SurfaceGenie: a web-based application for prioritizing cell-type-specific marker candidates

MOTIVATION Cell-type specific surface proteins can be exploited as valuable markers for a range of applications including immunophenotyping live cells, targeted drug delivery, and in vivo imaging. Despite their utility and relevance, the unique combination of molecules present at the cell surface are not yet described for most cell types. A significant challenge in analyzing 'omic' discovery datasets is the selection of candidate markers that are most applicable for downstream applications. RESULTS Here, we developed GenieScore, a prioritization metric that integrates a consensus-based prediction of cell surface localization with user-input data to rank-order candidate cell-type specific surface markers. In this report, we demonstrate the utility of GenieScore for analyzing human and rodent data from proteomic and transcriptomic experiments in the areas of cancer, stem cell, and islet biology. We also demonstrate that permutations of GenieScore, termed IsoGenieScore and OmniGenieScore, can efficiently prioritize co-expressed and intracellular cell-type specific markers, respectively. AVAILABILITY Calculation of GenieScores and lookup of SPC scores is made freely accessible via the SurfaceGenie web-application: www.cellsurfer.net/surfacegenie. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

[1]  F. Ashcroft,et al.  Pancreatic β-Cell Electrical Activity and Insulin Secretion: Of Mice and Men. , 2018, Physiological reviews.

[2]  F. Russo,et al.  Polyamine biosynthesis in relation to K‐ras and p‐53 mutations in colorectal carcinoma , 2004, Scandinavian journal of gastroenterology.

[3]  A Habr-Gama,et al.  Bioinformatics construction of the human cell surfaceome , 2009, Proceedings of the National Academy of Sciences.

[4]  R. Gundry,et al.  SP2: Rapid and Automatable Contaminant Removal from Peptide Samples for Proteomic Analyses. , 2019, Journal of proteome research.

[5]  William Stafford Noble,et al.  Calibration Using a Single-Point External Reference Material Harmonizes Quantitative Mass Spectrometry Proteomics Data between Platforms and Laboratories. , 2018, Analytical chemistry.

[6]  A. DeAngelis CEACAM1: A Link Between Insulin and Lipid Metabolism , 2008 .

[7]  M. Bantscheff,et al.  Monitoring Cell-surface N-Glycoproteome Dynamics by Quantitative Proteomics Reveals Mechanistic Insights into Macrophage Differentiation* , 2017, Molecular & Cellular Proteomics.

[8]  H. Meyerson,et al.  Juvenile myelomonocytic leukemia with prominent CD141+ myeloid dendritic cell differentiation. , 2017, Human pathology.

[9]  D. Mukhopadhyay,et al.  Genetic status of KRAS modulates the role of Neuropilin-1 in tumorigenesis , 2017, Scientific Reports.

[10]  I. Weissman,et al.  The Macrophage 'Do not eat me' signal, CD47, is a clinically validated cancer immunotherapy target. , 2019, Annals of oncology : official journal of the European Society for Medical Oncology.

[11]  Rebekah L. Gundry,et al.  Cell Surface Proteomics of N‐Linked Glycoproteins for Typing of Human Lymphocytes , 2017, Proteomics.

[12]  M. Ashburner,et al.  Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.

[13]  A. Carracedo,et al.  Oil for the cancer engine: The cross-talk between oncogenic signaling and polyamine metabolism , 2018, Science Advances.

[14]  Max A. Horlbeck,et al.  Targeting RAS-driven human cancer cells with antibodies to upregulated and essential cell-surface proteins , 2018, eLife.

[15]  Erik K. Malm,et al.  A Human Protein Atlas for Normal and Cancer Tissues Based on Antibody Proteomics* , 2005, Molecular & Cellular Proteomics.

[16]  M. J. Broekman,et al.  CD39 activity correlates with stage and inhibits platelet reactivity in chronic lymphocytic leukemia , 2007, Journal of Translational Medicine.

[17]  Xiao-Jie Yan,et al.  B-cell chronic lymphocytic leukemia cells express a surface membrane phenotype of activated, antigen-experienced B lymphocytes. , 2002, Blood.

[18]  Rebekah L. Gundry,et al.  A Cell Surfaceome Map for Immunophenotyping and Sorting Pluripotent Stem Cells* , 2012, Molecular & Cellular Proteomics.

