The role of the MAD2-TLR4-MyD88 axis in paclitaxel resistance in ovarian cancer
Despite the use of front-line anticancer drugs such as paclitaxel for ovarian cancer treatment, mortality rates have remained almost unchanged for the past three decades and the majority of patients will develop recurrent chemoresistant disease which remains largely untreatable. Overcoming chemoresi...
Gespeichert in:
| Veröffentlicht in: | PloS one 2020-12, Vol.15 (12), p.e0243715-e0243715 |
|---|---|
| Hauptverfasser: | , , , , , , , , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | e0243715 |
|---|---|
| container_issue | 12 |
| container_start_page | e0243715 |
| container_title | PloS one |
| container_volume | 15 |
| creator | Bates, Mark Spillane, Cathy D Gallagher, Michael F McCann, Amanda Martin, Cara Blackshields, Gordon Keegan, Helen Gubbins, Luke Brooks, Robert Brooks, Doug Selemidis, Stavros O'Toole, Sharon O'Leary, John J |
| description | Despite the use of front-line anticancer drugs such as paclitaxel for ovarian cancer treatment, mortality rates have remained almost unchanged for the past three decades and the majority of patients will develop recurrent chemoresistant disease which remains largely untreatable. Overcoming chemoresistance or preventing its onset in the first instance remains one of the major challenges for ovarian cancer research. In this study, we demonstrate a key link between senescence and inflammation and how this complex network involving the biomarkers MAD2, TLR4 and MyD88 drives paclitaxel resistance in ovarian cancer. This was investigated using siRNA knockdown of MAD2, TLR4 and MyD88 in two ovarian cancer cell lines, A2780 and SKOV-3 cells and overexpression of MyD88 in A2780 cells. Interestingly, siRNA knockdown of MAD2 led to a significant increase in TLR4 gene expression, this was coupled with the development of a highly paclitaxel-resistant cell phenotype. Additionally, siRNA knockdown of MAD2 or TLR4 in the serous ovarian cell model OVCAR-3 resulted in a significant increase in TLR4 or MAD2 expression respectively. Microarray analysis of SKOV-3 cells following knockdown of TLR4 or MAD2 highlighted a number of significantly altered biological processes including EMT, complement, coagulation, proliferation and survival, ECM remodelling, olfactory receptor signalling, ErbB signalling, DNA packaging, Insulin-like growth factor signalling, ion transport and alteration of components of the cytoskeleton. Cross comparison of the microarray data sets identified 7 overlapping genes including MMP13, ACTBL2, AMTN, PLXDC2, LYZL1, CCBE1 and CKS2. These results demonstrate an important link between these biomarkers, which to our knowledge has never before been shown in ovarian cancer. In the future, we hope that triaging patients into alterative treatment groups based on the expression of these three biomarkers or therapeutic targeting of the mechanisms they are involved in will lead to improvements in patient outcome and prevent the development of chemoresistance. |
| doi_str_mv | 10.1371/journal.pone.0243715 |
| format | Article |
| fullrecord | <record><control><sourceid>gale_plos_</sourceid><recordid>TN_cdi_plos_journals_2473448630</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A646874230</galeid><doaj_id>oai_doaj_org_article_1b4173fb417c4b46a697ca0c7cfb267a</doaj_id><sourcerecordid>A646874230</sourcerecordid><originalsourceid>FETCH-LOGICAL-c692t-bc782e81c4cef5e2ad9fba43dbeac427dc967ce6320e1b23a080392431249b283</originalsourceid><addsrcrecordid>eNqNkl1r2zAUhs3YWLtu_2BshsHYLpzJkiLJN4PQ7iPQEuiy3YpjWU4UFCuV7JL--8mNW-LRiyGQxNFzXukcvUnyNkeTnPD8y8Z1vgE72blGTxCmMTZ9lpzmBcEZw4g8P9qfJK9C2CA0JYKxl8kJIYQjQsRpsliudeqd1amr0zbur2YXOFteXtPs6u5CiBT2JqSmSXegrGlhr23qdTChhUbp_sDdgjfQpKoP-NfJixps0G-G9Sz5_f3b8vxndrn4MT-fXWaKFbjNSsUF1iJXVOl6qjFURV0CJVWpQVHMK1UwrjQjGOm8xASQQKSIReaYFiUW5Cx5f9DdWRfk0IsgMeWEUsEIisT8QFQONnLnzRb8nXRg5H3A-ZUE3xpltcxLmnNS97OiJWXACq4AKa7qEjMOUevrcFtXbnWldNN6sCPR8Ulj1nLlbiXnrKCsf8ynQcC7m06HVm5NUNpaaLTrDu_mVIjpNKIf_kGfrm6gVhALME3t4r2qF5UzRpngFN9TkyeoOCq9NSoapzYxPkr4PEqITKv37Qq6EOT81_X_s4s_Y_bjEbvWYNt1cLZrjWvCGKQHUHkXgtf1Y5NzJHvfP3RD9r6Xg-9j2rvjD3pMejA6-QsHsfrO</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2473448630</pqid></control><display><type>article</type><title>The