Characterizing mutation–expression network relationships in multiple cancers

BackgroundData made available through large cancer consortia like The Cancer Genome Atlas make for a rich source of information to be studied across and between cancers. In recent years, network approaches have been applied to such data in uncovering the complex interrelationships between mutational and expression profiles, but lack direct testing for expression changes via mutation. In this pan-cancer study we analyze mutation and gene expression information in an integrative manner by considering the networks generated by testing for differences in expression in direct association with specific mutations. We relate our findings among the 19 cancers examined to identify commonalities and differences as well as their characteristics.ResultsUsing somatic mutation and gene expression information across 19 cancers, we generated mutation–expression networks per cancer. On evaluation we found that our generated networks were significantly enriched for known cancer-related genes, such as skin cutaneous melanoma (p < 0.01 using Network of Cancer Genes 4.0). Our framework identified that while different cancers contained commonly mutated genes, there was little concordance between associated gene expression changes among cancers. Comparison between cancers showed a greater overlap of network nodes for cancers with higher overall non-silent mutation load, compared to those with a lower overall non-silent mutation load.ConclusionsThis study offers a framework that explores network information through co-analysis of somatic mutations and gene expression profiles. Our pan-cancer application of this approach suggests that while mutations are frequently common among cancer types, the impact they have on the surrounding networks via gene expression changes varies. Despite this finding, there are some cancers for which mutation-associated network behaviour appears to be similar: suggesting a potential framework for uncovering related cancers for which similar therapeutic strategies may be applicable. Our framework for understanding relationships among cancers has been integrated into an interactive R Shiny application, PAn Cancer Mutation Expression Networks (PACMEN), containing dynamic and static network visualization of the mutation–expression networks. PACMEN also features tools for further examination of network topology characteristics among cancers.     

Screening disrupted molecular functions and pathways associated with clear cell renal cell carcinoma using Gibbs sampling

ObjectiveTo explore the disturbed molecular functions and pathways in clear cell renal cell carcinoma (ccRCC) using Gibbs sampling.MethodsGene expression data of ccRCC samples and adjacent non-tumor renal tissues were recruited from public available database. Then, molecular functions of expression changed genes in ccRCC were classed to Gene Ontology (GO) project, and these molecular functions were converted into Markov chains. Markov chain Monte Carlo (MCMC) algorithm was implemented to perform posterior inference and identify probability distributions of molecular functions in Gibbs sampling. Differentially expressed molecular functions were selected under posterior value more than 0.95, and genes with the appeared times in differentially expressed molecular functions ≥5 were defined as pivotal genes. Functional analysis was employed to explore the pathways of pivotal genes and their strongly co-regulated genes.ResultsIn this work, we obtained 396 molecular functions, and 13 of them were differentially expressed. Oxidoreductase activity showed the highest posterior value. Gene composition analysis identified 79 pivotal genes, and survival analysis indicated that these pivotal genes could be used as a strong independent predictor of poor prognosis in patients with ccRCC. Pathway analysis identified one pivotal pathway − oxidative phosphorylation.ConclusionsWe identified the differentially expressed molecular functions and pivotal pathway in ccRCC using Gibbs sampling. The results could be considered as potential signatures for early detection and therapy of ccRCC.     

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.     

Theoretical investigation of different reactivities of Fe(IV)O and Ru(IV)O complexes with the same ligand topology

The structures and mechanisms for hydrogen abstraction from isopropylbenzene for four high-valence complexes, cis-β-[Fe^IV(O)(BQCN)]²⁺ (Fe-2b and Fe-2b-2) and cis-β-[Ru^IV(O)(BQCN)]²⁺ (Ru-2b and Ru-2b-2) (BQCN = N,N′-dimethyl-N,N′-bis(8-quinolyl)-cyclohexanediamine), were investigated using density functional theory. Of the two iron complexes, Fe-2b-2 has more exposed FeO units than Fe-2b, with iron being further out of the equatorial plane because of the steric interaction of the same ligand topologies with the iron-oxo group trans to a quinolyl or amine nitrogen. The contribution of BQCN to Fe-2b is higher than the contribution to Fe-2b-2 as shown by the density-of-states spectra. The iron isomers can abstract hydrogen from isopropylbenzene via two-state reactivity patterns, whereas the ruthenium isomers react with isopropylbenzene via a single-state mechanism. In the gas phase, the relative reactivity exhibits the trend Fe-2b > Fe-2b-2, whereas with the addition of the ZPE correction and the SMD model, the relative reactivity follows Fe-2b-2 > Fe-2b. For the ruthenium complexes, the relative reactivity follows the trend Ru-2b-2 > Ru-2b in both the gas phase and solvent. Thus, the same ligand topologies with the metal-oxo group trans to a different nitrogen affect the reactivities of the iron and ruthenium complexes.     

