Creation of an antibody-based subcellular protein atlas

Subcellular proteomics

The eukaryotic cell is compartmentalized into subcellular niches, including membrane-bound and membrane-less organelles. Proteins localize to these niches to fulfil their function, enabling discreet biological processes to occur in synchrony. Dynamic movement of proteins between niches is essential for cellular processes such as signalling, growth, proliferation, motility and programmed cell death, and mutations causing aberrant protein localization are associated with a wide range of diseases. Determining the location of proteins in different cell states and cell types and how proteins relocalize following perturbation is important for understanding their functions, related cellular processes and pathologies associated with their mislocalization. In this Primer, we cover the major spatial proteomics methods for determining the location, distribution and abundance of proteins within subcellular structures. These technologies include fluorescent imaging, protein proximity labelling, organelle purification and cell-wide biochemical fractionation. We describe their workflows, data outputs and applications in exploring different cell biological scenarios, and discuss their main limitations. Finally, we describe emerging technologies and identify areas that require technological innovation to allow better characterization of the spatial proteome.

Imaging the future: the emerging era of single-cell spatial proteomics

The proteome of a human cell is partitioned within organelles, such as the nucleus, and other subcellular compartments, such as the cytoplasm, forming a myriad of membrane-bound and membrane-free ultrastructures. This compartmentalization allows discrete biochemical processes to occur efficiently in isolation, with relevant proteins localized to appropriate niches to fulfill their biological function(s). Proper delivery and dynamic exchange of proteins between compartments underlie the regulation of many cellular processes, such as cell signaling, division, and programmed cell death. To this end, cells deploy dedicated trafficking mechanisms to ensure correct protein localization, as mis-localization can result in pathology. In addition to trafficking, variation in the expression, modification, and physical associations of proteins within and between cells can result in biological heterogeneity, motivating the need for single-cell measurements. In this review, we introduce diverse platform technologies developed for subcellular proteomics and high-throughput systems biology, with the aim of providing mechanistic insights into fundamental cell biological processes underlying healthy and diseased states, and valuable public data resources. In contrast to the rapidly advancing field of single-cell genomics, the single-cell spatial proteomics toolbox remains in its infancy, but is poised to make considerable advances in the coming years.

Loss of ER retention motif of AGR2 can impact mTORC signaling and promote cancer metastasis

Anterior gradient 2 (AGR2) is a member of the protein disulfide isomerase (PDI) family, which plays a role in the regulation of protein homeostasis and the unfolded protein response pathway (UPR). AGR2 has also been characterized as a proto-oncogene and a potential cancer biomarker. Cellular localization of AGR2 is emerging as a key component for understanding the role of AGR2 as a proto-oncogene. Here, we provide evidence that extracellular AGR2 (eAGR2) promotes tumor metastasis in various in vivo models. To further characterize the role of the intracellular-resident versus extracellular protein, we performed a comprehensive protein-protein interaction screen. Based on these results, we identify AGR2 as an interacting partner of the mTORC2 pathway. Importantly, our data indicates that eAGR2 promotes increased phosphorylation of RICTOR (T1135), while intracellular AGR2 (iAGR2) antagonizes its levels and phosphorylation. Localization of AGR2 also has opposing effects on the Hippo pathway, spheroid formation, and response to chemotherapy in vitro. Collectively, our results identify disparate phenotypes predicated on AGR2 localization. Our findings also provide credence for screening of eAGR2 to guide therapeutic decisions.

Progress on the HUPO Draft Human Proteome: 2017 Metrics of the Human Proteome Project

The Human Proteome Organization (HUPO) Human Proteome Project (HPP) continues to make progress on its two overall goals: (1) completing the protein parts list, with an annual update of the HUPO draft human proteome, and (2) making proteomics an integrated complement to genomics and transcriptomics throughout biomedical and life sciences research. neXtProt version 2017-01-23 has 17 008 confident protein identifications (Protein Existence [PE] level 1) that are compliant with the HPP Guidelines v2.1 ( https://hupo.org/Guidelines ), up from 13 664 in 2012-12 and 16 518 in 2016-04. Remaining to be found by mass spectrometry and other methods are 2579 "missing proteins" (PE2+3+4), down from 2949 in 2016. PeptideAtlas 2017-01 has 15 173 canonical proteins, accounting for nearly all of the 15 290 PE1 proteins based on MS data. These resources have extensive data on PTMs, single amino acid variants, and splice isoforms. The Human Protein Atlas v16 has 10 492 highly curated protein entries with tissue and subcellular spatial localization of proteins and transcript expression. Organ-specific popular protein lists have been generated for broad use in quantitative targeted proteomics using SRM-MS or DIA-SWATH-MS studies of biology and disease.