role of the MAD2-TLR4-MyD88 axis in paclitaxel resistance in ovarian cancer</title><source>MEDLINE</source><source>DOAJ Directory of Open Access Journals</source><source>Public Library of Science (PLoS) Journals Open Access</source><source>EZB-FREE-00999 freely available EZB journals</source><source>PubMed Central</source><source>Free Full-Text Journals in Chemistry</source><creator>Bates, Mark ; Spillane, Cathy D ; Gallagher, Michael F ; McCann, Amanda ; Martin, Cara ; Blackshields, Gordon ; Keegan, Helen ; Gubbins, Luke ; Brooks, Robert ; Brooks, Doug ; Selemidis, Stavros ; O'Toole, Sharon ; O'Leary, John J</creator><contributor>Chan, David Wai</contributor><creatorcontrib>Bates, Mark ; Spillane, Cathy D ; Gallagher, Michael F ; McCann, Amanda ; Martin, Cara ; Blackshields, Gordon ; Keegan, Helen ; Gubbins, Luke ; Brooks, Robert ; Brooks, Doug ; Selemidis, Stavros ; O'Toole, Sharon ; O'Leary, John J ; Chan, David Wai</creatorcontrib><description>Despite the use of front-line anticancer drugs such as paclitaxel for ovarian cancer treatment, mortality rates have remained almost unchanged for the past three decades and the majority of patients will develop recurrent chemoresistant disease which remains largely untreatable. Overcoming chemoresistance or preventing its onset in the first instance remains one of the major challenges for ovarian cancer research. In this study, we demonstrate a key link between senescence and inflammation and how this complex network involving the biomarkers MAD2, TLR4 and MyD88 drives paclitaxel resistance in ovarian cancer. This was investigated using siRNA knockdown of MAD2, TLR4 and MyD88 in two ovarian cancer cell lines, A2780 and SKOV-3 cells and overexpression of MyD88 in A2780 cells. Interestingly, siRNA knockdown of MAD2 led to a significant increase in TLR4 gene expression, this was coupled with the development of a highly paclitaxel-resistant cell phenotype. Additionally, siRNA knockdown of MAD2 or TLR4 in the serous ovarian cell model OVCAR-3 resulted in a significant increase in TLR4 or MAD2 expression respectively. Microarray analysis of SKOV-3 cells following knockdown of TLR4 or MAD2 highlighted a number of significantly altered biological processes including EMT, complement, coagulation, proliferation and survival, ECM remodelling, olfactory receptor signalling, ErbB signalling, DNA packaging, Insulin-like growth factor signalling, ion transport and alteration of components of the cytoskeleton. Cross comparison of the microarray data sets identified 7 overlapping genes including MMP13, ACTBL2, AMTN, PLXDC2, LYZL1, CCBE1 and CKS2. These results demonstrate an important link between these biomarkers, which to our knowledge has never before been shown in ovarian cancer. In the future, we hope that triaging patients into alterative treatment groups based on the expression of these three biomarkers or therapeutic targeting of the mechanisms they are involved in will lead to improvements in patient outcome and prevent the development of chemoresistance.