Antibody-based tissue profiling as a tool for clinical proteomics

Data-Driven Discovery of Molecular Targets for Antibody-Drug Conjugates in Cancer Treatment

Antibody-drug conjugate therapy has attracted considerable attention in recent years. Since the selection of appropriate targets is a critical aspect of antibody-drug conjugate research and development, a big data research for discovery of candidate targets per tumor type is outstanding and of high interest. Thus, the purpose of this study was to identify and prioritize candidate antibody-drug conjugate targets with translational potential across common types of cancer by mining the Human Protein Atlas, as a unique big data resource. To perform a multifaceted screening process, XML and TSV files including immunohistochemistry expression data for 45 normal tissues and 20 tumor types were downloaded from the Human Protein Atlas website. For genes without high protein expression across critical normal tissues, a quasi H-score (range, 0-300) was computed per tumor type. All genes with a quasi H - score ≥ 150 were extracted. Of these, genes with cell surface localization were selected and included in a multilevel validation process. Among 19670 genes that encode proteins, 5520 membrane protein-coding genes were included in this study. During a multistep data mining procedure, 332 potential targets were identified based on the level of the protein expression across critical normal tissues and 20 tumor types. After validation, 23 cell surface proteins were identified and prioritized as candidate antibody-drug conjugate targets of which two have interestingly been approved by the FDA for use in solid tumors, one has been approved for lymphoma, and four have currently been entered in clinical trials. In conclusion, we identified and prioritized several candidate targets with translational potential, which may yield new clinically effective and safe antibody-drug conjugates. This large-scale antibody-based proteomic study allows us to go beyond the RNA-seq studies, facilitates bench-to-clinic research of targeted anticancer therapeutics, and offers valuable insights into the development of new antibody-drug conjugates.

Living Cell Microarrays: An Overview of Concepts

Living cell microarrays are a highly efficient cellular screening system. Due to the low number of cells required per spot, cell microarrays enable the use of primary and stem cells and provide resolution close to the single-cell level. Apart from a variety of conventional static designs, microfluidic microarray systems have also been established. An alternative format is a microarray consisting of three-dimensional cell constructs ranging from cell spheroids to cells encapsulated in hydrogel. These systems provide an in vivo-like microenvironment and are preferably used for the investigation of cellular physiology, cytotoxicity, and drug screening. Thus, many different high-tech microarray platforms are currently available. Disadvantages of many systems include their high cost, the requirement of specialized equipment for their manufacture, and the poor comparability of results between different platforms. In this article, we provide an overview of static, microfluidic, and 3D cell microarrays. In addition, we describe a simple method for the printing of living cell microarrays on modified microscope glass slides using standard DNA microarray equipment available in most laboratories. Applications in research and diagnostics are discussed, e.g., the selective and sensitive detection of biomarkers. Finally, we highlight current limitations and the future prospects of living cell microarrays.

Manual evaluation of tissue microarrays in a high-throughput research project: The contribution of Indian surgical pathology to the Human Protein Atlas (HPA) project

The Human Protein Atlas (HPA) program (www.proteinatlas.org) is an international program that has been set up to allow for a systematic exploration of the human proteome using antibody-based proteomics. This is accomplished by combining high-throughput generation of affinity-purified (mono-specific) antibodies with protein profiling in a multitude of tissues/cell types assembled in tissue microarrays. Twenty-six surgical pathologists over a seven-and-half year period have annotated and curated approximately sixteen million tissue images derived from immunostaining of normal and cancer tissues by approximately 23 000 antibodies. Web-based annotation software that allows for a basic and rapid evaluation of immunoreactivity in tissues has been utilized. Intensity, fraction of immunoreactive cells and subcellular localization were recorded for each given cell population. A text comment summarizing the characteristics for each antibody was added. The methods used and the challenges encountered for this exercise, the largest effort ever by a single group of surgical pathologists, are discussed. Manual annotation of digital images is an important tool that may be successfully utilized in high-throughput research projects. This is the first time an Indian private pathology laboratory has been associated with cutting-edge research internationally providing a classic example of developed and emerging nation collaboration.

A breast cancer cell microarray (CMA) as a rapid method to characterize candidate biomarkers

Tissue microarrays (TMAs) have become an invaluable tool in cancer research to evaluate expression and subcellular localization of proteins in cells and tissues. As the catalogs of candidate biomarkers and therapeutic targets become more extensive, there is a need to characterize and validate these targets and biomarkers in cell lines as a primary biological system in research laboratories. Thus, cell microarrays (CMAs) are useful as a high-throughput screening tool. Here, we constructed a CMA containing 32 publicly available immortalized breast cell lines with the goal of creating a method to rapidly screen for antigens of interest in breast cancer research in a relatively easy, rapid and cost-effective manner. As proof of concept, we performed immunocytochemical staining of the HER2 receptor, as the status of this protein is relevant to breast cancer and has previously been reported for these cell lines. We observed a complete concordance of our staining with the published status of HER2 in these cell lines. In addition, we examined the expression of CD44, epithelial markers EpCAM and E-cadherin and tyrosine phosphoproteins. The labeling of these proteins correlates with the known biology of the cell lines. Our results demonstrate the utility of our method to screen for potential biomarkers and therapeutic targets in breast cancer and we suggest that CMAs be used as a general approach in breast cancer research.

