Immunocytochemistry/IF - cells


Besides the immunohistochemically stained tissues, the protein atlas displays high resolution, multicolor images of immunofluorescently labeled proteins at the single cell level. This provides spatial information on protein expression patterns on a fine cellular and subcellular level.

Originally three cell lines, U-2 OS, A-431 and U-251 MG, originating from different human tissues were chosen to be included in the immunofluorescent analysis. In year 2012, the cell line panel was expanded to include additional cell lines: A-549, BJ, CACO-2, HaCaT, HEK 293, HeLa, Hep-G2, MCF-7, PC-3, RH-30, RT-4, SH-SY5Y, SiHa, SK-MEL-30 and TIME. In the HPA16 release, 12 additional cell lines have been added. To enhance the probability for a large number of proteins to be expressed, the cell lines were selected from different lineages, e.g. tumor cell lines from mesenchymal, epithelial and glial tumors. The selection was furthermore based on morphological characteristics, widespread use and multitude of publications using these cell lines. Information regarding sex and age of the donor, cellular origin and source is listed here. Based on mRNA expression data, two suitable cell lines from the cell line panel are selected for the immunofluorescent analysis of each protein. In order to localize the whole human proteome on a subcellular level in one specific cell line a third cell line, U-2 OS, is always chosen.

In addition to the human cell lines, the mouse cell line NIH 3T3 is also stained. This is only done for the antibodies corresponding to genes where the mouse and human genes are orthologous.

In order to facilitate the annotation of the subcellular localization of the protein targeted by the HPA antibody, the cells are also stained with reference markers. The following probes/organelles are used as references; (i) DAPI for the nucleus, (ii) anti-tubulin antibody as internal control and marker of microtubules, and (iii) anti-calreticulin or anti-KDEL for the endoplasmic reticulum (ER).

The resulting confocal images are single slice images representing one optical section of the cells. The microscope settings are optimized for each sample. The different organelle probes are displayed as different channels in the multicolor images; the HPA antibody staining is shown in green, nuclear stain in blue, microtubules in red and ER in yellow.

Annotation


In order to provide an interpretation of the staining patterns, all images of immunofluorescently stained cell lines are manually annotated. For each cell line and antibody the intensity and subcellular location of the staining is described. The staining intensity is classified as negative, weak, moderate or strong based on the laser power and detector gain settings used for image acquisition in combination with the visual appearance of the image. The subcellular location is further combined with parameters describing the staining characteristics (e.g. smooth, granular, speckled or fibrous). The table below lists the subcellular locations used, links to the cell structure dictionary and corresponding GO terms.

Subcellular location GO term
Actin filaments GO:0015629
Aggresome GO:0016235
Cell Junctions GO:0030054
Centrosome GO:0005813
Cytokinetic bridge GO:0045171
Cytoplasmic bodies GO:0036464
Cytosol GO:0005829
Endoplasmic reticulum GO:0005783
Endosomes GO:0005768
Focal adhesion sites GO:0005925
Golgi apparatus GO:0005794
Intermediate filaments GO:0045111
Lipid droplets GO:0005811
Lysosomes GO:0005764
Microtubule organizing center GO:0005815
Microtubules GO:0015630
Midbody GO:0030496
Midbody ring GO:0090543
Mitochondria GO:0005739
Mitotic spindle GO:0072686
Nuclear bodies GO:0016604
Nuclear membrane GO:0031965
Nuclear speckles GO:0016607
Nucleoli GO:0005730
Nucleoli fibrillar center GO:0001650
Nucleoplasm GO:0005654
Nucleus GO:0005634
Peroxisomes GO:0005777
Plasma membrane GO:0005886
Vesicles GO:0043231


Knowledge-based annotation


Knowledge-based annotation of subcellular location aims to provide an interpretation of the subcellular localization of a specific protein in at least three human cell lines. The conflation of immunofluorescence data from two or more antibody sources directed towards the same protein and a review of available protein/gene characterization data, allows for a knowledge-based interpretation of the subcellular location.

Reliability score


A reliability score is set for all genes and indicates the level of reliability of the analyzed protein expression pattern based on available protein/RNA/gene characterization data.