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0243715</identifier><identifier>PMID: 33370338</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Antineoplastic Agents, Phytogenic - pharmacology ; Antineoplastic Agents, Phytogenic - therapeutic use ; Antineoplastic drugs ; Antitumor agents ; Biological activity ; Biology and life sciences ; Biomarkers ; Biomarkers, Tumor - genetics ; Cancer therapies ; Care and treatment ; Cell division ; Cell Line, Tumor ; Cellular Senescence - genetics ; Chemoresistance ; Chromosomes ; Coagulation ; Collagenase 3 ; Cytokines ; Cytoskeleton ; Deoxyribonucleic acid ; Development and progression ; DNA ; DNA microarrays ; Drug development ; Drug resistance ; Drug Resistance, Neoplasm - genetics ; ErbB protein ; Extracellular matrix ; Female ; Gene expression ; Gene Expression Regulation, Neoplastic ; Gene Knockdown Techniques ; Genotype & phenotype ; Growth factors ; Gynecology ; Health sciences ; Histopathology ; Hospitals ; Humans ; Insulin ; Ion transport ; Laboratories ; Ligands ; Mad2 Proteins - genetics ; Medical prognosis ; Medical research ; Medicine and Health Sciences ; MyD88 protein ; Myeloid Differentiation Factor 88 - genetics ; Obstetrics ; Ovarian cancer ; Ovarian carcinoma ; Ovarian Neoplasms - drug therapy ; Ovarian Neoplasms - genetics ; Ovarian Neoplasms - pathology ; Packaging ; Paclitaxel ; Paclitaxel - pharmacology ; Paclitaxel - therapeutic use ; Pathology ; Patient outcomes ; Patients ; Pharmacy ; Phenotypes ; Prevention ; Research and Analysis Methods ; RNA, Small Interfering - metabolism ; Senescence ; Signaling ; siRNA ; Therapeutic targets ; TLR4 protein ; Toll-Like Receptor 4 - genetics ; Toll-like receptors ; Tumor cell lines ; Womens health</subject><ispartof>PloS one, 2020-12, Vol.15 (12), p.e0243715-e0243715</ispartof><rights>COPYRIGHT 2020 Public Library of Science</rights><rights>2020 Bates et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://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>2020 Bates et al 2020 Bates et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-bc782e81c4cef5e2ad9fba43dbeac427dc967ce6320e1b23a080392431249b283</citedby><cites>FETCH-LOGICAL-c692t-bc782e81c4cef5e2ad9fba43dbeac427dc967ce6320e1b23a080392431249b283</cites><orcidid>0000-0002-5916-5403 ; 0000-0003-1535-8999</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7769460/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7769460/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2102,2928,23866,27924,27925,53791,53793,79600,79601</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33370338$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Chan, David Wai</contributor><creatorcontrib>Bates, Mark</creatorcontrib><creatorcontrib>Spillane, Cathy D</creatorcontrib><creatorcontrib>Gallagher, Michael F</creatorcontrib><creatorcontrib>McCann, Amanda</creatorcontrib><creatorcontrib>Martin, Cara</creatorcontrib><creatorcontrib>Blackshields, Gordon</creatorcontrib><creatorcontrib>Keegan, Helen</creatorcontrib><creatorcontrib>Gubbins, Luke</creatorcontrib><creatorcontrib>Brooks, Robert</creatorcontrib><creatorcontrib>Brooks, Doug</creatorcontrib><creatorcontrib>Selemidis, Stavros</creatorcontrib><creatorcontrib>O'Toole, Sharon</creatorcontrib><creatorcontrib>O'Leary, John J</creatorcontrib><title>The role of the MAD2-TLR4-MyD88 axis in paclitaxel resistance in ovarian cancer</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Despite the use of front-line anticancer drugs such as paclitaxel for ovarian cancer treatment, mortality rates have remained almost unchanged for the past three decades and the majority of patients will develop recurrent chemoresistant disease which remains largely untreatable. Overcoming chemoresistance or preventing its onset in the first instance remains one of the major challenges for ovarian cancer research. In this study, we demonstrate a key link between senescence and inflammation and how this complex network involving the biomarkers MAD2, TLR4 and MyD88 drives paclitaxel resistance in ovarian cancer. This was investigated using siRNA knockdown of MAD2, TLR4 and MyD88 in two ovarian cancer cell lines, A2780 and SKOV-3 cells and overexpression of MyD88 in A2780 