Quantification and discovery of sequence determinants of protein-per-mRNA amount in 29 human tissues.

Despite their importance in determining protein abundance, a comprehensive catalogue of sequence features controlling protein-to-mRNA (PTR) ratios and a quantification of their effects are still lacking. Here, we quantified PTR ratios for 11,575 proteins across 29 human tissues using matched transcriptomes and proteomes. We estimated by regression the contribution of known sequence determinants of protein synthesis and degradation in addition to 45 mRNA and 3 protein sequence motifs that we found by association testing. While PTR ratios span more than 2 orders of magnitude, our integrative model predicts PTR ratios at a median precision of 3.2-fold. A reporter assay provided functional support for two novel UTR motifs, and an immobilized mRNA affinity competition-binding assay identified motif-specific bound proteins for one motif. Moreover, our integrative model led to a new metric of codon optimality that captures the effects of codon frequency on protein synthesis and degradation. Altogether, this study shows that a large fraction of PTR ratio variation in human tissues can be predicted from sequence, and it identifies many new candidate post-transcriptional regulatory elements.

A deep proteome and transcriptome abundance atlas of 29 healthy human tissues.

Genome-, transcriptome- and proteome-wide measurements provide insights into how biological systems are regulated. However, fundamental aspects relating to which human proteins exist, where they are expressed and in which quantities are not fully understood. Therefore, we generated a quantitative proteome and transcriptome abundance atlas of 29 paired healthy human tissues from the Human Protein Atlas project representing human genes by 18,072 transcripts and 13,640 proteins including 37 without prior protein-level evidence. The analysis revealed that hundreds of proteins, particularly in testis, could not be detected even for highly expressed mRNAs, that few proteins show tissue-specific expression, that strong differences between mRNA and protein quantities within and across tissues exist and that protein expression is often more stable across tissues than that of transcripts. Only 238 of 9,848 amino acid variants found by exome sequencing could be confidently detected at the protein level showing that proteogenomics remains challenging, needs better computational methods and requires rigorous validation. Many uses of this resource can be envisaged including the study of gene/protein expression regulation and biomarker specificity evaluation.

Cross-talk between the Tissue Factor/coagulation factor VIIa complex and the tyrosine kinase receptor EphA2 in cancer.

BACKGROUND: Tissue Factor (TF) forms a proteolytically active complex together with coagulation factor VIIa (FVIIa) and functions as the trigger of blood coagulation or alternatively activates cell signaling. We recently described that EphA2 of the Eph tyrosine kinase receptor family is cleaved directly by the TF/FVIIa complex. The aim of the present study was to further characterize the cross-talk between TF/FVIIa and EphA2 using in vitro model systems and human cancer specimens. METHODS: Cleavage and phosphorylation of EphA2 was studied by Western blot. Subcellular localization of TF and EphA2 was investigated by a proximity ligation assay and confocal microscopy. Phalloidin staining of the actin cytoskeleton was used to study cell rounding and retraction fiber formation. Expression of TF and EphA2 in human colorectal cancer specimens was examined by immunohistochemistry. RESULTS: TF and EphA2 co-localized constitutively in MDA-MB-231 cells, and addition of FVIIa resulted in cleavage of EphA2 by a PAR2-independent mechanism. Overexpression of TF in U251 glioblastoma cells lead to co-localization with EphA2 at the leading edge and FVIIa-dependent cleavage of EphA2. FVIIa potentiated ephrin-A1-induced cell rounding and retraction fiber formation in MDA-MB-231 cells through a RhoA/ROCK-dependent pathway that did not require PAR2-activation. TF and EphA2 were expressed in colorectal cancer specimens, and were significantly correlated. CONCLUSIONS: These results suggest that TF/FVIIa-EphA2 cross-talk might potentiate ligand-dependent EphA2 signaling in human cancers, and provide initial evidence that it is possible for this interaction to occur in vivo.

Analysis of the human tissue-specific expression by genome-wide integration of transcriptomics and antibody-based proteomics.

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.

Identification of anticancer drugs for hepatocellular carcinoma through personalized genome-scale metabolic modeling.