The reliability of the annotated protein expression data is also scored depending on similarity in immunostaining patterns and consistency with available experimental gene/protein characterization data in the UniProtKB/Swiss-Prot database.

The overall score encompass several factors: Reproducibility of the antibody staining in different cell lines (and if signal strength correlates with RNA expression levels); reproducibility of the staining using antibodies binding to different epitopes on the same target protein; validation data for the specificity of the antibody (including knockdown/knock out methods, matching signal with fluorescent-tagged protein); experimental evidence for location described in literature. Considerations are also made on whether the antibody performs in non IF-related methods like Western blot or immunohistochemistry.

The final score leads to the assignment into one of the following four classes:

  • Validated - If there is more than one source supporting the localization; for example, two independent antibodies show the same localization and this is also observed in experiments outside the Human Protein Atlas project.
  • Supported - If there is one source supporting the localization.
  • Approved - If the localization of the protein has not been previously described and was detected by only one antibody without additional antibody validation.
  • Uncertain - If the antibody-staining pattern contradicts experimental data or no expression is detected on the RNA level.


Immunohistochemistry - tissues


The Human Protein Atlas contains images of histological sections from normal and cancer tissues obtained by immunohistochemistry. Antibodies are labeled with DAB (3,3'-diaminobenzidine) and the resulting brown staining indicates where an antibody has bound to its corresponding antigen. The section is furthermore counterstained with hematoxylin to enable visualization of microscopical features.

Tissue microarrays are used to show antibody staining in samples from 144 individuals corresponding to 44 different normal tissue types, and samples from 216 cancer patients corresponding to 20 different types of cancer (movie about tissue microarray production and immunohistochemical staining). Each sample is represented by 1 mm tissue cores, resulting in a total number of 576 images for each antibody. Normal tissues are represented by samples from three individuals each, one core per individual, except for endometrium, skin, soft tissue and stomach, which are represented by samples from six individuals each and parathyroid gland, which is represented by one sample. Protein expression is annotated in 76 different normal cell types present in these tissue samples. For cancer tissues, two cores are sampled from each individual and protein expression is annotated in tumor cells. A small fraction of the 576 images are missing for most antibodies due to technical issues. Specimens containing normal and cancer tissue have been collected and sampled from anonymized paraffin embedded material of surgical specimens, in accordance with approval from the local ethics committee.

For selected proteins extended tissue profiling is performed in addition to standard tissue microarrays. Examined tissues include mouse brain, human lactating breast, eye, hair and extended samples of adrenal gland, skin and brain.

Since specimens are derived from surgical material, normal is here defined as non-neoplastic and morphologically normal. It is not always possible to obtain fully normal tissues and thus several of the tissues denoted as normal will include alterations due to inflammation, degeneration and tissue remodeling. In rare tissues, hyperplasia or benign proliferations are included as exceptions. It should also be noted that within normal morphology there may exist interindividual differences and variations due to primary diseases, age, sex etc. Such differences may also affect protein expression and thereby immunohistochemical staining patterns.

Samples from cancer are also derived from surgical material. Due to subgroups and heterogeneity of tumors within each cancer type, included cases represent a typical mix of specimens from surgical pathology. The inclusion of tumors is based on availability and representativity, however, an effort has been made to include high and low grade malignancies where such is applicable. In certain tumor groups, subtypes have been included, e.g. breast cancer includes both ductal and lobular cancer, lung cancer includes both squamous cell carcinoma and adenocarcinoma and liver cancer includes both hepatocellular and cholangiocellular carcinoma etc. Tumor heterogeneity and interindividual differences may be reflected in diverse expression of proteins resulting in variable immunohistochemical staining patterns.

Annotation


In order to provide an overview of protein expression patterns, all images of immunohistochemically stained tissues are manually annotated by a specialist followed by verification by a second specialist. Annotation of each different normal and cancer tissue is performed using fixed guidelines for classification of immunohistochemical results. Each tissue is examined for representability, and subsequently immunoreactivity in the different cell types present in normal or cancer tissues was annotated. Basic annotation parameters include an evaluation of i) staining intensity (negative, weak, moderate or strong), ii) fraction of stained cells (rare, <25%, 25-75% or >75%) and iii) subcellular localization (nuclear and/or cytoplasmic/membranous). The manual annotation also provides two summarizing texts describing the staining pattern for each antibody in normal tissues and in cancer tissues.