cells. Interestingly, siRNA knockdown of MAD2 led to a significant increase in TLR4 gene expression, this was coupled with the development of a highly paclitaxel-resistant cell phenotype. Additionally, siRNA knockdown of MAD2 or TLR4 in the serous ovarian cell model OVCAR-3 resulted in a significant increase in TLR4 or MAD2 expression respectively. Microarray analysis of SKOV-3 cells following knockdown of TLR4 or MAD2 highlighted a number of significantly altered biological processes including EMT, complement, coagulation, proliferation and survival, ECM remodelling, olfactory receptor signalling, ErbB signalling, DNA packaging, Insulin-like growth factor signalling, ion transport and alteration of components of the cytoskeleton. Cross comparison of the microarray data sets identified 7 overlapping genes including MMP13, ACTBL2, AMTN, PLXDC2, LYZL1, CCBE1 and CKS2. These results demonstrate an important link between these biomarkers, which to our knowledge has never before been shown in ovarian cancer. In the future, we hope that triaging patients into alterative treatment groups based on the expression of these three biomarkers or therapeutic targeting of the mechanisms they are involved in will lead to improvements in patient outcome and prevent the development of chemoresistance.</description><subject>Antineoplastic Agents, Phytogenic - pharmacology</subject><subject>Antineoplastic Agents, Phytogenic - therapeutic use</subject><subject>Antineoplastic drugs</subject><subject>Antitumor agents</subject><subject>Biological activity</subject><subject>Biology and life sciences</subject><subject>Biomarkers</subject><subject>Biomarkers, Tumor - genetics</subject><subject>Cancer therapies</subject><subject>Care and treatment</subject><subject>Cell division</subject><subject>Cell Line, Tumor</subject><subject>Cellular Senescence - genetics</subject><subject>Chemoresistance</subject><subject>Chromosomes</subject><subject>Coagulation</subject><subject>Collagenase 3</subject><subject>Cytokines</subject><subject>Cytoskeleton</subject><subject>Deoxyribonucleic acid</subject><subject>Development and progression</subject><subject>DNA</subject><subject>DNA microarrays</subject><subject>Drug development</subject><subject>Drug resistance</subject><subject>Drug Resistance, Neoplasm - genetics</subject><subject>ErbB protein</subject><subject>Extracellular matrix</subject><subject>Female</subject><subject>Gene expression</subject><subject>Gene Expression Regulation, Neoplastic</subject><subject>Gene Knockdown Techniques</subject><subject>Genotype & phenotype</subject><subject>Growth factors</subject><subject>Gynecology</subject><subject>Health sciences</subject><subject>Histopathology</subject><subject>Hospitals</subject><subject>Humans</subject><subject>Insulin</subject><subject>Ion transport</subject><subject>Laboratories</subject><subject>Ligands</subject><subject>Mad2 Proteins - genetics</subject><subject>Medical prognosis</subject><subject>Medical research</subject><subject>Medicine and Health Sciences</subject><subject>MyD88 protein</subject><subject>Myeloid Differentiation Factor 88 - genetics</subject><subject>Obstetrics</subject><subject>Ovarian cancer</subject><subject>Ovarian carcinoma</subject><subject>Ovarian Neoplasms - drug therapy</subject><subject>Ovarian Neoplasms - genetics</subject><subject>Ovarian Neoplasms - pathology</subject><subject>Packaging</subject><subject>Paclitaxel</subject><subject>Paclitaxel - pharmacology</subject><subject>Paclitaxel - therapeutic use</subject><subject>Pathology</subject><subject>Patient outcomes</subject><subject>Patients</subject><subject>Pharmacy</subject><subject>Phenotypes</subject><subject>Prevention</subject><subject>Research and Analysis Methods</subject><subject>RNA, Small Interfering - metabolism</subject><subject>Senescence</subject><subject>Signaling</subject><subject>siRNA</subject><subject>Therapeutic