Three previously undescribed protoilludane-type sesquiterpene aryl esters, armillanals A-C (1-3), along with seven known ones (4-10) were obtained from Armillaria gallica Marxm. & Romagn. Compounds 1 and 2 were a rare class of sesquiterpenes featuring the Δ
<p>Figure S1. Analysis of correlation between AR and β-catenin in PCa. Figure S2. The Wnt/β-catenin pathway is activated in cell lines and human specimens. Figure S3. Treatment with ICG001 overcomes enzalutamide resistance in PCa. Figure S4. Activation of the Wnt/β-catenin pathway contributes to enzalutamide resistance. Figure S5. Different gene signature in human PCa specimens and correlation between β-catenin and survival probability.</p>
Rhizoma Gastrodia (Orchidaceae; Gastrodia elata Blume), the rhizome of Gastrodia elata Blume (GE), is traditionally used as both a medicinal and functional food, with proven efficacy in treating mental disorders. In traditional processing, GE is washed, steamed with water, dried, and sliced. In this study, a novel processing technology-alcohol steamed GE (AGE) was proposed as an alternative. Totally, 17 compounds were identified in fresh GE and AGE. Compared with fresh GE, the relative content of parishin A and parishin E decreased after alcohol steaming, whereas gastrodin (GAS), p-hydroxylbenzyl alcohol (HBA), Parishin B, and Parishin C were increased. Additionally, the pentobarbital-induced sleep mice model and Chronic Restraint Stress (CRS) model were applied to evaluate the pharmacological effects of fresh GE and steamed GE, and both fresh and steamed GE showed an intensive hypnotic and anti-anxiety effect. Furthermore, the anti-anxiety mechanism based on serum metabolic was investigated and the tryptophan metabolic pathway was considered the response to the anti-anxiety effect of GE. Although the optimization of the processing technology of AGE still needs to be further explored, the current results have provided new thoughts for the processing technology and clinical application of GE.
Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal human cancers and shows insensitivity towards many chemotherapeutic drugs and target-based drugs. There is an urgently need to identify PDAC disease mechanism and detect novelty drug targets. With the large availability of protein interaction networks and microarray data supported, to identify the disease essential genes that have biological significance for potential drug targets is a challenge issue still.Methods: In this study, protein interaction network PathPPI, DrugBank targets and 374 transcriptome profiles from Gene Expression Omnibus (GEO) by Affymetrix HU 133 Plus 2.0 array test are collected. These microarray data includes 140 PDAC, 92 pancreatic cancer cell-line, 58 human normal pancreas tissues, and 72 patient original xenograft mouse. Based on these datasets, a novelty-integrated algorithm was developed for drug target prioritization by perturbed gene expression and network information. The integration network included data driven reconstruction network of gene regulatory (GRN) by Bayesian Network and protein interaction PathPPI network. The perturbed gene expression was refer to the differential expression genes of tumor verse adjacent normal. A novel hybrid method based on genetic algorithm (GA) is proposed to search the attractor with the maximum network perturbation for candidate drug targets in PDAC.These targets' molecular mechanism was revealed further by network structure comparison of PDAC that is consistent with xerograph mouse model and cancer cells.Results: Highly accordance 56 genes with high perturbation score both in mRNAs and protein-protein network were identified and recommended as candidate drug targets for PDAC, including 16 novel targets, such as PSMD2, EPOR and PSMB9. Fifty-four essential genes shown strong concordance among tumor-model, patient drive xenograft mouse and pancreatic cancer cell-line by systematically comparison. We identified 1375 dysregulated genes that enriched in 25 pathways in PDAC by Gene Set Enrichment Analysis, among which 244 genes played as hubs in reconstructed PDAC regulatory network.Conclusion: In the study, we developed a global optimization-based inference of network perturbation to detect attractor for drug-target identification in PDAC tumors. The assembling Bayesian Network-based approach with protein-protein interaction provides a comprehensive information to observe energy transfer of gene perturbation in network to detect global optimum attractor for drug target selection.Citation Format: Lijun Cheng, Enze Liu, Li Lang, Xiaolin Cheng, Xiaotian Kong, Korc Murray. Integrated network analysis reveals potentially novel molecular pathways mechanism and therapeutic targets of pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4257.
Non-alcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH) is the most common chronic liver disease in the world. However, there are still no drugs for NAFLD/NASH in the market. Gastrodin (GAS) is a bioactive compound that is extracted from
Because there is no effective treatment for late-stage prostate cancer (PCa) at this moment, identifying novel targets for therapy of advanced PCa is urgently needed.A new network-based systems biology approach, XDeath, is developed to detect crosstalk of signaling pathways associated with PCa progression.This unique integrated network merges gene causal regulation networks and protein-protein interactions to identify novel co-targets for PCa treatment.The results show that polo-like kinase 1 (Plk1) and DNA methyltransferase 3A (DNMT3a)-related signaling pathways are robustly enhanced during PCa progression and together they regulate autophagy as a common death mode.Mechanistically, it is shown that Plk1 phosphorylation of DNMT3a leads to its degradation in mitosis and that DNMT3a represses Plk1 transcription to inhibit autophagy in interphase, suggesting a negative feedback loop between these two proteins.Finally, a combination of the DNMT inhibitor 5-Aza-2'-deoxycytidine (5-Aza) with inhibition of Plk1 suppresses PCa synergistically.
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