The terminology and ontology used is compliant with standards used in pathology and medical science. SNOMED classification is used for assignment of topography and morphology. SNOMED classification also underlies the given original diagnosis from which normal as well as cancer samples were collected.

A histological dictionary used in the annotation is available as a PDF-document, containing images which are immunohistochemically stained with antibodies included in the Human Protein Atlas. The dictionary displays subtypes of cells distinguishable from each other and also shows specific expression patterns in different intracellular structures. Annotation dictionary: screen usage (15 MB), printing (95 MB).

Knowledge-based annotation


Knowledge-based annotation aims to create a comprehensive overview of protein expression patterns in normal human tissues. This is achieved by stringent evaluation of immunohistochemical staining pattern, RNA-seq data from internal and external sources and available protein/gene characterization data, with special emphasis on RNA-seq. Annotated protein expression profiles are performed using single antibodies as well as independent antibodies (two or more independent antibodies directed against different, non-overlapping epitopes on the same protein). For independent antibodies, the immunohistochemical data from all the different antibodies are taken into consideration. The immunohistochemical staining pattern in normal tissues is subjectively annotated according to strict guidelines. It is based on the experienced evaluation of positive immunohistochemical signals in the 76 normal cell types analyzed. The review also takes suboptimal experimental procedures and interindividual variations into consideration.

The final annotated protein expression is considered a best estimate and as such reflects the most probable histological distribution and relative expression level for each protein. To enable a protein expression profile, one or several of the following additional data sources is necessary; i) an independent antibody targeting another epitope of the same protein ii) RNA-seq data, and iii) available protein/gene characterization data. The result of the knowledge-based annotation is considered inconclusive when the information available at the time of analysis is evaluated as not sufficient for verification of the staining pattern and an estimation of the expected protein expression.

The knowledge-based protein expression profiles are performed using fixed guidelines on evaluation and presentation of the resulting expression profiles. Standardized explanatory sentences are used when necessary to provide additional information required for full understanding of the expression profile. A reliability score, set as Supported (visualized with a yellow star symbol), Approved, or Uncertain is set for each annotated protein expression profile based on evaluation of all available data.

Reliability score


A reliability score is manually set for all genes and indicates the level of reliability of the analyzed protein expression pattern based on available RNA-seq data and/or protein/gene characterization data.

The reliability score is divided into Supported, Approved, or Uncertain. Supported is indicated by a star on the image that links to the tissue atlas data for a particular gene. If there is available data from more than one antibody, the staining patterns of all antibodies are taken in consideration during evaluation of reliability score.

  • Supported - Consistency with RNA-seq and/or protein/gene characterization data, in combination with similar staining pattern if independent antibodies are available.
  • Approved - Consistency with RNA-seq data in combination with inconsistency with, or lack of, protein/gene characterization data. Alternatively, consistency with protein/gene characterization data in combination with inconsistency with RNA-seq data. If independent antibodies are available, the staining pattern is partly similar or dissimilar.
  • Uncertain - Inconsistency with, or lack of, RNA-seq and/or protein/gene characterization data, in combination with dissimilar staining pattern if independent antibodies are available.


Immunohistochemistry/IF - mouse brain


As a complement to the immunohistochemically stained tissues, the protein atlas also includes the mouse brain atlas as a sub compartment of the normal tissue atlas. In which comprehensive profiles are available in mouse brain. A selected set of targets have been analyzed by using the antibodies in serial sections of mouse brain which covers 129 areas and subfields of the brain, several of these regions difficult to cover in the human brain. In addition pituitary, retina and trigeminal ganglions are included in recent and future image series but not annotated yet.