Defining the Human Brain Proteome Using Transcriptomics and Antibody-Based Profiling with a Focus on the Cerebral Cortex

The mammalian brain is a complex organ composed of many specialized cells, harboring sets of both common, widely distributed, as well as specialized and discretely localized proteins. Here we focus on the human brain, utilizing transcriptomics and public available Human Protein Atlas (HPA) data to analyze brain-enriched (frontal cortex) polyadenylated messenger RNA and long non-coding RNA and generate a genome-wide draft of global and cellular expression patterns of the brain. Based on transcriptomics analysis of altogether 27 tissues, we have estimated that approximately 3% (n=571) of all protein coding genes and 13% (n=87) of the long non-coding genes expressed in the human brain are enriched, having at least five times higher expression levels in brain as compared to any of the other analyzed peripheral tissues. Based on gene ontology analysis and detailed annotation using antibody-based tissue micro array analysis of the corresponding proteins, we found the majority of brain-enriched protein coding genes to be expressed in astrocytes, oligodendrocytes or in neurons with molecular properties linked to synaptic transmission and brain development. Detailed analysis of the transcripts and the genetic landscape of brain-enriched coding and non-coding genes revealed brain-enriched splice variants. Several clusters of neighboring brain-enriched genes were also identified, suggesting regulation of gene expression on the chromatin level. This multi-angle approach uncovered the brain-enriched transcriptome and linked genes to cell types and functions, providing novel insights into the molecular foundation of this highly specialized organ.

The human gastrointestinal tract-specific transcriptome and proteome as defined by RNA sequencing and antibody-based profiling

BACKGROUND

The gastrointestinal tract (GIT) is subdivided into different anatomical organs with many shared functions and characteristics, but also distinct differences. We have combined a genome-wide transcriptomics analysis with immunohistochemistry-based protein profiling to describe the gene and protein expression patterns that define the human GIT.

METHODS

RNA sequencing data derived from stomach, duodenum, jejunum/ileum and colon specimens were compared to gene expression levels in 23 other normal human tissues analysed with the same method. Protein profiling based on immunohistochemistry and tissue microarrays was used to sub-localize the corresponding proteins with GIT-specific expression into sub-cellular compartments and cell types.

RESULTS

Approximately 75% of all human protein-coding genes were expressed in at least one of the GIT tissues. Only 51 genes showed enriched expression in either one of the GIT tissues and an additional 83 genes were enriched in two or more GIT tissues. The list of GIT-enriched genes with validated protein expression patterns included various well-known but also previously uncharacterised or poorly studied genes. For instance, the colon-enriched expression of NXPE family member 1 (NXPE1) was established, while NLR family, pyrin domain-containing 6 (NLRP6) expression was primarily found in the human small intestine.

CONCLUSIONS

We have applied a genome-wide analysis based on transcriptomics and antibody-based protein profiling to identify genes that are expressed in a specific manner within the human GIT. These genes and proteins constitute important starting points for an improved understanding of the normal function and the different states of disease associated with the GIT.

The transcriptomic and proteomic landscapes of bone marrow and secondary lymphoid tissues

Background

The sequencing of the human genome has opened doors for global gene expression profiling, and the immense amount of data will lay an important ground for future studies of normal and diseased tissues. The Human Protein Atlas project aims to systematically map the human gene and protein expression landscape in a multitude of normal healthy tissues as well as cancers, enabling the characterization of both housekeeping genes and genes that display a tissue-specific expression pattern. This article focuses on identifying and describing genes with an elevated expression in four lymphohematopoietic tissue types (bone marrow, lymph node, spleen and appendix), based on the Human Protein Atlas-strategy that combines high throughput transcriptomics with affinity-based proteomics.

Results

An enriched or enhanced expression in one or more of the lymphohematopoietic tissues, compared to other tissue-types, was seen for 693 out of 20,050 genes, and the highest levels of expression were found in bone marrow for neutrophilic and erythrocytic genes. A majority of these genes were found to constitute well-characterized genes with known functions in lymphatic or hematopoietic cells, while others are not previously studied, as exemplified by C19ORF59.

Conclusions

In this paper we present a strategy of combining next generation RNA-sequencing with in situ affinity-based proteomics in order to identify and describe new gene targets for further research on lymphatic or hematopoietic cells and tissues. The results constitute lists of genes with enriched or enhanced expression in the four lymphohematopoietic tissues, exemplified also on protein level with immunohistochemical images.