targets</subject><subject>TLR4 protein</subject><subject>Toll-Like Receptor 4 - genetics</subject><subject>Toll-like receptors</subject><subject>Tumor cell lines</subject><subject>Womens health</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>DOA</sourceid><recordid>eNqNkl1r2zAUhs3YWLtu_2BshsHYLpzJkiLJN4PQ7iPQEuiy3YpjWU4UFCuV7JL--8mNW-LRiyGQxNFzXukcvUnyNkeTnPD8y8Z1vgE72blGTxCmMTZ9lpzmBcEZw4g8P9qfJK9C2CA0JYKxl8kJIYQjQsRpsliudeqd1amr0zbur2YXOFteXtPs6u5CiBT2JqSmSXegrGlhr23qdTChhUbp_sDdgjfQpKoP-NfJixps0G-G9Sz5_f3b8vxndrn4MT-fXWaKFbjNSsUF1iJXVOl6qjFURV0CJVWpQVHMK1UwrjQjGOm8xASQQKSIReaYFiUW5Cx5f9DdWRfk0IsgMeWEUsEIisT8QFQONnLnzRb8nXRg5H3A-ZUE3xpltcxLmnNS97OiJWXACq4AKa7qEjMOUevrcFtXbnWldNN6sCPR8Ulj1nLlbiXnrKCsf8ynQcC7m06HVm5NUNpaaLTrDu_mVIjpNKIf_kGfrm6gVhALME3t4r2qF5UzRpngFN9TkyeoOCq9NSoapzYxPkr4PEqITKv37Qq6EOT81_X_s4s_Y_bjEbvWYNt1cLZrjWvCGKQHUHkXgtf1Y5NzJHvfP3RD9r6Xg-9j2rvjD3pMejA6-QsHsfrO</recordid><startdate>20201228</startdate><enddate>20201228</enddate><creator>Bates, Mark</creator><creator>Spillane, Cathy D</creator><creator>Gallagher, Michael F</creator><creator>McCann, Amanda</creator><creator>Martin, Cara</creator><creator>Blackshields, Gordon</creator><creator>Keegan, Helen</creator><creator>Gubbins, Luke</creator><creator>Brooks, Robert</creator><creator>Brooks, Doug</creator><creator>Selemidis, Stavros</creator><creator>O'Toole, Sharon</creator><creator>O'Leary, John J</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>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-5916-5403</orcidid><orcidid>https://orcid.org/0000-0003-1535-8999</orcidid></search><sort><creationdate>20201228</creationdate><title>The role of the MAD2-TLR4-MyD88 axis in paclitaxel resistance in ovarian cancer</title><author>Bates, Mark ; Spillane, Cathy D ; Gallagher, Michael F ; McCann, Amanda ; Martin, Cara ; Blackshields, Gordon ; Keegan, Helen ; Gubbins, Luke ; Brooks, Robert ; Brooks, Doug ; Selemidis, Stavros ; O'Toole, Sharon ; O'Leary, John J</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c692t-bc782e81c4cef5e2ad9fba43dbeac427dc967ce6320e1b23a080392431249b283</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Antineoplastic Agents, Phytogenic - pharmacology</topic><topic>Antineoplastic Agents, Phytogenic - therapeutic use</topic><topic>Antineoplastic drugs</topic><topic>Antitumor agents</topic><topic>Biological activity</topic><topic>Biology and life sciences</topic><topic>Biomarkers</topic><topic>Biomarkers, Tumor - genetics</topic><topic>Cancer therapies</topic><topic>Care and treatment</topic><topic>Cell division</topic><topic>Cell Line, Tumor</topic><topic>Cellular Senescence - genetics</topic><topic>Chemoresistance</topic><topic>Chromosomes</topic><topic>Coagulation</topic><topic>Collagenase 3</topic><topic>Cytokines</topic><topic>Cytoskeleton</topic><topic>Deoxyribonucleic acid</topic><topic>Development and progression</topic><topic>DNA</topic><topic>DNA microarrays</topic><topic>Drug development</topic><topic>Drug resistance</topic><topic>Drug Resistance, Neoplasm - genetics</topic><topic>ErbB protein</topic><topic>Extracellular matrix</topic><topic>Female</topic><topic>Gene expression</topic><topic>Gene Expression Regulation, Neoplastic</topic><topic>Gene Knockdown Techniques</topic><topic>Genotype & phenotype</topic><topic>Growth factors</topic><topic>Gynecology</topic><topic>Health sciences</topic><topic>Histopathology</topic><topic>Hospitals</topic><topic>Humans</topic><topic>Insulin</topic><topic>Ion transport</topic><topic>Laboratories</topic><topic>Ligands</topic><topic>Mad2 Proteins - genetics</topic><topic>Medical prognosis</topic><topic>Medical research</topic><topic>Medicine and Health Sciences</topic><topic>MyD88 protein</topic><topic>Myeloid Differentiation Factor 88 - genetics</topic><topic>Obstetrics</topic><topic>Ovarian