The tissue micro array method used within the human protein atlas enabled the global mapping of proteins in the human body, including the brain. Currently, the human tissue atlas covers four areas of the human brain: cerebral cortex, hippocampus, caudate and cerebellum. Due to the heterogeneous structure of the brain, with many nuclei and cell-types organized in complex networks, it is difficult to achieve a comprehensive overview in a 1 mm tissue sample. Analysis of more human brain samples, including smaller brain nuclei, is thus desirable in order to generate a more detailed map of protein distribution in the brain. Therefore, we here complemented the human brain atlas effort with a more comprehensive analysis of the mouse brain. A series of mouse brain sections is explored for protein expression and distribution in a large number of brain regions.

Antibodies are selected against protein involved in normal brain physiology, brain development and neuropathological processes. A limit of 60% homology (human vs mouse) is used as cut off when comparing the PrEST sequence for the antibody targets.

Selected antibodies are applied to test-sections containing brain regions or cell types with known expression based on in situ hybridization (Allen Brain Atlas) and single cell RNAseq data (Linnarsson Lab and Barres Lab). Staining patterns are evaluated based on consistency between staining patterns of multiple antibodies against the same target and match to transcriptomics data. Antibody immunoreactivity is visualized using tyramid signal amplification shown in green. A nuclear reference staining (DAPI) is visualized in blue. The immunofluorescence protocol is standardized though antibody concentration and incubation time are variable depending on protein abundance and antibody affinity determined during the test staining. The complete mouse brain profile is represented by serial coronal sections of adult mouse brain, 16 µm thick. Stained slides are then scanned and digitalized before further processing.

Table 1. Brain regions. Abbreviations are based on The Mouse Brain in Stereotaxic Coordinates, Third Edition: The coronal plates and diagrams (ISBN: 9780123742445)

Region Abbreviation Allen Brain Atlas
forebrain olfactory bulb anterior olfactory nucleus aon AON
forebrain olfactory bulb granule cell layer gro MOBgr
forebrain olfactory bulb internal plexiform layer ipl MOBipl
forebrain olfactory bulb mitral cell layer mi MOBmi
forebrain olfactory bulb glomerular layer gl MOBgl
forebrain olfactory bulb rostral migratory stream rms SEZ
forebrain olfactory bulb external plexiform layer epl MOBopl
forebrain olfactory bulb external plexiform layer of the accessory OB epla
forebrain olfactory bulb granule cell layer of the accessory OB gra AOBgr
forebrain olfactory bulb glomerular layer of the accessory OB gla AOBgl
forebrain basal forebrain dorsal tenia tecta dtt TTd
forebrain basal forebrain caudate putamen cpu CP
forebrain basal forebrain accumbens nucleus, core acbc ACB
forebrain basal forebrain accumbens nucleus, shell acbsh ACB
forebrain basal forebrain island of Calleja icj isl
forebrain basal forebrain ventral pallidum vp PALv
forebrain basal forebrain medial septum ms MS
forebrain basal forebrain nucleus of the vertical limb of the diagonal band vdb NDB
forebrain basal forebrain lateral septum ls LS
forebrain basal forebrain nucleus of the horizontal limb of the diagonal band hdb NDB
forebrain basal forebrain globus pallidus gp PALd
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Annotation


The digitalized images are processed (axel-adjusted and tissue edges defined) and regions of interest (ROIs) are then marked according to the table above. Theses ROIs are then used for image analysis and the relative fluorescence intensity is listed for each region. The relative fluorescence is defined intensity of the annotated region relative to the intensity of the region with highest intensity.

The overview and preserved orientation in the mouse brain has enabled us to annotate additional cell classes (ependymal), glial subpopulations (microglia, oligodendrocytes, and astrocytes), and additional brain specific subcellular locations (axon, dendrite, synapse, and glia endfeet) for each investigated protein.

All images of immunofluorescence stained sections were manually annotated by specially educated personnel followed by review and verification by a second qualified member of the staff. The cellular and sub cellular location of the immunoreactivity is defined and a summarizing text is provided describing the general staining pattern.

Specificity is validated by comparing the data with in situ hybridization data (Allen brain atlas) and/or available literature; support from other data leads to a supportive reliability score, while more unknown targets are viewed as uncertain and awaits further validation.

Reliability score


A reliability score is set for all genes and indicates the level of reliability of the analyzed protein expression pattern based on available protein/RNA/gene characterization data.