Identification of key genes and expression profiles in osteoarthritis by co-expressed network analysis

BackgroundThe underlying molecular characteristics of osteoarthritis (OA), a common age-related joint disease, remains elusive. Here, we aimed to identify potential early diagnostic biomarkers and elucidate underlying mechanisms of OA using weighted gene co-expression network analysis (WGCNA).Material and methodsWe obtained the gene expression profile dataset GSE55235, GSE55457, and GSE55584, from the Gene Expression Omnibus. WGCNA was used to investigate the changes in co-expressed genes between normal and OA synovial membrane samples. Modules that were highly correlated to OA were subjected to functional enrichment analysis using the R clusterProfiler package. Differentially expressed genes (DEGs) between the two samples were screened using the “limma” package in R. A Venn diagram was constructed to intersect the genes in significant modules and DEGs. RT -PCR was used to further verify the hub gene expression levels between normal and OA samples.ResultsThe preserved significant module was found to be highly associated with OA development and progression (P < 1e-200, correlation = 0.92). Functional enrichment analysis suggested that the antiquewhite4 module was highly correlated to FoxO signaling pathway, and the metabolism of fatty acids and 2-oxocarboxylic acid. A total of 13 hub genes were identified based on significant module network topology and DEG analysis, and RT-PCR confirmed that these genes were significantly increased in OA samples compared with that in normal samples.ConclusionsWe identified 13 hub genes correlated to the development and progression of OA, which may provide new biomarkers and drug targets for OA.     

Investigating ego modules involved in TGFβ3-induced chondrogenesis in mesenchymal stem cells based on ego network

ObjectiveThis paper aimed to investigate ego modules for TGFβ3-induced chondrogenesis in mesenchymal stem cells (MSCs) using ego network algorithm.MethodsThe ego network algorithm comprised three parts, extracting differential expression network (DEN) based on gene expression data and protein-protein interaction (PPI) data; exploring ego genes by reweighting DEN; and searching ego modules by ego gene expansions. Subsequently, permutation test was carried out to evaluate the statistical significance of the ego modules. Finally, pathway enrichment analysis was conducted to investigate ego pathways enriched by the ego modules.ResultsA total of 15 ego genes were obtained from the DEN, such as PSMA4, HNRNPM and WDR77. Starting with each ego genes, 15 candidate modules were gained. When setting the thresholds of the area under the receiver operating characteristics curve (AUC) ≥0.9 and gene size ≥4, three ego modules (Module 3, Module 8 and Module 14) were identified, and all of them had statistical significances between normal and TGFβ3-induced chondrogenesis in MSCs. By mapping module genes to confirmed pathway database, their ego pathways were detected, Cdc20:Phospho-APC/C mediated degradation of Cyclin A for Module 3, Mitotic G1-G1/S phases for Module 8, and mRNA Splicing for Module 14.ConclusionsWe have successfully identified three ego modules, evaluated their statistical significances and investigated their functional enriched ego pathways. The findings might provide potential biomarkers and give great insights to reveal molecular mechanism underlying this process.     

Studies on the metabolism of the Δ9‐tetrahydrocannabinol precursor Δ9‐tetrahydrocannabinolic acid A (Δ9‐THCA‐A) in rat using LC‐MS/MS,LC‐QTOF MS and GC‐MS techniques

