Statins: a repurposed drug to fight cancer Jiang, Wen; Hu, Jin-Wei; He, Xu-Ran ...
Journal of experimental & clinical cancer research,
07/2021, Volume:
40, Issue:
1
Journal Article
Peer reviewed
Open access
As competitive HMG-CoA reductase (HMGCR) inhibitors, statins not only reduce cholesterol and improve cardiovascular risk, but also exhibit pleiotropic effects that are independent of their ...lipid-lowering effects. Among them, the anti-cancer properties of statins have attracted much attention and indicated the potential of statins as repurposed drugs for the treatment of cancer. A large number of clinical and epidemiological studies have described the anticancer properties of statins, but the evidence for anticancer effectiveness of statins is inconsistent. It may be that certain molecular subtypes of cancer are more vulnerable to statin therapy than others. Whether statins have clinical anticancer effects is still an active area of research. Statins appear to enhance the efficacy and address the shortcomings associated with conventional cancer treatments, suggesting that statins should be considered in the context of combined therapies for cancer. Here, we present a comprehensive review of the potential of statins in anti-cancer treatments. We discuss the current understanding of the mechanisms underlying the anti-cancer properties of statins and their effects on different malignancies. We also provide recommendations for the design of future well-designed clinical trials of the anti-cancer efficacy of statins.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
The continued threat of emerging, highly lethal infectious pathogens such as Middle East respiratory syndrome coronavirus (MERS‐CoV) calls for the development of novel vaccine technology that offers ...safe and effective prophylactic measures. Here, a novel nanoparticle vaccine is developed to deliver subunit viral antigens and STING agonists in a virus‐like fashion. STING agonists are first encapsulated into capsid‐like hollow polymeric nanoparticles, which show multiple favorable attributes, including a pH‐responsive release profile, prominent local immune activation, and reduced systemic reactogenicity. Upon subsequent antigen conjugation, the nanoparticles carry morphological semblance to native virions and facilitate codelivery of antigens and STING agonists to draining lymph nodes and immune cells for immune potentiation. Nanoparticle vaccine effectiveness is supported by the elicitation of potent neutralization antibody and antigen‐specific T cell responses in mice immunized with a MERS‐CoV nanoparticle vaccine candidate. Using a MERS‐CoV‐permissive transgenic mouse model, it is shown that mice immunized with this nanoparticle‐based MERS‐CoV vaccine are protected against a lethal challenge of MERS‐CoV without triggering undesirable eosinophilic immunopathology. Together, the biocompatible hollow nanoparticle described herein provides an excellent strategy for delivering both subunit vaccine candidates and novel adjuvants, enabling accelerated development of effective and safe vaccines against emerging viral pathogens.
To improve vaccination efforts against Middle East respiratory syndrome coronavirus (MERS‐CoV), a virus‐mimicking vaccine is herein prepared with a capsid‐like hollow polymeric nanoparticle loaded with STING agonists and coated in MERS‐CoV antigens. The viromimetic nanoparticle facilitates safe and effective vaccination against the lethal virus and offers a versatile platform for combatting emerging infectious threats.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
• Under-sampling class imbalance data by the clustering technique is studied.• Cluster centers and their nearest neighbors of the majority class are used individually.• Using the nearest neighbors of ...cluster centers in the majority class performs the best.• This approach combined with the MLP classifier is a better choice for small scale datasets.• This approach combined with C4.5 classifier ensembles is good at large scale datasets.
