A systems approach to uncovering the adaptive response of cancer to targeted therapies
Thesis (S.M.)--Massachusetts Institute of Technology, Computational and Systems Biology Program, 2012. === Cataloged from PDF version of thesis. === Includes bibliographical references (p. 47-53). === Tyrosine kinase inhibitors have significant promise in the fight to develop agents that can target...
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ndltd-MIT-oai-dspace.mit.edu-1721.1-729672019-05-02T15:52:41Z A systems approach to uncovering the adaptive response of cancer to targeted therapies Randall, Adrian Joseph Forest M. White. Massachusetts Institute of Technology. Computational and Systems Biology Program. Massachusetts Institute of Technology. Computational and Systems Biology Program. Computational and Systems Biology Program. Thesis (S.M.)--Massachusetts Institute of Technology, Computational and Systems Biology Program, 2012. Cataloged from PDF version of thesis. Includes bibliographical references (p. 47-53). Tyrosine kinase inhibitors have significant promise in the fight to develop agents that can target cancer in a tumor-specific manner. A number of drugs have been and are currently in development to inhibit specific kinases that can mediate uncontrolled proliferation; however, an unfortunate eventuality for most patients receiving these treatments is the development of resistance that renders these drugs almost completely ineffective. While a number of mechanisms can evolve within a tumor to mitigate effects of kinase inhibitors, we sought to uncover what changes are occurring in the tyrosine phosphorylation network at both short timescales (minutes to 72 hours) and long timescales (120 hours+) that can be playing a role in helping a tumor become resistant to driver-kinase inhibition. It is our hypothesis that specific feedback networks are able to detect and overcome driver kinase inhibition through activation of potential other pathways, which can go on to mediate a longer term resistance phenotype. In order to probe dynamics in the tyrosine phosphorylation network, we employed mass spectrometry to analyze peptides derived from six non-small cell lung cancer cell lines that we classify as either EGFR+ or EML4-ALK+. From both mass spectrometry data and growth assays, we identified an unintuitive boost in signaling and growth in response to low inhibitor concentrations, suggestive of a cellular mechanism that is adaptive to driver kinase inhibition. Studies of EML4-ALK driven H3122 cells showed that this short-term response is not the same as the known long-term resistance mechanism to ALK inhibition, leading support to the notion that the short-term "adaptive response" may be a novel type of mechanism to aid tumor adaptation to targeted therapies. In an effort to better probe signaling events occurring downstream of the phosphotyrosine network, a new pull down technique for mass spectrometry using 14-3-3 protein against phosphoserine and phosphothreonine peptides is described. The results of these studies open up many potential avenues for further exploration into the immediate and long-term signaling response of cancer to targeted therapies. by Adrian Joseph Randall. S.M. 2012-09-14T17:15:44Z 2012-09-14T17:15:44Z 2012 2012 Thesis http://hdl.handle.net/1721.1/72967 806957193 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 53 p. application/pdf Massachusetts Institute of Technology |
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Computational and Systems Biology Program. Randall, Adrian Joseph A systems approach to uncovering the adaptive response of cancer to targeted therapies |
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Thesis (S.M.)--Massachusetts Institute of Technology, Computational and Systems Biology Program, 2012. === Cataloged from PDF version of thesis. === Includes bibliographical references (p. 47-53). === Tyrosine kinase inhibitors have significant promise in the fight to develop agents that can target cancer in a tumor-specific manner. A number of drugs have been and are currently in development to inhibit specific kinases that can mediate uncontrolled proliferation; however, an unfortunate eventuality for most patients receiving these treatments is the development of resistance that renders these drugs almost completely ineffective. While a number of mechanisms can evolve within a tumor to mitigate effects of kinase inhibitors, we sought to uncover what changes are occurring in the tyrosine phosphorylation network at both short timescales (minutes to 72 hours) and long timescales (120 hours+) that can be playing a role in helping a tumor become resistant to driver-kinase inhibition. It is our hypothesis that specific feedback networks are able to detect and overcome driver kinase inhibition through activation of potential other pathways, which can go on to mediate a longer term resistance phenotype. In order to probe dynamics in the tyrosine phosphorylation network, we employed mass spectrometry to analyze peptides derived from six non-small cell lung cancer cell lines that we classify as either EGFR+ or EML4-ALK+. From both mass spectrometry data and growth assays, we identified an unintuitive boost in signaling and growth in response to low inhibitor concentrations, suggestive of a cellular mechanism that is adaptive to driver kinase inhibition. Studies of EML4-ALK driven H3122 cells showed that this short-term response is not the same as the known long-term resistance mechanism to ALK inhibition, leading support to the notion that the short-term "adaptive response" may be a novel type of mechanism to aid tumor adaptation to targeted therapies. In an effort to better probe signaling events occurring downstream of the phosphotyrosine network, a new pull down technique for mass spectrometry using 14-3-3 protein against phosphoserine and phosphothreonine peptides is described. The results of these studies open up many potential avenues for further exploration into the immediate and long-term signaling response of cancer to targeted therapies. === by Adrian Joseph Randall. === S.M. |
author2 |
Forest M. White. |
author_facet |
Forest M. White. Randall, Adrian Joseph |
author |
Randall, Adrian Joseph |
author_sort |
Randall, Adrian Joseph |
title |
A systems approach to uncovering the adaptive response of cancer to targeted therapies |
title_short |
A systems approach to uncovering the adaptive response of cancer to targeted therapies |
title_full |
A systems approach to uncovering the adaptive response of cancer to targeted therapies |
title_fullStr |
A systems approach to uncovering the adaptive response of cancer to targeted therapies |
title_full_unstemmed |
A systems approach to uncovering the adaptive response of cancer to targeted therapies |
title_sort |
systems approach to uncovering the adaptive response of cancer to targeted therapies |
publisher |
Massachusetts Institute of Technology |
publishDate |
2012 |
url |
http://hdl.handle.net/1721.1/72967 |
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AT randalladrianjoseph asystemsapproachtouncoveringtheadaptiveresponseofcancertotargetedtherapies AT randalladrianjoseph systemsapproachtouncoveringtheadaptiveresponseofcancertotargetedtherapies |
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1719030239255855104 |