Defining the human gallbladder proteome by transcriptomics and affinity proteomics

Global protein analysis of human gallbladder tissue is vital for identification of molecular regulators and effectors of its physiological activity. Here, we employed a genome-wide deep RNA sequencing analysis in 28 human tissues to identify the genes overrepresented in the gallbladder and complemented it with antibody-based immunohistochemistry in 48 human tissues. We characterized human gallbladder proteins and identified 140 gallbladder-specific proteins with an elevated expression in the gallbladder as compared to the other analyzed tissues. Five genes were categorized as enriched, with at least fivefold higher levels in gallbladder, 60 genes were categorized as group enriched with elevated transcript levels in gallbladder shared with at least one other tissue and 75 genes were categorized as enhanced with higher expression than the average expression in other tissues. We explored the localization of the genes within the gallbladder through cell-type specific antibody-based protein profiling and the subcellular localization of the genes through immunofluorescent-based profiling. Finally, we revealed the biological processes and metabolic functions carried out by these genes through the use of GO, KEGG Pathway, and HMR2.0 that is compilation of the human metabolic reactions. We demonstrated the results of the combined analysis of the transcriptomics and affinity proteomics.

Evaluation of HER2 Protein Expression Using 2 New Monoclonal Antibodies

This study describes the performance of 2 new mouse anti-HER2 monoclonal antibodies (Abs), clones 33F and 410G, in evaluating HER2 overexpression in a series of 123 invasive breast carcinoma cases. In-house immunohistochemistry (IHC) was performed and the results were compared with those for the SP3 and A0485 anti-HER2 Abs. Chromogenic in situ hybridization was used to detect ERBB2 amplification and its concordance with IHC was analyzed. Comparison of IHC results for 33F with SP3 and A0485 yielded concordance rates (K) of 0.81 and 0.75, respectively; the same concordance rates were found when comparing results for 410G with SP3 and A0485. Compared with SP3 and A0485, 33F and 410G specificities were 98.6% and 98.6%, and 100% and 100%, respectively, whereas the sensitivities were 80% and 74.1%, and 78% and 72.2%, respectively. The K values between 33F and 410G HER2+ expression and chromogenic in situ hybridization-positive amplification were 1 and 0.96, respectively. These concordance rates were reproduced in another production batch (K=0.96 and K=0.96). Together, these results show that the tested monoclonal Abs would be well suited for detecting HER2 protein overexpression by IHC.

The human liver-specific proteome defined by transcriptomics and antibody-based profiling

Human liver physiology and the genetic etiology of the liver diseases can potentially be elucidated through the identification of proteins with enriched expression in the liver. Here, we combined data from RNA sequencing (RNA-Seq) and antibody-based immunohistochemistry across all major human tissues to explore the human liver proteome with enriched expression, as well as the cell type-enriched expression in hepatocyte and bile duct cells. We identified in total 477 protein-coding genes with elevated expression in the liver: 179 genes have higher expression as compared to all the other analyzed tissues; 164 genes have elevated transcript levels in the liver shared with at least one other tissue type; and an additional 134 genes have a mild level of increased expression in the liver. We identified the precise localization of these proteins through antibody-based protein profiling and the subcellular localization of these proteins through immunofluorescent-based profiling. We also identified the biological processes and metabolic functions associated with these proteins, investigated their contribution in the occurrence of liver diseases, and identified potential targets for their treatment. Our study demonstrates the use of RNA-Seq and antibody-based immunohistochemistry for characterizing the human liver proteome, as well as the use of tissue-specific proteins in identification of novel drug targets and discovery of biomarkers.-Kampf, C., Mardinoglu, A., Fagerberg, L., Hallström, B. M., Edlund, K., Lundberg, E., Pontén, F., Nielsen, J., Uhlen, M. The human liver-specific proteome defined by transcriptomics and antibody-based profiling.

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.

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.

Detection of the human endogenous retrovirus ERV3-encoded Env-protein in human tissues using antibody-based proteomics

OBJECTIVES

There is growing evidence to suggest that human endogenous retroviruses (HERVs) have contributed to human evolution, being expressed in development, normal physiology and disease. A key difficulty in the scientific evaluation of this potential viral contribution is the accurate demonstration of virally expressed protein in specific human cells and tissues. In this study, we have adopted the endogenous retrovirus, ERV3, as our test model in developing a reliable high-capacity methodology for the expression of such endogenous retrovirus-coded protein.

DESIGN

Two affinity-purified polyclonal antibodies to ERV3 Env-encoded protein were generated to detect the corresponding protein expression pattern in specific human cells, tissues and organs.

PARTICIPANTS

Sampling included normal tissues from 144 individuals ranging from childhood to old age. This included more than forty different tissues and organs and some 216 different cancer tissues representing the twenty commonest forms of human cancer.

SETTING

The Rudbeck Laboratory, Uppsala University and Uppsala University Hospital, Uppsala, Sweden.

MAIN OUTCOME MEASURES

The potential expression at likely physiological level of the ERV3Env encoded protein in a wide range of human cells, tissues and organs.

