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Systemic modeling myeloma-osteoclast interactions under normoxic/hypoxic condition using a novel computational approach
Interaction of myeloma cells with osteoclasts (OC) can enhance tumor cell expansion through activation of complex signaling transduction networks. Both cells reside in the bone marrow, a hypoxic niche. How OC-myeloma interaction in a hypoxic environment affects myeloma cell growth and their response...
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Published in: | Scientific reports 2015-08, Vol.5 (1), p.13291-13291, Article 13291 |
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description | Interaction of myeloma cells with osteoclasts (OC) can enhance tumor cell expansion through activation of complex signaling transduction networks. Both cells reside in the bone marrow, a hypoxic niche. How OC-myeloma interaction in a hypoxic environment affects myeloma cell growth and their response to drug treatment is poorly understood. In this study, we
i
) cultured myeloma cells in the presence/absence of OCs under normoxia and hypoxia conditions and did protein profiling analysis using reverse phase protein array;
ii
) computationally developed an Integer Linear Programming approach to infer OC-mediated myeloma cell-specific signaling pathways under normoxic and hypoxic conditions. Our modeling analysis indicated that in the presence OCs, (1) cell growth-associated signaling pathways, PI3K/AKT and MEK/ERK, were activated and apoptotic regulatory proteins, BAX and BIM, down-regulated under normoxic condition; (2) β1 Integrin/FAK signaling pathway was activated in myeloma cells under hypoxic condition. Simulation of drug treatment effects by perturbing the inferred cell-specific pathways showed that targeting myeloma cells with the combination of PI3K and integrin inhibitors potentially (1) inhibited cell proliferation by reducing the expression/activation of NF-κB, S6, c-Myc and c-Jun under normoxic condition; (2) blocked myeloma cell migration and invasion by reducing the expression of FAK and PKC under hypoxic condition. |
doi_str_mv | 10.1038/srep13291 |
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i
) cultured myeloma cells in the presence/absence of OCs under normoxia and hypoxia conditions and did protein profiling analysis using reverse phase protein array;
ii
) computationally developed an Integer Linear Programming approach to infer OC-mediated myeloma cell-specific signaling pathways under normoxic and hypoxic conditions. Our modeling analysis indicated that in the presence OCs, (1) cell growth-associated signaling pathways, PI3K/AKT and MEK/ERK, were activated and apoptotic regulatory proteins, BAX and BIM, down-regulated under normoxic condition; (2) β1 Integrin/FAK signaling pathway was activated in myeloma cells under hypoxic condition. Simulation of drug treatment effects by perturbing the inferred cell-specific pathways showed that targeting myeloma cells with the combination of PI3K and integrin inhibitors potentially (1) inhibited cell proliferation by reducing the expression/activation of NF-κB, S6, c-Myc and c-Jun under normoxic condition; (2) blocked myeloma cell migration and invasion by reducing the expression of FAK and PKC under hypoxic condition.</description><identifier>ISSN: 2045-2322</identifier><identifier>EISSN: 2045-2322</identifier><identifier>DOI: 10.1038/srep13291</identifier><identifier>PMID: 26282073</identifier><language>eng</language><publisher>London: Nature Publishing Group UK</publisher><subject>1-Phosphatidylinositol 3-kinase ; 631/114/2391 ; 631/553/2695 ; AKT protein ; Algorithms ; Apoptosis ; BAX protein ; BIM protein ; Bone marrow ; Bone Marrow - metabolism ; Bone Marrow - pathology ; c-Jun protein ; c-Myc protein ; Cell activation ; Cell adhesion & migration ; Cell Communication ; Cell growth ; Cell Hypoxia ; Cell Line, Tumor ; Cell migration ; Cell proliferation ; Computer applications ; Computer Simulation ; Humanities and Social Sciences ; Humans ; Hypoxia ; Linear programming ; Models, Biological ; multidisciplinary ; Multiple myeloma ; Multiple Myeloma - metabolism ; Multiple Myeloma - pathology ; Myc protein ; Myeloma ; Neoplasm Proteins - metabolism ; Osteoclasts ; Osteoclasts - metabolism ; Osteoclasts - pathology ; Oxygen - metabolism ; Programming, Linear ; Protein arrays ; Protein kinase C ; Science ; Signal transduction ; Transcription factors ; Tumor Microenvironment</subject><ispartof>Scientific reports, 2015-08, Vol.5 (1), p.13291-13291, Article 13291</ispartof><rights>The Author(s) 2015</rights><rights>Copyright Nature Publishing Group Aug 2015</rights><rights>Copyright © 2015, Macmillan Publishers Limited 2015 Macmillan Publishers Limited</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c438t-b7401398bac49b93131822c359c0d81e92f9c30c51b0dc8e32f5329630773ec13</citedby><cites>FETCH-LOGICAL-c438t-b7401398bac49b93131822c359c0d81e92f9c30c51b0dc8e32f5329630773ec13</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/1899733545/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/1899733545?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,724,777,781,882,25734,27905,27906,36993,36994,44571,53772,53774,74875</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26282073$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ji, Zhiwei</creatorcontrib><creatorcontrib>Wu, Dan</creatorcontrib><creatorcontrib>Zhao, Weiling</creatorcontrib><creatorcontrib>Peng, Huiming</creatorcontrib><creatorcontrib>Zhao, Shengjie</creatorcontrib><creatorcontrib>Huang, Deshuang</creatorcontrib><creatorcontrib>Zhou, Xiaobo</creatorcontrib><title>Systemic modeling myeloma-osteoclast interactions under normoxic/hypoxic condition using a novel computational approach</title><title>Scientific reports</title><addtitle>Sci Rep</addtitle><addtitle>Sci Rep</addtitle><description>Interaction of myeloma cells with osteoclasts (OC) can enhance tumor cell expansion through activation of complex signaling transduction networks. Both cells reside in the bone marrow, a hypoxic niche. How OC-myeloma interaction in a hypoxic environment affects myeloma cell growth and their response to drug treatment is poorly understood. In this study, we
i
) cultured myeloma cells in the presence/absence of OCs under normoxia and hypoxia conditions and did protein profiling analysis using reverse phase protein array;
ii
) computationally developed an Integer Linear Programming approach to infer OC-mediated myeloma cell-specific signaling pathways under normoxic and hypoxic conditions. Our modeling analysis indicated that in the presence OCs, (1) cell growth-associated signaling pathways, PI3K/AKT and MEK/ERK, were activated and apoptotic regulatory proteins, BAX and BIM, down-regulated under normoxic condition; (2) β1 Integrin/FAK signaling pathway was activated in myeloma cells under hypoxic condition. Simulation of drug treatment effects by perturbing the inferred cell-specific pathways showed that targeting myeloma cells with the combination of PI3K and integrin inhibitors potentially (1) inhibited cell proliferation by reducing the expression/activation of NF-κB, S6, c-Myc and c-Jun under normoxic condition; (2) blocked myeloma cell migration and invasion by reducing the expression of FAK and PKC under hypoxic condition.</description><subject>1-Phosphatidylinositol 3-kinase</subject><subject>631/114/2391</subject><subject>631/553/2695</subject><subject>AKT protein</subject><subject>Algorithms</subject><subject>Apoptosis</subject><subject>BAX protein</subject><subject>BIM protein</subject><subject>Bone marrow</subject><subject>Bone Marrow - metabolism</subject><subject>Bone Marrow - pathology</subject><subject>c-Jun protein</subject><subject>c-Myc protein</subject><subject>Cell activation</subject><subject>Cell adhesion & migration</subject><subject>Cell Communication</subject><subject>Cell growth</subject><subject>Cell Hypoxia</subject><subject>Cell Line, Tumor</subject><subject>Cell migration</subject><subject>Cell proliferation</subject><subject>Computer applications</subject><subject>Computer Simulation</subject><subject>Humanities and Social