Loading…
Analysis of compound synergy in high-throughput cellular screens by population-based lifetime modeling
Despite the successful introduction of potent anti-cancer therapeutics, most of these drugs lead to only modest tumor-shrinkage or transient responses, followed by re-growth of tumors. Combining different compounds has resulted in enhanced tumor control and prolonged survival. However, methods query...
Saved in:
Published in: | PloS one 2010-01, Vol.5 (1), p.e8919 |
---|---|
Main Authors: | , , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c691t-72471b82be96e1e2cbecd5d65d215c6f80e03ca2c4f6af9677941f3ef6a53a033 |
---|---|
cites | |
container_end_page | |
container_issue | 1 |
container_start_page | e8919 |
container_title | PloS one |
container_volume | 5 |
creator | Peifer, Martin Weiss, Jonathan Sos, Martin L Koker, Mirjam Heynck, Stefanie Netzer, Christian Fischer, Stefanie Rode, Haridas Rauh, Daniel Rahnenführer, Jörg Thomas, Roman K |
description | Despite the successful introduction of potent anti-cancer therapeutics, most of these drugs lead to only modest tumor-shrinkage or transient responses, followed by re-growth of tumors. Combining different compounds has resulted in enhanced tumor control and prolonged survival. However, methods querying the efficacy of such combinations have been hampered by limited scalability, analytical resolution, statistical feasibility, or a combination thereof. We have developed a theoretical framework modeling cellular viability as a stochastic lifetime process to determine synergistic compound combinations from high-throughput cellular screens. We apply our method to data derived from chemical perturbations of 65 cancer cell lines with two inhibitors. Our analysis revealed synergy for the combination of both compounds in subsets of cell lines. By contrast, in cell lines in which inhibition of one of both targets was sufficient to induce cell death, no synergy was detected, compatible with the topology of the oncogenically activated signaling network. In summary, we provide a tool for the measurement of synergy strength for combination perturbation experiments that might help define pathway topologies and direct clinical trials. |
doi_str_mv | 10.1371/journal.pone.0008919 |
format | article |
fullrecord | <record><control><sourceid>gale_plos_</sourceid><recordid>TN_cdi_plos_journals_1289258249</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A473916056</galeid><doaj_id>oai_doaj_org_article_d43d914520a846449df82e6532342907</doaj_id><sourcerecordid>A473916056</sourcerecordid><originalsourceid>FETCH-LOGICAL-c691t-72471b82be96e1e2cbecd5d65d215c6f80e03ca2c4f6af9677941f3ef6a53a033</originalsourceid><addsrcrecordid>eNqNkl2L1DAUhoso7rr6D0QLguBFx3w1bW6EYfFjYGHBr9uQpqdthrSpSSvOvzfjdJcpKEgukpw8583h5U2S5xhtMC3w272b_aDsZnQDbBBCpcDiQXKJBSUZJ4g-PDtfJE9C2COU05Lzx8kFQRjjArPLpNlGjUMwIXVNql0_unmo03AYwLeH1AxpZ9oumzrv5rYb5ynVYO1slU-D9gBDSKtDOroxlibjhqxSAerUmgYm00PauxqsGdqnyaNG2QDPlv0q-fbh_dfrT9nN7cfd9fYm01zgKSsIK3BVkgoEBwxEV6DrvOZ5TXCueVMiQFQrolnDVSN4UQiGGwrxllOFKL1KXp50R-uCXCwKEpNSkLwkTERidyJqp_Zy9KZX_iCdMvJPwflWKj8ZbUHWjNYCs5wgVTLOmKibkgDPKaGMCFRErXfLb3PVQ61hmLyyK9H1y2A62bqfkpTRflpGgVeLgHc_ZgjTP0ZeqFbFqczQuCimexO03LKCCsxRziO1-QsVVw290TEkjYn1VcObVUNkJvg1tWoOQe6-fP5_9vb7mn19xnag7NQFZ-djPsIaZCdQexeCh-beOYzkMeN3bshjxuWS8dj24tz1-6a7UNPflcP3sg</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1289258249</pqid></control><display><type>article</type><title>Analysis of compound synergy in high-throughput cellular screens by population-based lifetime modeling</title><source>Publicly Available Content Database</source><source>PubMed Central</source><creator>Peifer, Martin ; Weiss, Jonathan ; Sos, Martin L ; Koker, Mirjam ; Heynck, Stefanie ; Netzer, Christian ; Fischer, Stefanie ; Rode, Haridas ; Rauh, Daniel ; Rahnenführer, Jörg ; Thomas, Roman K</creator><contributor>Zanger, Ulrich</contributor><creatorcontrib>Peifer, Martin ; Weiss, Jonathan ; Sos, Martin L ; Koker, Mirjam ; Heynck, Stefanie ; Netzer, Christian ; Fischer, Stefanie ; Rode, Haridas ; Rauh, Daniel ; Rahnenführer, Jörg ; Thomas, Roman K ; Zanger, Ulrich</creatorcontrib><description>Despite the successful introduction of potent anti-cancer therapeutics, most of these drugs lead to only modest tumor-shrinkage or transient responses, followed by re-growth of tumors. Combining different compounds has resulted in enhanced tumor control and prolonged survival. However, methods querying the efficacy of such combinations have been hampered by limited scalability, analytical resolution, statistical feasibility, or a combination thereof. We have developed a theoretical framework modeling cellular viability as a stochastic lifetime process to determine synergistic compound combinations from high-throughput cellular screens. We apply our method to data derived from chemical perturbations of 65 cancer cell lines with two inhibitors. Our analysis revealed synergy for the combination of both compounds in subsets of cell lines. By contrast, in cell lines in which inhibition of one of both targets was sufficient to induce cell death, no synergy was detected, compatible with the topology of the oncogenically activated signaling network. In summary, we provide a tool for the measurement of synergy strength for combination perturbation experiments that might help define pathway topologies and direct clinical trials.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0008919</identifier><identifier>PMID: 20111714</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Algorithms ; Analysis ; Antineoplastic Agents - pharmacology ; Biotechnology ; Cancer ; Cancer therapies ; Cancer treatment ; Cell death ; Cell Line, Tumor ; Chemotherapy ; Clinical trials ; Computational Biology ; Drug dosages ; Drug Synergism ; Drugs ; Enzymes ; Epidermal growth factor ; Estimates ; Feasibility studies ; Genetics and Genomics/Pharmacogenomics ; Genomics ; Humans ; Laboratories ; Leukemia ; Ligands ; Lung cancer ; Medical research ; Medical screening ; Modelling ; Models, Theoretical ; Mutation ; Neoplasms - drug therapy ; Neoplasms - pathology ; Oncology/Lung Cancer ; Pharmacology/Drug Development ; Pharmacology/Personalized Medicine ; Physicists ; Population (statistical) ; Recipes ; Shrinkage ; Signaling ; Stochastic Processes ; Stochasticity ; Topology ; Transient response ; Tumor cell lines ; Tumors</subject><ispartof>PloS one, 2010-01, Vol.5 (1), p.e8919</ispartof><rights>COPYRIGHT 2010 Public Library of Science</rights><rights>2010 Peifer et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://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. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>Peifer et al. 2010</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c691t-72471b82be96e1e2cbecd5d65d215c6f80e03ca2c4f6af9677941f3ef6a53a033</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/1289258249/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/1289258249?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,44590,53791,53793,75126</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/20111714$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Zanger, Ulrich</contributor><creatorcontrib>Peifer, Martin</creatorcontrib><creatorcontrib>Weiss, Jonathan</creatorcontrib><creatorcontrib>Sos, Martin L</creatorcontrib><creatorcontrib>Koker, Mirjam</creatorcontrib><creatorcontrib>Heynck, Stefanie</creatorcontrib><creatorcontrib>Netzer, Christian</creatorcontrib><creatorcontrib>Fischer, Stefanie</creatorcontrib><creatorcontrib>Rode, Haridas</creatorcontrib><creatorcontrib>Rauh, Daniel</creatorcontrib><creatorcontrib>Rahnenführer, Jörg</creatorcontrib><creatorcontrib>Thomas, Roman