RESULTS

We found that ERV3 encoded Env protein is expressed at substantive levels in placenta, testis, adrenal gland, corpus luteum, Fallopian tubes, sebaceous glands, astrocytes, bronchial epithelium and the ducts of the salivary glands. Substantive expression was also seen in a variety of epithelial cells as well as cells known to undergo fusion in inflammation and in normal physiology, including fused macrophages, myocardium and striated muscle. This contrasted strongly with the low levels expressed in other tissues types. These findings suggest that this virus plays a significant role in human physiology and may also play a possible role in disease.

CONCLUSION

This technique can now be extended to the study of other HERV genomes within the human chromosomes that may have contributed to human evolution, physiology and disease.

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.

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 ).

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.

Rapid characterization of candidate biomarkers for pancreatic cancer using cell microarrays (CMAs)

Tissue microarrays have become a valuable tool for high-throughput analysis using immunohistochemical labeling. However, the large majority of biochemical studies are carried out in cell lines to further characterize candidate biomarkers or therapeutic targets with subsequent studies in animals or using primary tissues. Thus, cell line-based microarrays could be a useful screening tool in some situations. Here, we constructed a cell microarray (CMA) containing a panel of 40 pancreatic cancer cell lines available from American Type Culture Collection in addition to those locally available at Johns Hopkins. As proof of principle, we performed immunocytochemical labeling of an epithelial cell adhesion molecule (Ep-CAM), a molecule generally expressed in the epithelium, on this pancreatic cancer CMA. In addition, selected molecules that have been previously shown to be differentially expressed in pancreatic cancer in the literature were validated. For example, we observed strong labeling of CA19-9 antigen, a prognostic and predictive marker for pancreatic cancer. We also carried out a bioinformatics analysis of a literature curated catalog of pancreatic cancer biomarkers developed previously by our group and identified two candidate biomarkers, HLA class I and transmembrane protease, serine 4 (TMPRSS4), and examined their expression in the cell lines represented on the pancreatic cancer CMAs. Our results demonstrate the utility of CMAs as a useful resource for rapid screening of molecules of interest and suggest that CMAs can become a universal standard platform in cancer research.

Novel pancreatic beta cell-specific proteins: antibody-based proteomics for identification of new biomarker candidates

Beta cell-specific surface targets are required for non-invasive monitoring of beta cell mass, which could be used for evaluation of new diabetes treatments as well as to help unravel pathogenic mechanisms underlying beta cell dysfunction. By antibody-based proteomics, we have identified and explored a set of islet cell-specific proteins. A search algorithm in the Human Protein Atlas was set up for identification of islet-specific proteins that yielded 27 hits, of which twelve showed a clear membranous expression pattern or had predicted transmembrane regions. The specificity of the identified proteins was investigated by immunohistochemical staining of pancreas sections from diabetic and non-diabetic subjects. No expression of these antigens could be detected in the exocrine pancreas. Colocalization with insulin and glucagon was further determined by confocal microscopy using isolated human islets. All antibodies specifically stained human islets and colocalization analysis revealed that four proteins were exclusively expressed in beta cells. Importantly, these antibodies were negative in sections from subjects with long-standing type 1 diabetes. In the present study, we present four proteins; DGCR2, GBF1, GPR44 and SerpinB10, the expression of which has not previously been described in beta cells.

Scalable in situ hybridization on tissue arrays for validation of novel cancer and tissue-specific biomarkers

Tissue localization of gene expression is increasingly important for accurate interpretation of large scale datasets from expression and mutational analyses. To this end, we have (1) developed a robust and scalable procedure for generation of mRNA hybridization probes, providing >95% first-pass success rate in probe generation to any human target gene and (2) adopted an automated staining procedure for analyses of formalin-fixed paraffin-embedded tissues and tissue microarrays. The in situ mRNA and protein expression patterns for genes with known as well as unknown tissue expression patterns were analyzed in normal and malignant tissues to assess procedure specificity and whether in situ hybridization can be used for validating novel antibodies. We demonstrate concordance between in situ transcript and protein expression patterns of the well-known pathology biomarkers KRT17, CHGA, MKI67, PECAM1 and VIL1, and provide independent validation for novel antibodies to the biomarkers BRD1, EZH2, JUP and SATB2. The present study provides a foundation for comprehensive in situ gene set or transcriptome analyses of human normal and tumor tissues.

The Human Protein Atlas as a proteomic resource for biomarker discovery

The analysis of tissue-specific expression at both the gene and protein levels is vital for understanding human biology and disease. Antibody-based proteomics provides a strategy for the systematic generation of antibodies against all human proteins to combine with protein profiling in tissues and cells using tissue microarrays, immunohistochemistry and immunofluorescence. The Human Protein Atlas project was launched in 2003 with the aim of creating a map of protein expression patterns in normal cells, tissues and cancer. At present, 11,200 unique proteins corresponding to over 50% of all human protein-encoding genes have been analysed. All protein expression data, including underlying high-resolution images, are published on the free and publically available Human Protein Atlas portal (http://www.proteinatlas.org). This database provides an important source of information for numerous biomedical research projects, including biomarker discovery efforts. Moreover, the global analysis of how our genome is expressed at the protein level has provided basic knowledge on the ubiquitous expression of a large proportion of our proteins and revealed the paucity of cell- and tissue-type-specific proteins.