In Cannabis sativa, Δ9‐Tetrahydrocannabinolic acid‐A (Δ9‐THCA‐A) is the non‐psychoactive precursor of Δ9‐tetrahydrocannabinol (Δ9‐THC). In fresh plant material, about 90% of the total Δ9‐THC is available as Δ9‐THCA‐A. When heated (smoked or baked), Δ9‐THCA‐A is only partially converted to Δ9‐THC and therefore, Δ9‐THCA‐A can be detected in serum and urine of cannabis consumers. The aim of the presented study was to identify the metabolites of Δ9‐THCA‐A and to examine particularly whether oral intake of Δ9‐THCA‐A leads to in vivo formation of Δ9‐THC in a rat model. After oral application of pure Δ9‐THCA‐A to rats (15 mg/kg body mass), urine samples were collected and metabolites were isolated and identified by liquid chromatography‐mass spectrometry (LC‐MS), liquid chromatography‐tandem mass spectrometry (LC‐MS/MS) and high resolution LC‐MS using time of flight‐mass spectrometry (TOF‐MS) for accurate mass measurement. For detection of Δ9‐THC and its metabolites, urine extracts were analyzed by gas chromatography‐mass spectrometry (GC‐MS). The identified metabolites show that Δ9‐THCA‐A undergoes a hydroxylation in position 11 to 11‐hydroxy‐Δ9‐tetrahydrocannabinolic acid‐A (11‐OH‐Δ9‐THCA‐A), which is further oxidized via the intermediate aldehyde 11‐oxo‐Δ9‐THCA‐A to 11‐nor‐9‐carboxy‐Δ9‐tetrahydrocannabinolic acid‐A (Δ9‐THCA‐A‐COOH). Glucuronides of the parent compound and both main metabolites were identified in the rat urine as well. Furthermore, Δ9‐THCA‐A undergoes hydroxylation in position 8 to 8‐alpha‐ and 8‐beta‐hydroxy‐Δ9‐tetrahydrocannabinolic acid‐A, respectively, (8α‐Hydroxy‐Δ9‐THCA‐A and 8β‐Hydroxy‐Δ9‐THCA‐A, respectively) followed by dehydration. Both monohydroxylated metabolites were further oxidized to their bishydroxylated forms. Several glucuronidation conjugates of these metabolites were identified. In vivo conversion of Δ9‐THCA‐A to Δ9‐THC was not observed. Copyright © 2009 John Wiley & Sons, Ltd.     

Investigating dysregulated pathways in Staphylococcus aureus (SA) exposed macrophages based on pathway interaction network

ObjectiveThis work aimed to identify dysregulated pathways for Staphylococcus aureus (SA) exposed macrophages based on pathway interaction network (PIN).MethodsThe inference of dysregulated pathways was comprised of four steps: preparing gene expression data, protein–protein interaction (PPI) data and pathway data; constructing a PIN dependent on the data and Pearson correlation coefficient (PCC); selecting seed pathway from PIN by computing activity score for each pathway according to principal component analysis (PCA) method; and investigating dysregulated pathways in a minimum set of pathways (MSP) utilizing seed pathway and the area under the receiver operating characteristics curve (AUC) index implemented in support vector machines (SVM) model.ResultsA total of 20,545 genes, 449,833 interactions and 1189 pathways were obtained in the gene expression data, PPI data and pathway data, respectively. The PIN was consisted of 8388 interactions and 1189 nodes, and Respiratory electron transport, ATP synthesis by chemiosmotic coupling, and heat production by uncoupling proteins was identified as the seed pathway. Finally, 15 dysregulated pathways in MSP (AUC = 0.999) were obtained for SA infected samples, such as Respiratory electron transport and DNA Replication.ConclusionsWe have identified 15 dysregulated pathways for SA infected macrophages based on PIN. The findings might provide potential biomarkers for early detection and therapy of SA infection, and give insights to reveal the molecular mechanism underlying SA infections. However, how these dysregulated pathways worked together still needs to be studied.     

Bioinformatics analysis and verification of gene targets for renal clear cell carcinoma

