A Ru(II)-Based Nanoassembly Exhibiting Theranostic PACT Activity in NIR Region

Photoactivated chemotherapy (PACT) has appealing merits over traditional chemotherapy as well as photodynamic therapy (PDT) by virtue of its spatial and temporal control on drug activity and oxygen-independent mechanisms of action. However, the short photoactivation wavelengths, e.g., visible light–activated Ru(II)-based PACT agents, limit the clinical application severely. In this work, a facile construction of supramolecular nanoparticles from a poly(ethylene glycol) (PEG)-modified [Ru(dip)₂(py-SO₃)]⁺ (abbreviated as Ru-PEG, dip = 4,7-diphenyl-1,10-phenanthroline, py-SO₃ = pyridine-2-sulfonate) and 1,3-phenylenebis(pyren-1-ylmethanone) (BP) is shown. While Ru-PEG may undergo photoinduced ligand dissociation and release anticancer species of [Ru(dip)₂(H₂O)₂]²⁺, BP has extremely large two-photon absorption cross sections (δ₂) in the NIR region and intense fluorescence over the wavelengths where Ru-PEG has strong absorption. Thus, two-photon excitation of BP followed by an efficient Förster resonance energy transfer (FRET) from BP to Ru-PEG may lead to a potent inactivation against cisplatin-resistant cancer cells and 3D multicellular tumor spheroids (MCTSs). The residue fluorescence of BP also allows the cellular uptake of the particles to be visualized. This work provides a universal and convenient strategy to realize theranostic PACT in the ideal phototherapeutic window of 650–900 nm.     

Metabolic Tumor Imaging with Rapidly Signal-Enhanced 1-13C-Pyruvate-d3

The metabolism of malignant cells differs significantly from that of healthy cells and thus, it is possible to perform metabolic imaging to reveal not only the exact location of a tumor, but also intratumoral areas of high metabolic activity. Herein, we demonstrate the feasibility of metabolic tumor imaging using signal-enhanced 1-¹³C-pyruvate-d₃, which is rapidly enhanced via para-hydrogen, and thus, the signal is amplified by several orders of magnitudes in less than a minute. Using as a model, human melanoma xenografts injected with signal-enhanced 1-¹³C-pyruvate-d3, we show that the conversion of pyruvate into lactate can be monitored along with its kinetics, which could pave the way for rapidly detecting and monitoring changes in tumor metabolism.     

Advances in Targeting Drug Biological Carriers for Enhancing Tumor Therapy Efficacy

Chemotherapy drugs continue to be the main component of oncology treatment research and have been proven to be the main treatment modality in tumor therapy. However, the poor delivery efficiency of cancer therapeutic drugs and their potential off-target toxicity significantly limit their effectiveness and extensive application. The recent integration of biological carriers and functional agents is expected to camouflage synthetic biomimetic nanoparticles for targeted delivery. The promising candidates, including but not limited to red blood cells and their membranes, platelets, tumor cell membrane, bacteria, immune cell membrane, and hybrid membrane are typical representatives of biological carriers because of their excellent biocompatibility and biodegradability. Biological carriers are widely used to deliver chemotherapy drugs to improve the effectiveness of drug delivery and therapeutic efficacy in vivo, and tremendous progress is made in this field. This review summarizes recent developments in biological vectors as targeted drug delivery systems based on microenvironmental stimuli-responsive release, thus highlighting the potential applications of target drug biological carriers. The review also discusses the possibility of clinical translation, as well as the exploitation trend of these target drug biological carriers.     

血液中循环肿瘤细胞捕获与释放方法研究进展

血液中的循环肿瘤细胞(CTCs)与癌症转移密切相关,对CTCs进行检测有利于实现癌症早期诊断。但由于血液中CTCs个数稀少且存在异质性,因此急需发展血液中CTCs的高效分离及检测方法。此外,释放被捕获的细胞并进行后续培养及基因水平分析,将会进一步推进癌症的个性化治疗。本文综述了近年来CTCs捕获及释放的相关研究进展,并展望了其应用前景及发展方向。     

Far‐Red and Near‐IR AIE‐Active Fluorescent Organic Nanoprobes with Enhanced Tumor‐Targeting Efficacy: Shape‐Specific Effects

The rational design of high‐performance fluorescent materials for cancer targeting in vivo is still challenging. A unique molecular design strategy is presented that involves tailoring aggregation‐induced emission (AIE)‐active organic molecules to realize preferable far‐red and NIR fluorescence, well‐controlled morphology (from rod‐like to spherical), and also tumor‐targeted bioimaging. The shape‐tailored organic quinoline–malononitrile (QM) nanoprobes are biocompatible and highly desirable for cell‐tracking applications. Impressively, the spherical shape of QM‐5 nanoaggregates exhibits excellent tumor‐targeted bioimaging performance after intravenously injection into mice, but not the rod‐like aggregates of QM‐2.     

