Quantifying assays: inhibition of signalling pathways of cancer
Abstract Inhibiting a signalling pathway concerns controlling the cellular processes of a cancer cell’s viability, cell division and death. Assay protocols created to see if the molecular structures of the drugs being tested have the desired inhibition qualities often show great variability across e...
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Veröffentlicht in: | Mathematical medicine and biology 2023-09, Vol.40 (3), p.266-290 |
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creator | Anguelov, Roumen Manjunath, G Phiri, Avulundiah E Nyakudya, Trevor T Bipath, Priyesh C. Serem, June N. Hlophe, Yvette |
description | Abstract
Inhibiting a signalling pathway concerns controlling the cellular processes of a cancer cell’s viability, cell division and death. Assay protocols created to see if the molecular structures of the drugs being tested have the desired inhibition qualities often show great variability across experiments, and it is imperative to diminish the effects of such variability while inferences are drawn. In this paper, we propose the study of experimental data through the lenses of a mathematical model depicting the inhibition mechanism and the activation-inhibition dynamics. The method is exemplified through assay data obtained from an experimental study of the inhibition of the chemokine receptor 4 (CXCR4) and chemokine ligand 12 (CXCL12) signalling pathway of melanoma cells. The quantitative analysis is conducted as a two step process: (i) deriving theoretically from the model the cell viability as a function of time depending on several parameters; (ii) estimating the values of the parameters by using the experimental data. The cell viability is obtained as a function of concentration of the inhibitor and time, thus providing a comprehensive characterization of the potential therapeutic effect of the considered inhibitor, e.g. $IC_{50}$ can be computed for any time point. |
doi_str_mv | 10.1093/imammb/dqad005 |
format | Article |
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Inhibiting a signalling pathway concerns controlling the cellular processes of a cancer cell’s viability, cell division and death. Assay protocols created to see if the molecular structures of the drugs being tested have the desired inhibition qualities often show great variability across experiments, and it is imperative to diminish the effects of such variability while inferences are drawn. In this paper, we propose the study of experimental data through the lenses of a mathematical model depicting the inhibition mechanism and the activation-inhibition dynamics. The method is exemplified through assay data obtained from an experimental study of the inhibition of the chemokine receptor 4 (CXCR4) and chemokine ligand 12 (CXCL12) signalling pathway of melanoma cells. The quantitative analysis is conducted as a two step process: (i) deriving theoretically from the model the cell viability as a function of time depending on several parameters; (ii) estimating the values of the parameters by using the experimental data. The cell viability is obtained as a function of concentration of the inhibitor and time, thus providing a comprehensive characterization of the potential therapeutic effect of the considered inhibitor, e.g. $IC_{50}$ can be computed for any time point.</description><identifier>ISSN: 1477-8599</identifier><identifier>EISSN: 1477-8602</identifier><identifier>DOI: 10.1093/imammb/dqad005</identifier><identifier>PMID: 37669569</identifier><language>eng</language><publisher>England: Oxford University Press</publisher><subject>Cell Line, Tumor ; Chemokine CXCL12 - metabolism ; Chemokine CXCL12 - pharmacology ; Neoplasms - drug therapy ; Receptors, CXCR4 - metabolism ; Signal Transduction</subject><ispartof>Mathematical medicine and biology, 2023-09, Vol.40 (3), p.266-290</ispartof><rights>The Author(s) 2023. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved. 2023</rights><rights>The Author(s) 2023. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c369t-29679d22182bf4c70aed52aef8ba87d0d05e4a1a068d30c1f4e88a11cb2792303</citedby><cites>FETCH-LOGICAL-c369t-29679d22182bf4c70aed52aef8ba87d0d05e4a1a068d30c1f4e88a11cb2792303</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27922,27923</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37669569$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Anguelov, Roumen</creatorcontrib><creatorcontrib>Manjunath, G</creatorcontrib><creatorcontrib>Phiri, Avulundiah E</creatorcontrib><creatorcontrib>Nyakudya, Trevor T</creatorcontrib><creatorcontrib>Bipath, Priyesh</creatorcontrib><creatorcontrib>C. Serem, June</creatorcontrib><creatorcontrib>N. Hlophe, Yvette</creatorcontrib><title>Quantifying assays: inhibition of signalling pathways of cancer</title><title>Mathematical medicine and biology</title><addtitle>Math Med Biol</addtitle><description>Abstract
