Cell surface profiling using high-throughput flow cytometry: a platform for biomarker discovery and analysis of cellular heterogeneity
Cell surface proteins have a wide range of biological functions, and are often used as lineage-specific markers. Antibodies that recognize cell surface antigens are widely used as research tools, diagnostic markers, and even therapeutic agents. The ability to obtain broad cell surface protein profil...
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| Veröffentlicht in: | PloS one 2014-08, Vol.9 (8), p.e105602-e105602 |
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| creator | Gedye, Craig A Hussain, Ali Paterson, Joshua Smrke, Alannah Saini, Harleen Sirskyj, Danylo Pereira, Keira Lobo, Nazleen Stewart, Jocelyn Go, Christopher Ho, Jenny Medrano, Mauricio Hyatt, Elzbieta Yuan, Julie Lauriault, Stevan Meyer, Mona Kondratyev, Maria van den Beucken, Twan Jewett, Michael Dirks, Peter Guidos, Cynthia J Danska, Jayne Wang, Jean Wouters, Bradly Neel, Benjamin Rottapel, Robert Ailles, Laurie E |
| description | Cell surface proteins have a wide range of biological functions, and are often used as lineage-specific markers. Antibodies that recognize cell surface antigens are widely used as research tools, diagnostic markers, and even therapeutic agents. The ability to obtain broad cell surface protein profiles would thus be of great value in a wide range of fields. There are however currently few available methods for high-throughput analysis of large numbers of cell surface proteins. We describe here a high-throughput flow cytometry (HT-FC) platform for rapid analysis of 363 cell surface antigens. Here we demonstrate that HT-FC provides reproducible results, and use the platform to identify cell surface antigens that are influenced by common cell preparation methods. We show that multiple populations within complex samples such as primary tumors can be simultaneously analyzed by co-staining of cells with lineage-specific antibodies, allowing unprecedented depth of analysis of heterogeneous cell populations. Furthermore, standard informatics methods can be used to visualize, cluster and downsample HT-FC data to reveal novel signatures and biomarkers. We show that the cell surface profile provides sufficient molecular information to classify samples from different cancers and tissue types into biologically relevant clusters using unsupervised hierarchical clustering. Finally, we describe the identification of a candidate lineage marker and its subsequent validation. In summary, HT-FC combines the advantages of a high-throughput screen with a detection method that is sensitive, quantitative, highly reproducible, and allows in-depth analysis of heterogeneous samples. The use of commercially available antibodies means that high quality reagents are immediately available for follow-up studies. HT-FC has a wide range of applications, including biomarker discovery, molecular classification of cancers, or identification of novel lineage specific or stem cell markers. |
| doi_str_mv | 10.1371/journal.pone.0105602 |
| format | Article |
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Antibodies that recognize cell surface antigens are widely used as research tools, diagnostic markers, and even therapeutic agents. The ability to obtain broad cell surface protein profiles would thus be of great value in a wide range of fields. There are however currently few available methods for high-throughput analysis of large numbers of cell surface proteins. We describe here a high-throughput flow cytometry (HT-FC) platform for rapid analysis of 363 cell surface antigens. Here we demonstrate that HT-FC provides reproducible results, and use the platform to identify cell surface antigens that are influenced by common cell preparation methods. We show that multiple populations within complex samples such as primary tumors can be simultaneously analyzed by co-staining of cells with lineage-specific antibodies, allowing unprecedented depth of analysis of heterogeneous cell populations. Furthermore, standard informatics methods can be used to visualize, cluster and downsample HT-FC data to reveal novel signatures and biomarkers. We show that the cell surface profile provides sufficient molecular information to classify samples from different cancers and tissue types into biologically relevant clusters using unsupervised hierarchical clustering. Finally, we describe the identification of a candidate lineage marker and its subsequent validation. In summary, HT-FC combines the advantages of a high-throughput screen with a detection method that is sensitive, quantitative, highly reproducible, and allows in-depth analysis of heterogeneous samples. The use of commercially available antibodies means that high quality reagents are immediately available for follow-up studies. HT-FC has a wide range of applications, including biomarker discovery, molecular classification of cancers, or identification of novel lineage specific or stem cell markers.