Fluorescent In Situ Targeting Probes for Rapid Imaging of Ovarian‐Cancer‐Specific γ‐Glutamyltranspeptidase

γ‐Glutamyltranspeptidase (GGT) is a tumor biomarker that selectively catalyzes the cleavage of glutamate overexpressed on the plasma membrane of tumor cells. Here, we developed two novel fluorescent in situ targeting (FIST) probes that specifically target GGT in tumor cells, which comprise 1) a GGT‐specific substrate unit (GSH), and 2) a boron–dipyrromethene (BODIPY) moiety for fluorescent signalling. In the presence of GGT, sulfur‐substituted BODIPY was converted to amino‐substituted BODIPY, resulting in dramatic fluorescence variations. By exploiting this enzyme‐triggered photophysical property, we employed these FIST probes to monitor the GGT activity in living cells, which showed remarkable differentiation between ovarian cancer cells and normal cells. These probes represent two first‐generation chemodosimeters featuring enzyme‐mediated rapid, irreversible aromatic hydrocarbon transfer between the sulfur and nitrogen atoms accompanied by switching of photophysical properties.     

Network-based ranking methods for prediction of novel disease associated microRNAs

BackgroundMany studies have shown roles of microRNAs on human disease and a number of computational methods have been proposed to predict such associations by ranking candidate microRNAs according to their relevance to a disease. Among them, machine learning-based methods usually have a limitation in specifying non-disease microRNAs as negative training samples. Meanwhile, network-based methods are becoming dominant since they well exploit a “disease module” principle in microRNA functional similarity networks. Of which, random walk with restart (RWR) algorithm-based method is currently state-of-the-art. The use of this algorithm was inspired from its success in predicting disease gene because the “disease module” principle also exists in protein interaction networks. Besides, many algorithms designed for webpage ranking have been successfully applied in ranking disease candidate genes because web networks share topological properties with protein interaction networks. However, these algorithms have not yet been utilized for disease microRNA prediction.MethodsWe constructed microRNA functional similarity networks based on shared targets of microRNAs, and then we integrated them with a microRNA functional synergistic network, which was recently identified. After analyzing topological properties of these networks, in addition to RWR, we assessed the performance of (i) PRINCE (PRIoritizatioN and Complex Elucidation), which was proposed for disease gene prediction; (ii) PageRank with Priors (PRP) and K-Step Markov (KSM), which were used for studying web networks; and (iii) a neighborhood-based algorithm.ResultsAnalyses on topological properties showed that all microRNA functional similarity networks are small-worldness and scale-free. The performance of each algorithm was assessed based on average AUC values on 35 disease phenotypes and average rankings of newly discovered disease microRNAs. As a result, the performance on the integrated network was better than that on individual ones. In addition, the performance of PRINCE, PRP and KSM was comparable with that of RWR, whereas it was worst for the neighborhood-based algorithm. Moreover, all the algorithms were stable with the change of parameters. Final, using the integrated network, we predicted six novel miRNAs (i.e., hsa-miR-101, hsa-miR-181d, hsa-miR-192, hsa-miR-423-3p, hsa-miR-484 and hsa-miR-98) associated with breast cancer.ConclusionsNetwork-based ranking algorithms, which were successfully applied for either disease gene prediction or for studying social/web networks, can be also used effectively for disease microRNA prediction.     

Application of organometallic chemistry in the formulation of a modern therapeutic drug by Ag nanoparticles green-mediated by Allium to treat the breast cancer

In the recent study, we decided to survey the capacities of metallic nanoparticles formulated by Allium monanthum (AgNPs) as a novel chemotherapeutic drug in the treatment of several types of breast cancers. Characterization of AgNPs was done by UV–Visible Spectroscopy (UV–Vis), Fourier Transformed Infrared Spectroscopy (FT‐IR), Transmission Electron Microscopy (TEM), and Field Emission Scanning Electron Microscopy (FE‐SEM). For investigating the antioxidant properties of AgNO₃, Allium monanthum, and AgNPs, the DPPH test was used in the presence of butylated hydroxytoluene as the positive control. To survey the cytotoxicity and anti-breast cancer effects of AgNO₃, Allium monanthum, and AgNPs, MTT assay was used on the breast adenocarcinoma (MCF7), breast carcinoma (Hs 578Bst), infiltrating ductal cell carcinoma (Hs 319.T), infiltrating lobular carcinoma of breast (UACC-3133), inflammatory carcinoma of the breast (UACC-732), and metastatic carcinoma (MDA-MB-453) cell lines. DPPH test revealed similar antioxidant potentials for Allium monanthum, AgNPs, and butylated hydroxytoluene. Silver nanoparticles had very low cell viability and anti-breast cancer properties dose-dependently against MCF7, Hs 578Bst, Hs 319.T, UACC-3133, UACC-732, and MDA-MB-453 cell lines without any cytotoxicity on the normal cell line. The best result of anti-breast cancer properties of AgNPs against the above cell lines was seen in the case of the UACC-3133 cell line. According to the above findings, the silver nanoparticles containing Allium monanthum aqueous extract can be administrated in humans for the treatment of several types of breast cancer especially breast adenocarcinoma, breast carcinoma, infiltrating ductal cell carcinoma, infiltrating lobular carcinoma of breast, inflammatory carcinoma of the breast, and metastatic carcinoma.