[19]  Rebekah L. Gundry,et al.  A Human Pluripotent Stem Cell Surface N-Glycoproteome Resource Reveals Markers, Extracellular Epitopes, and Drug Targets , 2014, Stem cell reports.

[20]  Fabian J Theis,et al.  The Human Cell Atlas , 2017, bioRxiv.

[21]  Jinn Shiun Chen,et al.  Secreted Heat Shock Protein 90α Induces Colorectal Cancer Cell Invasion through CD91/LRP-1 and NF-κB-mediated Integrin αV Expression* , 2010, The Journal of Biological Chemistry.

[22]  Hanspeter Pfister,et al.  UpSet: Visualization of Intersecting Sets , 2014, IEEE Transactions on Visualization and Computer Graphics.

[23]  Marc Chadeau-Hyam,et al.  Comparison of statistical methods and the use of quality control samples for batch effect correction in human transcriptome data , 2018, PloS one.

[24]  T. Ohtsuka,et al.  CD166/ALCAM Expression Is Characteristic of Tumorigenicity and Invasive and Migratory Activities of Pancreatic Cancer Cells , 2014, PloS one.

[25]  Michael J. MacCoss,et al.  Platform-independent and Label-free Quantitation of Proteomic Data Using MS1 Extracted Ion Chromatograms in Skyline , 2012, Molecular & Cellular Proteomics.

[26]  R. Gundry,et al.  Mapping the Cell-Surface N-Glycoproteome of Human Hepatocytes Reveals Markers for Selecting a Homogeneous Population of iPSC-Derived Hepatocytes , 2016, Stem cell reports.

[27]  M. Larrayoz,et al.  Proteomics Profiling of CLL Versus Healthy B-cells Identifies Putative Therapeutic Targets and a Subtype-independent Signature of Spliceosome Dysregulation* , 2018, Molecular & Cellular Proteomics.

[28]  Ruedi Aebersold,et al.  A Mass Spectrometric-Derived Cell Surface Protein Atlas , 2015, PloS one.

[29]  L. Gatto,et al.  A draft map of the mouse pluripotent stem cell spatial proteome , 2016, Nature Communications.

[30]  F. Song,et al.  Roles of low-density lipoprotein receptor-related protein 1 in tumors , 2016, Chinese journal of cancer.

[31]  Ruedi Aebersold,et al.  Mass-spectrometric identification and relative quantification of N-linked cell surface glycoproteins , 2009, Nature Biotechnology.

[32]  R. Kulkarni,et al.  Carcinoembryonic Antigen-Related Cell Adhesion Molecule 1 , 2008, Diabetes.

[33]  J. George,et al.  Single-cell transcriptomes identify human islet cell signatures and reveal cell-type–specific expression changes in type 2 diabetes , 2017, Genome research.

[34]  C. Donaldson,et al.  The transcriptional landscape of mouse beta cells compared to human beta cells reveals notable species differences in long non-coding RNA and protein-coding gene expression , 2014, BMC Genomics.

[35]  M. Reth,et al.  Continuous signaling of CD79b and CD19 is required for the fitness of Burkitt lymphoma B cells , 2018, The EMBO journal.

[36]  R. Gundry,et al.  N‐glycoprotein surfaceome of human induced pluripotent stem cell derived hepatic endoderm , 2017, Proteomics.

[37]  J. Licinio,et al.  Modulation of pancreatic islets-stress axis by hypothalamic releasing hormones and 11β-hydroxysteroid dehydrogenase , 2011, Proceedings of the National Academy of Sciences.

[38]  P. Engel,et al.  Towards a comprehensive human cell-surface immunome database. , 2011, Immunology letters.

[39]  Olga T. Schubert,et al.  The in silico human surfaceome , 2018, Proceedings of the National Academy of Sciences.

[40]  Søren Brunak,et al.  Non-classical protein secretion in bacteria , 2005, BMC Microbiology.

[41]  Alexander Lex,et al.  UpSetR: an R package for the visualization of intersecting sets and their properties , 2017, bioRxiv.

[42]  James C. Hu,et al.  The Gene Ontology Resource: 20 years and still GOing strong , 2019 .

[43]  G. Mazzucchelli,et al.  Novel comprehensive approach for accessible biomarker identification and absolute quantification from precious human tissues. , 2011, Journal of proteome research.

[44]  Sally M. Harrison,et al.  Exploring the surfaceome of Ewing sarcoma identifies a new and unique therapeutic target , 2016, Proceedings of the National Academy of Sciences.