cancer</topic><topic>Ovarian carcinoma</topic><topic>Ovarian Neoplasms - drug therapy</topic><topic>Ovarian Neoplasms - genetics</topic><topic>Ovarian Neoplasms - pathology</topic><topic>Packaging</topic><topic>Paclitaxel</topic><topic>Paclitaxel - pharmacology</topic><topic>Paclitaxel - therapeutic use</topic><topic>Pathology</topic><topic>Patient outcomes</topic><topic>Patients</topic><topic>Pharmacy</topic><topic>Phenotypes</topic><topic>Prevention</topic><topic>Research and Analysis Methods</topic><topic>RNA, Small Interfering - metabolism</topic><topic>Senescence</topic><topic>Signaling</topic><topic>siRNA</topic><topic>Therapeutic targets</topic><topic>TLR4 protein</topic><topic>Toll-Like Receptor 4 - genetics</topic><topic>Toll-like receptors</topic><topic>Tumor cell lines</topic><topic>Womens health</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bates, Mark</creatorcontrib><creatorcontrib>Spillane, Cathy D</creatorcontrib><creatorcontrib>Gallagher, Michael F</creatorcontrib><creatorcontrib>McCann, Amanda</creatorcontrib><creatorcontrib>Martin, Cara</creatorcontrib><creatorcontrib>Blackshields, Gordon</creatorcontrib><creatorcontrib>Keegan, Helen</creatorcontrib><creatorcontrib>Gubbins, Luke</creatorcontrib><creatorcontrib>Brooks, Robert</creatorcontrib><creatorcontrib>Brooks, Doug</creatorcontrib><creatorcontrib>Selemidis, Stavros</creatorcontrib><creatorcontrib>O'Toole, Sharon</creatorcontrib><creatorcontrib>O'Leary, John J</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 Edition)</collection><collection>ProQuest Central UK/Ireland</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>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>Agricultural Science Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Engineering Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Advanced Technologies & Aerospace Database</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>Access via ProQuest (Open Access)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</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>Bates, Mark</au><au>Spillane, Cathy D</au><au>Gallagher, Michael F</au><au>McCann, Amanda</au><au>Martin, Cara</au><au>Blackshields, Gordon</au><au>Keegan, Helen</au><au>Gubbins, Luke</au><au>Brooks, Robert</au><au>Brooks, Doug</au><au>Selemidis, Stavros</au><au>O'Toole, Sharon</au><au>O'Leary, John J</au><au>Chan, David Wai</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The role of the MAD2-TLR4-MyD88 axis in paclitaxel resistance in ovarian cancer</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2020-12-28</date><risdate>2020</risdate><volume>15</volume><issue>12</issue><spage>e0243715</spage><epage>e0243715</epage><pages>e0243715-e0243715</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Despite the use of front-line anticancer drugs such as paclitaxel for ovarian cancer treatment, mortality rates have remained almost unchanged for the past three decades and the majority of patients will develop recurrent chemoresistant disease which remains largely untreatable. Overcoming chemoresistance or preventing its onset in the first instance remains one of the major challenges for ovarian cancer research. In this study, we demonstrate a key link between senescence and inflammation and how this complex network involving the biomarkers MAD2, TLR4 and MyD88 drives paclitaxel resistance in ovarian cancer. This was investigated using siRNA knockdown of MAD2, TLR4 and MyD88 in two ovarian cancer cell lines, A2780 and SKOV-3 cells and overexpression of MyD88 in A2780 cells. Interestingly, siRNA knockdown of MAD2 led to a significant increase in TLR4 gene expression, this was coupled with the development of a highly paclitaxel-resistant cell phenotype. Additionally, siRNA knockdown of MAD2 or TLR4 in the serous ovarian cell model OVCAR-3 