The reaction of arsenite with proteins relies on solution conditions.

Arsenic is a biologically interesting element with both antitumor and carcinogenic effects. Zinc finger proteins (ZFPs) have been confirmed to be the cellular targets of arsenite; however, arsenite inhibits ZFPs much less efficiently in vitro than in vivo. The molecular mechanism of this difference is unknown. In this work, we found that the reaction of arsenite with ZFPs relies on the presence of small biomolecules such as glutathione (GSH), histidine, and cysteine (Cys). The weak acidity also enhances the reaction. Further study shows that the coordination of zinc is much more susceptible than that of arsenic to these solution conditions, which enhance the competition of arsenic. Notably, different from C3H-type ZFPs, the C2H2-type ZFPs are more significantly influenced by the presence of thiol-containing molecules in the reaction. GSH and Cys can facilitate the reaction by participation of the coordination to As(III) together with C2H2-type ZFPs. Consequently, the reactions are promoted both thermodynamically and kinetically via the formation of ternary complexes GSH-As-ZFP or Cys-As-ZFP. These results indicate that the reactions between arsenite and proteins are considerably modulated by environments such as the small biomolecules and the acidity of the solution. This finding clarifies the discrepancy observed in the reactions of arsenite in vitro versus in cells, and provides an insight into the molecular mechanism of arsenite.

Predicting Drug-Disease Associations Through Similarity Network Fusion and Multi-View Feature Projection Representation.

Predicting drug-disease associations (DDAs) through computational methods has become a prevalent trend in drug development because of their high efficiency and low cost. Existing methods usually focus on constructing heterogeneous networks by collecting multiple data resources to improve prediction ability. However, potential association possibilities of numerous unconfirmed drug-related or disease-related pairs are not sufficiently considered. In this article, we propose a novel computational model to predict new DDAs. First, a heterogeneous network is constructed, including four types of nodes (drugs, targets, cell lines, diseases) and three types of edges (associations, association scores, similarities). Second, an updating and merging-based similarity network fusion method, termed UM-SF, is presented to fuse various similarity networks with diverse weights. Finally, an intermediate layer-mediated multi-view feature projection representation method, termed IM-FP, is proposed to calculate the predicted DDA scores. This method uses multiple association scores to construct multi-view drug features, then projects them into disease space through the intermediate layer, where an intermediate layer similarity constraint is designed to learn the projection matrices. Results of comparative experiments reveal the effectiveness of our innovations. Comparisons with other state-of-the-art models by the 10-fold cross-validation experiment indicate our model's advantage on AUROC and AUPR metrics. Moreover, our proposed model successfully predicted 107 novel high-ranked DDAs.

Prediction performance of twelve tumor mutation burden panels in melanoma and non-small cell lung cancer.

As a potential biomarker to predict the response to immunotherapy, tumor mutation burden (TMB) which can be estimated by the cancer gene panel (CGP) has received considerable attention. However, it is not clear which CGP is better in predicting the efficacy of immunotherapy. To evaluate the twelve CGPs, we compared them on 13 datasets of melanoma and non-small cell lung cancer (NSCLC) from the perspective of gene composition, reliability of measuring TMB and prediction performance of patient treatment benefits. The larger CGPs generally performed better, but their proportions of driver genes and function densities were smaller. The CGPs performed differently on melanoma and NSCLC patients treated with two blockades. Moreover, their ability to classify and predict patients with or without long-term clinical benefits was similar but not good enough, so it is necessary to explore a higher-performance biomarker.

Early myeloid-derived suppressor cells accelerate epithelial-mesenchymal transition by downregulating ARID1A in luminal A breast cancer.

Early myeloid-derived suppressor cells (eMDSCs) are a newly characterized subclass of MDSCs, which exhibit more potent immunosuppressive capacity than classical MDSCs. Previously, we found high eMDSCs infiltration was correlated with poor prognosis of breast cancer, though the regulatory mechanisms have not been fully understood. Here, we constructed a 21-gene signature to evaluate the status of eMDSCs infiltration within breast cancer tissues and found that highly infiltrated eMDSCs affected the prognosis of breast cancer patients, especially in luminal A subtype. We also found that eMDSCs promoted epithelial-mesenchymal transition (EMT) and accelerated cell migration and invasion in vitro. Meanwhile, eMDSCs significantly downregulated ARID1A expression in luminal A breast cancer, which was closely associated with EMT and was an important prognostic factor in breast cancer patients. Moreover, significant changes of EMT-related genes were detected in luminal A breast cancer cells after co-cultured with eMDSCs or ARID1A knock-down and overexpression of ARID1A significantly reversed this procedure. These results implied that eMDSCs might suppress the ARID1A expression to promote EMT in luminal A breast cancer cells, which might provide a new light on developing novel treatment regimens for relapsed luminal A breast cancer after conventional therapies.

A network-based pathway-extending approach using DNA methylation and gene expression data to identify altered pathways.

Pathway analysis allows us to gain insights into a comprehensive understanding of the molecular mechanisms underlying cancers. Currently, high-throughput multi-omics data and various types of large-scale biological networks enable us to identify cancer-related pathways by comprehensively analyzing these data. Combining information from multidimensional data, pathway databases and interaction networks is a promising strategy to identify cancer-related pathways. Here we present a novel network-based approach for integrative analysis of DNA methylation and gene expression data to extend original pathways. The results show that the extension of original pathways can provide a basis for discovering new components of the original pathway and understanding the crosstalk between pathways in a large-scale biological network. By inputting the gene lists of the extended pathways into the classical gene set analysis (ORA and FCS), we effectively identified the altered pathways which are correlated well with the corresponding cancer. The method is evaluated on three datasets retrieved from TCGA (BRCA, LUAD and COAD). The results show that the integration of DNA methylation and gene expression data through a network of known gene interactions is effective in identifying altered pathways.