Antibody-based protein profiling of the human chromosome 21

The Human Proteome Project has been proposed to create a knowledge-based resource based on a systematical mapping of all human proteins, chromosome by chromosome, in a gene-centric manner. With this background, we here describe the systematic analysis of chromosome 21 using an antibody-based approach for protein profiling using both confocal microscopy and immunohistochemistry, complemented with transcript profiling using next generation sequencing data. We also describe a new approach for protein isoform analysis using a combination of antibody-based probing and isoelectric focusing. The analysis has identified several genes on chromosome 21 with no previous evidence on the protein level, and the isoform analysis indicates that a large fraction of human proteins have multiple isoforms. A chromosome-wide matrix is presented with status for all chromosome 21 genes regarding subcellular localization, tissue distribution, and molecular characterization of the corresponding proteins. The path to generate a chromosome-specific resource, including integrated data from complementary assay platforms, such as mass spectrometry and gene tagging analysis, is discussed.

Classification of protein profiles from antibody microarrays using heat and detergent treatment

Antibody microarrays offer new opportunities for exploring the proteome and to identify biomarker candidates in human serum and plasma. Here, we have investigated the effect of heat and detergents on an antibody-based suspension bead array (SBA) assay using polyclonal antibodies and biotinylated plasma samples. With protein profiles from more than 2300 antibodies generated in 384-plex antibody SBAs, three major classes of heat and detergent susceptibility could be described. The results show that washing of the beads with SDS (rather than Tween) after target binding lowered intensity levels of basically all profiles and that about 50% of the profiles appeared to be lowered to a similar extent by heating of the sample. About 33% of the profiles appeared to be insensitive to heat treatment while another 17% showed a positive influence of heat to yield elevated profiles. The results suggest that the classification of antibodies is driven by the molecular properties of the antibody-antigen interaction and can generally not be predicted based on protein class or Western blot data. The experimental scheme presented here can be used to systematically categorize antibodies and thereby combine antibodies with similar properties into targeted arrays for analysis of plasma and serum.

SOX10 expression in superficial spreading and nodular malignant melanomas

SOX10 is a transcription factor expressed in nerve cells and melanocytes. The aim of this study was to investigate the protein expression pattern of SOX10 in malignant melanoma tumors and to analyze whether the results correlated with clinical parameters and the proliferation marker Ki-67. Furthermore, proliferation and migration were analyzed in three different cell lines employing SOX10 small interfering RNA-mediated silencing. Expression patterns were determined in 106 primary tumors and 39 metastases in addition to 16 normal skin samples and six benign nevi employing immunohistochemistry and tissue microarrays. The immunohistochemical staining was evaluated manually and with an automated algorithm. SOX10 was strongly expressed in the benign tissues, but for the malignant tumors superficial spreading melanomas stained stronger than nodular malignant melanomas (P=0.008). The staining intensity was also inversely correlated with T-stage (Spearman's ρ=-0.261, P=0.008). Overall survival and time to recurrence were significantly correlated with SOX10 intensity, but not in multivariate analysis including T-stage. With the automated algorithm there was an inverse correlation between the SOX10 staining intensity and the proliferation marker, Ki-67 (ρ=-0.173, P=0.02) and a significant difference in the intensity signal between the benign tissues, the primary tumors and the metastases where the metastases stained the weakest (P≤0.001). SOX10 downregulation resulted in variable effects on proliferation and migration rates in the melanoma cell lines. In conclusion, the SOX10 intensity level differed depending on the tissue studied and SOX10 might have a role in survival. No conclusion regarding the role of SOX10 for in-vitro proliferation and migration could be drawn.

Antibody-based proteomics: fast-tracking molecular diagnostics in oncology

The effective implementation of personalized cancer therapeutic regimens depends on the successful identification and translation of informative biomarkers to aid clinical decision making. Antibody-based proteomics occupies a pivotal space in the cancer biomarker discovery and validation pipeline, facilitating the high-throughput evaluation of candidate markers. Although the clinical utility of these emerging technologies remains to be established, the traditional use of antibodies as affinity reagents in clinical diagnostic and predictive assays suggests that the rapid translation of such approaches is an achievable goal. Furthermore, in combination with, or as alternatives to, genomic and transcriptomic methods for patient stratification, antibody-based proteomics approaches offer the promise of additional insight into cancer disease states. In this Review, we discuss the current status of antibody-based proteomics and its contribution to the development of new assays that are crucial for the realization of individualized cancer therapy.

