| 1. |
- Barbe, Laurent, et al.
(författare)
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Toward a confocal subcellular atlas of the human proteome
- 2008
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Ingår i: Molecular and cellular proteomics. - 1535-9476 .- 1535-9484. ; 7:3, s. 499-508
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Tidskriftsartikel (refereegranskat)abstract
- Information on protein localization on the subcellular level is important to map and characterize the proteome and to better understand cellular functions of proteins. Here we report on a pilot study of 466 proteins in three human cell lines aimed to allow large scale confocal microscopy analysis using protein-specific antibodies. Approximately 3000 high resolution images were generated, and more than 80% of the analyzed proteins could be classified in one or multiple subcellular compartment(s). The localizations of the proteins showed, in many cases, good agreement with the Gene Ontology localization prediction model. This is the first large scale antibody-based study to localize proteins into subcellular compartments using antibodies and confocal microscopy. The results suggest that this approach might be a valuable tool in conjunction with predictive models for protein localization.
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| 2. |
- Berglund, Lisa, et al.
(författare)
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A genecentric Human Protein Atlas for expression profiles based on antibodies
- 2008
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Ingår i: Molecular & Cellular Proteomics. - 1535-9476 .- 1535-9484. ; 7:10, s. 2019-2027
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Forskningsöversikt (refereegranskat)abstract
- An attractive path forward in proteomics is to experimentally annotate the human protein complement of the genome in a genecentric manner. Using antibodies, it might be possible to design protein-specific probes for a representative protein from every protein-coding gene and to subsequently use the antibodies for systematical analysis of cellular distribution and subcellular localization of proteins in normal and disease tissues. A new version (4.0) of the Human Protein Atlas has been developed in a genecentric manner with the inclusion of all human genes and splice variants predicted from genome efforts together with a visualization of each protein with characteristics such as predicted membrane regions, signal peptide, and protein domains and new plots showing the uniqueness (sequence similarity) of every fraction of each protein toward all other human proteins. The new version is based on tissue profiles generated from 6120 antibodies with more than five million immunohistochemistry-based images covering 5067 human genes, corresponding to approximately 25% of the human genome. Version 4.0 includes a putative list of members in various protein classes, both functional classes, such as kinases, transcription factors, G-protein-coupled receptors, etc., and project-related classes, such as candidate genes for cancer or cardiovascular diseases. The exact antigen sequence for the internally generated antibodies has also been released together with a visualization of the application-specific validation performed for each antibody, including a protein array assay, Western blot analysis, immunohistochemistry, and, for a large fraction, immunofluorescence-based confocal microscopy. New search functionalities have been added to allow complex queries regarding protein expression profiles, protein classes, and chromosome location. The new version of the protein atlas thus is a resource for many areas of biomedical research, including protein science and biomarker discovery.
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| 3. |
- Fagerberg, Linn, et al.
(författare)
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Analysis of the human tissue-specific expression by genome-wide integration of transcriptomics and antibody-based proteomics
- 2014
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Ingår i: Molecular & Cellular Proteomics. - 1535-9476 .- 1535-9484. ; 13:2, s. 397-406
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Tidskriftsartikel (refereegranskat)abstract
- Global classification of the human proteins with regards to spatial expression patterns across organs and tissues is important for studies of human biology and disease. Here, we used a quantitative transcriptomics analysis (RNA-Seq) to classify the tissue-specific expression of genes across a representative set of all major human organs and tissues and combined this analysis with antibody- based profiling of the same tissues. To present the data, we launch a new version of the Human Protein Atlas that integrates RNA and protein expression data corresponding to 80% of the human protein-coding genes with access to the primary data for both the RNA and the protein analysis on an individual gene level. We present a classification of all human protein-coding genes with regards to tissue-specificity and spatial expression pattern. The integrative human expression map can be used as a starting point to explore the molecular constituents of the human body.
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| 4. |
- Fagerberg, Linn, et al.
