Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer with high proliferative and metastatic phenotypes. CDCA7, a new member of the cell division cycle associated family of genes, is involved in embryonic development and dysregulated in various types of human cancer. However, the biological role and molecular mechanism of CDCA7 in TNBC have not been defined. Herein, we found that CDCA7 was preferentially and markedly expressed in TNBC cell lines and tissues. High expression of CDCA7 was associated with metastatic relapse status and predicted poorer disease-free survival in patients with TNBC. We observed that CDCA7 silencing in TNBC cell lines effectively impaired cell proliferation, invasion and migration in vitro. Importantly, depletion of CDCA7 strongly reduced the tumorigenicity and distant colonization capacities of TNBC cells in vivo. Furthermore, CDCA7 increased the expression of EZH2, a marker of aggressive breast cancer that is involved in tumor progression, by enhancing the transcriptional activity of its promoter. This increase in EZH2 expression was essential for the CDCA7-mediated effects on TNBC progression. Finally, our immunohistochemical analysis revealed that the CDCA7/EZH2 axis was clinical relevant. These findings suggest CDCA7 plays a crucial role in TNBC progression by transcriptionally upregulating EZH2 and might be a potential prognostic factor and therapeutic target in TNBC.
The near-infrared (NIR)-mediated novel strategy to control the drug release from nanocarriers has developed rapidly in recent decades. Polyaniline as a non-cytotoxic and electroactive material for studying cellular proliferation has attracted great attention in recent years. In the present work, polyaniline-mediated polymeric nanoparticles were developed to target the delivery of cisplatin and release it in a controllable way. The prepared polyaniline nanoparticles displayed a size of 90 ± 1.0 nm, a favorable morphology in water, and could be targeted to tumors through the high affinity between trastuzumab and the overexpressed Her2 in tumor cells. In addition, the developed nanoparticles demonstrated exciting photothermal conversion efficiency induced by NIR light and achieved significant cell inhibition efficiency (93.97%) in vitro when exposed to an 808 nm NIR laser with the power of 1.54 W for 5 min. Therefore, the developed external control release delivery system with excellent specificity and high cytotoxicity exhibited great potential in cell research and our research demonstrated that the polyaniline also has potential in the application of photothermal conversion in biomedicine.
The process of computationally identifying and categorizing opinions expressed in a piece of text is of great importance to support better understanding and services to online users in the digital environment. However, accurate and fast multi-label automatic classification is still insufficient. By considering not only individual in-sentence features but also the features in the adjacent sentences and the full text of the tweet, this study adjusted the Multi-label K-Nearest Neighbors (MLkNN) classifier to allow iterative corrections of the multi-label emotion classification. It applies the new method to improve both the accuracy and speed of emotion classification for short texts on Twitter. By carrying out three groups of experiments on the Twitter corpus, this study compares the performance of the base classifier of MLkNN, the sample-based MLkNN (S-MLkNN), and the label-based MLkNN (L-MLkNN). The results show that the improved MLkNN algorithm can effectively improve the accuracy of emotion classification of short texts, especially when the value of K in the MLkNN base classifier is 8, and the value of α is 0.7, and the improved L-MLkNN algorithm outperforms the other methods in the overall performance and the recall rate reaches 0.8019. This study attempts to obtain an efficient classifier with smaller training samples and lower training costs for sentiment analysis. It is suggested that future studies should pay more attention to balancing the efficiency of the model with smaller training sample sizes and the completeness of the model to cover various scenarios.
Cisplatin is a potent antitumor drug, which is widely applied in clinical cancer treatment. However, cisplatin can hardly distinguish between healthy tissue and tumor tissue, resulting in serious toxic side effects. Indocyanine green (ICG) is a FDA-approved near-infrared (NIR) fluorescence dye which has been used in photothermal therapy and optically mediated diagnostic, but the application of ICG is limited by its concentration-dependent aggregation, poor aqueous stability in vitro, lack of target specificity and rapid elimination from the body. Herein, to overcome these limitations of cisplatin and ICG, we fabricated folate-modified, cisplatin, ICG-loaded lipid-polymer hybrid nanoparticles (FCINPs) using a single-step sonication method. The FCINPs exhibited well-defined monodispersity, significant stability and excellent NIR penetration ability. The intracellular uptake experiment showed that the targeting efficacy of the FCINPs was more effective in folate receptors (FRs) over-expressing MCF-7 cells than FRs negative A549 cells. In addition, compared with chemo or photothermal treatment alone, the treatment of FCINPs in combination with 808 nm NIR laser irradiation can significantly induce the apoptosis and necrosis of MCF-7 cells. These findings indicated that the FCINPs would be a promising nanosized drug formulation for tumor-targeted therapy in the future.
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