Subcellular distribution and expression of prenylated Rab acceptor 1 domain family, member 2 (PRAF2) in malignant glioma: Influence on cell survival and migration

Our previous studies revealed that the expression of the 19-kDa protein prenylated Rab acceptor 1 domain family, member 2 (PRAF2) is elevated in cancer tissues of the breast, colon, lung, and ovary, when compared to noncancerous tissues of paired samples. PRAF2 mRNA expression also correlated with several genetic and clinical features and is a candidate prognostic marker in the pediatric cancer neuroblastoma. The PRAF2-related proteins, PRAF1 and PRAF3, play multiple roles in cellular processes, including endo/exocytic vesicle trafficking and glutamate uptake. PRAF2 shares a high sequence homology with these family members, but its function remains unknown. In this study, we examined PRAF2 mRNA and protein expression in 20 different human cancer types using Affymetrix microarray and human tissue microarray (TMA) analyses, respectively. In addition, we investigated the subcellular distribution of PRAF2 by immunofluorescence microscopy and cell fractionation studies. PRAF2 mRNA and protein expression was elevated in several cancer tissues with highest levels in malignant glioma. At the molecular level, we detected native PRAF2 in small, vesicle-like structures throughout the cytoplasm as well as in and around cell nuclei of U-87 malignant glioma cells. We further found that monomeric and dimeric forms of PRAF2 are associated with different cell compartments, suggesting possible functional differences. Importantly, PRAF2 down-regulation by RNA interference significantly reduced the cell viability, migration, and invasiveness of U-87 cells. This study shows that PRAF2 expression is elevated in various tumors with exceptionally high expression in malignant gliomas, and PRAF2 therefore presents a candidate molecular target for therapeutic intervention.

Candidate serological biomarkers for cancer identified from the secretomes of 23 cancer cell lines and the human protein atlas

Although cancer cell secretome profiling is a promising strategy used to identify potential body fluid-accessible cancer biomarkers, questions remain regarding the depth to which the cancer cell secretome can be mined and the efficiency with which researchers can select useful candidates from the growing list of identified proteins. Therefore, we analyzed the secretomes of 23 human cancer cell lines derived from 11 cancer types using one-dimensional SDS-PAGE and nano-LC-MS/MS performed on an LTQ-Orbitrap mass spectrometer to generate a more comprehensive cancer cell secretome. A total of 31,180 proteins was detected, accounting for 4,584 non-redundant proteins, with an average of 1,300 proteins identified per cell line. Using protein secretion-predictive algorithms, 55.8% of the proteins appeared to be released or shed from cells. The identified proteins were selected as potential marker candidates according to three strategies: (i) proteins apparently secreted by one cancer type but not by others (cancer type-specific marker candidates), (ii) proteins released by most cancer cell lines (pan-cancer marker candidates), and (iii) proteins putatively linked to cancer-relevant pathways. We then examined protein expression profiles in the Human Protein Atlas to identify biomarker candidates that were simultaneously detected in the secretomes and highly expressed in cancer tissues. This analysis yielded 6-137 marker candidates selective for each tumor type and 94 potential pan-cancer markers. Among these, we selectively validated monocyte differentiation antigen CD14 (for liver cancer), stromal cell-derived factor 1 (for lung cancer), and cathepsin L1 and interferon-induced 17-kDa protein (for nasopharyngeal carcinoma) as potential serological cancer markers. In summary, the proteins identified from the secretomes of 23 cancer cell lines and the Human Protein Atlas represent a focused reservoir of potential cancer biomarkers.

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.

Nuclear expression of the RNA-binding protein RBM3 is associated with an improved clinical outcome in breast cancer

Single-strand RNA-binding proteins (RBPs) are involved in many aspects of RNA metabolism and in the regulation of gene transcription. The RBP RBM3 was recently suggested to be a proto-oncogene in colorectal cancer; however, such a role has not been corroborated by previous studies in the colon or other tumor types, and the prognostic implications of tumor-specific RBM3 expression remain unclear. Mono-specific antibodies against RBM3 were generated. Antibody specificity was confirmed using siRNA gene silencing, western blotting and immunohistochemistry on a panel of breast cancer cell lines. Using tissue microarrays and IHC, RBM3 protein expression was examined in 48 normal tissues and in 20 common cancers. Additional analysis in two independent breast cancer cohorts (n=1016) with long-term follow-up was also carried out. RBM3 was upregulated in cancer compared to normal tissues. The nuclear expression of RBM3 in breast cancer was associated with low grade (P<0.001), small tumors (P<0.001), estrogen receptor (ER) positivity (P<0.001) and Ki-67 negativity (P<0.001) in both the breast cancer cohorts. An increased nuclear expression of RBM3 was associated with a prolonged overall and recurrence-free survival. The prognostic value was particularly pronounced in hormone receptor-positive tumors and remained significant in multivariate interaction analysis after controlling for tamoxifen treatment (HR: 0.49, 95% CI: 0.30-0.79, P=0.004). These data strongly indicate that nuclear RBM3 is an independent favorable prognostic factor in breast cancer, and seems to have a specific role in ER-positive tumors.