Class imbalance is often a problem in various real-world data sets, where one class (i.e. the minority class) contains a small number of data points and the other (i.e. the majority class) contains a large number of data points. It is notably difficult to develop an effective model using current data mining and machine learning algorithms without considering data preprocessing to balance the imbalanced data sets. Random undersampling and oversampling have been used in numerous studies to ensure that the different classes contain the same number of data points. A classifier ensemble (i.e. a structure containing several classifiers) can be trained on several different balanced data sets for later classification purposes. In this paper, we introduce two undersampling strategies in which a clustering technique is used during the data preprocessing step. Specifically, the number of clusters in the majority class is set to be equal to the number of data points in the minority class. The first strategy uses the cluster centers to represent the majority class, whereas the second strategy uses the nearest neighbors of the cluster centers. A further study was conducted to examine the effect on performance of the addition or deletion of 5 to 10 cluster centers in the majority class. The experimental results obtained using 44 small-scale and 2 large-scale data sets revealed that the clustering-based undersampling approach with the second strategy outperformed five state-of-the-art approaches. Specifically, this approach combined with a single multilayer perceptron classifier and C4.5 decision tree classifier ensembles delivered optimal performance over both small- and large-scale data sets.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Abstract
The remarkable advances in next-generation sequencing technology have enabled the wide usage of sequencing as a clinical tool. To promote the advance of precision oncology for breast cancer ...in China, here we report a large-scale prospective clinical sequencing program using the Fudan-BC panel, and comprehensively analyze the clinical and genomic characteristics of Chinese breast cancer. The mutational landscape of 1,134 breast cancers reveals that the most significant differences between Chinese and Western patients occurred in the hormone receptor positive, human epidermal growth factor receptor 2 negative breast cancer subtype. Mutations in p53 and Hippo signaling pathways are more prevalent, and 2 mutually exclusive and 9 co-occurring patterns exist among 9 oncogenic pathways in our cohort. Further preclinical investigation partially suggests that
NF2
loss-of-function mutations can be sensitive to a Hippo-targeted strategy. We establish a public database (Fudan Portal) and a precision medicine knowledge base for data exchange and interpretation. Collectively, our study presents a leading approach to Chinese precision oncology treatment and reveals potentially actionable mutations in breast cancer.
The health crisis due to coronavirus disease 2019 (COVID-19) has shocked the world, with more than 1 million infections and casualties. COVID-19 can present from mild illness to multi-organ ...involvement, but especially acute respiratory distress syndrome. Cardiac injury and arrhythmias, including atrial fibrillation (AF), are not uncommon in COVID-19. COVID-19 is highly contagious, and therapy against the virus remains premature and largely unknown, which makes the management of AF patients during the pandemic particularly challenging. We describe a possible pathophysiological link between COVID-19 and AF, and therapeutic considerations for AF patients during this pandemic.
•A novel approach for under-sampling class imbalanced datasets is proposed.•It is based on combining clustering analysis and instance selection.•Instance selection is used for the clustering result ...of the majority class dataset.•The proposed approach outperforms five baseline approaches over 44 datasets.
Class-imbalanced datasets, i.e., those with the number of data samples in one class being much larger than that in another class, occur in many real-world problems. Using these datasets, it is very difficult to construct effective classifiers based on the current classification algorithms, especially for distinguishing small or minority classes from the majority class. To solve the class imbalance problem, the under/oversampling techniques have been widely used to reduce and enlarge the numbers of data samples in the majority and minority classes, respectively. Moreover, the combinations of certain sampling approaches with ensemble classifiers have shown reasonably good performance. In this paper, a novel undersampling approach called cluster-based instance selection (CBIS) that combines clustering analysis and instance selection is introduced. The clustering analysis component groups similar data samples of the majority class dataset into ‘subclasses’, while the instance selection component filters out unrepresentative data samples from each of the ‘subclasses’. The experimental results based on the KEEL dataset repository show that the CBIS approach can make bagging and boosting-based MLP ensemble classifiers perform significantly better than six state-of-the-art approaches, regardless of what kinds of clustering (affinity propagation and k-means) and instance selection (IB3, DROP3 and GA) algorithms are used.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
As the dawn of the postantibiotic era we approach, antibacterial vaccines are becoming increasingly important for managing bacterial infection and reducing the need for antibiotics. Despite the ...success of vaccination, vaccines remain unavailable for many pressing microbial diseases, including tuberculosis, chlamydia, and staphylococcus infections. Amid continuing research efforts in antibacterial vaccine development, the advancement of nanomaterial engineering has brought forth new opportunities in vaccine designs. With increasing knowledge in antibacterial immunity and immunologic adjuvants, innovative nanoparticles are designed to elicit the appropriate immune responses for effective antimicrobial defense. Rationally designed nanoparticles are demonstrated to overcome delivery barriers to shape the adaptive immunity. This article reviews the advances in nanoparticle‐ and nanomaterial‐based antibacterial vaccines and summarizes the development of nanoparticulate adjuvants for immune potentiation against microbial pathogens. In addition, challenges and progress in ongoing antibacterial vaccine development are discussed to highlight the opportunities for future vaccine designs.