(författare)
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Contribution of antibody-based protein profiling to the human chromosome-centric proteome project (C-HPP)
- 2013
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Ingår i: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 12:6, s. 2439-2448
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Tidskriftsartikel (refereegranskat)abstract
- A gene-centric Human Proteome Project has been proposed to characterize the human protein-coding genes in a chromosome-centered manner to understand human biology and disease. Here, we report on the protein evidence for all genes predicted from the genome sequence based on manual annotation from literature (UniProt), antibody-based profiling in cells, tissues and organs and analysis of the transcript profiles using next generation sequencing in human cell lines of different origins. We estimate that there is good evidence for protein existence for 69% (n = 13985) of the human protein-coding genes, while 23% have only evidence on the RNA level and 7% still lack experimental evidence. Analysis of the expression patterns shows few tissue-specific proteins and approximately half of the genes expressed in all the analyzed cells. The status for each gene with regards to protein evidence is visualized in a chromosome-centric manner as part of a new version of the Human Protein Atlas (www.proteinatlas.org).
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| 5. |
- Kampf, Caroline, et al.
(författare)
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A tool to facilitate clinical biomarker studies - a tissue dictionary based on the Human Protein Atlas
- 2012
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Ingår i: BMC Medicine. - : Springer Science and Business Media LLC. - 1741-7015. ; 10, s. 103-
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Tidskriftsartikel (refereegranskat)abstract
- The complexity of tissue and the alterations that distinguish normal from cancer remain a challenge for translating results from tumor biological studies into clinical medicine. This has generated an unmet need to exploit the findings from studies based on cell lines and model organisms to develop, validate and clinically apply novel diagnostic, prognostic and treatment predictive markers. As one step to meet this challenge, the Human Protein Atlas project has been set up to produce antibodies towards human protein targets corresponding to all human protein coding genes and to map protein expression in normal human tissues, cancer and cells. Here, we present a dictionary based on microscopy images created as an amendment to the Human Protein Atlas. The aim of the dictionary is to facilitate the interpretation and use of the image-based data available in the Human Protein Atlas, but also to serve as a tool for training and understanding tissue histology, pathology and cell biology. The dictionary contains three main parts, normal tissues, cancer tissues and cells, and is based on high-resolution images at different magnifications of full tissue sections stained with H & E. The cell atlas is centered on immunofluorescence and confocal microscopy images, using different color channels to highlight the organelle structure of a cell. Here, we explain how this dictionary can be used as a tool to aid clinicians and scientists in understanding the use of tissue histology and cancer pathology in diagnostics and biomarker studies.
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| 6. |
- Lundberg, Emma, et al.
(författare)
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The correlation between cellular size and protein expression levels--normalization for global protein profiling
- 2008
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Ingår i: Journal of proteomics. - : Elsevier BV. - 1874-3919. ; 71:4, s. 448-460
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Tidskriftsartikel (refereegranskat)abstract
- An automated image analysis system was used for protein quantification of 1862 human proteins in 47 cancer cell lines and 12 clinical cell samples using cell microarrays and immunohistochemistry. The analysis suggests that most proteins are expressed in a cell size dependent manner, and that normalization is required for comparative protein quantification in order to correct for the inherent bias of cell size and systematic ambiguities associated with immunohistochemistry. Two reference standards were evaluated, and normalized protein expression values were found to allow for protein profiling across a panel of morphologically diverse cells, revealing putative patterns of over- and underexpression. Using this approach, proteins with stable expression as well as cell-line specific expression were identified. The results demonstrate the value of large-scale, automated proteome analysis using immunohistochemistry, in revealing functional correlations and establishing methods to interpret and mine proteomic data.
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| 7. |
- Pontén, Fredrik, et al.
