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A tool to facilitate clinical biomarker studies - a tissue dictionary based on the Human Protein Atlas

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,...

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Autores principales: Kampf, Caroline, Bergman, Julia, Oksvold, Per, Asplund, Anna, Navani, Sanjay, Wiking, Mikaela, Lundberg, Emma, Uhlén, Mathias, Ponten, Fredrik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3523031/
https://www.ncbi.nlm.nih.gov/pubmed/22971420
http://dx.doi.org/10.1186/1741-7015-10-103
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author Kampf, Caroline
Bergman, Julia
Oksvold, Per
Asplund, Anna
Navani, Sanjay
Wiking, Mikaela
Lundberg, Emma
Uhlén, Mathias
Ponten, Fredrik
author_facet Kampf, Caroline
Bergman, Julia
Oksvold, Per
Asplund, Anna
Navani, Sanjay
Wiking, Mikaela
Lundberg, Emma
Uhlén, Mathias
Ponten, Fredrik
author_sort Kampf, Caroline
collection PubMed
description 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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spelling pubmed-35230312012-12-16 A tool to facilitate clinical biomarker studies - a tissue dictionary based on the Human Protein Atlas Kampf, Caroline Bergman, Julia Oksvold, Per Asplund, Anna Navani, Sanjay Wiking, Mikaela Lundberg, Emma Uhlén, Mathias Ponten, Fredrik BMC Med Correspondence 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. BioMed Central 2012-09-12 /pmc/articles/PMC3523031/ /pubmed/22971420 http://dx.doi.org/10.1186/1741-7015-10-103 Text en Copyright ©2012 Kampf et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Correspondence
Kampf, Caroline
Bergman, Julia
Oksvold, Per
Asplund, Anna
Navani, Sanjay
Wiking, Mikaela
Lundberg, Emma
Uhlén, Mathias
Ponten, Fredrik
A tool to facilitate clinical biomarker studies - a tissue dictionary based on the Human Protein Atlas
title A tool to facilitate clinical biomarker studies - a tissue dictionary based on the Human Protein Atlas
title_full A tool to facilitate clinical biomarker studies - a tissue dictionary based on the Human Protein Atlas
title_fullStr A tool to facilitate clinical biomarker studies - a tissue dictionary based on the Human Protein Atlas
title_full_unstemmed A tool to facilitate clinical biomarker studies - a tissue dictionary based on the Human Protein Atlas
title_short A tool to facilitate clinical biomarker studies - a tissue dictionary based on the Human Protein Atlas
title_sort tool to facilitate clinical biomarker studies - a tissue dictionary based on the human protein atlas
topic Correspondence
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3523031/
https://www.ncbi.nlm.nih.gov/pubmed/22971420
http://dx.doi.org/10.1186/1741-7015-10-103
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