Genome-scale metabolic models (GEMs) have proven useful as scaffolds for the integration of omics data for understanding the genotype-phenotype relationship in a mechanistic manner. Here, we evaluated the presence/absence of proteins encoded by 15,841 genes in 27 hepatocellular carcinoma (HCC) patients using immunohistochemistry. We used this information to reconstruct personalized GEMs for six HCC patients based on the proteomics data, HMR 2.0, and a task-driven model reconstruction algorithm (tINIT). The personalized GEMs were employed to identify anticancer drugs using the concept of antimetabolites; i.e., drugs that are structural analogs to metabolites. The toxicity of each antimetabolite was predicted by assessing the in silico functionality of 83 healthy cell type-specific GEMs, which were also reconstructed with the tINIT algorithm. We predicted 101 antimetabolites that could be effective in preventing tumor growth in all HCC patients, and 46 antimetabolites which were specific to individual patients. Twenty-two of the 101 predicted antimetabolites have already been used in different cancer treatment strategies, while the remaining antimetabolites represent new potential drugs. Finally, one of the identified targets was validated experimentally, and it was confirmed to attenuate growth of the HepG2 cell line.

Defining the human adipose tissue proteome to reveal metabolic alterations in obesity.

White adipose tissue (WAT) has a major role in the progression of obesity. Here, we combined data from RNA-Seq and antibody-based immunohistochemistry to describe the normal physiology of human WAT obtained from three female subjects and explored WAT-specific genes by comparing WAT to 26 other major human tissues. Using the protein evidence in WAT, we validated the content of a genome-scale metabolic model for adipocytes. We employed this high-quality model for the analysis of subcutaneous adipose tissue (SAT) gene expression data obtained from subjects included in the Swedish Obese Subjects Sib Pair study to reveal molecular differences between lean and obese individuals. We integrated SAT gene expression and plasma metabolomics data, investigated the contribution of the metabolic differences in the mitochondria of SAT to the occurrence of obesity, and eventually identified cytosolic branched-chain amino acid (BCAA) transaminase 1 as a potential target that can be used for drug development. We observed decreased glutaminolysis and alterations in the BCAAs metabolism in SAT of obese subjects compared to lean subjects. We also provided mechanistic explanations for the changes in the plasma level of BCAAs, glutamate, pyruvate, and α-ketoglutarate in obese subjects. Finally, we validated a subset of our model-based predictions in 20 SAT samples obtained from 10 lean and 10 obese male and female subjects.

Integration of clinical data with a genome-scale metabolic model of the human adipocyte.

We evaluated the presence/absence of proteins encoded by 14 077 genes in adipocytes obtained from different tissue samples using immunohistochemistry. By combining this with previously published adipocyte-specific proteome data, we identified proteins associated with 7340 genes in human adipocytes. This information was used to reconstruct a comprehensive and functional genome-scale metabolic model of adipocyte metabolism. The resulting metabolic model, iAdipocytes1809, enables mechanistic insights into adipocyte metabolism on a genome-wide level, and can serve as a scaffold for integration of omics data to understand the genotype-phenotype relationship in obese subjects. By integrating human transcriptome and fluxome data, we found an increase in the metabolic activity around androsterone, ganglioside GM2 and degradation products of heparan sulfate and keratan sulfate, and a decrease in mitochondrial metabolic activities in obese subjects compared with lean subjects. Our study hereby shows a path to identify new therapeutic targets for treating obesity through combination of high throughput patient data and metabolic modeling.

Tyrosine phosphorylation profiling via in situ proximity ligation assay.

BACKGROUND: Tyrosine phosphorylation (pTyr) is an important cancer relevant posttranslational modification since it regulates protein activity and cellular localization. By controlling cell growth and differentiation it plays an important role in tumor development. This paper describes a novel approach for detection and visualization of a panel of pTyr proteins in tumors using in situ proximity ligation assay. METHODS: K562 leukemia cells were treated with tyrosine kinase and/or phosphatase inhibitors to induce differences in pTyr levels and mimic cells with different malignant properties. Cells were then probed with one antibody against the pTyr modification and another probe against the detected protein, resulting in a detectable fluorescent signal once the probes were in proximity. RESULTS: Total and protein specific pTyr levels on ABL, SHC, ERK2 and PI3K proteins were detected and samples of control and treated cells were distinguished at the pTyr level using this novel approach. Promising results were also detected for formalin fixed and paraffin embedded cells in the micro array format. CONCLUSIONS: This application of in situ proximity ligation assay is valuable in order to study the pTyr modification of a panel of proteins in large data sets to validate mass spectrometric data and to be combined with tissue microarrays. The approach offers new opportunities to reveal the pTyr signatures in cells of different malignant properties that can be used as biomarker of disease in the future.

Contribution of antibody-based protein profiling to the human Chromosome-centric Proteome Project (C-HPP).

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 ).

Socioeconomic characteristics, housing conditions and criminal offences among women with cervical neoplasia.