(författare)
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A global view of protein expression in human cells, tissues, and organs
- 2009
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Ingår i: Molecular Systems Biology. - : EMBO. - 1744-4292 .- 1744-4292. ; 5
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Tidskriftsartikel (refereegranskat)abstract
- Defining the protein profiles of tissues and organs is critical to understanding the unique characteristics of the various cell types in the human body. In this study, we report on an anatomically comprehensive analysis of 4842 protein profiles in 48 human tissues and 45 human cell lines. A detailed analysis of over 2 million manually annotated, high-resolution, immunohistochemistry- based images showed a high fraction (>65%) of expressed proteins in most cells and tissues, with very few proteins (<2%) detected in any single cell type. Similarly, confocal microscopy in three human cell lines detected expression of more than 70% of the analyzed proteins. Despite this ubiquitous expression, hierarchical clustering analysis, based on global protein expression patterns, shows that the analyzed cells can be still subdivided into groups according to the current concepts of histology and cellular differentiation. This study suggests that tissue specificity is achieved by precise regulation of protein levels in space and time, and that different tissues in the body acquire their unique characteristics by controlling not which proteins are expressed but how much of each is produced. Molecular Systems Biology 5: 337; published online 22 December 2009; doi:10.1038/msb.2009.93
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| 8. |
- Stadler, Charlotte, et al.
(författare)
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RNA- and Antibody-Based Profiling of the Human Proteome with Focus on Chromosome 19
- 2014
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Ingår i: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 13:4, s. 2019-2027
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Tidskriftsartikel (refereegranskat)abstract
- An important part of the Human Proteome Project is to characterize the protein complement of the genome with antibody-based profiling. Within the framework of this effort, a new version 12 of the Human Protein Atlas (www.proteinatlas.org) has been launched, including transcriptomics data for 27 tissues and 44 cell lines to complement the protein expression data from antibody-based profiling. Besides the extensive addition of transcriptomics data, the Human Protein Atlas now contains antibody-based protein profiles for 82% of the 20 329 putative protein-coding genes. The comprehensive data resulting from RNA-seq analysis and antibody-based profiling performed within the Human Protein Atlas as well as information from UniProt were used to generate evidence summary scores for each of the 20 329 genes, of which 94% now have experimental evidence at least at transcript level. The evidence scores for all individual genes are displayed with regards to both RNA- and antibody-based protein profiles, including chromosome-centric visualizations. An analysis of the human chromosome 19 shows that similar to 43% of the genes are expressed at the transcript level in all 27 tissues analyzed, suggesting a "house-keeping" function, while 12% of the genes show a more tissue-specific pattern with enriched expression in one of the analyzed tissues only.
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| 9. |
- Thul, Peter J., et al.
(författare)
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A subcellular map of the human proteome
- 2017
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Ingår i: Science. - : American Association for the Advancement of Science. - 0036-8075 .- 1095-9203. ; 356:6340
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Tidskriftsartikel (refereegranskat)abstract
- Resolving the spatial distribution of the human proteome at a subcellular level can greatly increase our understanding of human biology and disease. Here we present a comprehensive image-based map of subcellular protein distribution, the Cell Atlas, built by integrating transcriptomics and antibody-based immunofluorescence microscopy with validation by mass spectrometry. Mapping the in situ localization of 12,003 human proteins at a single-cell level to 30 subcellular structures enabled the definition of the proteomes of 13 major organelles. Exploration of the proteomes revealed single-cell variations in abundance or spatial distribution and localization of about half of the proteins to multiple compartments. This subcellular map can be used to refine existing protein-protein interaction networks and provides an important resource to deconvolute the highly complex architecture of the human cell.
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| 10. |
- Uhlén, Mathias, et al.
(författare)
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A pathology atlas of the human cancer transcriptome
- 2017
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Ingår i: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 357:6352, s. 660-
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Tidskriftsartikel (refereegranskat)abstract
- Cancer is one of the leading causes of death, and there is great interest in understanding the underlying molecular mechanisms involved in the pathogenesis and progression of individual tumors. We used systems-level approaches to analyze the genome-wide transcriptome of the protein-coding genes of 17 major cancer types with respect to clinical outcome. A general pattern emerged: Shorter patient survival was associated with up-regulation of genes involved in cell growth and with down-regulation of genes involved in cellular differentiation. Using genome-scale metabolic models, we show that cancer patients have widespread metabolic heterogeneity, highlighting the need for precise and personalized medicine for cancer treatment. All data are presented in an interactive open-access database (www.proteinatlas.org/pathology) to allow genome-wide exploration of the impact of individual proteins on clinical outcomes.
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