Department of Histopathology, Trinity College Dublin, Dublin, Ireland.
Emer Casey Molecular Pathology Research Laboratory, Coombe Women & Infants University Hospital, Dublin, Ireland.
PLoS One. 2020 Dec 28;15(12):e0243715. doi: 10.1371/journal.pone.0243715. eCollection 2020.
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.
尽管在卵巢癌治疗中使用了紫杉醇等一线抗癌药物，但在过去的三十年中，死亡率几乎没有变化，而且大多数患者会出现复发性化疗耐药疾病，而这种疾病在很大程度上仍然无法治疗。克服化疗耐药性或在第一时间预防其发生仍然是卵巢癌研究的主要挑战之一。在这项研究中，我们证明了衰老和炎症之间存在着关键联系，以及涉及生物标志物 MAD2、TLR4 和 MyD88 的这种复杂网络如何驱动卵巢癌对紫杉醇的耐药性。我们使用两种卵巢癌细胞系 A2780 和 SKOV-3 中的 MAD2、TLR4 和 MyD88 的 siRNA 敲低以及 A2780 细胞中 MyD88 的过表达来研究这一点。有趣的是，MAD2 的 siRNA 敲低导致 TLR4 基因表达显著增加，这与紫杉醇耐药细胞表型的发展有关。此外，在浆液性卵巢细胞模型 OVCAR-3 中，MAD2 或 TLR4 的 siRNA 敲低分别导致 TLR4 或 MAD2 表达的显著增加。TLR4 或 MAD2 敲低后的 SKOV-3 细胞的微阵列分析突出了许多显著改变的生物学过程，包括 EMT、补体、凝血、增殖和存活、ECM 重塑、嗅觉受体信号、ErbB 信号、DNA 包装、胰岛素样生长因子信号、离子转运和细胞骨架成分的改变。微阵列数据集的交叉比较确定了 7 个重叠基因，包括 MMP13、ACTBL2、AMTN、PLXDC2、LYZL1、CCBE1 和 CKS2。这些结果表明这些生物标志物之间存在重要联系，据我们所知，这在卵巢癌中从未有过报道。在未来，我们希望根据这三个生物标志物的表达或它们所涉及的机制的治疗靶向，将患者分诊到替代治疗组，从而改善患者的预后并防止化疗耐药性的发展。