Dual functional dinuclear platinum complex with selective reactivity towards c-myc G-quadruplex.

G-quadruplexes (GQ) folded by the oncogenic G-rich sequences are the promising targets for developing anticancer therapeutic molecules. However, the current drug development mainly focused on non-covalent dynamic binders to stabilize GQ structures, while the covalent targeting from inorganic complexes via chelating principles, as a potent therapeutic strategy was surprisingly lack of exploration. Herein, a series of dinuclear platinum complexes, [(Pt(Dip)Cl)2(µ-diamine)](NO3)2 (Dip: 4,7-diphenyl-1,10-phenanthroline), were designed to contain two dual-functional Pt cores connected by an alkyl linkage. Pt3 with nonanediamine linkage optimized the specific binding towards c-myc G-quadruplex via dual functional clamp on GQ as 1) non-covalently π-stacking of aromatic ligands, and 2) two Pt(II) cores covalently chelated to guanines at both 3'- and 5'-ends.

Durability-enhanced two-dimensional hole gas of C-H diamond surface for complementary power inverter applications.

Complementary power field effect transistors (FETs) based on wide bandgap materials not only provide high-voltage switching capability with the reduction of on-resistance and switching losses, but also enable a smart inverter system by the dramatic simplification of external circuits. However, p-channel power FETs with equivalent performance to those of n-channel FETs are not obtained in any wide bandgap material other than diamond. Here we show that a breakdown voltage of more than 1600 V has been obtained in a diamond metal-oxide-semiconductor (MOS) FET with a p-channel based on a two-dimensional hole gas (2DHG). Atomic layer deposited (ALD) Al2O3 induces the 2DHG ubiquitously on a hydrogen-terminated (C-H) diamond surface and also acts as both gate insulator and passivation layer. The high voltage performance is equivalent to that of state-of-the-art SiC planar n-channel FETs and AlGaN/GaN FETs. The drain current density in the on-state is also comparable to that of these two FETs with similar device size and VB.

Cisplatin binds to human copper chaperone Cox17: the mechanistic implication of drug delivery to mitochondria.

Cox17 facilitates the platinum accumulation in mitochondria, which contributes to the overall cytotoxicity of cisplatin.

Chemical and cellular investigations of trans-ammine-pyridine-dichlorido-platinum(II), the likely metabolite of the antitumor active cis-diammine-pyridine-chorido-platinum(II).

It has been proposed that the well-studied monofunctional platinum complex cis-[PtCl(NH3)2(py)](+) (cDPCP) forms DNA adducts similar to those of the trans platinum complex trans-[PtCl2(NH3)(py)] (ampyplatin, py=pyridine). Thus this latter could be the active form of cDPCP. Detailed studies on the mechanism of ampyplatin action were performed in this work. Results indicate that ampyplatin has significantly higher antiproliferative activity than cDPCP and is comparable to cisplatin. Cellular uptake experiments indicate that ampyplatin can be efficiently accumulated in A549 cancer cells. Binding of ampyplatin to DNA mainly produces monofunctional adducts; remarkably, these adducts can be recognized by the HMGB1 protein. Kinetic studies on the reaction with GMP indicate that the reactivity of ampyplatin is much lower than that of transplatin and is more similar to that of trans-[PtCl2{E-HN=C(Me)OMe}2] (trans-EE), a widely investigated antitumor active trans-oriented platinum complex. In addition, the hydrolysis of ampyplatin is significantly suppressed, whereas the hydrolysis of the mono-GMP adduct is highly enhanced. These results indicate that the mechanism of ampyplatin differs not only from that of antitumor inactive transplatin but also from that of antitumor active trans-EE and this could account for the remarkable activity of parent cDPCP.

Gold nanorods for platinum based prodrug delivery.

PEGylated gold nanorods (PEG-GNRs) conjugate with Pt(iv) prodrug as a drug delivery system, showing superior cytotoxicity compared to cisplatin against different types of cancer cells.

Tetraethylenepentamine-directed controllable synthesis of wurtzite ZnSe nanostructures with tunable morphology.

A novel tetraethylenepentamine (TEPA)-directed method has been successfully developed for the controlled synthesis of ZnSe particles with distinctive morphologies, including nanobelts, nanowires, and hierarchically solid/hollow spheres. These structures, self-assembled from nanobelts and nanorods, have been synthesized by adjusting the reaction parameters, such as the solvent composition, reaction temperature, and the aging time. Results reveal that the volume ratio of H2O and TEPA plays a crucial role in the final morphology of ZnSe products. The mechanisms of phase formation and morphology control of ZnSe particles are proposed and discussed in detail. The products have been characterized by means of X-ray diffraction, field-emission scanning electron microscopy, transmission electron microscopy (TEM), selected area electron diffraction, high-resolution TEM, Raman spectra and luminescence spectroscopy. The as-prepared ZnSe nanoparticles display shape- and size-dependent photoluminescent optical properties. This is the first time to report preparation of complex hollow structures of ZnSe crystals with hierarchy through a simple solution-based route. This synthetic route is designed to exploit a new H2O/TEPA/N2H4H2O system possibly for the preparation of other semiconductor nanomaterials.