Interferon‐induced transmembrane proteins (IFITMs) are frequently overexpressed in cancer cells, including cervical carcinoma cells, and play a role in the progression of various cancer types. However, their mechanisms of action remain incompletely understood. In the present study, by employing a combination of surface membrane protein isolation and quantitative mass spectrometry, it was comprehensively described how the IFITM1 protein influences the composition of the cervical cancer cell surfaceome. Additionally, the effects of interferon‐γ on protein expression and cell surface exposure were evaluated in the presence and absence of IFITM1. The IFITM1‐regulated membrane and membrane‐associated proteins identified are involved mainly in processes such as endocytosis and lysosomal transport, cell‐cell and cell‐extracellular matrix adhesion, antigen presentation and the immune response. To complement the proteomic data, gene expression was analyzed using reverse transcription‐quantitative PCR to distinguish whether the observed changes in protein levels were attributable to transcriptional regulation or differential protein dynamics. Furthermore, the proteomic and gene expression data are supported by functional studies demonstrating the impact of the IFITM1 and IFITM3 proteins on the adhesive, migratory and invasive capabilities of cervical cancer cells, as well as their interactions with immune cells.

• MeSH
• Cell Adhesion MeSH
• Antigens, Differentiation * metabolism   genetics   MeSH
• Phenotype MeSH
• Interferon-gamma pharmacology   metabolism   MeSH
• Humans MeSH
• Membrane Proteins * metabolism   genetics   MeSH
• Cell Line, Tumor MeSH
• Uterine Cervical Neoplasms * pathology   genetics   metabolism   immunology   MeSH
• Cell Movement MeSH
• RNA-Binding Proteins * metabolism   genetics   MeSH
• Proteome * MeSH
• Proteomics methods   MeSH
• Gene Expression Regulation, Neoplastic MeSH
• Check Tag
• Humans MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

The epithelial-mesenchymal plasticity, in tight association with stemness, contributes to the mammary gland homeostasis, evolution of early neoplastic lesions and cancer dissemination. Focused on cell surfaceome, we used mouse models of pre-neoplastic mammary epithelial and cancer stem cells to reveal the connection between cell surface markers and distinct cell phenotypes. We mechanistically dissected the TGF-β family-driven regulation of Sca-1, one of the most commonly used adult stem cell markers. We further provided evidence that TGF-β disrupts the lineage commitment and promotes the accumulation of tumor-initiating cells in pre-neoplastic cells.

• MeSH
• Ataxin-1 metabolism   MeSH
• Epithelial-Mesenchymal Transition genetics   MeSH
• Epithelial Cells pathology   MeSH
• Mammary Neoplasms, Experimental genetics   pathology   MeSH
• Humans MeSH
• Mammary Glands, Animal pathology   MeSH
• Mice MeSH
• Cell Line, Tumor transplantation   MeSH
• Neoplastic Stem Cells pathology   MeSH
• Breast Neoplasms genetics   pathology   MeSH
• Cell Plasticity genetics   MeSH
• Receptor, ErbB-2 genetics   MeSH
• Gene Expression Regulation, Neoplastic MeSH
• Recombinant Proteins genetics   metabolism   MeSH
• Signal Transduction genetics   MeSH
• Transforming Growth Factor beta genetics   metabolism   MeSH
• Animals MeSH
• Check Tag
• Humans MeSH
• Mice MeSH
• Female MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

Biological treatment of many cancers currently targets membrane bound receptors located on a cell surface. To identify novel membrane proteins associated with migration and metastasis of breast cancer cells, a more migrating subpopulation of MDA-MB-231 breast cancer cell line is selected and characterized. A high-resolution quantitative mass spectrometry with SILAC labeling is applied to analyze their surfaceome and it is compared with that of parental MDA-MB-231 cells. Among 824 identified proteins (FDR < 0.01), 128 differentially abundant cell surface proteins with at least one transmembrane domain are found. Of these, i) desmocollin-1 (DSC1) is validated as a protein connected with lymph node status of luminal A breast cancer, tumor grade, and Her-2 status by immunohistochemistry in the set of 96 primary breast tumors, and ii) catechol-O-methyltransferase is successfully verified as a protein associated with lymph node metastasis of triple negative breast cancer as well as with tumor grade by targeted data extraction from the SWATH-MS data of the same set of tissues. The findings indicate importance of both proteins for breast cancer development and metastasis and highlight the potential of biomarker validation strategy via targeted data extraction from SWATH-MS datasets.