K</creatorcontrib><title>Analysis of compound synergy in high-throughput cellular screens by population-based lifetime modeling</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Despite the successful introduction of potent anti-cancer therapeutics, most of these drugs lead to only modest tumor-shrinkage or transient responses, followed by re-growth of tumors. Combining different compounds has resulted in enhanced tumor control and prolonged survival. However, methods querying the efficacy of such combinations have been hampered by limited scalability, analytical resolution, statistical feasibility, or a combination thereof. We have developed a theoretical framework modeling cellular viability as a stochastic lifetime process to determine synergistic compound combinations from high-throughput cellular screens. We apply our method to data derived from chemical perturbations of 65 cancer cell lines with two inhibitors. Our analysis revealed synergy for the combination of both compounds in subsets of cell lines. By contrast, in cell lines in which inhibition of one of both targets was sufficient to induce cell death, no synergy was detected, compatible with the topology of the oncogenically activated signaling network. In summary, we provide a tool for the measurement of synergy strength for combination perturbation experiments that might help define pathway topologies and direct clinical trials.</description><subject>Algorithms</subject><subject>Analysis</subject><subject>Antineoplastic Agents - pharmacology</subject><subject>Biotechnology</subject><subject>Cancer</subject><subject>Cancer therapies</subject><subject>Cancer treatment</subject><subject>Cell death</subject><subject>Cell Line, Tumor</subject><subject>Chemotherapy</subject><subject>Clinical trials</subject><subject>Computational Biology</subject><subject>Drug dosages</subject><subject>Drug Synergism</subject><subject>Drugs</subject><subject>Enzymes</subject><subject>Epidermal growth factor</subject><subject>Estimates</subject><subject>Feasibility studies</subject><subject>Genetics and Genomics/Pharmacogenomics</subject><subject>Genomics</subject><subject>Humans</subject><subject>Laboratories</subject><subject>Leukemia</subject><subject>Ligands</subject><subject>Lung cancer</subject><subject>Medical research</subject><subject>Medical screening</subject><subject>Modelling</subject><subject>Models, Theoretical</subject><subject>Mutation</subject><subject>Neoplasms - drug therapy</subject><subject>Neoplasms - pathology</subject><subject>Oncology/Lung Cancer</subject><subject>Pharmacology/Drug Development</subject><subject>Pharmacology/Personalized Medicine</subject><subject>Physicists</subject><subject>Population (statistical)</subject><subject>Recipes</subject><subject>Shrinkage</subject><subject>Signaling</subject><subject>Stochastic Processes</subject><subject>Stochasticity</subject><subject>Topology</subject><subject>Transient response</subject><subject>Tumor cell lines</subject><subject>Tumors</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNqNkl2L1DAUhoso7rr6D0QLguBFx3w1bW6EYfFjYGHBr9uQpqdthrSpSSvOvzfjdJcpKEgukpw8583h5U2S5xhtMC3w272b_aDsZnQDbBBCpcDiQXKJBSUZJ4g-PDtfJE9C2COU05Lzx8kFQRjjArPLpNlGjUMwIXVNql0_unmo03AYwLeH1AxpZ9oumzrv5rYb5ynVYO1slU-D9gBDSKtDOroxlibjhqxSAerUmgYm00PauxqsGdqnyaNG2QDPlv0q-fbh_dfrT9nN7cfd9fYm01zgKSsIK3BVkgoEBwxEV6DrvOZ5TXCueVMiQFQrolnDVSN4UQiGGwrxllOFKL1KXp50R-uCXCwKEpNSkLwkTERidyJqp_Zy9KZX_iCdMvJPwflWKj8ZbUHWjNYCs5wgVTLOmKibkgDPKaGMCFRErXfLb3PVQ61hmLyyK9H1y2A62bqfkpTRflpGgVeLgHc_ZgjTP0ZeqFbFqczQuCimexO03LKCCsxRziO1-QsVVw290TEkjYn1VcObVUNkJvg1tWoOQe6-fP5_9vb7mn19xnag7NQFZ-djPsIaZCdQexeCh-beOYzkMeN3bshjxuWS8dj24tz1-6a7UNPflcP3sg</recordid><startdate>20100127</startdate><enddate>20100127</enddate><creator>Peifer, Martin</creator><creator>Weiss, Jonathan</creator><creator>Sos, Martin