Human Protein Atlas
|Description||The Human Protein Atlas portal is a publicly available database with millions of high-resolution images showing the spatial distribution of proteins in normal human tissues and different cancer types, as well the sub cellular localisation in single cells.|
|Research center||KTH, UU, SciLifeLab, Sweden|
|Primary citation||Uhlén M, et al. (January 2015). "Proteomics. Tissue-based map of the human proteome". Science. 347 (6220): 1260419. doi:10.1126/science.1260419. PMID 25613900.|
|Web||Advanced search, bulk retrieval/download|
|Curation policy||Yes – manual|
|Yes – both individual protein entries and searches|
The Human Protein Atlas (HPA) is a Swedish-based program started in 2003 with the aim to map of all the human proteins in cells, tissues and organs using integration of various omics technologies, including antibody-based imaging, mass spectrometry-based proteomics, transcriptomics and systems biology. All the data in the knowledge resource is open access to allow scientists both in academia and industry to freely access the data for exploration of the human proteome. The version 18 (launched December 1, 2017) consists of three separate parts, each focusing on a particular aspect of the genome-wide analysis of the human proteins; the Tissue Atlas showing the distribution of the proteins across all major tissues and organs in the human body, the Cell Atlas showing the subcellular localization of proteins in single cells, and finally the new Pathology Atlas showing the impact of protein levels for survival of patients with cancer. The Human Protein Atlas program has already contributed to several thousands of publications in the field of human biology and disease and it was recently (July 25, 2017) selected by the organization ELIXIR as a European core resource due to its fundamental importance for a wider life science community. The HPA consortium is funded by the Knut and Alice Wallenberg Foundation.
The Human Protein Atlas consists of three sub-atlases:
The Tissue Atlas: contains information regarding the expression profiles of human genes both on the mRNA and protein level. The protein expression data is derived from antibody-based protein profiling using immunohistochemistry. Altogether 76 different cell types, corresponding to 44 normal human tissue types, have been analyzed and the data is presented as pathology-based annotation of protein expression levels. All underlying images of immunohistochemistry stained normal tissues are available as high-resolution images in the normal tissue atlas.
The Cell Atlas: provides high-resolution insights into the spatial distribution of proteins within cells. The protein expression data is derived from antibody-based profiling using immunofluorescence confocal microscopy. A panel of 56 cell lines, selected to represent various cell populations in different organs of the human body, forms the basis of the Cell Atlas. In this cell line panel the mRNA expression of all human genes have been characterized using deep RNA-sequencing. The subcellular distribution of proteins is investigated in a subset of the cell lines, and classified into 32 different organelles and fine cellular structures.
The Pathology Atlas: is based on the analysis of 17 main cancer types using data from 8,000 patients. In addition, a new concept for showing patient survival data is introduced, called Interactive Survival Scatter plots, and the atlas includes more than 400,000 such plots. A national supercomputer center was used to analyze more than 2.5 petabytes of underlying publicly available data from the Cancer Genome Atlas (TCGA) to generate more than 900,000 survival plots describing the consequence of RNA and protein levels on clinical survival. The Pathology Atlas also contains 5 million pathology-based images generated by the Human Protein Atlas consortium.
The Human Protein Atlas program was started in 2003 and funded by the non-profit organization Knut and Alice Wallenberg Foundation (KAW). The main site of the project is the Royal Institute of Technology (KTH), School of Biotechnology (Stockholm, Sweden). Professor Mathias Uhlén is the director of the program.
The research underpinning the start of the exploration of the whole human proteome in the Human Protein Atlas program was carried out in the late 1990s and early 2000s. A pilot study employing an affinity proteomics strategy using affinity-purified antibodies raised against recombinant human protein fragments was carried out for a chromosome-wide protein profiling of chromosome 21. Other projects were also carried out to establish processes for parallel and automated affinity purification of mono-specific antibodies and their validation.
Antibodies and antigens, produced in the Human Protein Atlas workflow, are used in research projects to study potential biomarkers in various diseases, such as breast cancer, prostate cancer, colon cancer, diabetes, autoimmune diseases, ovarian cancer and renal failure.