• MeSH
• Survival Analysis MeSH
• Cell Membrane metabolism   MeSH
• Desmocollins genetics   metabolism   MeSH
• Phenotype MeSH
• Neoplasm Invasiveness MeSH
• Catechol O-Methyltransferase genetics   metabolism   MeSH
• Humans MeSH
• Lymphatic Metastasis pathology   MeSH
• Cell Line, Tumor MeSH
• Breast Neoplasms genetics   metabolism   pathology   MeSH
• Cell Movement * genetics   MeSH
• Proteomics * MeSH
• Receptor, ErbB-2 MeSH
• Gene Expression Regulation, Neoplastic MeSH
• Triple Negative Breast Neoplasms genetics   metabolism   pathology   MeSH
• Up-Regulation genetics   MeSH
• Check Tag
• Humans MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

CD molecules are surface molecules expressed on cells of the immune system that play key roles in immune cell-cell communication and sensing the microenvironment. These molecules are essential markers for the identification and isolation of leukocytes and lymphocyte subsets. Here, we present the results of the first phase of the CD Maps study, mapping the expression of CD1-CD100 (n = 110) on 47 immune cell subsets from blood, thymus, and tonsil using an eight-color standardized EuroFlow approach and quantification of expression. The resulting dataset included median antibody binding capacities (ABCs) and percentage of positivity for all markers on all subsets and was developed into an interactive CD Maps web resource. Using the resource, we examined differentially expressed proteins between granulocyte, monocyte, and dendritic cell subsets, and profiled dynamic expression of markers during thymocyte differentiation, T-cell maturation, and between functionally distinct B-cell subset clusters. The CD Maps resource will serve as a benchmark of antibody reactivities ensuring improved reproducibility of flow cytometry-based research. Moreover, it will provide a full picture of the surfaceome of human immune cells and serves as a useful platform to increase our understanding of leukocyte biology, as well as to facilitate the identification of new biomarkers and therapeutic targets of immunological and hematological diseases.

• MeSH
• B-Lymphocytes immunology   metabolism   MeSH
• Antigens, CD biosynthesis   MeSH
• Datasets as Topic MeSH
• Dendritic Cells immunology   metabolism   MeSH
• Child MeSH
• Adult MeSH
• Granulocytes immunology   metabolism   MeSH
• Immunophenotyping MeSH
• Internet MeSH
• Leukocytes immunology   metabolism   MeSH
• Humans MeSH
• Lymphopoiesis MeSH
• Monocytes immunology   metabolism   MeSH
• Peptide Mapping MeSH
• Lymphocyte Subsets immunology   metabolism   MeSH
• Child, Preschool MeSH
• Flow Cytometry MeSH
• Reproducibility of Results MeSH
• Cell Separation MeSH
• T-Lymphocytes immunology   metabolism   MeSH
• Check Tag
• Child MeSH
• Adult MeSH
• Humans MeSH
• Child, Preschool MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

UNLABELLED: Pluripotent stem cell-derived committed neural precursors are an important source of cells to treat neurodegenerative diseases including spinal cord injury. There remains an urgency to identify markers for monitoring of neural progenitor specificity, estimation of neural fate and follow-up correlation with therapeutic effect in preclinical studies using animal disease models. Cell surface capture technology was used to uncover the cell surface exposed N-glycoproteome of neural precursor cells upon neuronal differentiation as well as post-mitotic mature hNT neurons. The data presented depict an extensive study of surfaceome during neuronal differentiation, confirming glycosylation at a particular predicted site of many of the identified proteins. Quantitative changes detected in cell surface protein levels reveal a set of proteins that highlight the complexity of the neuronal differentiation process. Several of these proteins including the cell adhesion molecules ICAM1, CHL1, and astrotactin1 as well as LAMP1 were validated by SRM. Combination of immunofluorescence staining of ICAM1 and flow cytometry indicated a possible direction for future scrutiny of such proteins as targets for enrichment of the neuronal subpopulation from mixed cultures after differentiation of neural precursor cells. These surface proteins hold an important key for development of safe strategies in cell-replacement therapies of neuronal disorders. BIOLOGICAL SIGNIFICANCE: Neural stem and/or precursor cells have a great potential for cell-replacement therapies of neuronal diseases. Availability of well characterised and expandable neural cell lineage specific populations is critical for addressing such a challenge. In our study we identified and relatively quantified several hundred surface N-glycoproteins in the course of neuronal differentiation. We further confirmed the abundant changes for several cell adhesion proteins by SRM and outlined a strategy for utilisation of such N-glycoproteins in antibody based cell sorting. The comprehensive dataset presented here demonstrates the molecular background of neuronal differentiation highly useful for development of new plasma membrane markers to identify and select neuronal subpopulation from mixed neural cell cultures.