L</creator><creator>Koker, Mirjam</creator><creator>Heynck, Stefanie</creator><creator>Netzer, Christian</creator><creator>Fischer, Stefanie</creator><creator>Rode, Haridas</creator><creator>Rauh, Daniel</creator><creator>Rahnenführer, Jörg</creator><creator>Thomas, Roman K</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>IOV</scope><scope>ISR</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>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>5PM</scope><scope>DOA</scope></search><sort><creationdate>20100127</creationdate><title>Analysis of compound synergy in high-throughput cellular screens by population-based lifetime modeling</title><author>Peifer, Martin ; Weiss, Jonathan ; Sos, Martin L ; Koker, Mirjam ; Heynck, Stefanie ; Netzer, Christian ; Fischer, Stefanie ; Rode, Haridas ; Rauh, Daniel ; Rahnenführer, Jörg ; Thomas, Roman K</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c691t-72471b82be96e1e2cbecd5d65d215c6f80e03ca2c4f6af9677941f3ef6a53a033</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Algorithms</topic><topic>Analysis</topic><topic>Antineoplastic Agents - pharmacology</topic><topic>Biotechnology</topic><topic>Cancer</topic><topic>Cancer therapies</topic><topic>Cancer treatment</topic><topic>Cell death</topic><topic>Cell Line, Tumor</topic><topic>Chemotherapy</topic><topic>Clinical trials</topic><topic>Computational Biology</topic><topic>Drug dosages</topic><topic>Drug Synergism</topic><topic>Drugs</topic><topic>Enzymes</topic><topic>Epidermal growth factor</topic><topic>Estimates</topic><topic>Feasibility studies</topic><topic>Genetics and Genomics/Pharmacogenomics</topic><topic>Genomics</topic><topic>Humans</topic><topic>Laboratories</topic><topic>Leukemia</topic><topic>Ligands</topic><topic>Lung cancer</topic><topic>Medical research</topic><topic>Medical screening</topic><topic>Modelling</topic><topic>Models, Theoretical</topic><topic>Mutation</topic><topic>Neoplasms - drug therapy</topic><topic>Neoplasms - pathology</topic><topic>Oncology/Lung Cancer</topic><topic>Pharmacology/Drug Development</topic><topic>Pharmacology/Personalized Medicine</topic><topic>Physicists</topic><topic>Population (statistical)</topic><topic>Recipes</topic><topic>Shrinkage</topic><topic>Signaling</topic><topic>Stochastic Processes</topic><topic>Stochasticity</topic><topic>Topology</topic><topic>Transient response</topic><topic>Tumor cell lines</topic><topic>Tumors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Peifer, Martin</creatorcontrib><creatorcontrib>Weiss, Jonathan</creatorcontrib><creatorcontrib>Sos, Martin L</creatorcontrib><creatorcontrib>Koker, Mirjam</creatorcontrib><creatorcontrib>Heynck, Stefanie</creatorcontrib><creatorcontrib>Netzer, Christian</creatorcontrib><creatorcontrib>Fischer, Stefanie</creatorcontrib><creatorcontrib>Rode, Haridas</creatorcontrib><creatorcontrib>Rauh, Daniel</creatorcontrib><creatorcontrib>Rahnenführer, Jörg</creatorcontrib><creatorcontrib>Thomas, Roman K</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale In Context: Opposing Viewpoints</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>ProQuest Engineering Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Agriculture Science Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>ProQuest Biological Science Journals</collection><collection>Engineering Database</collection><collection>Nursing & Allied Health Premium</collection><collection>ProQuest advanced technologies & aerospace journals</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>Materials science collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering collection</collection><collection>Environmental Science Collection</collection><collection>Genetics Abstracts</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>Peifer, Martin</au><au>Weiss, Jonathan</au><au>Sos, Martin