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Sökning: WFRF:(Vuu Jimmy)

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1.
  • Blokzijl, Andries, et al. (författare)
  • Elevated Levels of SOX10 in Serum from Vitiligo and Melanoma Patients, Analyzed by Proximity Ligation Assay
  • 2016
  • Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 11:4
  • Tidskriftsartikel (refereegranskat)abstract
    • BackgroundThe diagnosis of malignant melanoma currently relies on clinical inspection of the skin surface and on the histopathological status of the excised tumor. The serum marker S100B is used for prognostic estimates at later stages of the disease, but analyses are marred by false positives and inadequate sensitivity in predicting relapsing disorder.ObjectivesTo investigate SOX10 as a potential biomarker for melanoma and vitiligo.MethodsIn this study we have applied proximity ligation assay (PLA) to detect the transcription factor SOX10 as a possible serum marker for melanoma. We studied a cohort of 110 melanoma patients. We further investigated a second cohort of 85 patients with vitiligo, which is a disease that also affects melanocytes.ResultsThe specificity of the SOX10 assay in serum was high, with only 1% of healthy blood donors being positive. In contrast, elevated serum SOX10 was found with high frequency among vitiligo and melanoma patients. In patients with metastases, lack of SOX10 detection was associated with treatment benefit. In two responding patients, a change from SOX10 positivity to undetectable levels was seen before the response was evident clinically.ConclusionsWe show for the first time that SOX10 represents a promising new serum melanoma marker for detection of early stage disease, complementing the established S100B marker. Our findings imply that SOX10 can be used to monitor responses to treatment and to assess if the treatment is of benefit at stages earlier than what is possible radiologically.
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2.
  • Karlsson, Max, et al. (författare)
  • Genome-wide single cell annotation of the human protein-coding genes
  • Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
    • An important quest for the life science community is to deliver a complete annotation of the human building-blocks of life, the genes and the proteins. Here, we report on a genome-wide effort to annotate all protein-coding genes based on single cell transcriptomics data representing all major tissues and organs in the human body, integrated with data from bulk transcriptomics and antibody-based tissue profiling. Altogether, 25 tissues have been analyzed with single cell transcriptomics resulting in genome-wide expression in 444 single cell types using a strategy involving pooling data from individual cells to obtain genome-wide expression profiles of individual cell type. We introduce a new genome-wide classification tool based on clustering of similar expression profiles across single cell types, which can be visualized using dimensional reduction maps (UMAP). The clustering classification is integrated with a new “tau” score classification for all protein-coding genes, resulting in a measure of single cell specificity across all cell types for all individual genes. The analysis has allowed us to annotate all human protein-coding genes with regards to function and spatial distribution across individual cell types across all major tissues and organs in the human body. A new version of the open access Human Protein Atlas (www.proteinatlas.org) has been launched to enable researchers to explore the new genome-wide annotation on an individual gene level.
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3.
  • Sivertsson, Åsa, et al. (författare)
  • Enhanced Validation of Antibodies Enables the Discovery of Missing Proteins
  • 2020
  • Ingår i: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 19:12, s. 4766-4781
  • Tidskriftsartikel (refereegranskat)abstract
    • The localization of proteins at a tissue- or cell-type-specific level is tightly linked to the protein function. To better understand each protein's role in cellular systems, spatial information constitutes an important complement to quantitative data. The standard methods for determining the spatial distribution of proteins in single cells of complex tissue samples make use of antibodies. For a stringent analysis of the human proteome, we used orthogonal methods and independent antibodies to validate 5981 antibodies that show the expression of 3775 human proteins across all major human tissues. This enhanced validation uncovered 56 proteins corresponding to the group of "missing proteins" and 171 proteins of unknown function. The presented strategy will facilitate further discussions around criteria for evidence of protein existence based on immunohistochemistry and serves as a useful guide to identify candidate proteins for integrative studies with quantitative proteomics methods.
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4.
  • Sjöstedt, Evelina, et al. (författare)
  • Integration of Transcriptomics and Antibody-Based Proteomics for Exploration of Proteins Expressed in Specialized Tissues
  • 2018
  • Ingår i: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 17:12, s. 4127-4137
  • Tidskriftsartikel (refereegranskat)abstract
    • A large portion of human proteins are referred to as missing proteins, defined as protein-coding genes that lack experimental data on the protein level due to factors such as temporal expression, expression in tissues that are difficult to sample, or they actually do not encode functional proteins. In the present investigation, an integrated omics approach was used for identification and exploration of missing proteins. Transcriptomics data from three different sourcesthe Human Protein Atlas (HPA), the GTEx consortium, and the FANTOM5 consortiumwere used as a starting point to identify genes selectively expressed in specialized tissues. Complementing the analysis with profiling on more specific tissues based on immunohistochemistry allowed for further exploration of cell-type-specific expression patterns. More detailed tissue profiling was performed for >300 genes on complementing tissues. The analysis identified tissue-specific expression of nine proteins previously listed as missing proteins (POU4F1, FRMD1, ARHGEF33, GABRG1, KRTAP2-1, BHLHE22, SPRR4, AVPR1B, and DCLK3), as well as numerous proteins with evidence of existence on the protein level that previously lacked information on spatial resolution and cell-type- specific expression pattern. We here present a comprehensive strategy for identification of missing proteins by combining transcriptomics with antibody-based proteomics. The analyzed proteins provide interesting targets for organ-specific research in health and disease.
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5.
  • Uhlén, Mathias, et al. (författare)
  • The human secretome
  • 2019
  • Ingår i: Science Signaling. - : American Association for the Advancement of Science (AAAS). - 1945-0877 .- 1937-9145. ; 12:609
  • Tidskriftsartikel (refereegranskat)abstract
    • The proteins secreted by human cells (collectively referred to as the secretome) are important not only for the basic understanding of human biology but also for the identification of potential targets for future diagnostics and therapies. Here, we present a comprehensive analysis of proteins predicted to be secreted in human cells, which provides information about their final localization in the human body, including the proteins actively secreted to peripheral blood. The analysis suggests that a large number of the proteins of the secretome are not secreted out of the cell, but instead are retained intracellularly, whereas another large group of proteins were identified that are predicted to be retained locally at the tissue of expression and not secreted into the blood. Proteins detected in the human blood by mass spectrometry-based proteomics and antibody-based immuno-assays are also presented with estimates of their concentrations in the blood. The results are presented in an updated version 19 of the Human Protein Atlas in which each gene encoding a secretome protein is annotated to provide an open-access knowledge resource of the human secretome, including body-wide expression data, spatial localization data down to the single-cell and subcellular levels, and data about the presence of proteins that are detectable in the blood.
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