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Träfflista för sökning "WFRF:(Lundberg Mathias) ;pers:(Agnarsdóttir Margrét)"

Sökning: WFRF:(Lundberg Mathias) > Agnarsdóttir Margrét

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1.
  • Rexhepaj, Elton, et al. (författare)
  • A Texture Based Pattern Recognition Approach to Distinguish Melanoma from Non-Melanoma Cells in Histopathological Tissue Microarray Sections
  • 2013
  • Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 8:5, s. e62070-
  • Tidskriftsartikel (refereegranskat)abstract
    • Aims: Immunohistochemistry is a routine practice in clinical cancer diagnostics and also an established technology for tissue-based research regarding biomarker discovery efforts. Tedious manual assessment of immunohistochemically stained tissue needs to be fully automated to take full advantage of the potential for high throughput analyses enabled by tissue microarrays and digital pathology. Such automated tools also need to be reproducible for different experimental conditions and biomarker targets. In this study we present a novel supervised melanoma specific pattern recognition approach that is fully automated and quantitative. Methods and Results: Melanoma samples were immunostained for the melanocyte specific target, Melan-A. Images representing immunostained melanoma tissue were then digitally processed to segment regions of interest, highlighting Melan-A positive and negative areas. Color deconvolution was applied to each region of interest to separate the channel containing the immunohistochemistry signal from the hematoxylin counterstaining channel. A support vector machine melanoma classification model was learned from a discovery melanoma patient cohort (n = 264) and subsequently validated on an independent cohort of melanoma patient tissue sample images (n = 157). Conclusion: Here we propose a novel method that takes advantage of utilizing an immuhistochemical marker highlighting melanocytes to fully automate the learning of a general melanoma cell classification model. The presented method can be applied on any protein of interest and thus provides a tool for quantification of immunohistochemistry-based protein expression in melanoma.
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2.
  • Stromberg, Sara, et al. (författare)
  • Selective Expression of Syntaxin-7 Protein in Benign Melanocytes and Malignant Melanoma
  • 2009
  • Ingår i: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 8:4, s. 1639-1646
  • Tidskriftsartikel (refereegranskat)abstract
    • To search for proteins expressed in human melanocytes and melanoma, we employed an antibody-based proteomics strategy to screen for protein expression in tissue microarrays containing normal tissues, cancer tissues and cell lines. Syntaxin-7 (STX7) was identified as a novel protein, not previously characterized in cells of melanocytic lineage, displaying a cell type-specific protein expression pattern. In tumor tissues, STX7 was expressed in malignant melanoma and lymphoma. The protein was further characterized regarding subcellular localization, specificity, tissue distribution pattern and potential as a diagnostic and prognostic marker using cell lines and tissue microarrays containing normal skin, melanocytic nevi and primary and metastatic melanoma. STX7 was expressed in normal melanocytes, various benign melanocytic nevi, atypical nevi and malignant melanoma. Analysis in two independent melanoma cohorts demonstrated STX7 expression in nearly all investigated tumors, although at varying levels (>90% positive tumors). The expression level of STX7 protein was inversely correlated to tumor stage, suggesting that decreased expression of STX7 is associated with more aggressive tumors. In conclusion, we present protein profiling data for a novel protein showing high sensitivity and specificity for cells of the melanocytic lineage. The presented antibody-based proteomics approach can be used as an effective strategy to identify novel tumor markers and evaluate their potential clinical relevance.
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