OBJECTIVE: To investigate the association between cervical neoplasia and socioeconomic factors, housing conditions and criminal offences. DESIGN: Longitudinal observational study. SETTING: Falun county hospital, Sweden. POPULATION: A total of 1331 women diagnosed with cervical intraepithelial neoplasia I-III or cervical cancer between 1967 and 1978 were compared with 2604 age-matched controls from the same geographical area in Sweden. METHODS: The Population and Housing Censuses were used for information about civil status, education, housing conditions, employment and socioeconomic status. The Swedish Register of Conviction Decisions was used to access information on criminal offences. MAIN OUTCOME MEASURES: Socioeconomic status, housing conditions, criminal offences. RESULTS: Women with cervical neoplasia had a lower socioeconomic status and a lower educational level than their age-matched controls. They were more often divorced and did not own their home as often as controls. A significant association with criminal offences was observed, and it persisted after adjustment for socioeconomic status. Differences in socioeconomic factors between women with cervical neoplasia and their controls had not diminished in the younger, compared with the older, part of the study population. CONCLUSIONS: The results indicate that women with cervical neoplasia belong to a socioeconomically disadvantaged group. Furthermore, the study provides information about an association with criminal offences.

Antibodies for profiling the human proteome-The Human Protein Atlas as a resource for cancer research.

In this review, we present an update on the progress of the Human Protein Atlas, with an emphasis on strategies for validating immunohistochemistry-based protein expression patterns and on the possibilities to extend the map of protein expression patterns for cancer research projects. The objectives underlying the Human Protein Atlas include (i) the generation of validated antibodies toward a major isoform of all proteins encoded by the human genome, (ii) creating an information database of protein expression patterns in normal human tissues, in cells, and in cancer, and (iii) utilizing generated antibodies and protein expression data as tools to identify clinically useful biomarkers. The success of such an effort is dependent on the validity of antibodies as specific binders of intended targets in applications used to map protein expression patterns. The development of strategies to support specific target binding is crucial and remains a challenge as a large fraction of proteins encoded by the human genome is poorly characterized, including the approximately one-third of all proteins lacking evidence of existence. Conceivable methods for validation include the use of paired antibodies, i.e. two independent antibodies targeting different and nonoverlapping epitopes on the same protein as well as comparative analysis of mRNA expression patterns with corresponding proteins.

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, 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.

Large-scale protein profiling in human cell lines using antibody-based proteomics.

Human cancer cell lines grown in vitro are frequently used to decipher basic cell biological phenomena and to also specifically study different forms of cancer. Here we present the first large-scale study of protein expression patterns in cell lines using an antibody-based proteomics approach. We analyzed the expression pattern of 5436 proteins in 45 different cell lines using hierarchical clustering, principal component analysis, and two-group comparisons for the identification of differentially expressed proteins. Our results show that immunohistochemically determined protein profiles can categorize cell lines into groups that overall reflect the tumor tissue of origin and that hematological cell lines appear to retain their protein profiles to a higher degree than cell lines established from solid tumors. The two-group comparisons reveal well-characterized proteins as well as previously unstudied proteins that could be of potential interest for further investigations. Moreover, multiple myeloma cells and cells of myeloid origin were found to share a protein profile, relative to the protein profile of lymphoid leukemia and lymphoma cells, possibly reflecting their common dependency of bone marrow microenvironment. This work also provides an extensive list of antibodies, for which high-resolution images as well as validation data are available on the Human Protein Atlas ( www.proteinatlas.org ), that are of potential use in cell line studies.

High-risk HPV infection and CIN grade correlates to the expression of c-myc, CD4+, FHIT, E-cadherin, Ki-67, and p16INK4a.

OBJECTIVE: : This study aimed to investigate correlations between a panel of biomarkers/tumor markers and high-risk (HR) human papillomavirus (HPV)-positive versus HR-HPV-negative cervical lesions. MATERIALS AND METHODS: : The study included 188 women who consecutively attended a colposcopy clinic because of PAP smears suggesting cervical intraepithelial neoplasia (CIN), and 40 women with normal vaginal cytology. Tissue microarray blocks were prepared from representative cervical cone or punch biopsies. Sections were stained for 12 biological markers, previously shown to be relevant in cervical neoplasms, and expression was correlated to the presence or absence of HR-HPV in cervical lesions. RESULTS: : No correlations between expression of biomarkers and HPV status were found in normal epithelium. Expression of c-myc, CD4, Ki-67, and p16 correlated significantly to HR-HPV-infected epithelium compared with HR-HPV-negative epithelium. When adjustment was made for CIN grade, only the expression of Ki-67 correlated significantly with HPV status and CIN grade. Human papillomavirus status was stratified to normal epithelium, low-grade CIN, and high-grade CIN. Fragile histidine triad (FHIT), E-cadherin, Rb, Ki-67, and p16 expression was significantly increased in HPV-positive tissue by increasing CIN grade. No correlation to tumor marker expression was observed in the HPV-negative tissue. CONCLUSIONS: : This study described correlations, previously not investigated, between HPV status and tumor marker expression, that is, E-cadherin, Rb, and fragile histidine triad. Surprisingly, p16 was not, although Ki-67 expression was, independently correlated to HPV positivity. The results of this study suggest that p16 instead correlates independently with increasing CIN grade.

