A Tissue Dictionary for Normal and Cancer Tissues: A complimentary tool for the Human Protein Atlas

By: Caroline Kampf*, Julia Bergman*, Per Oksvold#, Anna Asplund*, Sanjay Navani+, Mikaela Wiking#, Emma Lundberg#, Mathias Uhlén# and Fredrik Ponten*, Poster - The Human Protein Atlas
*Department of Immunology, Genetics, Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden. #Science for Life Laboratory, Royal Institute of Technology, Stockholm, Sweden. +Lab Surgpath, Mumbai, India

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Background

The Human Protein Atlas project was initiated in 2003 to establish a systematic high-throughput generation of affinity-purified polyclonal antibodies towards all human proteins and to use these antibodies to map protein localization within the human body. Protein expression data for over 70% of the human protein-coding genome is currently publically available in the free, online protein atlas database (www.proteinatlas.org) that contain more than 11 million digital images. The database is a histology-based map for global visualization of protein expression patterns at a tissue/cellular resolution for over 46 normal tissues, 20 different cancer types and 47 cell lines and serve as a valuable tool for research and virtual pathology.

Tissue Dictionary

The know-how and experience within the Human Protein Atlas has made the creation of a comprehensive and publically available tissue dictionary possible. The dictionary covers three main parts: normal tissues, cancer tissues and subcellular structures. An additional anatomical part is included showing the localization of the organs in the body. All images and examples include descriptive text boxes and supporting background text to facilitate interpretation of the complex patterns underlying normal tissue histology, tumor pathology and cell biology.

The dictionary will be of great use for Human Protein Atlas users to aid in the interpretation of human tissues and cells. It also constitutes a valuable resource to complement microscopy and histology teaching as the internet-based dictionary is easy accessible for lectures and self-studies 24/7.

The tissue dictionary will be released at the 2012 HUPO meeting concomitant with the release of the 10th version of the Human Protein Atlas.

Figure 1. On the overview page all 45 normal tissues, 20 cancer and 18 cell structures that are included in the dictionary are listed in alphabetical order. Navigation between the three dictionary parts is easily accessible in the navigation menu. The tissue specimens keep high quality and include totally 162 normal tissue images, 67 IF cells images and 36 IHC cell images. The 173 cancer images are moreover divided into 20 cancer types and 99 sub groups.

Tissue Dictionary

Browsing the Dictionary

Figure 2A-B. Normal tissues are represented by the 45 normal tissues used for protein profiling in the Human Protein Atlas. The images are displayed with text boxes and arrows to assist the viewer. Examples show normal colon and normal breast at three levels of magnification.

Figure 2C-D. Cancer is represented by the cancer types that are also used for protein profiling in the Human Protein Atlas. Cases have been selected to demonstrate the most common variants of these 20 cancer types. Breast cancer is eg. represented by four different cases, selected according to established pathological classifications. In the figure, one case of high grade and one case of low-grade ductal cancer is shown.

Tissues

 

Figure 3. Cells are represented by altogether 18 different subcellular structures and organelles that are exemplified by images obtained after IF and IHC depending on which subcellular structure is visualized. Two examples are shown with IF and IHC images representing antibodies targeting proteins in the nucleoli and the mitochondria respectively.

IF and IHC images representing antibodies targeting proteins in the nucleoli and the mitochondria respectively

Acknowledgements

This work was supported by grants from the Knut and Alice Wallenberg foundation. Pathologists at the Clinical Department of Pathology, Akademiska Hospital, Uppsala, Sweden is greatly acknowledged for all expertise supporting the dictionary and Human Protein Atlas. The authors wish to especially thank Dijana Djureinovic, Sofie Gustafsson, Elene Karlberg, Dijana Cerjan and John Juter for assistance with the dictionary work.

 

References

  1. Uhlen M: Antibody-based proteomics for human tissue profiling. Mol Cell Proteomics 2005, 4:384-393.
  2. Kampf C: Antibody-based tissue profiling as a tool for clinical proteomics. Clinical Proteomics 2004, 1:285-299.
  3. Barbe L: Toward a confocal subcellular atlas of the human proteome. Mol Cell Proteomics 2008, 7:499-508.
  4. Uhlen M: A human protein atlas for normal and cancer tissues based on antibody proteomics. Mol Cell Proteomics 2005, 4:1920-1932.
  5. Uhlen M: Towards aknowledge-based Human Protein Atlas. Nat Biotechnol 2010, 28:1248-1250.
  6. Ponten F: The Human Protein Atlas as a proteomic resource for biomarker discovery. Journal of internal medicine 2011, 270:428-446.

 

The HPR project is funded by the Knut & Alice Wallenberg foundation. The atlas is part of the HUPO Human Antibody Initiative (HAI).

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