Current therapy and drug resistance in metastatic castration-resistant prostate cancer.

Castration-resistant prostate cancer (CRPC), especially metastatic castration-resistant prostate cancer (mCRPC) is one of the most prevalent malignancies and main cause of cancer-related death among men in the world. In addition, it is very difficult for clinical treatment because of the natural or acquired drug resistance of CRPC. Mechanisms of drug resistance are extremely complicated and how to overcome it remains an urgent clinical problem to be solved. Thus, a comprehensive and thorough understanding for mechanisms of drug resistance in mCRPC is indispensable to develop novel and better therapeutic strategies. In this review, we aim to review new insight of the treatment of mCRPC and elucidate mechanisms governing resistance to new drugs: taxanes, androgen receptor signaling inhibitors (ARSIs) and poly (ADP-ribose) polymerase (PARP) inhibitors (PARPi). Most importantly, in order to improve efficacy of these drugs, strategies of overcoming drug resistance are also discussed based on their mechanisms respectively.

Hsa_circ_0003258 promotes prostate cancer metastasis by complexing with IGF2BP3 and sponging miR-653-5p.

BACKGROUND: More and more studies have shown that circular RNAs (circRNAs) play a critical regulatory role in many cancers. However, the potential molecular mechanism of circRNAs in prostate cancer (PCa) remains largely unknown. METHODS: Differentially expressed circRNAs were identified by RNA sequencing. The expression of hsa_circ_0003258 was evaluated using quantitative real-time PCR and RNA in situ hybridization. The impacts of hsa_circ_0003258 on the metastasis of PCa cells were investigated by a series of in vitro and in vivo assays. Lastly, the underlying mechanism of hsa_circ_0003258 was revealed by Western blot, biotin-labeled RNA pulldown, RNA immunoprecipitation, luciferase assays and rescue experiments. RESULTS: Increased expression of hsa_circ_0003258 was found in PCa tissues and was associated with advanced TNM stage and ISUP grade. Overexpression of hsa_circ_0003258 promoted PCa cell migration by inducing epithelial mesenchymal transformation (EMT) in vitro as well as tumor metastasis in vivo, while knockdown of hsa_circ_0003258 exerts the opposite effect. Mechanistically, hsa_circ_0003258 could elevate the expression of Rho GTPase activating protein 5 (ARHGAP5) via sponging miR-653-5p. In addition, hsa_circ_0003258 physically binds to insulin like growth factor 2 mRNA binding protein 3 (IGF2BP3) in the cytoplasm and enhanced HDAC4 mRNA stability, in which it activates ERK signalling pathway, then triggers EMT programming and finally accelerates the metastasis of PCa. CONCLUSIONS: Upregulation of hsa_circ_0003258 drives tumor progression through both hsa_circ_0003258/miR-653-5p/ARHGAP5 axis and hsa_circ_0003258/IGF2BP3 /HDAC4 axis. Hsa_circ_0003258 may act as a promising biomarker for metastasis of PCa and an attractive target for PCa intervention.

An environmentally friendly sodium dodecyl sulfate-synergistic microwave-assisted extraction followed by ultra-high-performance liquid chromatography with photodiode array method for the simultaneous extraction and determination of iridoids, phenylpropanoids, and lignans from Eucommiae Cortex.

A simple and green sodium dodecyl sulfate-synergistic microwave-assisted extraction method was developed to extract and determine the iridoids, phenylpropanoids, and lignans in Eucommiae Cortex followed by ultra-high-performance liquid chromatography with photodiode array detection. The biodegradable solution (sodium dodecyl sulfate) was used as a promising alternative to organic solvents. The response surface methodology provided the optimum extraction conditions (2 mg/mL sodium dodecyl sulfate, 1100 W microwave power, and 6 min extraction time). The recoveries of three types of components ranged from 95.0 to 105% (RSDs < 5%). The intra- and inter-day precision and accuracy were less than 3.40% and within the range of 97.1-105%, respectively. Compared with other extraction methods, this newly established method was more efficient and environmental friendly. The results demonstrated that sodium dodecyl sulfate-synergistic microwave-assisted extraction followed by ultra-high-performance liquid chromatography with photodiode array method was applicable for the simultaneous extraction and determination of these three types of compounds for quality evaluation of Eucommiae Cortex.

Identification of a basement membrane gene signature for predicting prognosis and estimating the tumor immune microenvironment in prostate cancer.

Basement membrane plays an important role in tumor invasion and metastasis, which is closely related to prognosis. However, the prognostic value and biology of basement membrane genes (BMGs) in prostate cancer (PCa) remain unknown. In the TCGA training set, we used differentially expressed gene analysis, protein-protein interaction networks, univariate and multivariate Cox regression, and least absolute shrinkage and selection operator regression to construct a basement membrane-related risk model (BMRM) and validated its effectiveness in the MSKCC validation set. Furthermore, the accurate nomogram was constructed to improve clinical applicability. Patients with PCa were divided into high-risk and low-risk groups according to the optimal cut-off value of the basement membrane-related risk score (BMRS). It was found that BMRS was significantly associated with RFS, T-stage, Gleason score, and tumor microenvironmental characteristics in PCa patients. Further analysis showed that the model grouping was closely related to tumor immune microenvironment characteristics, immune checkpoint inhibitors, and chemotherapeutic drug sensitivity. In this study, we developed a new BMGs-based prognostic model to determine the prognostic value of BMGs in PCa. Finally, we confirmed that THBS2, a key gene in BMRM, may be an important link in the occurrence and progression of PCa. This study provides a novel perspective to assess the prognosis of PCa patients and provides clues for the selection of future personalized treatment regimens.