Sciences</subject><subject>Humans</subject><subject>Hypoxia</subject><subject>Linear programming</subject><subject>Models, Biological</subject><subject>multidisciplinary</subject><subject>Multiple myeloma</subject><subject>Multiple Myeloma - metabolism</subject><subject>Multiple Myeloma - pathology</subject><subject>Myc protein</subject><subject>Myeloma</subject><subject>Neoplasm Proteins - metabolism</subject><subject>Osteoclasts</subject><subject>Osteoclasts - metabolism</subject><subject>Osteoclasts - pathology</subject><subject>Oxygen - metabolism</subject><subject>Programming, Linear</subject><subject>Protein arrays</subject><subject>Protein kinase C</subject><subject>Science</subject><subject>Signal transduction</subject><subject>Transcription factors</subject><subject>Tumor Microenvironment</subject><issn>2045-2322</issn><issn>2045-2322</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><recordid>eNplkU1v1DAQhi0EotXSA38AReJCkUJtT7KxL0hVVT6kShyAs-VMvLuu_BHspLD_HkdbVgv4Mta8j94Z-yXkJaPvGAVxlZMZGXDJnpBzTpu25sD505P7GbnI-Z6W03LZMPmcnPE1F5x2cE5-ft3nyXiLlY-DcTZsK783LnpdxyJEdDpPlQ2TSRonG0Ou5jCYVIWYfPxl8Wq3H5daYQyDXYhqzouNLsiDcaXvx3nSi6JdpccxRY27F-TZRrtsLh7rinz_cPvt5lN99-Xj55vruxobEFPddw1lIEWvsZG9BAZMcI7QSqSDYEbyjUSg2LKeDigM8E1b_mINtOvAIIMVeX_wHefemwFNmJJ2akzW67RXUVv1txLsTm3jg2pakGsqisGbR4MUf8wmT8rbjMY5HUycs2IdbZsOZMcL-vof9D7Oqby6UELKDqAtrityeaAwxVzC2xyXYVQtiapjooV9dbr9kfyTXwHeHoBcpLA16WTkf26_AZr7rVY</recordid><startdate>20150818</startdate><enddate>20150818</enddate><creator>Ji, Zhiwei</creator><creator>Wu, Dan</creator><creator>Zhao, Weiling</creator><creator>Peng, Huiming</creator><creator>Zhao, Shengjie</creator><creator>Huang, Deshuang</creator><creator>Zhou, Xiaobo</creator><general>Nature Publishing Group UK</general><general>Nature Publishing Group</general><scope>C6C</scope><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>7X7</scope><scope>7XB</scope><scope>88A</scope><scope>88E</scope><scope>88I</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M2P</scope><scope>M7P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20150818</creationdate><title>Systemic modeling myeloma-osteoclast interactions under normoxic/hypoxic condition using a novel computational approach</title><author>Ji, Zhiwei ; Wu, Dan ; Zhao, Weiling ; Peng, Huiming ; Zhao, Shengjie ; Huang, Deshuang ; Zhou, Xiaobo</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c438t-b7401398bac49b93131822c359c0d81e92f9c30c51b0dc8e32f5329630773ec13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>1-Phosphatidylinositol 3-kinase</topic><topic>631/114/2391</topic><topic>631/553/2695</topic><topic>AKT protein</topic><topic>Algorithms</topic><topic>Apoptosis</topic><topic>BAX protein</topic><topic>BIM protein</topic><topic>Bone marrow</topic><topic>Bone Marrow - metabolism</topic><topic>Bone Marrow - pathology</topic><topic>c-Jun protein</topic><topic>c-Myc protein</topic><topic>Cell activation</topic><topic>Cell adhesion & migration</topic><topic>Cell Communication</topic><topic>Cell growth</topic><topic>Cell Hypoxia</topic><topic>Cell Line, Tumor</topic><topic>Cell migration</topic><topic>Cell proliferation</topic><topic>Computer applications</topic><topic>Computer Simulation</topic><topic>Humanities and Social Sciences</topic><topic>Humans</topic><topic>Hypoxia</topic><topic>Linear programming</topic><topic>Models, Biological</topic><topic>multidisciplinary</topic><topic>Multiple myeloma</topic><topic>Multiple Myeloma - metabolism</topic><topic>Multiple Myeloma - pathology</topic><topic>Myc protein</topic><topic>Myeloma</topic><topic>Neoplasm Proteins - metabolism</topic><topic>Osteoclasts</topic><topic>Osteoclasts - metabolism</topic><topic>Osteoclasts - pathology</topic><topic>Oxygen - metabolism</topic><topic>Programming, Linear</topic><topic>Protein arrays</topic><topic>Protein kinase C</topic><topic>Science</topic><topic>Signal transduction</topic><topic>Transcription factors</topic><topic>Tumor