L</au><au>Koker, Mirjam</au><au>Heynck, Stefanie</au><au>Netzer, Christian</au><au>Fischer, Stefanie</au><au>Rode, Haridas</au><au>Rauh, Daniel</au><au>Rahnenführer, Jörg</au><au>Thomas, Roman K</au><au>Zanger, Ulrich</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Analysis of compound synergy in high-throughput cellular screens by population-based lifetime modeling</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2010-01-27</date><risdate>2010</risdate><volume>5</volume><issue>1</issue><spage>e8919</spage><pages>e8919-</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Despite the successful introduction of potent anti-cancer therapeutics, most of these drugs lead to only modest tumor-shrinkage or transient responses, followed by re-growth of tumors. Combining different compounds has resulted in enhanced tumor control and prolonged survival. However, methods querying the efficacy of such combinations have been hampered by limited scalability, analytical resolution, statistical feasibility, or a combination thereof. We have developed a theoretical framework modeling cellular viability as a stochastic lifetime process to determine synergistic compound combinations from high-throughput cellular screens. We apply our method to data derived from chemical perturbations of 65 cancer cell lines with two inhibitors. Our analysis revealed synergy for the combination of both compounds in subsets of cell lines. By contrast, in cell lines in which inhibition of one of both targets was sufficient to induce cell death, no synergy was detected, compatible with the topology of the oncogenically activated signaling network. In summary, we provide a tool for the measurement of synergy strength for combination perturbation experiments that might help define pathway topologies and direct clinical trials.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>20111714</pmid><doi>10.1371/journal.pone.0008919</doi><tpages>e8919</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1932-6203 |
ispartof | PloS one, 2010-01, Vol.5 (1), p.e8919 |
issn | 1932-6203 1932-6203 |
language | eng |
recordid | cdi_plos_journals_1289258249 |
source | Publicly Available Content Database; PubMed Central |
subjects | Algorithms Analysis Antineoplastic Agents - pharmacology Biotechnology Cancer Cancer therapies Cancer treatment Cell death Cell Line, Tumor Chemotherapy Clinical trials Computational Biology Drug dosages Drug Synergism Drugs Enzymes Epidermal growth factor Estimates Feasibility studies Genetics and Genomics/Pharmacogenomics Genomics Humans Laboratories Leukemia Ligands Lung cancer Medical research Medical screening Modelling Models, Theoretical Mutation Neoplasms - drug therapy Neoplasms - pathology Oncology/Lung Cancer Pharmacology/Drug Development Pharmacology/Personalized Medicine Physicists Population (statistical) Recipes Shrinkage Signaling Stochastic Processes Stochasticity Topology Transient response Tumor cell lines Tumors |
title | Analysis of compound synergy in high-throughput cellular screens by population-based lifetime modeling |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-27T07%3A05%3A52IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Analysis%20of%20compound%20synergy%20in%20high-throughput%20cellular%20screens%20by%20population-based%20lifetime%20modeling&rft.jtitle=PloS%20one&rft.au=Peifer,%20Martin&rft.date=2010-01-27&rft.volume=5&rft.issue=1&rft.spage=e8919&rft.pages=e8919-&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0008919&rft_dat=%3Cgale_plos_%3EA473916056%3C/gale_plos_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c691t-72471b82be96e1e2cbecd5d65d215c6f80e03ca2c4f6af9677941f3ef6a53a033%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=1289258249&rft_id=info:pmid/20111714&rft_galeid=A473916056&rfr_iscdi=true |