The reliability score of the antibodies in mouse brain atlas is scored as Supported or Uncertain depending on support from in situ hybridization data (Allen brain atlas) and/or previous published data, UniProtKB/Swiss-Prot database.



Immunohistochemistry - cells


For antibody validation purposes a selection of 44 different widely used and well characterized human cell lines are used for immunohistochemical staining on cell microarrays. Included cell lines are derived from DSMZ, ATCC or academic research groups (kindly provided by cell line founders). Information regarding sex and age of the donor, tissue origin and source is listed here. All cells are fixed in 4% paraformaldehyde and dispersed in agarose prior to paraffin embedding and immunohistochemical staining.

The cell microarray (CMA) enables representation of leukemia and lymphoma cell lines, covering major hematopoietic neoplasms and even different stages of differentiation. Cell lines from solid tumors are also included in the CMA. A subset originate from solid tumors not represented in the TMAs, e.g. sarcoma, choriocarcinoma, small cell lung carcinoma, and the remaining cell lines are derived from tumor types also represented in the tissue microarray.

Antibodies are labeled with DAB (3,3'-diaminobenzidine) and the resulting brown staining indicates where an antibody has bound to its corresponding antigen. The section is furthermore counterstained with hematoxylin to enable visualization of microscopical features.

Annotation


All images of immunohistochemically stained cell lines are annotated using an automated recognition software for image analysis. The image analysis software, TMAx (Beecher Instruments, Sun Prairie, WI, USA), built on an object-oriented image analysis engine from Definiens, utilizes rule-based operations and multiple iterative segmentation processes together with fuzzy logic to identify cells and immunohistochemical stain deposits.

Output parameters from the software always displayed in conjunction with the annotated images are:

  • number of objects defined as cells in the image
  • staining intensity (negative, weak, moderate and strong)
  • fraction (%) of positive cells
In addition, two overlay images with additional numerical information are presented to facilitate interpretation. The information displayed includes:
  • Cell: object based view representing fraction (%) of immunostained cells. The color code for each cell represents a range of immunoreactivity, blue (negative/very weak), yellow (weak/moderate), orange (moderate/strong) and red (strong) cells. This classification is based on areas of different intensities within each object (cell). This differs slightly from the subjective classification provided by manual annotation of cells in normal and cancer tissue.
  • Area: area-based view representing immunostained areas (%) within cells. The color code represents a range of immunoreactivity, yellow (weak/moderate), green (moderate/strong) and red (strong). Negative/very weak areas are transparent. The intensity score is generated from the total of this area based analysis.

The annotation data is used for formal antibody validation based on Pearson correlation between independent antibodies and an orthogonal method (RNA-seq). More information can be found here.

Protein array


All purified antibodies are analyzed on antigen microarrays. The specificity profile for each antibody is determined based on the interaction with 384 different antigens including its own target. The antigens present on the arrays are consecutively exchanged in order to correspond to the next set of 384 purified antibodies. Each microarray is divided into 21 replicated subarrays, enabling the analysis of 21 antibodies simultaneously. The antibodies are detected through a fluorescently labeled secondary antibody and a dual color system is used in order to verify the presence of the spotted proteins. A specificity profile plot is generated for each antibody, where the signal from the binding to its own antigen is compared to the eventual off target interactions to all the other antigens. The vast majority (86%) of antibodies are given a pass and the remaining are failed either due to low signal or low specificity.



Western blot


Western blot analysis of antibody specificity has been done using a routine sample setup composed of IgG/HSA-depleted human plasma and protein lysates from a limited number of human tissues and cell lines. Antibodies with an uncertain routine WB have been revalidated using an over-expression lysate (VERIFY Tagged Antigen(TM), OriGene Technologies, Rockville, MD) as a positive control. Antibody binding was visualized by chemiluminescence detection in a CCD-camera system using a peroxidase (HRP) labeled secondary antibody.

Antibodies included in the Human Protein Atlas have been analyzed without further efforts to optimize the procedure and therefore it cannot be excluded that certain observed binding properties are due to technical rather than biological reasons and that further optimization could result in a different outcome.