The impact of tissue fixatives on morphology and antibody-based protein profiling in tissues and cells

Pathology archives harbor large amounts of formalin-fixed, paraffin-embedded tissue samples, used mainly in clinical diagnostics but also for research purposes. Introduction of heat-induced antigen retrieval has enabled the use of tissue samples for extensive immunohistochemical analysis, despite the fact that antigen retrieval may not recover all epitopes, owing to alterations of the native protein structure induced by formalin. The aim of this study was to investigate how different fixatives influence protein recognition by immunodetection methods in tissues, cell preparations, and protein lysates, as compared with formalin. Seventy-two affinity-purified polyclonal antibodies were used to evaluate seven different fixatives. The aldehyde-based fixative Glyo-fixx proved to be excellent for preservation of proteins in tissue detected by immunohistochemistry (IHC), similar to formalin. A non-aldehyde-based fixative, NEO-FIX was superior for fixation of cultured cells, in regard to morphology, and thereby also advantageous for IHC. Large variability in the amount of protein extracted from the differently fixed tissues was observed, and the HOPE fixative provided the overall highest yield of protein. In conclusion, morphological resolution and immunoreactivity were superior in tissues fixed with aldehyde-based fixatives, whereas the use of non-aldehyde-based fixatives can be advantageous in obtaining high protein yield for Western blot analysis. This manuscript contains online supplemental material at http://www.jhc.org. Please visit this article online to view these materials.

The E3 ligase axotrophin/MARCH-7: protein expression profiling of human tissues reveals links to adult stem cells

Axotrophin/MARCH-7 was first identified in mouse embryonic stem cells as a neural stem cell gene. Using the axotrophin/MARCH-7 null mouse, we discovered profound effects on T lymphocyte responses, including 8-fold hyperproliferation and 5-fold excess release of the stem cell cytokine leukemia inhibitory factor (LIF). Our further discovery that axotrophin/MARCH-7 is required for targeted degradation of the LIF receptor subunit gp190 implies a direct role in the regulation of LIF signaling. Bioinformatics studies revealed a highly conserved RING-CH domain in common with the MARCH family of E3-ubiquitin ligases, and accordingly, axotrophin was renamed "MARCH-7." To probe protein expression of human axotrophin/MARCH-7, we prepared antibodies against different domains of the protein. Each antibody bound its specific target epitope with high affinity, and immunohistochemistry cross-validated target specificity. Forty-eight human tissue types were screened. Epithelial cells stained strongly, with trophoblasts having the greatest staining. In certain tissues, specific cell types were selectively positive, including neurons and neuronal progenitor cells in the hippocampus and cerebellum, endothelial sinusoids of the spleen, megakaryocytes in the bone marrow, crypt stem cells of the small intestine, and alveolar macrophages in the lung. Approximately 20% of central nervous system neuropils were positive. Notably, axotrophin/MARCH-7 has an expression profile that is distinct from that of other MARCH family members. This manuscript contains online supplemental material at http://www.jhc.org. Please visit this article online to view these materials.

The Human Protein Atlas--a tool for pathology

Tissue-based diagnostics and research is incessantly evolving with the development of new molecular tools. It has long been realized that immunohistochemistry can add an important new level of information on top of morphology and that protein expression patterns in a cancer may yield crucial diagnostic and prognostic information. We have generated an immunohistochemistry-based map of protein expression profiles in normal tissues, cancer and cell lines. For each antibody, altogether 708 spots of tissues and cells are analysed and the resulting images and data are presented as freely available in the Human Protein Atlas (www.proteinatlas.org). The new version 4 of the atlas, including more than 5 million images of immunohistochemically stained tissues and cells, is based on 6122 antibodies, representing 5011 human proteins encoded by approximately 25% of the human genome. The gene-centric database includes a putative classification of proteins in various protein classes, both functional classes, such as kinases or transcription factors and project-related classes, such as candidate genes for cancer or cardiovascular diseases. For each of the internally generated antibodies, the exact antigen sequence is presented, together with a visualization of application-specific validation data, including a protein array assay, western blot analysis, immunohistochemistry and, in most cases, immunofluorescent-based confocal microscopy. The updated version also includes new search algorithms to allow complex queries regarding expression profiles, protein classes and chromosome location. Thus, the presented Human Protein Atlas provides a resource for pathology-based biomedical research, including protein science and biomarker discovery.

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.

Antibodypedia, a portal for sharing antibody and antigen validation data

Antibodies are useful tools to characterize the components of the human proteome and to validate potential protein biomarkers discovered through various clinical proteomics efforts. The lack of validation results across various applications for most antibodies often makes it necessary to perform cumbersome investigations to ensure specificity of a particular antibody in a certain application. A need therefore exists for a standardized system for sharing validation data about publicly available antibodies and to allow antibody providers as well as users to contribute and edit experimental evidence data, including data also on the antigen. Here we describe a new publicly available portal called Antibodypedia, which has been developed to allow sharing of information regarding validation of antibodies in which providers can submit their own validation results and reliability scores. We report standardized validation criteria and submission rules for applications such as Western blots, protein arrays, immunohistochemistry, and immunofluorescence. The contributor is expected to provide experimental evidence and a validation score for each antibody, and the users can subsequently provide feedback and comments on the use of the antibody. The database thus provides a virtual resource of publicly available antibodies toward human proteins with accompanying experimental evidence supporting an individual validation score for each antibody in an application-specific manner.