Microenvironment</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ji, Zhiwei</creatorcontrib><creatorcontrib>Wu, Dan</creatorcontrib><creatorcontrib>Zhao, Weiling</creatorcontrib><creatorcontrib>Peng, Huiming</creatorcontrib><creatorcontrib>Zhao, Shengjie</creatorcontrib><creatorcontrib>Huang, Deshuang</creatorcontrib><creatorcontrib>Zhou, Xiaobo</creatorcontrib><collection>SpringerOpen</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Biology Database (Alumni Edition)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest SciTech 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>ProQuest Central (Alumni)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Biological Sciences</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Science Database</collection><collection>Biological Science Database</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 Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Scientific reports</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ji, Zhiwei</au><au>Wu, Dan</au><au>Zhao, Weiling</au><au>Peng, Huiming</au><au>Zhao, Shengjie</au><au>Huang, Deshuang</au><au>Zhou, Xiaobo</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Systemic modeling myeloma-osteoclast interactions under normoxic/hypoxic condition using a novel computational approach</atitle><jtitle>Scientific reports</jtitle><stitle>Sci Rep</stitle><addtitle>Sci Rep</addtitle><date>2015-08-18</date><risdate>2015</risdate><volume>5</volume><issue>1</issue><spage>13291</spage><epage>13291</epage><pages>13291-13291</pages><artnum>13291</artnum><issn>2045-2322</issn><eissn>2045-2322</eissn><abstract>Interaction of myeloma cells with osteoclasts (OC) can enhance tumor cell expansion through activation of complex signaling transduction networks. Both cells reside in the bone marrow, a hypoxic niche. How OC-myeloma interaction in a hypoxic environment affects myeloma cell growth and their response to drug treatment is poorly understood. In this study, we
i
) cultured myeloma cells in the presence/absence of OCs under normoxia and hypoxia conditions and did protein profiling analysis using reverse phase protein array;
ii
) computationally developed an Integer Linear Programming approach to infer OC-mediated myeloma cell-specific signaling pathways under normoxic and hypoxic conditions. Our modeling analysis indicated that in the presence OCs, (1) cell growth-associated signaling pathways, PI3K/AKT and MEK/ERK, were activated and apoptotic regulatory proteins, BAX and BIM, down-regulated under normoxic condition; (2) β1 Integrin/FAK signaling pathway was activated in myeloma cells under hypoxic condition. Simulation of drug treatment effects by perturbing the inferred cell-specific pathways showed that targeting myeloma cells with the combination of PI3K and integrin inhibitors potentially (1) inhibited cell proliferation by reducing the expression/activation of NF-κB, S6, c-Myc and c-Jun under normoxic condition; (2) blocked myeloma cell migration and invasion by reducing the expression of FAK and PKC under hypoxic condition.</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><pmid>26282073</pmid><doi>10.1038/srep13291</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
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subjects | 1-Phosphatidylinositol 3-kinase 631/114/2391 631/553/2695 AKT protein Algorithms Apoptosis BAX protein BIM protein Bone marrow Bone Marrow - metabolism Bone Marrow - pathology c-Jun protein c-Myc protein Cell activation Cell adhesion & migration Cell Communication Cell growth Cell Hypoxia Cell Line, Tumor Cell migration Cell proliferation Computer applications Computer Simulation Humanities and Social Sciences Humans Hypoxia Linear programming Models, Biological multidisciplinary Multiple myeloma Multiple Myeloma - metabolism Multiple Myeloma - pathology Myc protein Myeloma Neoplasm Proteins - metabolism Osteoclasts Osteoclasts - metabolism Osteoclasts - pathology Oxygen - metabolism Programming, Linear Protein arrays Protein kinase C Science Signal transduction Transcription factors Tumor Microenvironment |
title | Systemic modeling myeloma-osteoclast interactions under normoxic/hypoxic condition using a novel computational approach |
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