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Bayesian model of signal rewiring reveals mechanisms of gene dysregulation in acquired drug resistance in breast cancer
Small molecule inhibitors, such as lapatinib, are effective against breast cancer in clinical trials, but tumor cells ultimately acquire resistance to the drug. Maintaining sensitization to drug action is essential for durable growth inhibition. Recently, adaptive reprogramming of signaling circuitr...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5348014/ https://www.ncbi.nlm.nih.gov/pubmed/28288164 http://dx.doi.org/10.1371/journal.pone.0173331 |
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author | Azad, A. K. M. Lawen, Alfons Keith, Jonathan M. |
author_facet | Azad, A. K. M. Lawen, Alfons Keith, Jonathan M. |
author_sort | Azad, A. K. M. |
collection | PubMed |
description | Small molecule inhibitors, such as lapatinib, are effective against breast cancer in clinical trials, but tumor cells ultimately acquire resistance to the drug. Maintaining sensitization to drug action is essential for durable growth inhibition. Recently, adaptive reprogramming of signaling circuitry has been identified as a major cause of acquired resistance. We developed a computational framework using a Bayesian statistical approach to model signal rewiring in acquired resistance. We used the p(1)-model to infer potential aberrant gene-pairs with differential posterior probabilities of appearing in resistant-vs-parental networks. Results were obtained using matched gene expression profiles under resistant and parental conditions. Using two lapatinib-treated ErbB2-positive breast cancer cell-lines: SKBR3 and BT474, our method identified similar dysregulated signaling pathways including EGFR-related pathways as well as other receptor-related pathways, many of which were reported previously as compensatory pathways of EGFR-inhibition via signaling cross-talk. A manual literature survey provided strong evidence that aberrant signaling activities in dysregulated pathways are closely related to acquired resistance in EGFR tyrosine kinase inhibitors. Our approach predicted literature-supported dysregulated pathways complementary to both node-centric (SPIA, DAVID, and GATHER) and edge-centric (ESEA and PAGI) methods. Moreover, by proposing a novel pattern of aberrant signaling called V-structures, we observed that genes were dysregulated in resistant-vs-sensitive conditions when they were involved in the switch of dependencies from targeted to bypass signaling events. A literature survey of some important V-structures suggested they play a role in breast cancer metastasis and/or acquired resistance to EGFR-TKIs, where the mRNA changes of TGFBR2, LEF1 and TP53 in resistant-vs-sensitive conditions were related to the dependency switch from targeted to bypass signaling links. Our results suggest many signaling pathway structures are compromised in acquired resistance, and V-structures of aberrant signaling within/among those pathways may provide further insights into the bypass mechanism of targeted inhibition. |
format | Online Article Text |
id | pubmed-5348014 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-53480142017-03-30 Bayesian model of signal rewiring reveals mechanisms of gene dysregulation in acquired drug resistance in breast cancer Azad, A. K. M. Lawen, Alfons Keith, Jonathan M. PLoS One Research Article Small molecule inhibitors, such as lapatinib, are effective against breast cancer in clinical trials, but tumor cells ultimately acquire resistance to the drug. Maintaining sensitization to drug action is essential for durable growth inhibition. Recently, adaptive reprogramming of signaling circuitry has been identified as a major cause of acquired resistance. We developed a computational framework using a Bayesian statistical approach to model signal rewiring in acquired resistance. We used the p(1)-model to infer potential aberrant gene-pairs with differential posterior probabilities of appearing in resistant-vs-parental networks. Results were obtained using matched gene expression profiles under resistant and parental conditions. Using two lapatinib-treated ErbB2-positive breast cancer cell-lines: SKBR3 and BT474, our method identified similar dysregulated signaling pathways including EGFR-related pathways as well as other receptor-related pathways, many of which were reported previously as compensatory pathways of EGFR-inhibition via signaling cross-talk. A manual literature survey provided strong evidence that aberrant signaling activities in dysregulated pathways are closely related to acquired resistance in EGFR tyrosine kinase inhibitors. Our approach predicted literature-supported dysregulated pathways complementary to both node-centric (SPIA, DAVID, and GATHER) and edge-centric (ESEA and PAGI) methods. Moreover, by proposing a novel pattern of aberrant signaling called V-structures, we observed that genes were dysregulated in resistant-vs-sensitive conditions when they were involved in the switch of dependencies from targeted to bypass signaling events. A literature survey of some important V-structures suggested they play a role in breast cancer metastasis and/or acquired resistance to EGFR-TKIs, where the mRNA changes of TGFBR2, LEF1 and TP53 in resistant-vs-sensitive conditions were related to the dependency switch from targeted to bypass signaling links. Our results suggest many signaling pathway structures are compromised in acquired resistance, and V-structures of aberrant signaling within/among those pathways may provide further insights into the bypass mechanism of targeted inhibition. Public Library of Science 2017-03-13 /pmc/articles/PMC5348014/ /pubmed/28288164 http://dx.doi.org/10.1371/journal.pone.0173331 Text en © 2017 Azad et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Azad, A. K. M. Lawen, Alfons Keith, Jonathan M. Bayesian model of signal rewiring reveals mechanisms of gene dysregulation in acquired drug resistance in breast cancer |
title | Bayesian model of signal rewiring reveals mechanisms of gene dysregulation in acquired drug resistance in breast cancer |
title_full | Bayesian model of signal rewiring reveals mechanisms of gene dysregulation in acquired drug resistance in breast cancer |
title_fullStr | Bayesian model of signal rewiring reveals mechanisms of gene dysregulation in acquired drug resistance in breast cancer |
title_full_unstemmed | Bayesian model of signal rewiring reveals mechanisms of gene dysregulation in acquired drug resistance in breast cancer |
title_short | Bayesian model of signal rewiring reveals mechanisms of gene dysregulation in acquired drug resistance in breast cancer |
title_sort | bayesian model of signal rewiring reveals mechanisms of gene dysregulation in acquired drug resistance in breast cancer |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5348014/ https://www.ncbi.nlm.nih.gov/pubmed/28288164 http://dx.doi.org/10.1371/journal.pone.0173331 |
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