resulted in a significant increase in TLR4 or MAD2 expression respectively. Microarray analysis of SKOV-3 cells following knockdown of TLR4 or MAD2 highlighted a number of significantly altered biological processes including EMT, complement, coagulation, proliferation and survival, ECM remodelling, olfactory receptor signalling, ErbB signalling, DNA packaging, Insulin-like growth factor signalling, ion transport and alteration of components of the cytoskeleton. Cross comparison of the microarray data sets identified 7 overlapping genes including MMP13, ACTBL2, AMTN, PLXDC2, LYZL1, CCBE1 and CKS2. These results demonstrate an important link between these biomarkers, which to our knowledge has never before been shown in ovarian cancer. In the future, we hope that triaging patients into alterative treatment groups based on the expression of these three biomarkers or therapeutic targeting of the mechanisms they are involved in will lead to improvements in patient outcome and prevent the development of chemoresistance.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>33370338</pmid><doi>10.1371/journal.pone.0243715</doi><tpages>e0243715</tpages><orcidid>https://orcid.org/0000-0002-5916-5403</orcidid><orcidid>https://orcid.org/0000-0003-1535-8999</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2020-12, Vol.15 (12), p.e0243715-e0243715 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_2473448630 |
| source | MEDLINE; DOAJ Directory of Open Access Journals; Public Library of Science (PLoS) Journals Open Access; EZB-FREE-00999 freely available EZB journals; PubMed Central; Free Full-Text Journals in Chemistry |
| subjects | Antineoplastic Agents, Phytogenic - pharmacology Antineoplastic Agents, Phytogenic - therapeutic use Antineoplastic drugs Antitumor agents Biological activity Biology and life sciences Biomarkers Biomarkers, Tumor - genetics Cancer therapies Care and treatment Cell division Cell Line, Tumor Cellular Senescence - genetics Chemoresistance Chromosomes Coagulation Collagenase 3 Cytokines Cytoskeleton Deoxyribonucleic acid Development and progression DNA DNA microarrays Drug development Drug resistance Drug Resistance, Neoplasm - genetics ErbB protein Extracellular matrix Female Gene expression Gene Expression Regulation, Neoplastic Gene Knockdown Techniques Genotype & phenotype Growth factors Gynecology Health sciences Histopathology Hospitals Humans Insulin Ion transport Laboratories Ligands Mad2 Proteins - genetics Medical prognosis Medical research Medicine and Health Sciences MyD88 protein Myeloid Differentiation Factor 88 - genetics Obstetrics Ovarian cancer Ovarian carcinoma Ovarian Neoplasms - drug therapy Ovarian Neoplasms - genetics Ovarian Neoplasms - pathology Packaging Paclitaxel Paclitaxel - pharmacology Paclitaxel - therapeutic use Pathology Patient outcomes Patients Pharmacy Phenotypes Prevention Research and Analysis Methods RNA, Small Interfering - metabolism Senescence Signaling siRNA Therapeutic targets TLR4 protein Toll-Like Receptor 4 - genetics Toll-like receptors Tumor cell lines Womens health |
| title | The role of the MAD2-TLR4-MyD88 axis in paclitaxel resistance in ovarian cancer |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-03T10%3A08%3A28IST&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=The%20role%20of%20the%20MAD2-TLR4-MyD88%20axis%20in%20paclitaxel%20resistance%20in%20ovarian%20cancer&rft.jtitle=PloS%20one&rft.au=Bates,%20Mark&rft.date=2020-12-28&rft.volume=15&rft.issue=12&rft.spage=e0243715&rft.epage=e0243715&rft.pages=e0243715-e0243715&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0243715&rft_dat=%3Cgale_plos_%3EA646874230%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2473448630&rft_id=info:pmid/33370338&rft_galeid=A646874230&rft_doaj_id=oai_doaj_org_article_1b4173fb417c4b46a697ca0c7cfb267a&rfr_iscdi=true |