Nanoparticle vaccines for antibacterial vaccination present a compelling intervention toward disease management in the postantibiotic era. This review article summarizes advances in the field of nanoparticle antibacterial vaccines and highlights the strengths of different carrier platforms. Challenges and opportunities in vaccine development against several pressing microbial pathogens are also examined.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
To identify the major infiltrating phagocytes during leptospirosis and examine the killing mechanism used by the host to eliminate Leptospira interrogans.
Major infiltrating phagocytes in ...Leptospira-infected C3H/HeJ mice were detected by immunohistochemistry. Chemokines and vascular endothelial cell adhesion molecules (VECAMs) of Leptospira-infected mice and leptospirosis patients were detected by microarray and immunohistochemistry. Leptospira-phagocytosing and -killing abilities of human or mouse macrophages and neutrophils, and the roles of intracellular ROS, NO and Ca2+i in Leptospira-killing process were evaluated by confocal microscopy and spectrofluorimetry.
Peripheral blood mononuclear-macrophages rather than neutrophils were the main infiltrating phagocytes in the lungs, liver and kidneys of infected mice. Levels of macrophage- but not neutrophil-specific chemokines and VECAMs were significantly increased in the samples from infected mice and patients. All macrophages tested had a higher ability than neutrophils to phagocytose and kill leptospires. Higher ROS and NO levels and Ca2+i in the macrophages were involved in killing leptospires. Human macrophages displayed more phagolysosome formation and a stronger leptospire-killing ability to than mouse macrophages.
Mononuclear-macrophages but not neutrophils represent the main infiltrating and anti-leptospiral phagocytes during leptospirosis. A lower level of phagosome-lysosome fusion may be responsible for the lower Leptospira-killing ability of human macrophages.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
A novel salicylideneaniline-based fluorescent sensor, SB1, with a unique excited-state intramolecular charge transfer–excited-state intramolecular proton transfer (ESICT–ESIPT) coupled system was ...synthesized and demonstrated to fluorescently sense CN– with specific selectivity and high sensitivity in aqueous media based on ESICT–ESIPT switching. A large blue shift (96 nm) was also observed in the absorption spectra in response to CN–. The bleaching of the color could be clearly observed by the naked eye. Moreover, SB1-based test strips were easily fabricated and low-cost, and could be used in practical and efficient CN– test kits. Density functional theory (DFT) and time-dependent DFT (TD-DFT) calculations further support the cyanide-induced ESICT–ESIPT switching mechanism. The results provide the proof of concept that the colorimetric and ratiometric fluorescent cyanide-selective chemodosimeter can be created based on an ESICT–ESIPT coupled system.
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IJS, KILJ, NUK, PNG, UL, UM
SMYD3, a member that belongs to the SET and MYND-domain (SMYD) family, has also been proven to largely participate in gene transcription regulation and progression of several human cancers as a ...histone lysine methyltransferase. However, the role and significance of SMYD3 in both the clinic and progression of hepatocellular carcinoma (HCC) remain unclear. Herein, we find that SMYD3 is increased in cirrhotic livers, and strikingly upregulated in hepatocellular carcinoma (HCC) tissues and cell lines. Subsequent analyses suggest that high expression level of SMYD3 significantly correlates with the malignant characteristics of HCC, and predicts poor prognosis in patients. Our results show that overexpression of SMYD3 increases, while silencing of SMYD3 inhibits, cell proliferation, invasiveness and tumorigenicity both in vitro and in vivo. SMYD3 also promotes intrahepatic metastasis of HCC cells. For the mechanisms, we identify that SMYD3 bound to CDK2 and MMP2 promoter and increased H3K4me3 modification at the corresponding promoters to promote gene transcription. Importantly, pharmacological targeting of SMYD3 with BCI-121 inhibitor effectively repressed the tumorigenicity of HCC cells. Finally, our results show that gene locus amplification is a cause for SMYD3 overexpression in HCC. These findings not only uncover that SMYD3 overexpression promotes the tumorigenicity and intrahepatic metastasis of HCC cell via upregulation of CDK2 and MMP2, but also suggest SMYD3 could be a practical prognosis marker or therapeutic target against the disease.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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