HPA RNA-seq data


In total, 56 cell lines and 37 tissues have been analyzed by RNA-seq to estimate the transcript abundance of each protein-coding gene.

For cell lines, early-split samples were used as duplicates and total RNA was extracted using the RNeasy mini kit. Information regarding cellular origin and source of each cell line is listed here.

For normal tissue, specimens were collected with consent from patients and all samples were anonymized in accordance with approval from the local ethics committee (ref #2011/473) and Swedish rules and legislation. All tissues were collected from the Uppsala Biobank and RNA samples were extracted from frozen tissue sections.

For a total number of 115 cell line samples and 172 tissue samples, mRNA sequencing was performed on Illumina HiSeq2000 and 2500 machines (Illumina, San Diego, CA, USA) using the standard Illumina RNA-seq protocol with a read length of 2x100 bases. Transcript abundance estimation was performed using Kallisto v0.42.4. For each gene, we report the abundance in 'Transcript Per Million' (TPM) as the sum of the TPM values of all its protein-coding transcripts. For each cell line and tissue type, the average TPM value for replicate samples were used as abundance score. The threshold level to detect presence of a transcript for a particular gene was set to ≥ 1 TPM.

The RNA-seq data was used to classify all genes according to their tissue-specific expression into one of six different categories, defined based on the total set of all TPM values in 37 tissues:

  • tissue enriched (expression in one tissue at least five-fold higher than all other tissues)
  • group enriched (five-fold higher average TPM in a group of two to seven tissues compared to all other tissues)
  • tissue enhanced (five-fold higher average TPM in one or more tissues compared to the mean TPM of all tissues)
  • expressed in all (≥ 1 TPM in all tissues)
  • not detected (< 1 TPM in all tissues)
  • mixed (detected in at least one tissue and in none of the above categories)

An additional category "elevated", containing all genes in the first three categories (tissue enriched, group enriched and tissue enhanced), has been used for some parts of the analysis.



GTEx RNA-seq data


The Genotype-Tissue Expression (GTEx) project collects and analyzes multiple human post mortem tissues. RNA-seq data from 31 of their tissues having a corresponding tissue in Human Protein Atlas have been included to allow for comparisons between the Human Protein Atlas data and GTEx data.

The GTEx RNA-seq data has been mapped using the ensembl gene id available from GTEx, and the RPKMs (number Reads Per Kilobase gene model and Million mapped reads) for each gene were subsequently used to categorize the genes using the same classification as described above but using 0.5 RPKM as threshold for detection.

Tissue GTEx tissue Number of samples
Adipose tissue Adipose - Subcutaneous 350
Adipose - Visceral (Omentum) 227
Adrenal gland Adrenal Gland 145
Breast Breast - Mammary Tissue 214
Caudate Brain - Caudate (basal ganglia) 117
Cerebellum Brain - Cerebellar Hemisphere 105
Brain - Cerebellum 125
Cerebral cortex Brain - Cortex 114
Brain - Frontal Cortex (BA9) 108
Cervix, uterine Cervix - Ectocervix 6
Cervix - Endocervix 5
Colon Colon - Sigmoid 149
Colon - Transverse 196
Endometrium Uterus - Endometrium 14
Esophagus Esophagus - Mucosa 286
Fallopian tube Fallopian Tube 6
Heart muscle Heart - Atrial Appendage 194
Heart - Left Ventricle 218
Hippocampus Brain - Hippocampus 94
Hypothalamus Brain - Hypothalamus 96
Kidney Kidney - Cortex 32
Liver Liver 119
Lung Lung 320
Ovary Ovary 97
Pancreas Pancreas 171
Pituitary gland Pituitary 103
Prostate Prostate 106
Salivary gland Minor Salivary Gland 57
Skeletal muscle Muscle - Skeletal 430
Skin Skin - Not Sun Exposed (Suprapubic) 250
Skin - Sun Exposed (Lower leg) 357
Small intestine Small Intestine - Terminal Ileum 88
Spleen Spleen 104
Stomach Stomach 193
Testis Testis 172
Thyroid gland Thyroid 323
Urinary bladder Bladder 11
Vagina Vagina 96