BackgroundIt is estimated that there are 338,000 new renal-cell carcinoma releases every year in the world. Renal cell carcinoma (RCC) is a heterogeneous tumor, of which more than 70% is clear cell renal cell carcinoma (ccRCC). It is estimated that about 30% of new renal-cell carcinoma patients have metastases at the time of diagnosis. However, the pathogenesis of renal clear cell carcinoma has not been elucidated. Therefore, it is necessary to further study the pathogenesis of ccRCC.MethodsTwo expression profiling datasets (GSE68417, GSE71963) were downloaded from the GEO database. Differentially expressed genes (DEGs) between ccRCC and normal tissue samples were identified by GEO2R. Functional enrichment analysis was made by the DAVID tool. Protein-protein interaction (PPI) network was constructed. The hub genes were excavated. The clustering analysis of expression level of hub genes was performed by UCSC (University of California Santa Cruz) Xena database. The hub gene on overall survival rate (OS) in patients with ccRCC was performed by Kaplan-Meier Plotter. Finally, we used the ccRCC renal tissue samples to verify the hub genes.Results1182 common DEGs between the two datasets were identified. The results of GO and KEGG analysis revealed that variations in were predominantly enriched in intracellular signaling cascade, oxidation reduction, intrinsic to membrane, integral to membrane, nucleoside binding, purine nucleoside binding, pathways in cancer, focal adhesion, cell adhesion molecules. 10 hub genes ITGAX, CD86, LY86, TLR2, TYROBP, FCGR2A, FCGR2B, PTPRC, ITGB2, ITGAM were identified. FCGR2B and TYROBP were negatively correlated with the overall survival rate in patients with ccRCC (P < 0.05). RT-qPCR analysis showed that the relative expression levels of CD86, FCGR2A, FCGR2B, TYROBP, LY86, and TLR2 were significantly higher in ccRCC samples, compared with the adjacent renal tissue groups.ConclusionsIn summary, bioinformatics technology could be a useful tool to predict the progression of ccRCC. In addition, there are DEGs between ccRCC tumor tissue and normal renal tissue, and these DEGs might be considered as biomarkers for ccRCC.     

In-silico investigations of selective miRNA-gene targets and their validation studies in obstructive sleep apnea (OSA) patient cohorts

BackgroundObstructive sleep apnoea (OSA) is a prevalent form of sleep disordered breathing which results in sleep fragmentation and deprivation. Obesity and cardiovascular disorders are the major risk factors associated with OSA. Molecular analysis of the factors associated with OSA could demarcate the clinical analysis pattern in a population.ObjectiveThis study pertains to in-silico analyses of miRNA and their gene targets with validation for their potential role in OSA as putative biomarker candidates.MethodsmiRDB, TargetScan and miRanda databases were used to identify targets of miR-27 and let-7 that have documented role in OSA and co-related obesity and cardiovascular disorders. Quantitative PCR was used to analyze expression pattern of miR-27 and let-7 in obese and non-obese OSA patient cohorts with respective controls. In-silico analysis was done using PatchDoc to obtain atomic contact energy (ACE) scores that indicated the docked gene targets to the predicted miRNA structures. The docked structures were analysed using Maestro Suite 11 for the hydrogen and aromatic interactions.ResultsDownregulation of miR-27 and let-7 in OSA compared to controls was observed. In-silico data analysis was performed for gene targets (TGFBR1, TGFBR2, SMAD2, SMAD4, CRY2 and CNR1) of the selected miRNAs (miR-27 and let-7). Among all, CNR1 and CRY2 were found to be better targets for miR-27 and let-7 respectively as per ACE scores, ROC scores and expression fold change in OSA.ConclusionOur study gives insights to the expression profiling of miR-27 and let-7 and explore a set of potential target genes (CNR1 and CRY2) of these two miRNAs for a promising clinical relevance in OSA.     

Zur Kenntnis cyclischer Acylale, 18. Mitt.: Über die Einwirkung von Diazomethan auf substituierte Benzylidenmeldrumsäuren und ähnliche Verbindungen

Zusammenfassung Es wird die Reaktion der Kondensationsprodukte (1–3) vonMeldrumsäuren mit Diazomethan in Methanol/Äther beschrieben, die zu den Cyclopropanverbindungen1 b-3 b führt. Diese Reaktionsweise ist bekannt und auch nach quantenchemischen Berechnungen des einen von uns (P. Schuster) zu erwarten.Eine neue, bisher nicht beobachtete Reaktion wurde bei der Verbindung4 gefunden. Bei verschiedenen Temperaturen führt die Reaktion mit CH₂N₂ in Methanol/Äther (außer zu den Verbindungen4 a und4 b) zu4 c. In CHCl₃ entsteht nur4 b neben viel allem Anschein nach hochmolekularen Produkten.