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0105602</identifier><identifier>PMID: 25170899</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Antibodies ; Antigens ; Antigens, Surface - analysis ; Biology and Life Sciences ; Biomarkers ; Biomarkers - analysis ; Biophysics ; Cell Line, Tumor ; Cell surface ; Cells, Cultured ; Chemical compounds ; Cluster Analysis ; Clustering ; Cytometry ; Diagnostic software ; Diagnostic systems ; Fibroblasts ; Flow cytometry ; Flow Cytometry - methods ; Gene expression ; Health care networks ; Hospitals ; Humans ; Identification ; Immunoglobulins ; Informatics ; Jurkat Cells ; Mass spectrometry ; MCF-7 Cells ; Microscopy, Fluorescence ; Mutation ; Pharmacology ; Populations ; Prostate cancer ; Protein expression ; Proteins ; Proteome - analysis ; Proteome - classification ; Proteome - immunology ; Proteomics - methods ; Queens ; Reagents ; Reproducibility of Results ; Scientific imaging ; Stem cells ; Surface antigens ; Tumors</subject><ispartof>PloS one, 2014-08, Vol.9 (8), p.e105602-e105602</ispartof><rights>2014 Gedye et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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HT-FC has a wide range of applications, including biomarker discovery, molecular classification of cancers, or identification of novel lineage specific or stem cell markers.</description><subject>Antibodies</subject><subject>Antigens</subject><subject>Antigens, Surface - analysis</subject><subject>Biology and Life Sciences</subject><subject>Biomarkers</subject><subject>Biomarkers - analysis</subject><subject>Biophysics</subject><subject>Cell Line, Tumor</subject><subject>Cell surface</subject><subject>Cells, Cultured</subject><subject>Chemical compounds</subject><subject>Cluster Analysis</subject><subject>Clustering</subject><subject>Cytometry</subject><subject>Diagnostic software</subject><subject>Diagnostic systems</subject><subject>Fibroblasts</subject><subject>Flow cytometry</subject><subject>Flow Cytometry - methods</subject><subject>Gene expression</subject><subject>Health care networks</subject><subject>Hospitals</subject><subject>Humans</subject><subject>Identification</subject><subject>Immunoglobulins</subject><subject>Informatics</subject><subject>Jurkat Cells</subject><subject>Mass spectrometry</subject><subject>MCF-7 Cells</subject><subject>Microscopy, Fluorescence</subject><subject>Mutation</subject><subject>Pharmacology</subject><subject>Populations</subject><subject>Prostate cancer</subject><subject>Protein expression</subject><subject>Proteins</subject><subject>Proteome - analysis</subject><subject>Proteome - classification</subject><subject>Proteome - immunology</subject><subject>Proteomics - methods</subject><subject>Queens</subject><subject>Reagents</subject><subject>Reproducibility of Results</subject><subject>Scientific imaging</subject><subject>Stem cells</subject><subject>Surface antigens</subject><subject>Tumors</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><sourceid>DOA</sourceid><recordid>eNptUk1v1DAQjRCIlsI_QGCJC5ddxh9xYg6V0IqPSpW4wNlynHGSxRsHOynKH-B3k2XTqkUcPB7Z773xjF-WvaSwpbyg7_Zhir3x2yH0uAUKuQT2KDunirONZMAf38vPsmcp7QFyXkr5NDtjOS2gVOo8-71D70maojMWyRCD63zXN2RKx9h2TbsZ2ximph2mkTgffhE7j-GAY5zfE0MGb0YX4oEsgVRdOJj4AyOpu2TDDcaZmL5elvFz6hIJjtil3uRNJC2OGEODPXbj_Dx74oxP-GLdL7Lvnz5-233ZXH_9fLX7cL2xOZPjhtXgBApVOpeLCgteFK42aJjgIFVdg0UOeV7ZKucSuWNSgKxUIcBBaZzhF9nrk-7gQ9LrCJNmQAWXVECxIK5OiDqYvR5it3Q062A6_fcgxEabOHbWo2ayKnleOlZLK6CEyqIBUxVVnYPCQi5al2u1qTpgbbEfo_EPRB_e9F2rm3CjBRVKKFgE3q4CMfycMI36sAx2maDpMUxJ0-XTQakCjtA3_0D_3504oWwMKUV0d4-hoI-2umXpo630aquF9up-I3ekWx_xP_blz0k</recordid><startdate>20140829</startdate><enddate>20140829</enddate><creator>Gedye, Craig A</creator><creator>Hussain, Ali</creator><creator>Paterson, Joshua</creator><creator>Smrke, Alannah</creator><creator>Saini, Harleen</creator><creator>Sirskyj, Danylo</creator><creator>Pereira, Keira</creator><creator>Lobo, Nazleen</creator><creator>Stewart, Jocelyn</creator><creator>Go, Christopher</creator><creator>Ho, Jenny</creator><creator>Medrano, Mauricio</creator><creator>Hyatt, Elzbieta</creator><creator>Yuan, Julie</creator><creator>Lauriault, Stevan</creator><creator>Meyer, Mona</creator><creator>Kondratyev, Maria</creator><creator>van den Beucken, Twan</creator><creator>Jewett, Michael</creator><creator>Dirks, Peter</creator><creator>Guidos, Cynthia J</creator><creator>Danska, Jayne</creator><creator>Wang, Jean</creator><creator>Wouters, Bradly</creator><creator>Neel, Benjamin</creator><creator>Rottapel, Robert</creator><creator>Ailles, Laurie E</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20140829</creationdate><title>Cell surface profiling using high-throughput flow cytometry: a platform for biomarker discovery and analysis of cellular heterogeneity</title><author>Gedye, Craig A ; Hussain, Ali ; Paterson, Joshua ; Smrke, Alannah ; Saini, Harleen ; Sirskyj, Danylo ; Pereira, Keira ; Lobo, Nazleen ; Stewart, Jocelyn ; Go, Christopher ; Ho, Jenny ; Medrano, Mauricio ; Hyatt, Elzbieta ; Yuan, Julie ; Lauriault, Stevan ; Meyer, Mona ; Kondratyev, Maria ; van den Beucken, Twan ; Jewett, Michael ; Dirks, Peter ; Guidos, Cynthia J ; Danska, Jayne ; Wang, Jean ; Wouters, Bradly ; Neel, Benjamin ; Rottapel, Robert ; Ailles, Laurie E</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c526t-2d0f4e498ff54be7377fdaea243069dd0ce3055bcb536e3f26406b9740f08afa3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Antibodies</topic><topic>Antigens</topic><topic>Antigens, Surface - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gedye, Craig A</au><au>Hussain, Ali</au><au>Paterson, Joshua</au><au>Smrke, Alannah</au><au>Saini, Harleen</au><au>Sirskyj, Danylo</au><au>Pereira, Keira</au><au>Lobo, Nazleen</au><au>Stewart, Jocelyn</au><au>Go, Christopher</au><au>Ho, Jenny</au><au>Medrano, Mauricio</au><au>Hyatt, Elzbieta</au><au>Yuan, Julie</au><au>Lauriault, Stevan</au><au>Meyer, Mona</au><au>Kondratyev, Maria</au><au>van den Beucken, Twan</au><au>Jewett, Michael</au><au>Dirks, Peter</au><au>Guidos, Cynthia J</au><au>Danska, Jayne</au><au>Wang, Jean</au><au>Wouters, Bradly</au><au>Neel, Benjamin</au><au>Rottapel, Robert</au><au>Ailles, Laurie E</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Cell surface profiling using high-throughput flow cytometry: a platform for biomarker discovery and analysis of cellular heterogeneity</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2014-08-29</date><risdate>2014</risdate><volume>9</volume><issue>8</issue><spage>e105602</spage><epage>e105602</epage><pages>e105602-e105602</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Cell surface proteins have a wide range of biological functions, and are often used as lineage-specific markers. Antibodies that recognize cell surface antigens are widely used as research tools, diagnostic markers, and even therapeutic agents. The ability to obtain broad cell surface protein profiles would thus be of great value in a wide range of fields. There are however currently few available methods for high-throughput analysis of large numbers of cell surface proteins. We describe here a high-throughput flow cytometry (HT-FC) platform for rapid analysis of 363 cell surface antigens. Here we demonstrate that HT-FC provides reproducible results, and use the platform to identify cell surface antigens that are influenced by common cell preparation methods. We show that multiple populations within complex samples such as primary tumors can be simultaneously analyzed by co-staining of cells with lineage-specific antibodies, allowing unprecedented depth of analysis of heterogeneous cell populations. Furthermore, standard informatics methods can be used to visualize, cluster and downsample HT-FC data to reveal novel signatures and biomarkers. We show that the cell surface profile provides sufficient molecular information to classify samples from different cancers and tissue types into biologically relevant clusters using unsupervised hierarchical clustering. Finally, we describe the identification of a candidate lineage marker and its subsequent validation. In summary, HT-FC combines the advantages of a high-throughput screen with a detection method that is sensitive, quantitative, highly reproducible, and allows in-depth analysis of heterogeneous samples. The use of commercially available antibodies means that high quality reagents are immediately available for follow-up studies. HT-FC has a wide range of applications, including biomarker discovery, molecular classification of cancers, or identification of novel lineage specific or stem cell markers.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>25170899</pmid><doi>10.1371/journal.pone.0105602</doi><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2014-08, Vol.9 (8), p.e105602-e105602 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_2014361407 |
| source | PLoS; MEDLINE; DOAJ Directory of Open Access Journals; Free E-Journal (出版社公開部分のみ）; PubMed Central; Free Full-Text Journals in Chemistry |
| subjects | Antibodies Antigens Antigens, Surface - analysis Biology and Life Sciences Biomarkers Biomarkers - analysis Biophysics Cell Line, Tumor Cell surface Cells, Cultured Chemical compounds Cluster Analysis Clustering Cytometry Diagnostic software Diagnostic systems Fibroblasts Flow cytometry Flow Cytometry - methods Gene expression Health care networks Hospitals Humans Identification Immunoglobulins Informatics Jurkat Cells Mass spectrometry MCF-7 Cells Microscopy, Fluorescence Mutation Pharmacology Populations Prostate cancer Protein expression Proteins Proteome - analysis Proteome - classification Proteome - immunology Proteomics - methods Queens Reagents Reproducibility of Results Scientific imaging Stem cells Surface antigens Tumors |
| title | Cell surface profiling using high-throughput flow cytometry: a platform for biomarker discovery and analysis of cellular heterogeneity |
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