- Uhlén M, Fagerberg L, Hallström BM, Lindskog C, Oksvold P, Mardinoglu A, et al. (January 2015). "Proteomics. Tissue-based map of the human proteome". Science. 347 (6220): 1260419. doi:10.1126/science.1260419. PMID 25613900.
- Thul PJ, Åkesson L, Wiking M, Mahdessian D, Geladaki A, Ait Blal H, et al. (May 2017). "A subcellular map of the human proteome". Science. 356 (6340). doi:10.1126/science.aal3321. PMID 28495876.
- Uhlen M, Zhang C, Lee S, Sjöstedt E, Fagerberg L, Bidkhori G, et al. (August 2017). "A pathology atlas of the human cancer transcriptome". Science. 357 (6352). doi:10.1126/science.aan2507. PMID 28818916.
- Agaton C, Galli J, Höidén Guthenberg I, Janzon L, Hansson M, Asplund A, Brundell E, Lindberg S, Ruthberg I, Wester K, Wurtz D, Höög C, Lundeberg J, Ståhl S, Pontén F, Uhlén M (Jun 2003). "Affinity proteomics for systematic protein profiling of chromosome 21 gene products in human tissues". Molecular & Cellular Proteomics. 2 (6): 405–14. doi:10.1074/mcp.M300022-MCP200. PMID 12796447.
- Falk R, Agaton C, Kiesler E, Jin S, Wieslander L, Visa N, Hober S, Ståhl S (Dec 2003). "An improved dual-expression concept, generating high-quality antibodies for proteomics research". Biotechnology and Applied Biochemistry. 38 (Pt 3): 231–9. doi:10.1042/BA20030091. PMID 12875650.
- Uhlén M, Björling E, Agaton C, Szigyarto CA, Amini B, Andersen E, et al. (Dec 2005). "A human protein atlas for normal and cancer tissues based on antibody proteomics". Molecular & Cellular Proteomics. 4 (12): 1920–32. doi:10.1074/mcp.M500279-MCP200. PMID 16127175.
- Jonsson L, Gaber A, Ulmert D, Uhlén M, Bjartell A, Jirström K (2011). "High RBM3 expression in prostate cancer independently predicts a reduced risk of biochemical recurrence and disease progression". Diagnostic Pathology. 6: 91. doi:10.1186/1746-1596-6-91. PMC 3195697. PMID 21955582.
- Larsson A, Fridberg M, Gaber A, Nodin B, Levéen P, Jönsson G, Uhlén M, Birgisson H, Jirström K (2012). "Validation of podocalyxin-like protein as a biomarker of poor prognosis in colorectal cancer". BMC Cancer. 12: 282. doi:10.1186/1471-2407-12-282. PMC 3492217. PMID 22769594.
- Lindskog C, Asplund A, Engkvist M, Uhlen M, Korsgren O, Ponten F (Jun 2010). "Antibody-based proteomics for discovery and exploration of proteins expressed in pancreatic islets". Discovery Medicine. 9 (49): 565–78. PMID 20587347.
- Neiman M, Hedberg JJ, Dönnes PR, Schuppe-Koistinen I, Hanschke S, Schindler R, Uhlén M, Schwenk JM, Nilsson P (Nov 2011). "Plasma profiling reveals human fibulin-1 as candidate marker for renal impairment". Journal of Proteome Research. 10 (11): 4925–34. doi:10.1021/pr200286c. PMID 21888404.
- Nodin B, Fridberg M, Jonsson L, Bergman J, Uhlén M, Jirström K (2012). "High MCM3 expression is an independent biomarker of poor prognosis and correlates with reduced RBM3 expression in a prospective cohort of malignant melanoma". Diagnostic Pathology. 7: 82. doi:10.1186/1746-1596-7-82. PMC 3433373. PMID 22805320.
- Schwenk JM, Igel U, Neiman M, Langen H, Becker C, Bjartell A, Ponten F, Wiklund F, Grönberg H, Nilsson P, Uhlen M (Nov 2010). "Toward next generation plasma profiling via heat-induced epitope retrieval and array-based assays". Molecular & Cellular Proteomics. 9 (11): 2497–507. doi:10.1074/mcp.M110.001560. PMC 2984230. PMID 20682762.