Resolving the molecular details of proteome variation in the different tissues and organs of the human body will greatly increase our knowledge of human biology and disease. Here, we present a map of the human tissue proteome based on an integrated omics approach that involves quantitative transcriptomics at the tissue and organ level, combined with tissue microarray-based immunohistochemistry, to achieve spatial localization of proteins down to the single-cell level. Our tissue-based analysis detected more than 90% of the putative protein-coding genes. We used this approach to explore the human secretome, the membrane proteome, the druggable proteome, the cancer proteome, and the metabolic functions in 32 different tissues and organs. All the data are integrated in an interactive Web-based database that allows exploration of individual proteins, as well as navigation of global expression patterns, in all major tissues and organs in the human body.

Cancer is one of the leading causes of death, and there is great interest in understanding the underlying molecular mechanisms involved in the pathogenesis and progression of individual tumors. We used systems-level approaches to analyze the genome-wide transcriptome of the protein-coding genes of 17 major cancer types with respect to clinical outcome. A general pattern emerged: Shorter patient survival was associated with up-regulation of genes involved in cell growth and with down-regulation of genes involved in cellular differentiation. Using genome-scale metabolic models, we show that cancer patients have widespread metabolic heterogeneity, highlighting the need for precise and personalized medicine for cancer treatment. All data are presented in an interactive open-access database (www.proteinatlas.org/pathology) to allow genome-wide exploration of the impact of individual proteins on clinical outcomes.

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.

Abstract. Pontén F, Schwenk JM, Asplund A, Edqvist P-HD

The NUDIX enzymes are involved in cellular metabolism and homeostasis, as well as mRNA processing. Although highly conserved throughout all organisms, their biological roles and biochemical redundancies remain largely unclear. To address this, we globally resolve their individual properties and inter-relationships. We purify 18 of the human NUDIX proteins and screen 52 substrates, providing a substrate redundancy map. Using crystal structures, we generate sequence alignment analyses revealing four major structural classes. To a certain extent, their substrate preference redundancies correlate with structural classes, thus linking structure and activity relationships. To elucidate interdependence among the NUDIX hydrolases, we pairwise deplete them generating an epistatic interaction map, evaluate cell cycle perturbations upon knockdown in normal and cancer cells, and analyse their protein and mRNA expression in normal and cancer tissues. Using a novel FUSION algorithm, we integrate all data creating a comprehensive NUDIX enzyme profile map, which will prove fundamental to understanding their biological functionality.

Cell migration plays an important role during the development of the retina. In this work we have studied the migration of newborn horizontal cells in avian embryonic retina. Using the pattern of the early expressed transcription factors Lim1 and Prox1 we have shown that horizontal cells migrate bi-directionally from their site of birth, close to the ventricular side, to the adjacent (vitreal) side of the neuroepithelium, where they align just next to the prospective ganglion cell layer before migrating back again to their final laminar position in the external part of the inner nuclear layer. The migration occurs between Hamburger and Hamilton stages 24 and 33,which is equivalent to embryonic day 4.5 and 8. Between stages 26 and 30 the horizontal cells reside close to the ganglion cell layer and intra ocular injections of a cytochalasin D, an actin polymerisation blocker that inhibit migration, at stage 29 interfered with the migration of the horizontal cells to their final destination. Furthermore, using biolistic gene transfer with a green fluorescence protein expression vector of retinal slices we were able to record ventricle-directed migration by time-lapse microscopy. Combining biolistics with immunohistochemistry we showed that transfected cells, which have also been translocated in a ventricular direction were positive for the horizontal cell markers Lim1 and Prox1. The alternative path of migration that is described in this work differs from the generally accepted one for horizontal cells and this knowledge will influence the view of how the molecular determination of horizontal cells is specified.

Platelet-derived growth factor (PDGF) receptor signaling is a major functional determinant of cancerassociated fibroblasts (CAF). Elevated expression of PDGF receptors on stromal CAFs is associated with metastasis and poor prognosis, but mechanism(s) that underlie these connections are not understood. Here, we report the identification of the secreted glycoprotein stanniocalcin-1 (STC1) as a mediator of metastasis by PDGF receptor function in the setting of colorectal cancer. PDGF-stimulated fibroblasts increased migration and invasion of cocultured colorectal cancer cells in an STC1-dependent manner. Analyses of human colorectal cancers revealed significant associations between stromal PDGF receptor and STC1 expression. In an orthotopic mouse model of colorectal cancer, tumors formed in the presence of STC1-deficient fibroblasts displayed reduced intravasation of tumor cells along with fewer and smaller distant metastases formed. Our results reveal a mechanistic basis for understanding the contribution of PDGF-activated CAFs to cancer metastasis. Cancer Res; 73(4);

AimsIn 2010, four subtypes (classical, proneural, mesenchymal, and neural) of glioblastoma multiforme (GBM) were defined by molecular genetic analyses. The objective of this study was to assess whether gliomas, independently of the type and grade, could be subdivided into protein-based subtypes.Methods and resultsA tissue microarray (TMA) approach was applied to incorporate tissue samples of low-grade and high-grade gliomas into five TMAs. High expression levels of epidermal growth factor receptor (EGFR), CD44, c-MER proto-oncogene tyrosine kinase (MERTK), platelet-derived growth factor receptor α, p53, oligodendrocyte transcription factor 2 (OLIG2) and isocitrate dehydrogenase 1 with the R132H mutation were assessed using immunohistochemistry (IHC). Glioma could be subdivided into four subtypes by IHC. The majority of the low-grade gliomas were of the proneural subtype, i.e. high p53 expression (63% of grade II). The classical subtype, with high EGFR and low p53 expression, was most common in GBMs (39%), followed by the proneural (29%) and mesenchymal (with high CD44 and MERTK expression) (29%) subtypes, a frequency that is in line with previously published data based on molecular genetics.ConclusionsAssessment of the expression of the five proteins EGFR, CD44, MERTK, p53 and OLIG2 is sufficient for subtyping gliomas, and can be recommended for implementation in clinical practice for both low-grade and high-grade gliomas.