PubMed · 10027251
The source did not provide an abstract. Follow the original record for more information.
Explore connections, maps & timelines
H Nagahara, R R Latek, S A Ezhevsky, S F Dowdy. 1999. 2-D phosphopeptide mapping.. https://doi.org/10.1385/1-59259-584-7%3A271
Cite the original work for its findings. Save a collection to share your selection of sources.
KEEP EXPLORING
The metastatic spread of tumor cells in malignant progression is known to be a major cause of cancer mortality. Protein glycosylation is increasingly being recognized as one of the most prominent biochemical alterations associated with malignant transformation and tumorigenesis. The Multiplexed Proteomics (MP) approach is a new technology that permits quantitative, multicolor fluorescence detection of proteins in two-dimensional (2-D) gels and on Western blots. This methodology allows the parallel determination of both altered glycosylation patterns and protein expression level changes within a single 2-D gel experiment. The linear responses of the fluorescent dyes utilized allow rigorous quantitation of changes in protein expression over a broad 3-log linear dynamic range. Global analysis of changes in protein glycosylation and total protein expression is followed by dichromatic, lectin-based profiling methods for rapidly categorizing glycan branching structures. The MP approach was applied to whole tissue extracts of normal and cancerous liver, so that altered glycosylation modification patterns and protein expression levels could be determined. One prominent glycoprotein determined to be up-regulated in the tumor tissue was haptoglobin, an acute-phase response protein. The detection methodologies associated with the MP technology radically increase the information content of 2-D gel experiments. This new information greatly enhances the applicability of these experiments in addressing fundamental questions associated with proteome-wide glycosylation changes related to cancer.
Two-dimensional (2D) electrophoresis is the most wide spread technique for the separation of proteins in biological systems. This technique produces 2D maps of high complexity, which creates difficulties in the comparison of different samples. The method proposed in this paper for the comparison of different 2D maps can be summarised in four steps: (a) digitalisation of the image; (b) fuzzyfication of the digitalised map in order to consider the variability of the two-dimensional electrophoretic separation; (c) decoding by principal component analysis of the previously obtained fuzzy maps, in order to reduce the system dimensionality; (d) classification analysis (linear discriminant analysis), in order to separate the samples contained in the dataset according to the classes present in said dataset. This method was applied to a dataset constituted by eight samples: four belonging to healthy human lymph-nodes and four deriving from non-Hodgkin lymphomas. The amount of fuzzyfication of the original map is governed by the sigma parameter. The larger the value, the more fuzzy theresulting transformed map. The effect of the fuzzyfication parameter was investigated, the optimal results being obtained for sigma = 1.75 and 2.25. Principal component analysis and linear discriminant analysis allowed the separation of the two classes of samples without any misclassification.
Explore the source record for details and available documents.