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The reaction is described of the condensation products ofMeldrum's acid with aldehydes1–3 ² with diazomethane in methanol/ether, which leads to the cyclopropane compounds1 b-3 b. This is a known mode of reaction and is predicted by quantum chemical calculations ofP. Schuster.A reaction hitherto unobserved was found in the case of the compound4. The reaction with CH₂N₂ in methanol/ether at various temperatures yields the compound4 c as well as4 a and4 b. In CHCl₃ the reactions yields only4 b in addition to many other high molecular weight products.

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Mit 1 Abbildung

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Herrn Prof. Dr.F. Asinger zum 60. Geburtstag gewidmet.     

Assembly of beta-cyclodextrin with 3S-tetrahydro-beta-carboline-3-carboxylic acid and self-assembly of 6-(3'S-carboline-3'-carboxylaminoethylamino)-6-deoxy-beta-cyclodextrin: approaches to enhance anti-oxidation stability and anti-thrombotic potency

3 S-1,2,3,4-Tetrahydro-beta-carboline-3-carboxylic acid (THCA) isolated from Bulbus allii macrostemi was identified as the active antiplatelet aggregation ingredient. However, the very poor water solubility and the shortcoming of being oxidized easily in vivo seriously limit the clinical application of THCA. In the present study, two strategies were used to reduce this tendency. First, the inclusion complex of THCA with beta-cyclodextrin (beta-CD) was prepared. Spectral studies identified that the inclusion complex (beta-CD1,2/THCA) was in equilibrium between beta-CD/THCA and beta-CD2/THCA, and the proportion of two isomers was beta-CD concentration dependent; it was 89% vs 11% in our study. The oxidation of both THCA and beta-CD1,2/THCA by H2O2 followed first-order kinetics, and 35% of THCA and 33% of beta-CD1,2/THCA were oxidized during the monitoring period. In vitro antiplatelet aggregation and in vivo oral administration antithrombotic activity of THCA was largely increased via inclusion complexation with beta-CD. Second, a novel conjugate 6-(3' S-carboline-3'-carboxyamino-ethylamino)-6-deoxy-beta-CD (5-monomer) was prepared. Spectral characterizations demonstrated that 5-monomer was able to self-assemble into 5-dimer, which was coexisting with the monomer with a ratio of 79% vs 21% in solution. The in vitro oxidation of 5-monomer/5-dimer by H2O2 did not occur during the monitoring period. The in vitro antiplatelet aggregation and in vivo antithrombotic assays of 5-monomer /5-dimer demonstrated that the bioactivity of THCA was remarkably increased via conjugation with 6-ethylamino-6-deoxy-beta-CD and produced greater in vitro and in vivo effectiveness than that of the inclusion complex beta-CD1,2/THCA at the same dose. The significant improvement of the bioactivity and stability of THCA indicates that inclusion complexation and conjugation with beta-CD provide promising approaches to improve the practical use of THCA in clinical applications.     

Fluorination of tertiary alcohols derived from di-O-isopropylidenehexofuranose and O-isopropylidenepentofuranose

The stereo- and regioselectivity of the dehydroxyfluorination of various tertiary alcohols derived from di-O-isopropylidenehexofuranose and 1,2-O-isopropylidenepentofuranose has been studied. Reactions have been accomplished using DAST and PFPDEA (1,1,3,3,3-pentafluoropropene-diethylamine adduct) as fluorinating reagents. Dehydroxyfluorination of allylic alcohol 2a has occurred with an inversion of configuration and allylic rearrangement leading to two chiral regioisomers 6a and 7a. Analogous reaction of 2b has given allylic chiral fluoride 7b as the only product. In case of phenylacetylene, styryl and benzylic alcohols 3a/3b-5a/5b the single diastereoisomers 8a/8b-10a/10b have been obtained. Additionally, the participation of 1,2-O-substituent effect in carbocation stabilization during fluorination have been discussed.     