An Approach to Spatiotemporally Resolve Protein Interaction Networks in Living Cells

Cells operate through protein interaction networks organized in space and time. Here, we describe an approach to resolve both dimensions simultaneously by using proximity labeling mediated by engineered ascorbic acid peroxidase (APEX). APEX has been used to capture entire organelle proteomes with high temporal resolution, but its breadth of labeling is generally thought to preclude the higher spatial resolution necessary to interrogate specific protein networks. We provide a solution to this problem by combining quantitative proteomics with a system of spatial references. As proof of principle, we apply this approach to interrogate proteins engaged by G-protein-coupled receptors as they dynamically signal and traffic in response to ligand-induced activation. The method resolves known binding partners, as well as previously unidentified network components. Validating its utility as a discovery pipeline, we establish that two of these proteins promote ubiquitin-linked receptor downregulation after prolonged activation.

Gene-specific correlation of RNA and protein levels in human cells and tissues

An important issue for molecular biology is to establish whether transcript levels of a given gene can be used as proxies for the corresponding protein levels. Here, we have developed a targeted proteomics approach for a set of human non-secreted proteins based on parallel reaction monitoring to measure, at steady-state conditions, absolute protein copy numbers across human tissues and cell lines and compared these levels with the corresponding mRNA levels using transcriptomics. The study shows that the transcript and protein levels do not correlate well unless a gene-specific RNA-to-protein (RTP) conversion factor independent of the tissue type is introduced, thus significantly enhancing the predictability of protein copy numbers from RNA levels. The results show that the RTP ratio varies significantly with a few hundred copies per mRNA molecule for some genes to several hundred thousands of protein copies per mRNA molecule for others. In conclusion, our data suggest that transcriptome analysis can be used as a tool to predict the protein copy numbers per cell, thus forming an attractive link between the field of genomics and proteomics.

Integrin signalling regulates YAP and TAZ to control skin homeostasis

The skin is a squamous epithelium that is continuously renewed by a population of basal layer stem/progenitor cells and can heal wounds. Here, we show that the transcription regulators YAP and TAZ localise to the nucleus in the basal layer of skin and are elevated upon wound healing. Skin-specific deletion of both YAP and TAZ in adult mice slows proliferation of basal layer cells, leads to hair loss and impairs regeneration after wounding. Contact with the basal extracellular matrix and consequent integrin-Src signalling is a key determinant of the nuclear localisation of YAP/TAZ in basal layer cells and in skin tumours. Contact with the basement membrane is lost in differentiating daughter cells, where YAP and TAZ become mostly cytoplasmic. In other types of squamous epithelia and squamous cell carcinomas, a similar control mechanism is present. By contrast, columnar epithelia differentiate an apical domain that recruits CRB3, Merlin (also known as NF2), KIBRA (also known as WWC1) and SAV1 to induce Hippo signalling and retain YAP/TAZ in the cytoplasm despite contact with the basal layer extracellular matrix. When columnar epithelial tumours lose their apical domain and become invasive, YAP/TAZ becomes nuclear and tumour growth becomes sensitive to the Src inhibitor Dasatinib.

Development of a highly automated and multiplexed targeted proteome pipeline and assay for 112 rat brain synaptic proteins

We present a comprehensive workflow for large scale (>1000 transitions/run) label-free LC-MRM proteome assays. Innovations include automated MRM transition selection, intelligent retention time scheduling that improves S/N by twofold, and automatic peak modeling. Improvements to data analysis include a novel Q/C metric, normalized group area ratio, MLR normalization, weighted regression analysis, and data dissemination through the Yale protein expression database. As a proof of principle we developed a robust 90 min LC-MRM assay for mouse/rat postsynaptic density fractions which resulted in the routine quantification of 337 peptides from 112 proteins based on 15 observations per protein. Parallel analyses with stable isotope dilution peptide standards (SIS), demonstrate very high correlation in retention time (1.0) and protein fold change (0.94) between the label-free and SIS analyses. Overall, our method achieved a technical CV of 11.4% with >97.5% of the 1697 transitions being quantified without user intervention, resulting in a highly efficient, robust, and single injection LC-MRM assay.