Clonality analysis of synchronous lesions of cervical carcinoma based on X chromosome inactivation polymorphism, human papillomavirus type 16 genome mutations, and loss of heterozygosity.

One of the most common forms of carcinoma in women, cervical invasive squamous cell carcinoma (CIC), often coexists with multiple lesions of cervical intraepithelial neoplasia (CIN). CIC and CIN show heterogeneity with respect to both histopathology and biology. To understand the causes, origin, and model of progression of cervical carcinoma, we assessed the clonality of a case with multiple synchronous lesions by analyzing X chromosome inactivation polymorphism, human papillomavirus type 16 (HPV16) sequence variation/mutations, and loss of heterozygosity (LOH). Microdissection was performed on 24 samples from this case, representing the entire lesional situation. The combination of different X chromosome inactivation patterns, two HPV16 point mutations, and LOH at three genomic microsatellite loci, led to the identification of five different "monoclonal" lesions (CIN II, CIN III, and invasive carcinoma nests) and five different "polyclonal" areas (CIN II and normal squamous epithelium). This finding indicated that CIC can originate from multiple precursor cells, from which some clones might progress via multiple steps, namely via CIN II and CIN III, whereas others might develop independently and possibly directly from the carcinoma precursor cells. Our results also supported the view that HPV16 as a "field factor" causes cervical carcinoma, which is probably promoted by the loss of chromosomal material as indicated by the LOH.

A global view of protein expression in human cells, tissues, and organs.

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.

Tissue tumor marker expression in smokers, including serum cotinine concentrations, in women with cervical intraepithelial neoplasia or normal squamous cervical epithelium.

OBJECTIVE: The purpose of this study was to investigate correlations between smoking and serum cotinine, respectively, and tumor marker expression in cervical intraepithelial neoplasia (CIN) and normal epithelium. STUDY DESIGN: Women (n = 228) with cervical biopsy specimens that ranged histologically from normal to carcinoma in situ (CIN III) were included. Expression of 11 tumor markers with possible relevance in cervical neoplasms was studied. Smoking habits were recorded, and serum was assessed for cotinine concentrations. RESULTS: No differences were found in tumor marker expression in normal epithelium between smokers and nonsmokers. The tumor suppressors p53 and fragile histidine triad and the immunologic marker interleukin-10 were underexpressed, and the tumor markers cyclooxygenase-2 and Ki-67 were overexpressed in smoking, compared with nonsmoking, women with CIN and particularly in all fertile women. CONCLUSION: The molecular pattern indicates that smoking exerts unfavorable effects in cervical neoplasia. This provides biologic evidence of smoking being a true cofactor in cervical neoplasia.

Toward a confocal subcellular atlas of the human proteome.

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.

A genecentric Human Protein Atlas for expression profiles based on antibodies.

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.

Proximity Ligation Assay as a Tool for Antibody Validation in Human Tissues.

Immunohistochemistry (IHC) is the accepted standard for spatial analysis of protein expression in tissues. IHC is widely used for cancer diagnostics and in basic research. The development of new antibodies to proteins with unknown expression patterns has created a demand for thorough validation. We have applied resources from the Human Protein Atlas project and the Antibody Portal at National Cancer Institute to generate protein expression data for 12 proteins across 39 cancer cell lines and 37 normal human tissue types. The outcome of IHC on consecutive sections from both cell and tissue microarrays using two independent antibodies for each protein was compared with in situ proximity ligation (isPLA), where binding by both antibodies is required to generate detection signals. Semi-quantitative scores from IHC and isPLA were compared with expression of the corresponding 12 transcripts across all cell lines and tissue types. Our results show a more consistent correlation between mRNA levels and isPLA as compared to IHC. The main benefits of isPLA include increased detection specificity and decreased unspecific staining compared to IHC. We conclude that implementing isPLA as a complement to IHC for analysis of protein expression and in antibody validation pipelines can lead to more accurate localization of proteins in tissue.