FANTOM5 CAGE data


The Functional Annotation of Mammalian Genomes 5 (FANTOM5) project provides comprehensive expression profiles and functional annotation of mammalian cell-type specific transcriptomes using Cap Analysis of Gene Expression (CAGE) (Takahashi et al 2012), which is based on a series of full-length cDNA technologies developed in RIKEN. CAGE data for 35 of their tissues was obtained from the FANTOM5 repository and mapped to ENSEMBL. The normalized Tags Per Million for each gene were calculated and subsequently used to categorize the genes using the same classification as described above and using Tags Per Million ≥ 1 as threshold for detection to allow for comparisons with the Human Protein Atlas data.

Tissue FANTOM5 tissue Sample description FANTOM5 sample id
Adipose tissue Adipose tissue 65,65,76 years, mixed FF:10010-101C1
Appendix Appendix 29 years, male FF:10189-103D9
Brain Brain 77,79,81 years, mixed FF:10012-101C3
Breast Breast 77 years, female FF:10080-102A8
Caudate Caudate nucleus 76 years, female FF:10164-103B2
Cerebellum Cerebellum 22-68 years, mixed FF:10083-102B2
Cerebellum 76 years, female FF:10166-103B4
Cervix, uterine Cervix 40,46,57,65 years, female FF:10013-101C4
Colon Colon 62,83,84 years, mixed FF:10014-101C5
Endometrium Uterus 23-63 years, female FF:10100-102D1
Epididymis Epididymis 24 years, male FF:10197-103E8
Esophagus Esophagus 68,74,75 years, mixed FF:10015-101C6
Gallbladder Gall bladder 57 years, male FF:10198-103E9
Heart muscle Heart 70,73,74 years, mixed FF:10016-101C7
Left ventricle 73 years, female FF:10078-102A6
Hippocampus Hippocampus 76 years, female FF:10153-102I9
Hippocampus 60 years, female FF:10169-103B7
Kidney Kidney 60,62,63 years, female FF:10017-101C8
Liver Liver 64,69,70 years, mixed FF:10018-101C9
Lung Lung 46,65,94 years, mixed FF:10019-101D1
Lung - right lower lobe 29 years, male FF:10075-102A3
Lymph node Lymph node 30 years, male FF:10077-102A5
Ovary Ovary 47,75,84 years, female FF:10020-101D2
Pancreas Pancreas 52 years, male FF:10049-101G4
Pituitary gland Pituitary gland 76 years, female FF:10162-103A9
Placenta Placenta female FF:10021-101D3
Prostate Prostate 73,79,93 years, male FF:10022-101D4
Retina Retina 24-65 years, mixed FF:10030-101E3
Salivary gland Salivary gland 16-60 years, mixed FF:10093-102C3
Seminal vesicle Seminal vesicle 24 years, male FF:10201-103F3
Skeletal muscle Skeletal muscle 55,79,79 years, mixed FF:10023-101D5
Skeletal muscle - soleus muscle male FF:10282-104F3
Small intestine Small intestine 15,40,85 years, mixed FF:10024-101D6
Smooth muscle Smooth muscle 20-68 years, male FF:10048-101G3
Spleen Spleen 39,50,70 years, male FF:10025-101D7
Testis Testis 34,53,86 years, male FF:10026-101D8
Testis 14-64 years, male FF:10096-102C6
Thyroid gland Thyroid 67,68,78 years, mixed FF:10028-101E1
Tonsil Tonsil 22-61 years, mixed FF:10047-101G2
Urinary bladder Bladder 55,58,79 years, mixed FF:10011-101C2
Vagina Vagina 68 years, female FF:10204-103F6


TCGA RNA-seq data


The Cancer Genome Atlas (TCGA) project of Genomic Data Commons (GDC) collects and analyzes multiple human cancer samples. RNA-seq data from 17 cancer types representing 21 cancer subtypes with a corresponding major cancer type in the Human Pathology Atlas were included to allow for comparisons between the protein staining data from the Human Protein Atlas and RNA-seq from TCGA data.