Expression profile of PRAF2 in the human brain and enrichment in synaptic vesicles

PRA1 domain family, member 2 (PRAF2) is a novel 19-kDa protein with a prenylated Rab acceptor 1 (PRA1) motif and four transmembrane domains. Our previous studies revealed that PRAF2 is highly expressed in the brain and serves as a candidate prognostic marker in neuroblastoma (NB). PRAF2 is related to proteins PRAF1 (PRA1, prenylin, Yip3) and PRAF3 (GTRAP3-18, JWA, Arl6-IP5), both of which are enriched in the brain and implicated in cellular transport and endo/exocytic vesicle trafficking. However, the function for PRAF2 remains unknown. In this study, we analyzed the distribution and localization of PRAF2 in the mature human brain using two new antibodies specific for the protein. Analysis by immunohistochemistry revealed that in the human cerebellum, the PRAF2 protein was strongly expressed in Purkinje cells and, more moderately, in cells of the molecular and the granular layers. In the cerebral cortex, hippocampus, and lateral ventricles, PRAF2 protein was detected in neuronal cells, but not in non-neuronal cells. Intriguingly, immunoblot analysis revealed that PRAF2 is enriched in synaptic vesicles (SVs) prepared from rat brains. The expression of PRAF2 in specific regions of the brain including SVs suggest an important physiological function for this novel protein, possibly by participating in multiple aspects of SV maturation, transport, and signal transmission.

Prognostic ability of a panel of immunohistochemistry markers - retailoring of an 'old solution'

An urgent requirement exists for new prognostic and predictive assays in breast cancer. Despite the development of high-throughput technologies such as DNA microarrays, it would now appear that immunohistochemistry (IHC) may play an increasingly important role in the clinical management of breast cancer. In this editorial, the authors discuss the potential prognostic ability of a panel of IHC markers, and question whether this well-established assay technology may in fact allow for improved prognostic and predictive tests in breast cancer.

A web-based tool for in silico biomarker discovery based on tissue-specific protein profiles in normal and cancer tissues

Here we report the development of a publicly available Web-based analysis tool for exploring proteins expressed in a tissue- or cancer-specific manner. The search queries are based on the human tissue profiles in normal and cancer cells in the Human Protein Atlas portal and rely on the individual annotation performed by pathologists of images representing immunohistochemically stained tissue sections. Approximately 1.8 million images representing more than 3000 antibodies directed toward human proteins were used in the study. The search tool allows for the systematic exploration of the protein atlas to discover potential protein biomarkers. Such biomarkers include tissue-specific markers, cell type-specific markers, tumor type-specific markers, markers of malignancy, and prognostic or predictive markers of cancers. Here we show examples of database queries to generate sets of candidate biomarker proteins for several of these different categories. Expression profiles of candidate proteins can then subsequently be validated by examination of the underlying high resolution images. The present study shows examples of search strategies revealing several potential protein biomarkers, including proteins specifically expressed in normal cells and in cancer cells from specified tumor types. The lists of candidate proteins can be used as a starting point for further validation in larger patient cohorts using both immunological approaches and technologies utilizing more classical proteomics tools.

Sox10 Has a Broad Expression Pattern in Gliomas and Enhances Platelet-Derived Growth Factor-B–Induced Gliomagenesis

In a previously published insertional mutagenesis screen for candidate brain tumor genes in the mouse using a Moloney mouse leukemia virus encoding platelet-derived growth factor (PDGF)-B, the Sox10 gene was tagged in five independent tumors. The proviral integrations suggest an enhancer effect on Sox10. All Moloney murine leukemia virus/PDGFB tumors had a high protein expression of Sox10 independently of malignant grade or tumor type. To investigate the role of Sox10 in gliomagenesis, we used the RCAS/tv-a mouse model in which the expression of retroviral-encoded genes can be directed to glial progenitor cells (Ntv-a mice). Both Ntv-a transgenic mice, wild-type, and Ntv-a p19Arf null mice were injected with RCAS-SOX10 alone or in combination with RCAS-PDGFB. Infection with RCAS-SOX10 alone did not induce any gliomas. Combined infection of RCAS-SOX10 and RCAS-PDGFB in wild-type Ntv-a mice yielded a tumor frequency of 12%, and in Ntv-a Arf-/- mice the tumor frequency was 30%. This indicates that Sox10 alone is not sufficient to induce gliomagenesis but acts synergistically with PDGFB in glioma development. All induced tumors displayed characteristics of PNET-like structures and oligodendroglioma. The tumors had a strong and widely distributed expression of Sox10 and PDGFR-alpha. We investigated the expression of Sox10 in other human tumors and in a number of gliomas. The Sox10 expression was restricted to gliomas and melanomas. All glioma types expressed Sox10, and tumors of low-grade glioma had a much broader distribution of Sox10 compared with high-grade gliomas.