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.     

Fluorinated azole anticancer drugs: Synthesis,elaborated structure elucidation and docking studies

The present article deals with the synthesis of novel nano-sized fluorinated thiazoles and studying their anticancer potentiality. The targeted azoles could be accessed via trifluoro-methylated thiosemicarbazone (3) prepared by reaction of with thiosemicarbazide in acidic solution of ethanol. The latter a fluorinated building block (3) have been reacted with appropriate derivatives of a-halo compounds namely, N-aryl 2-oxopropane-hydrazonoyl chlorides 4a-f using dioxane containing TEA as base catalyst. Also, the reaction between N-(4-(1-(2-carbamothioylhydrazineylidene)ethyl)phenyl)-2,2,2-trifluoroacetamide (3) and chloroacetonitrile 8 under the same experimental conditions furnished the corresponding amino thiazole derivative 11. In the same manner the base catalyzed cyclocondensation reaction between N-(4-(1-(2-carbamothioylhydrazineylidene)ethyl)phenyl)-2,2,2-trifluoroacetamide (3) and phenacyl bromide derivatives 12a-d afforded the corresponding thiazoles 13a-d in good yield. The structure of all synthesized thiazole derivatives as well as their mechanistic pathways were studied based on spectral data analysis and physical characteristics. The nanosized products were confirmed by using XRD analysis. Moreover, twelve samples were submitted for evaluation of their cytotoxicity activities against MDA-MB-231 (breast cancer cell) using colorimetric MTT assay, in comparison with Cisplatin standard drug. Two nano-sized thiosemicarbazone derivative 3 and the thiazole derivative 7c showed potent activity with IC₅₀ = 7.7 and 2.97 µg/ml, respectively in compared with the IC₅₀ = 4.33 µg/ml of cisplatin. The nanosized thiazole derivative 7c was more potent than cisplatin. Also, two thiazole derivatives 13b and 7b showed good activity with IC₅₀ = 13.4 and 14.9 µg/ml. In addition, the molecular docking studies have been achieved using 4hy0, (X-chromosome-linked- inhibitor of apoptosis protein; (XIAP)).     

气相色谱-质谱法分析乳腺癌患者血清中的代谢物

建立了气相色谱-质谱法分析乳腺癌患者血清中代谢物的分析方法。分别收集乳腺癌患者、一般疾病者和健康对照组血清,样本用甲醇∶乙腈∶丙酮=1∶1∶1(V/V)提取,硅烷化试剂N,O-双甲氧基三氟乙酰胺+1%三甲基氯硅烷(BSTFA+1%TMCS)衍生后,采用气相色谱-质谱法分析其中的氨基酸、脂类和糖类的代谢谱,并用主成分分析(PCA)和随机森林(RF)算法对实验结果进行分析。结果表明,三组实验数据被成功分类,并发现磷酸、N-巴豆酰基甘氨酸、2,4-二羟基丁酸、棕榈酸、N-苯基甘氨酸和N-1-己酰甘氨酸等组分在乳腺癌组和健康对照组中的差异较为显著。     

Exploring the mechanism of Cremastra Appendiculata (SUANPANQI) against breast cancer by network pharmacology and molecular docking

BackgroundSUANPANQI, the pseudo phosphorous stem of Cremastra appendiculata, is one of the most well-known traditional Chinese medicine, which has been shown to inhibit tumorigenesis in various human cancers. However, the underlying mechanism of SUANPANQI treatment against breast cancer (BRCA) remains unclear. In this study. we aim to investigate the bioactive compounds and mechanisms of SUANPANQI in the treatment of BRCA based on network pharmacology and molecular docking.MethodsThe compounds were collected from previous research. SwissADME was used to screen bioactive compounds. The targets corresponding to SUANPANQI and BRCA were obtained using MalaCards and SwissTargetPrediction. SUANPANQI-related and BRCA-related targets were found and then overlapped to get intersections, which represented potential anti-BRCA targets of SUANPANQI. The Cytoscape software was used to construct bioactive compounds targeting the BRCA network. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of the targets was extracted from the metascape database, then conducted using the Cluster Profiler package in R software. Protein-Protein interaction (PPI) network was constructed using the STRING online database and analyzed using Cytoscape software. Pivotal genes were screened using the topological analysis, survival analysis, and pathological stage analysis. Molecular docking analysis was used to verify whether the bioactive compounds had a definite affinity with the pivotal targets.ResultsSixty-five bioactive compounds of SUANPANQI were involved with 225 predicted BRCA targets. Then, a compound-target network and a PPI network were constructed. The GO analysis and KEGG enrichment analysis suggested that SUANPANQI worked against BRCA via PI3K-Akt, Ras, FoxO, Rap1, and ErbB signaling pathways, etc. After topological analysis, survival analysis, and pathological stage analysis of the SUANPANQI potential targets against BRCA, 6 pivotal target genes (AR, HSP90AA1, MMP9, PGR, PTGS2, TNF) that were highly responsible for the therapeutic effects of SUANPANQI against BRCA were obtained. Molecular docking results showed that 6 bioactive compounds of SUANPANQI had strong binding efficiency with the 6 pivotal genes.ConclusionsThe present study clarifies the mechanism of SUANPANQI against BRCA through multiple targets and pathways, and provides evidence to support its clinical use.     