Inhibiting a signalling pathway concerns controlling the cellular processes of a cancer cell’s viability, cell division and death. Assay protocols created to see if the molecular structures of the drugs being tested have the desired inhibition qualities often show great variability across experiments, and it is imperative to diminish the effects of such variability while inferences are drawn. In this paper, we propose the study of experimental data through the lenses of a mathematical model depicting the inhibition mechanism and the activation-inhibition dynamics. The method is exemplified through assay data obtained from an experimental study of the inhibition of the chemokine receptor 4 (CXCR4) and chemokine ligand 12 (CXCL12) signalling pathway of melanoma cells. The quantitative analysis is conducted as a two step process: (i) deriving theoretically from the model the cell viability as a function of time depending on several parameters; (ii) estimating the values of the parameters by using the experimental data. The cell viability is obtained as a function of concentration of the inhibitor and time, thus providing a comprehensive characterization of the potential therapeutic effect of the considered inhibitor, e.g. $IC_{50}$ can be computed for any time point.</description><subject>Cell Line, Tumor</subject><subject>Chemokine CXCL12 - metabolism</subject><subject>Chemokine CXCL12 - pharmacology</subject><subject>Neoplasms - drug therapy</subject><subject>Receptors, CXCR4 - metabolism</subject><subject>Signal Transduction</subject><issn>1477-8599</issn><issn>1477-8602</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkEtLw0AQgBdRbK1ePUqOeki7j2QfXkSKLyiIoOdlsrtpV_JqNkH6701J69XTDMM33-FD6JrgOcGKLXwJZZkt7BYsxukJmpJEiFhyTE-Pe6rUBF2E8I0xZYTLczRhgnOVcjVFDx89VJ3Pd75aRxAC7MJ95KuNz3zn6yqq8yj4dQVFsQca6DY_A7I_G6iMay_RWQ5FcFeHOUNfz0-fy9d49f7ytnxcxYZx1cVUcaEspUTSLE-MwOBsSsHlMgMpLLY4dQkQwFxahg3JEyclEGIyKhRlmM3Q7eht2nrbu9Dp0gfjigIqV_dBU8kJT5JEkAGdj6hp6xBal-umHTK1O02w3kfTYzR9iDY83BzcfVY6-4cfKw3A3QjUffOf7BeVTniB</recordid><startdate>20230915</startdate><enddate>20230915</enddate><creator>Anguelov, Roumen</creator><creator>Manjunath, G</creator><creator>Phiri, Avulundiah E</creator><creator>Nyakudya, Trevor T</creator><creator>Bipath, Priyesh</creator><creator>C. Serem, June</creator><creator>N. Hlophe, Yvette</creator><general>Oxford University Press</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>7X8</scope></search><sort><creationdate>20230915</creationdate><title>Quantifying assays: inhibition of signalling pathways of cancer</title><author>Anguelov, Roumen ; Manjunath, G ; Phiri, Avulundiah E ; Nyakudya, Trevor T ; Bipath, Priyesh ; C. Serem, June ; N. Hlophe, Yvette</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c369t-29679d22182bf4c70aed52aef8ba87d0d05e4a1a068d30c1f4e88a11cb2792303</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Cell Line, Tumor</topic><topic>Chemokine CXCL12 - metabolism</topic><topic>Chemokine CXCL12 - pharmacology</topic><topic>Neoplasms - drug therapy</topic><topic>Receptors, CXCR4 - metabolism</topic><topic>Signal Transduction</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Anguelov, Roumen</creatorcontrib><creatorcontrib>Manjunath, G</creatorcontrib><creatorcontrib>Phiri, Avulundiah E</creatorcontrib><creatorcontrib>Nyakudya, Trevor T</creatorcontrib><creatorcontrib>Bipath, Priyesh</creatorcontrib><creatorcontrib>C. Serem, June</creatorcontrib><creatorcontrib>N. Hlophe, Yvette</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Mathematical medicine and biology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Anguelov, Roumen</au><au>Manjunath, G</au><au>Phiri, Avulundiah E</au><au>Nyakudya, Trevor T</au><au>Bipath, Priyesh</au><au>C. Serem, June</au><au>N. Hlophe, Yvette</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Quantifying assays: inhibition of signalling pathways of cancer</atitle><jtitle>Mathematical medicine and biology</jtitle><addtitle>Math Med Biol</addtitle><date>2023-09-15</date><risdate>2023</risdate><volume>40</volume><issue>3</issue><spage>266</spage><epage>290</epage><pages>266-290</pages><issn>1477-8599</issn><eissn>1477-8602</eissn><abstract>Abstract
Inhibiting a signalling pathway concerns controlling the cellular processes of a cancer cell’s viability, cell division and death. Assay protocols created to see if the molecular structures of the drugs being tested have the desired inhibition qualities often show great variability across experiments, and it is imperative to diminish the effects of such variability while inferences are drawn. In this paper, we propose the study of experimental data through the lenses of a mathematical model depicting the inhibition mechanism and the activation-inhibition dynamics. The method is exemplified through assay data obtained from an experimental study of the inhibition of the chemokine receptor 4 (CXCR4) and chemokine ligand 12 (CXCL12) signalling pathway of melanoma cells. The quantitative analysis is conducted as a two step process: (i) deriving theoretically from the model the cell viability as a function of time depending on several parameters; (ii) estimating the values of the parameters by using the experimental data. The cell viability is obtained as a function of concentration of the inhibitor and time, thus providing a comprehensive characterization of the potential therapeutic effect of the considered inhibitor, e.g. $IC_{50}$ can be computed for any time point.</abstract><cop>England</cop><pub>Oxford University Press</pub><pmid>37669569</pmid><doi>10.1093/imammb/dqad005</doi><tpages>25</tpages><oa>free_for_read</oa></addata></record> |
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source | MEDLINE; Oxford University Press Journals All Titles (1996-Current); Alma/SFX Local Collection |
subjects | Cell Line, Tumor Chemokine CXCL12 - metabolism Chemokine CXCL12 - pharmacology Neoplasms - drug therapy Receptors, CXCR4 - metabolism Signal Transduction |
title | Quantifying assays: inhibition of signalling pathways of cancer |
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