Proteomics reveals the importance of the dynamic redistribution of the subcellular location of proteins in breast cancer cells

At the molecular level, living cells are enormously complicated complex adaptive systems in which intertwined genomic, transcriptomic, proteomic and metabolic networks all play a crucial role. At the same time, cells are spatially heterogeneous systems in which subcellular compartmentalization of different functions is ubiquitous and requires efficient cross-compartmental communication. Dynamic redistribution of multitudinous proteins to different subcellular locations in response to cellular functional state is increasingly recognized as a crucial characteristic of cellular function that seems to be at least as important as overall changes in protein abundance. Characterization of the subcellular spatial dynamics of protein distribution is a major challenge for proteomics and recent results with MCF7 breast cancer cells suggest that this may be of particular importance for cancer cells.

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.

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.

Analysis of candidate genes for lineage-specific expression changes in humans and primates

RUNX2, a gene involved in skeletal development, has previously been shown to be potentially affected by positive selection during recent human evolution. Here we have used antibody-based proteomics to characterize potential differences in expression patterns of RUNX2 interacting partners during primate evolution. Tissue microarrays consisting of a large set of normal tissues from human and macaque were used for protein profiling of 50 RUNX2 partners with immunohistochemistry. Eleven proteins (AR, CREBBP, EP300, FGF2, HDAC3, JUN, PRKD3, RUNX1, SATB2, TCF3, and YAP1) showed differences in expression between humans and macaques. These proteins were further profiled in tissues from chimpanzee, gorilla, and orangutan, and the corresponding genes were analyzed with regard to genomic features. Moreover, protein expression data were compared with previously obtained RNA sequencing data from six different organs. One gene (TCF3) showed significant expression differences between human and macaque at both the protein and RNA level, with higher expression in a subset of germ cells in human testis compared with macaque. In conclusion, normal tissues from macaque and human showed differences in expression of some RUNX2 partners that could be mapped to various defined cell types. The applied strategy appears advantageous to characterize the consequences of altered genes selected during evolution.

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.

Plant cell wall proteomics: the leadership of Arabidopsis thaliana

Plant cell wall proteins (CWPs) progressively emerged as crucial components of cell walls although present in minor amounts. Cell wall polysaccharides such as pectins, hemicelluloses, and cellulose represent more than 90% of primary cell wall mass, whereas hemicelluloses, cellulose, and lignins are the main components of lignified secondary walls. All these polymers provide mechanical properties to cell walls, participate in cell shape and prevent water loss in aerial organs. However, cell walls need to be modified and customized during plant development and in response to environmental cues, thus contributing to plant adaptation. CWPs play essential roles in all these physiological processes and particularly in the dynamics of cell walls, which requires organization and rearrangements of polysaccharides as well as cell-to-cell communication. In the last 10 years, plant cell wall proteomics has greatly contributed to a wider knowledge of CWPs. This update will deal with (i) a survey of plant cell wall proteomics studies with a focus on Arabidopsis thaliana; (ii) the main protein families identified and the still missing peptides; (iii) the persistent issue of the non-canonical CWPs; (iv) the present challenges to overcome technological bottlenecks; and (v) the perspectives beyond cell wall proteomics to understand CWP functions.

Genome-scale modeling of human metabolism - a systems biology approach

Altered metabolism is linked to the appearance of various human diseases and a better understanding of disease-associated metabolic changes may lead to the identification of novel prognostic biomarkers and the development of new therapies. Genome-scale metabolic models (GEMs) have been employed for studying human metabolism in a systematic manner, as well as for understanding complex human diseases. In the past decade, such metabolic models - one of the fundamental aspects of systems biology - have started contributing to the understanding of the mechanistic relationship between genotype and phenotype. In this review, we focus on the construction of the Human Metabolic Reaction database, the generation of healthy cell type- and cancer-specific GEMs using different procedures, and the potential applications of these developments in the study of human metabolism and in the identification of metabolic changes associated with various disorders. We further examine how in silico genome-scale reconstructions can be employed to simulate metabolic flux distributions and how high-throughput omics data can be analyzed in a context-dependent fashion. Insights yielded from this mechanistic modeling approach can be used for identifying new therapeutic agents and drug targets as well as for the discovery of novel biomarkers. Finally, recent advancements in genome-scale modeling and the future challenge of developing a model of whole-body metabolism are presented. The emergent contribution of GEMs to personalized and translational medicine is also discussed.

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 ).

The promiscuous binding of pharmaceutical drugs and their transporter-mediated uptake into cells: what we (need to) know and how we can do so

A recent paper in this journal sought to counter evidence for the role of transport proteins in effecting drug uptake into cells, and questions that transporters can recognize drug molecules in addition to their endogenous substrates. However, there is abundant evidence that both drugs and proteins are highly promiscuous. Most proteins bind to many drugs and most drugs bind to multiple proteins (on average more than six), including transporters (mutations in these can determine resistance); most drugs are known to recognise at least one transporter. In this response, we alert readers to the relevant evidence that exists or is required. This needs to be acquired in cells that contain the relevant proteins, and we highlight an experimental system for simultaneous genome-wide assessment of carrier-mediated uptake in a eukaryotic cell (yeast).

