The role of the MAD2-TLR4-MyD88 axis in paclitaxel resistance in ovarian cancer.
Antineoplastic Agents, Phytogenic
/ pharmacology
Biomarkers, Tumor
/ genetics
Cell Line, Tumor
Cellular Senescence
/ genetics
Drug Resistance, Neoplasm
/ genetics
Female
Gene Expression Regulation, Neoplastic
Gene Knockdown Techniques
Humans
Mad2 Proteins
/ genetics
Myeloid Differentiation Factor 88
/ genetics
Ovarian Neoplasms
/ drug therapy
Paclitaxel
/ pharmacology
RNA, Small Interfering
/ metabolism
Toll-Like Receptor 4
/ genetics
Journal
PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081
Informations de publication
Date de publication:
2020
2020
Historique:
received:
24
10
2019
accepted:
25
11
2020
entrez:
28
12
2020
pubmed:
29
12
2020
medline:
2
2
2021
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 33370338
doi: 10.1371/journal.pone.0243715
pii: PONE-D-19-29743
pmc: PMC7769460
doi:
Substances chimiques
Antineoplastic Agents, Phytogenic
0
Biomarkers, Tumor
0
MAD2L1 protein, human
0
MYD88 protein, human
0
Mad2 Proteins
0
Myeloid Differentiation Factor 88
0
RNA, Small Interfering
0
TLR4 protein, human
0
Toll-Like Receptor 4
0
Paclitaxel
P88XT4IS4D
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e0243715Déclaration de conflit d'intérêts
The authors have declared that no competing interests exist.
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