BackgroundBromodomain and extra-terminal domain inhibitors like JQ1 have proved to be promising epigenetic agents for the treatment of malignant ovarian carcinoma. However, the resistance of ovarian cancer cells to BET inhibitors has not been elucidated. In this study, we investigated the potential mechanisms underlying the resistance of ovarian cancer cell lines to the BET inhibitor JQ1.Materials and methodsWe evaluated the apoptotic and proliferative response of four ovarian cancer cell lines to JQ1. The cell lines were designated as resistant (A2780 and HO-8910) and sensitive groups (SKOV-3 and HEY). Further experiments detected the different levels of JQ1-induced autophagy. Anti-tumour effect of the combination of JQ1 and autophagy inhibitors was tested both in vitro and in vivo.ResultsIn the JQ1-sensitive group, JQ1 effectively inhibited proliferation and apoptosis in a concentration-dependent manner. Conversely, JQ1 showed modest inhibition of proliferation and negligible apoptosis in the resistant group. We detected increased LC3-II lipidation, autophagosome formation, upregulation of Beclin-1 and ATG5, and downregulation of P62/SQSTM1 in the resistant group. Inhibition of JQ1-induced autophagy by pharmacologic inhibitors 3-MA and CQ enhanced the inhibition of proliferation and significantly increased the apoptosis in the JQ1-resistant group, which was also verified by in vivo experiments, indicating that JQ1-induced autophagy played a cytoprotective role. Inactivation of Akt (Ser473)/mTOR(Ser2448) pathway was associated with JQ1-induced autophagy in the resistant group. Overexpression of Akt1 suppressed autophagy and increased the anti-tumour effect of JQ1.ConclusionThese findings revealed that JQ1-induced pro-survival autophagy might be a potential mechanism in the resistance of ovarian cancer cells to BET inhibition by JQ1. Combination of JQ1 and autophagy inhibitors could be an effective therapeutic strategy for overcoming BET inhibitor resistance in ovarian cancer.
A high diversity of pleurostomatid ciliates has been discovered in the last decade, and their systematics needs to be improved in the light of new findings concerning their morphology and molecular phylogeny. In this work, a new genus, Protolitonotus gen. n., and two new species, Protolitonotus magnus sp. n. and Protolitonotus longus sp. n., were studied. Furthermore, 19 novel nucleotide sequences of SSU rDNA, LSU rDNA and ITS1‐5.8S‐ITS2 were collected to determine the phylogenetic relationships and systematic positions of the pleurostomatid ciliates in this study. Based on both molecular and morphological data, the results demonstrated that: (i) as disclosed by the sequence analysis of SSU rDNA, LSU rDNA and ITS1‐5.8S‐ITS2, Protolitonotus gen. n. is sister to all other pleurostomatids and thus represents an independent lineage and a separate family, Protolitonotidae fam. n., which is defined by the presence of a semi‐suture formed by the right somatic kineties near the dorsal margin of the body; (ii) the families Litonotidae and Kentrophyllidae are both monophyletic based on both SSU rDNA and LSU rDNA sequences, whereas Amphileptidae are non‐monophyletic in trees inferred from SSU rDNA sequences; and (iii) the genera Loxophyllum and Kentrophyllum are both monophyletic, whereas Litonotus is non‐monophyletic based on SSU rDNA analyses. ITS1‐5.8S‐ITS2 sequence data were used for the phylogenetic analyses of pleurostomatids for the first time; however, species relationships were less well resolved than in the SSU rDNA and LSU rDNA trees. In addition, a major revision to the classification of the order Pleurostomatida is suggested and a key to its families and genera is provided.
Aim: The effects of different types of gastric neuroendocrine tumors (G-NETs) on treatment strategy formulation and prognostic evaluation still remain controversial due to their rarity. Methods: 187 patients diagnosed with G-NETs were subdivided into four types based on the pathophysiology, etiology and presentation. Results: Type I, II G-NETs >1.0 cm and type III, IV G-NETs >2.0 cm are proved with aggressive behavior (p < 0.05). Type III G-NETs with higher Ki-67 index and tumor stage showed more invasive potential than type I and II G-NETs (p < 0.05). Endoscopic resection is the primary treatment for type I, II G-NETs, while surgical combined with chemotherapy is associated with favorable outcomes for type IV G-NETs. Conclusion: The clinical classifications of G-NETs are of great significance for the choice of treatment and the evaluation of prognosis.
The biological function and underlying mechanism of microRNA‐628‐5p (miR‐628‐5p) remains to be clarified in the growth and progression of pancreatic ductal adenocarcinoma (PDAC). Here, the expression levels of miR‐628‐5p in PDAC tissues and cells were detected by quantitative reverse transcriptase polymerase chain reaction and in situ hybridization. The relationship between miR‐628‐5p expression and clinicopathologic characteristics was examined in human PDAC tissue samples. Gain‐ and loss‐of‐function and the putative targets of miR‐628‐5p were evaluated in PDAC cell lines. The upstream and downstream signals of miR‐628‐5p in PDAC were also examined. MiR‐628‐5p was lowly expressed in PDAC tissues and cell lines, and low miR‐628‐5p expression in PDAC tissues was associated with poor clinicopathological characteristics and shorter overall survival. Functionally, restoration of miR‐628‐5p expression decreased PDAC cell proliferation, migration, invasion, and promoted cell apoptosis, whereas miR‐628‐5p silencing abolished these biological behaviors. MiR‐628‐5p was found to target and negatively regulate phospholipid scramblase 1 and insulin receptor substrate 1 expression, which resulted in the inhibition of the AKT/NF‐κB signaling pathway. MYC knockdown led to miR‐628‐5p upregulation, whereas MYC overexpression repressed miR‐628‐5p expression. These findings indicate that miR‐628‐5p functions as a tumor‐suppressive microRNA in PDAC and implicate miR‐628‐5p as a potential therapeutic target for PDAC patients.
The authors of this paper have advised that when they rechecked their data and figures, they found one mistake in Figure 1C on page 8065. Figure 1C reflects the effects of different concentrations of JQ1 on the apoptosis level.
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