Identification of key genes of hesperidin in inhibition of breast cancer stem cells by functional network analysis

Breast cancer therapy with classical chemotherapy is unable to eradicate breast cancer stem cells (BCSCs). Loss of p53 function causes growth and differentiation in cancer stem cells (CSCs); therefore, p53-targeted compounds can be developed for BCSCs-targeted drugs. Previously, hesperidin (HES), a citrus flavonoid, showed anticancer activities and increased efficacy of chemotherapy in several types of cancer in vitro and in vivo. This study was aimed to explore the key protein and molecular mechanism of hesperidin in the inhibition of BCSCs using bioinformatics and in vitro study. Bioinformatics analysis revealed about 75 potential therapeutic target proteins of HES in BCSCs (TH), in which TP53 was the only direct target protein (DTP) with a high degree score. Furthermore, the results of GO enrichment analysis showed that TH was taken part in the biological process of regulation of apoptosis and cell cycle. The KEGG pathway enrichment analysis also showed that TH is involved in several pathways, including cell cycle, p53 signaling pathway. In vitro experiment results showed that HES inhibited cell proliferation, mammosphere, and a colony formation, and migration in on MCF-7 3D cells (mammospheres). HES induced G0/G1 cell cycle arrest and apoptosis in MCF-7 cells 3D. In addition, HES treatment reduced the mRNA level of p21 but increased the mRNA level of cyclin D1 and p53 in the mammosphere. HES inhibits BCSCs in mammospheres. More importantly, this study highlighted p53 as a key protein in inhibition of BCSCs by HES. Future studies on the molecular mechanism are needed to validate the results of this study.     

The regulation of microRNA in each of cancer stage from two different ethnicities as potential biomarker for breast cancer

miRNA has recently emerged as a potential biomarker for breast cancer. Even though many studies have identified ethnic variation affecting miRNA regulation, the effect of cancer stage within specific ethnicities on miRNA epigenetic remains unclear. The present study is designed to investigate miRNA regulation from two distinct ethnicities in specific cancer stages (non-Hispanic white and non-Hispanic black) using the TCGA dataset. Differentially expressed miRNAs were calculated by using the edgeR package. miRNAs with the highest or lowest log fold Change from each cancer stage were selected as a potential biomarker. miRNA-gene interaction was analyzed by using spearman correlation analysis, CLUEGO, and DIANA-mirpath. The association of biomarker candidates with diagnostic and prognostic performance was assessed using ROC and Kaplan-Meier survival analysis. miRNA-gene interaction analysis revealed the involvement of selected miRNAs in cancer progression. From eleven selected aberrant miRNAs, four of the miRNAs (hsa-mir-495, hsa-mir-592, hsa-mir-6501, and hsa-mir-937) are significantly detrimental to breast cancer diagnosis and prognosis. Hence, our result provides valuable information to explore miRNA’s role in each cancer stage between non-Hispanic white and non-Hispanic black.     

Bacteria and cancer cell pearl chain under dielectrophoresis

In this work, we aim to observe and study the physics of bacteria and cancer cells pearl chain formation under dielectrophoresis (DEP). Experimentally, we visualized the formation of Bacillus subtilis bacterial pearl chain and human breast cancer cell (MCF-7) chain under positive and negative dielectrophoretic force, respectively. Through a simple simulation with creeping flow, AC/DC electric fields, and particle tracing modules in COMSOL, we examined the mechanism by which bacteria self-organize into a pearl chain across the gap between two electrodes via DEP. Our simulation results reveal that the region of greatest positive DEP force shifts from the electrode edge to the leading edge of the pearl chain, thus guiding the trajectories of free-flowing particles toward the leading edge via positive DEP. Our findings additionally highlight the mechanism why the free-flowing particles are more likely to join the existing pearl chain rather than starting a new pearl chain. This phenomenon is primarily due to the increase in magnitude of electric field gradient, and hence DEP force exerted, with the shortening gap between the pearl chain leading edge and the adjacent electrode. The findings shed light on the observed behavior of preferential pearl chain formation across electrode gaps.