Identification of molecular markers for the oncogenic differentiation of hepatocellular carcinoma

The aim of this study was to identify molecular markers associated with oncogenic differentiation in hepatocellular carcinoma (HCC). Using an unsupervised clustering method with a cDNA microarray, HCC (T) gene expression profiles and corresponding non-tumor tissues (NT) from 40 patients were analyzed. Of total 217 genes, 72 were expressed preferentially in HCC tissues. Among 186 differentially regulated genes, there were molecular chaperone and tumor suppressor gene clusters in the Edmondson grades I and II (GI/II) subclass compared with the liver cirrhosis (LC) subclass. The Edmondson grades III and IV (GIII/IV) subclass with a poor survival (P=0.0133) contained 122 differentially regulated genes with a cluster containing various metastasis- and invasion-related genes compared with the GI/II subclass. Immunohistochemical analysis revealed that ANXA2, one of the 72 genes preferentially expressed in HCC, was over-expressed in the sinusoidal endothelium and in malignant hepatocytes in HCC. The genes identified in the HCC subclasses will be useful molecular markers for the genesis and progression of HCC. In addition, ANXA2 might be a novel marker for tumor angiogenesis in HCC.     

Precise discovery of a STAT3 inhibitor from Eupatorium lindleyanum and evaluation of its activity of anti-triple-negative breast cancer

Michael reaction acceptors (MRAs) are a class of active compounds. There is a great prospect to screen STAT3 inhibitors from Eupatorium lindleyanum, furthermore, to discover lead compounds for anti-triple-negative breast cancer (TNBC). In this study, glutathione (GSH) was employed, and a UPLC-MS screening method was developed to discover MRAs. We screened MRAs which can inhibit STAT3 using a STAT3-dependent reporter system. Six sesquiterpene lactones, including a new compound Eupalinolide O (1), together with five known compounds, Eupalinolide I (2), Eupalinolide K (3), Eupalinolide H (4), Eupalinolide J (5) and Eupalinolide G (6) were isolated. Eupalinolide J was identified as MRA that decreased luciferase activity of STAT3. Preliminary activity assessment showed that Eupalinolide J could inhibit the viability of TNBC cell lines. We demonstrated that Eupalinolide J, which is a natural typical MRA, has a notable inhibition of STAT3 activity and a potential cytotoxic activity against TNBC cell lines.     

Euphorbiasteroid Abrogates EGFR and Wnt/β-Catenin Signaling in Non-Small-Cell Lung Cancer Cells to Impart Anticancer Activity

EGFR and Wnt/β-catenin signaling pathways play a prominent role in tumor progression in various human cancers including non-small-cell lung carcinoma (NSCLC). Transactivation and crosstalk between the EGFR and Wnt/β-catenin pathways may contribute to the aggressiveness of cancers. Targeting these oncogenic pathways with small molecules is an attractive approach to counteract various types of cancers. In this study, we demonstrate the effect of euphorbiasteroid (EPBS) on the EGFR and Wnt/β-catenin pathways in NSCLC cells. EPBS induced preferential cytotoxicity toward A549 (wildtype EGFR-expressing) cells over PC-9 (mutant EGFR-expressing) cells. EPBS suppressed the expression of EGFR, Wnt3a, β-catenin, and FZD-1, and the reduction in β-catenin levels was found to be mediated through the activation of GSK-3β. EPBS reduced the phosphorylation of GSK-3β^S9 with a parallel increase in β-TrCP and phosphorylation of GSK-3β^Y216. Lithium chloride treatment increased the phosphorylation of GSK-3β^S9 and nuclear localization of β-catenin, whereas EPBS reverted these effects. Forced expression or depletion of EGFR in NSCLC cells increased or decreased the levels of Wnt3a, β-catenin, and FZD-1, respectively. Overall, EPBS abrogates EGFR and Wnt/β-catenin pathways to impart its anticancer activity in NSCLC cells.     

A new biflavonoid from the whole herb of Lepisorus ussuriensis

A new biflavonoid, 7-O-methylnaringenin-(4′→O→6″)-scutellarein (1), together with 11 known compounds (2–12) were isolated from the whole herb of Lepisorus ussuriensis. The structure of compound 1 was elucidated by spectroscopic analyses. Amongst them, dihydroquercetin (6), diosmetin (9), baicalein (11) and 7,8-dihydroxyflavone (12) were reported from the family Polypodiaceae for the first time. Meanwhile, quercetin (7), diosmetin (9) and luteolin (10) inhibited TNF-α-induced NF-κB reporter gene expression on HeLa cells up to 30 and 100 μM.