• MeSH
• Cell Differentiation physiology   MeSH
• Cell Line MeSH
• Cells, Cultured MeSH
• Humans MeSH
• Membrane Glycoproteins metabolism   MeSH
• Neural Stem Cells cytology   metabolism   MeSH
• Nerve Tissue Proteins metabolism   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

Cell surface proteins are major targets of biomedical research due to their utility as cellular markers and their extracellular accessibility for pharmacological intervention. However, information about the cell surface protein repertoire (the surfaceome) of individual cells is only sparsely available. Here, we applied the Cell Surface Capture (CSC) technology to 41 human and 31 mouse cell types to generate a mass-spectrometry derived Cell Surface Protein Atlas (CSPA) providing cellular surfaceome snapshots at high resolution. The CSPA is presented in form of an easy-to-navigate interactive database, a downloadable data matrix and with tools for targeted surfaceome rediscovery (http://wlab.ethz.ch/cspa). The cellular surfaceome snapshots of different cell types, including cancer cells, resulted in a combined dataset of 1492 human and 1296 mouse cell surface glycoproteins, providing experimental evidence for their cell surface expression on different cell types, including 136 G-protein coupled receptors and 75 membrane receptor tyrosine-protein kinases. Integrated analysis of the CSPA reveals that the concerted biological function of individual cell types is mainly guided by quantitative rather than qualitative surfaceome differences. The CSPA will be useful for the evaluation of drug targets, for the improved classification of cell types and for a better understanding of the surfaceome and its concerted biological functions in complex signaling microenvironments.

• MeSH
• Cell Line MeSH
• Databases, Protein MeSH
• Mass Spectrometry methods   MeSH
• Humans MeSH
• Membrane Proteins chemistry   MeSH
• Mice MeSH
• Proteomics methods   MeSH
• Animals MeSH
• Check Tag
• Humans MeSH
• Mice MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Research Support, N.I.H., Extramural MeSH

A better description of the leukemia cell surface proteome (surfaceome) is a prerequisite for the development of diagnostic and therapeutic tools. Insights into the complexity of the surfaceome have been limited by the lack of suitable methodologies. We combined a leukemia xenograft model with the discovery-driven chemoproteomic Cell Surface Capture technology to explore the B-cell precursor acute lymphoblastic leukemia (BCP-ALL) surfaceome; 713 cell surface proteins, including 181 CD proteins, were detected through combined analysis of 19 BCP-ALL cases. Diagnostic immunophenotypes were recapitulated in each case, and subtype specific markers were detected. To identify new leukemia-associated markers, we filtered the surfaceome data set against gene expression information from sorted, normal hematopoietic cells. Nine candidate markers (CD18, CD63, CD31, CD97, CD102, CD157, CD217, CD305, and CD317) were validated by flow cytometry in patient samples at diagnosis and during chemotherapy. CD97, CD157, CD63, and CD305 accounted for the most informative differences between normal and malignant cells. The ALL surfaceome constitutes a valuable resource to assist the functional exploration of surface markers in normal and malignant lymphopoiesis. This unbiased approach will also contribute to the development of strategies that rely on complex information for multidimensional flow cytometry data analysis to improve its diagnostic applications.

• MeSH
• Precursor Cell Lymphoblastic Leukemia-Lymphoma immunology   metabolism   MeSH
• Antigens, CD analysis   MeSH
• Immunophenotyping MeSH
• Humans MeSH
• Membrane Proteins * analysis   metabolism   MeSH
• Mice MeSH
• Biomarkers, Tumor * analysis   MeSH
• Proteome * analysis   metabolism   MeSH
• Flow Cytometry MeSH
• Xenograft Model Antitumor Assays MeSH
• Animals MeSH
• Check Tag
• Humans MeSH
• Mice MeSH
• Animals MeSH