The TCGA RNA-seq data was mapped using the Ensembl gene id available from TCGA, and the FPKMs (number Fragments Per Kilobase of exon per Million reads) for each gene were subsequently used for quantification of expression with a detection threshold of 1 FPKM. Genes were categorized using the same classification as described above.

HPA cancer type TCGA cancer No. of samples in TCGA
Breast cancer Breast Invasive Carcinoma (BRCA) 1075
Cervical cancer Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (CESC) 291
Colorectal cancer Colon Adenocarcinoma (COAD) 438
Rectum Adenocarcinoma (READ) 159
Endometrial cancer Uterine Corpus Endometrial Carcinoma (UCEC) 541
Glioma Glioblastoma Multiforme (GBM) 153
Head and neck cancer Head and Neck Squamous Cell Carcinoma (HNSC) 499
Liver cancer Liver Hepatocellular Carcinoma (LIHC) 365
Lung cancer Lung Adenocarcinoma (LUAD) 500
Lung Squamous Cell Carcinoma (LUSC) 494
Melanoma Skin Cuteneous Melanoma (SKCM) 102
Ovarian cancer Ovary Serous Cystadenocarcinoma (OV) 373
Pancreatic cancer Pancreatic Adenocarcinoma (PAAD) 176
Prostate cancer Prostate Adenocarcinoma (PRAD) 494
Renal cancer Kidney Chromophobe (KICH) 64
Kidney Renal Clear Cell Carcinoma (KIRC) 528
Kidney Renal Papillary Cell Carcinoma (KIRP) 285
Stomach cancer Stomach Adenocarcinoma (STAD) 354
Testis cancer Testicular Germ Cell Tumor (TGCT) 134
Thyroid cancer Thyroid Carcinoma (THCA) 501
Urothelial cancer Bladder Urothelial Carcinoma (BLCA) 406

Survival


Based on the FPKM value of each gene, patients were classified into two expression groups and the correlation between expression level and patient survival was examined. Genes with a median expression less than FPKM 1 were excluded. The prognosis of each group of patients was examined by Kaplan-Meier survival estimators, and the survival outcomes of the two groups were compared by log-rank tests. Both median and maximally separated Kaplan-Meier plots are presented in the Human Protein Atlas, and genes with log rank P values less than 0.001 in maximally separated Kaplan-Meier analysis were defined as prognostic genes. If the group of patients with high expression of a selected prognostic gene has a higher observed event than expected event, it is an unfavourable prognostic gene; otherwise, it is a favourable prognostic gene.



Evidence


Protein evidence is calculated for each gene based on three different sources: UniProt protein existence (UniProt evidence); a Human Protein Atlas antibody- or RNA based score (HPA evidence); and evidence based on two proteogenomics studies (MS evidence). In addition, for each gene, a protein evidence summary score is based on the maximum level of evidence in all three independent evidence scores (Evidence summary).

All scores are classified into the following categories:

  • Evidence at protein level
  • Evidence at transcript level
  • No evidence
  • Not available

UniProt evidence is based on UniProt protein existence data, which uses five types of evidence for the existence of a protein. All genes in the classes "Experimental evidence at protein level" or "Experimental evidence at transcript level" are classified into the first two evidence categories, whereas genes from the "Inferred from homology", "Predicted", or "Uncertain" classes are classified as "No evidence". Genes where the gene identifier could not be mapped to UniProt from Ensembl version 83.38 are classified as "Not available".

The HPA evidence is calculated based on the manual curation of Western blot, tissue profiling and subcellular location as well as transcript profiling using RNA-seq. All genes with Data reliability "Supported" in one or both of the two methods immunohistochemistry and immunofluorescence, or standard validation "Supported" for the Western blot application (assays using over-expression lysates not included) are classified as "Evidence at protein level". For the remaining genes, all genes detected at TPM > 1 in at least one of the tissues or cell lines used in the RNA-seq analysis are classified as "Evidence at transcript level". The remaining genes are classified as "No evidence".

MS evidence is based on two proteogenomics studies Kim et al 2014 and Ezkurdia et al 2014. Each gene detected by at least one of the MS-based studies is classified as "Evidence at protein level" and all remaining genes as "Not available".