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.

Systems medicine and metabolic modelling

Several complex diseases are caused by the malfunction of human metabolism, and deciphering the underlying molecular mechanisms can elucidate their aetiology. Systems biology is an integrative approach combining experimental and computational biology to identify and describe the molecular mechanisms of complex biological systems. Systems medicine has the potential to elucidate the onset and progression of complex metabolic diseases through the use of computational approaches. Advances in biotechnology have resulted in the provision of high-throughput data, which provide information about different metabolic processes. The systems medicine approach can utilize such data to reconstruct genome-scale metabolic models that can be used to study the function of specific enzymes and pathways in the context of the complete metabolic network. In this review, we outline the importance of genome-scale models in systems medicine and discuss how they may contribute towards the development of personalized medicine.

An integrated chip for immunofluorescence and its application to analyze lysosomal storage disorders

Immunofluorescence (IF) is a common method to observe protein distribution and localization at the single-cell level through wide-field fluorescence or confocal microscopy. Conventional protocol for IF staining of cells typically requires a large amount of reagents, especially antibodies, and noticeable investment in both labor and time. Microfluidic technologies provide a cost-effective alternative: it can evaluate and optimize experimental conditions, and perform automatic and high-throughput IF staining on-chip. We employed this method to analyze lysosomal storage disorders (LSDs) based on the expression and morphological distribution of LAMP1 and LC3 in starving cells. With pneumatic valves integrated on-chip, the parallel staining process can be completed within a few hours. The total consumption of each antibody solution for the whole experiment is merely 0.3 μL. This device provides a promising tool for automated high-throughput molecular imaging at cell level that can be applied for diagnostic analysis.

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.

A Protein Epitope Signature Tag (PrEST) library allows SILAC-based absolute quantification and multiplexed determination of protein copy numbers in cell lines

Mass spectrometry-based proteomics increasingly relies on relative or absolute quantification. In relative quantification, stable isotope based methods often allow mixing at early stages of sample preparation, whereas for absolute quantification this has generally required recombinant expression of full length, labeled protein standards. Here we make use of a very large library of Protein Epitope Signature Tags (PrESTs) that has been developed in the course of the Human Protein Atlas Project. These PrESTs are expressed recombinantly in E. coli and they consist of a short and unique region of the protein of interest as well as purification and solubility tags. We first quantify a highly purified, stable isotope labeling of amino acids in cell culture (SILAC)-labeled version of the solubility tag and use it determine the precise amount of each PrEST by its SILAC ratios. The PrESTs are then spiked into cell lysates and the SILAC ratios of PrEST peptides to peptides from endogenous target proteins yield their cellular quantities. The procedure can readily be multiplexed, as we demonstrate by simultaneously determining the copy number of 40 proteins in HeLa cells. Among the proteins analyzed, the cytoskeletal protein vimentin was found to be most abundant with 20 million copies per cell, while the transcription factor and oncogene FOS only had 6000 copies. Direct quantification of the absolute amount of single proteins is possible via a SILAC experiment in which labeled cell lysate is mixed both with the heavy labeled solubility tag and with the corresponding PrEST. The SILAC-PrEST combination allows accurate and streamlined quantification of the absolute or relative amount of proteins of interest in a wide variety of applications.

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.

Global expression study in colorectal cancer on proteins with alkaline isoelectric point by two-dimensional difference gel electrophoresis

Colorectal cancer is one of the leading causes of cancer death worldwide. To identify candidates for biomarkers and therapeutic targets, we investigated the proteome of colorectal cancer tissues. Using 2D-DIGE in combination with our original large format electrophoresis apparatus, we compared surgically resected normal and tumor tissues from 53 patients with colorectal cancer. We focused on proteins with an alkaline pI using IPG gels for the alkaline range. We observed 1687 protein spots, and found 100 spots with statistical (p<0.01) and significant (>2-fold) differences between the normal and the tumor tissue groups. Among these 100 protein spots, five showed a different intensity between tumor tissues from the stage-II and the stage-III patients. MS experiments revealed that these 100 protein spots corresponded to 58 unique proteins. These included six proteins which had not been previously reported to be associated with colorectal cancer. Among these proteins, five were not reported in any type of malignancy. IEF/western blotting confirmed the differences in protein expression between the normal and the tumor tissues. These results may provide an insight for biomarker development and drug target discovery in colorectal cancer.