
PAGE |
| *Application of Microarrays for the Prediction of Therapy Response in Breast Cancer. B. GYORFFY, P. SUROWIAK, H. LAGE (Berlin, Germany; Budapest, Hungary; Wroclaw, Poland) |
255 |
| Expression of Integrins and Adhesive Properties of Human Endothelial Cell Line EA.hy 926. P. BARANSKA, H. JERCZYNSKA, Z. PAWLOWSKA, W. KOZIOLKIEWICZ, C. S. CIERNIEWSKI (Lodz, Poland) |
265 |
| The Protein Profile of the Human Immature T-cell Line CCRF-CEM. A. K. ANAGNOSTOPOULOS, K. VOUGAS, A. KOLIALEXI, A. MAVROU, M. FOUNTOULAKIS, G. T. TSANGARIS (Athens, Greece) |
271 |
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*Phylogenetics: Applications, Software and Challenges. A. STAMATAKIS (Heraklion, Greece) |
301 |
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| *Reviews
(pages 255,301) |
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CANCER GENOMICS & PROTEOMICS 2: 265-270 (2005)
Expression of Integrins and Adhesive Properties of Human Endothelial Cell Line EA.hy 926
PATRYCJA BARANSKA, HANNA JERCZYNSKA, ZOFIA PAWLOWSKA, WIKTOR KOZIOLKIEWICZ, CZESLAW S. CIERNIEWSKI
Department of Molecular and Medical Biophysics, Medical University of Lodz, Lodz, Poland
Abstract: Immortalized endothelial cell lines are very often used as a model of endothelium for studies of various processes connected with its functions. Among the hybrid cells, the EA.hy 926 cell line, derived by the fusion of HUVECs with the continuous human lung carcinoma cell line A549, is presently the best characterized macro-vascular endothelial cell line. Although EA.hy 926 cells retain several endothelial characteristics, our data show some differences between this cell line and primary human umbilical vein endothelial cells (HUVEC). Analysis of their proteomic pattern reveals that there are many proteins expressed only in the immortalized cell line, but several proteins of EA.hy 926 are missed when compared to HUVECs. We observed a distinct profile of integrin expression on the surface of both types of endothelial cells, that may be responsible for diminished EA.hy 926 adhesion and migration to selected adhesive proteins. Studies on proliferation and migration in the presence of VEGF showed lower growth factor responsiveness of EA.hy 926 in comparison with HUVECs, but hybrid endothelial cells can also be converted into a pro-angiogenic phenotype. These studies showed significant similarity of endothelial cell lines with primary HUVECs, but also pointed out marked phenotype differences.
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CANCER GENOMICS & PROTEOMICS 2: 271-300 (2005)
The Protein Profile of the Human Immature T-cell Line CCRF-CEM
ATHANASIOS K. ANAGNOSTOPOULOS1, KONSTANTINOS VOUGAS1, AGELIKI KOLIALEXI2, ARIADNI MAVROU2, MICHAEL FOUNTOULAKIS1, GEORGE T. TSANGARIS1
1Division of Biotechnology, Center of Basic Research,Foundation of Biomedical Research of the Academy of Athens, Athens;
2Medical Genetics, Athens University School of Medicine, Athens, Greece
Abstract: The human immature T-cell line CCRF-CEM is widely used for all kinds of in vitro studies in biochemistry, biology, toxicology and medicine. Knowledge about protein expression is limited and no comprehensive study on the proteome of this cell type has been reported to date. Proteomics technologies were applied in order to analyse the proteins of the CEM cell line. The proteins were separated by two-dimensional (2-D) gel electrophoresis and analysed by MALDI-MS and MALDI-MS-MS following in-gel digestion with trypsin and, finally, protein identification was carried out by peptide mass fingerprint (PMF) and post source decay (PSD), respectively. Approximately 4,500 spots, excised from four 2-D gels, were analysed. The analysis resulted in the identification of about 1,150 proteins, the products of 451 different genes. The majority of the identified proteins were enzymes, regulatory proteins and transporters, while leukocyte markers and oncogenes were also included. The CCRF-CEM cell database today represents one of the largest 2-D databases for eukaryotic proteomes, forming the basis for future expressional studies at the protein level.
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CANCER GENOMICS & PROTEOMICS 2: 301-306 (2005)
Phylogenetics: Applications, Software and Challenges
ALEXANDROS STAMATAKIS
Foundation for Research and Technology-Hellas, Institute of Computer Science, Crete, Greece
Abstract: Inference of phylogenetic trees comprising hundreds of organisms based on elaborate statistical models of evolution is an intensive computational task. However, in recent years there has been an impressive improvement in search algorithms, which currently allow for inference of huge phylogenetic trees comprising more than 1,000 taxa within a couple of hours on a single PC. This paper provides an overview of applications of phylogenetic trees to various areas of biological and medical research and reviews some of the most efficient software available for phylogenetic inference. Finally, some of the new challenges that the field currently faces in the areas of high performance computing and information visualization are discussed.
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CANCER GENOMICS & PROTEOMICS 2: 255-264 (2005)
Application of Microarrays for the Prediction of Therapy Response in Breast Cancer
BALAZS GYÏRFFY1,2, PAWEL SUROWIAK1,3, HERMANN LAGE1
1Institute of Pathology, Charité, Humboldt University Berlin, Germany;
2Szentágothai János Knowledge Centre, Semmelweis University Budapest, Hungary;
3Department of Histology and Embryology, University School of Medicine, Wroclaw, Poland
Abstract: Single genes, which can be used to predict response to therapy in breast cancer, including estrogen receptor (ER), HER-2, metallothionein and the ABC transporters are discussed. With the exception of the ER status, no single tumor marker has been shown to possess a sufficient predictive value to render it clinically useful. To achieve greater predictive power, multiple markers need to be examined and correlated with response to chemotherapy. With the advent of high-throughput quantification of gene expression, simultaneous assessment of thousands of genes is now possible, which allows identification of expression patterns in different breast cancers that might correlate with and, thereby, predict survival or response to treatment. Recent studies using microarrays to investigate survival prediction, chemotherapy resistance and therapy response are discussed. In vivo and in vitro experiments are discussed. Particular interest is given to anthracycline treatment, where in vitro drug resistance data may be useful for patient prognosis prediction. However, different microarray platforms can provide different results for the same experiment. A recommended statistical pathway is still not yet accepted. These problems have to be solved before future diagnostic applications using cDNA microarrays can be developed. In the near future, it can be expected that various microarray studies will be available to analyze hundreds to thousands of patients, selecting and validating predictive gene expression signatures.
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