An efficient method for qualitation and quantitation of multi-components of the herbal medicine Qingjin Yiqi Granules.

Qingjin Yiqi Granules (QJYQ) is a Traditional Chinese Medicines (TCMs) prescription for the patients with post-COVID-19 condition. It is essential to carry out the quality evaluation of QJYQ. A comprehensive investigation was conducted by establishing deep-learning assisted mass defect filter (deep-learning MDF) mode for qualitative analysis, ultra-high performance liquid chromatography and scheduled multiple reaction monitoring method (UHPLC-sMRM) for precise quantitation to evaluate the quality of QJYQ. Firstly, a deep-learning MDF was used to classify and characterize the whole phytochemical components of QJYQ based on the mass spectrum (MS) data of ultra-high performance liquid chromatography quadrupole time of flight tandem mass spectrometry (UHPLC-Q-TOF/MS). Secondly, the highly sensitive UHPLC-sMRM data-acquisition method was established to quantify the multi-ingredients of QJYQ. Totally, nine major types of phytochemical compounds in QJYQ were intelligently classified and 163 phytochemicals were initially identified. Furthermore, fifty components were rapidly quantified. The comprehensive evaluation strategy established in this study would provide an effective tool for accurately evaluating the quality of QJYQ as a whole.

A global profiling strategy for identification of the total constituents in Chinese herbal medicine based on online comprehensive two-dimensional liquid chromatography-quadrupole time-of-flight mass spectrometry combined with intelligentized chemical classification guidance.

A comprehensive strategy for effective identification of total constituents in Chinese patent medicine has been advanced applying full scan-preferred parent ions capture-static and active exclusion (FS-PIC-SAE) acquisition coupled with intelligent deep-learning supported mass defect filter (MDF) process, with Naoxintong capsule (NXT) as a case. Online comprehensive two-dimensional liquid chromatography (2DLC) coupled with Q-TOF-MS/MS system was established for obtaining the excellent separation and detection performance of total components, which could exhibit excellent peak capacity with 1052 and orthogonality with 0.69. In addition, a total of 901 unknown compounds could be classified into nine chemical classes rapidly and effectively, based on the intelligent deep-learning algorithm supported MDF model with 96.4% accuracy. Consequently, 276 compounds were successfully identified from NXT, especially including 44 flavonoids, 27 phenolic acids, 25 fatty acids, 17 saponins, 21 phthalocyanines, 20 triterpenes, 10 monoterpenes, 13 diterpenoid ketones, 14 amino acids, and others. It is concluded that the proposed program is an effective and practical strategy enabling the in-depth chemical profiling of complex herbal and biological samples.

An online stepwise background subtraction-based ultra-high pressure liquid chromatography quadrupole time of flight tandem mass spectrometry dynamic detection integrated with metabolic molecular network strategy for intelligent characterization of the absorbed chemical-fingerprint of QiangHuoShengShi decoction in vivo.

QiangHuoShengShi decoction (QHSS) was an ancient and classical traditional Chinese medicine (TCM) prescription. In the previous study, its phytochemical fingerprint had been comprehensively characterized. However, no reports were available on its absorbed prototypes and the related metabolites in rat plasma samples. In this study, an intelligent and innovate analysis strategy was built for characterizing metabolic chemical-fingerprint in rat plasma after oral administration of QHSS extract. Firstly, a very simple and highly efficient online stepwise background subtraction (BS)-based ultra-high pressure liquid chromatography quadrupole time of flight tandem mass spectrometry (UHPLC-Q-TOF-MS/MS) dynamic detection method was established to analyze the plasma samples. Secondly, the intelligent metabolic molecular network (MMN) technology was developed and used for rapidly screening out the metabolites of interest, which was followed by prediction of chemical types using the modified deep-learning assisted mass defect filter (MDF) analysis. Thirdly, the screened metabolites with identification features (metabolic pathways and chemical classification) were deeply characterized based on the MS/MS datasets. Finally, 58 prototypes of QHSS were successfully acquired and subsequently identified, including coumarins, chromones, phthalides, phenolic acids, flavonoids, and saponins. A total of 111 metabolites of the coumarins, chromones, phthalides were filtered to be tentatively characterized. This developed qualitative strategy was very helpful to quickly target medicine-related metabolites in the complex bio-matrix and, importantly, it could further visualize medicine-metabolic pathways hidden in the messy mass spectrum datasets. In all, the innovate strategy would provide a powerful tool for effectively acquiring and decode complex metabolic fingerprint of natural products in vivo.

Corrigendum to "Monitoring unbound warfarin in drug combination therapy by pharmacokinetics and fluorospectrometry" [Chinese Herbal Medicines 11 (2019) 92-97].

[This corrects the article DOI: 10.1016/j.chmed.2018.10.002.].

Notch Signaling Ligand Jagged1 Enhances Macrophage-Mediated Response to Helicobacter pylori.

Helicobacter pylori (H. pylori) is one of the gram-negative bacteria that mainly colonize the stomach mucosa and cause many gastrointestinal diseases, such as gastritis, peptic ulcer, and gastric cancer. Macrophages play a key role in eradicating H. pylori. Recent data have shown that Notch signaling could modulate the activation and bactericidal activities of macrophages. However, the role of Notch signaling in macrophages against H. pylori remains unclear. In the present study, in the co-culture model of macrophages with H. pylori, the inhibition of Notch signaling using γ-secretase decreased the expression of inducible nitric oxide synthase (iNOS) and its product, nitric oxide (NO), and downregulated the secretion of pro-inflammatory cytokine and attenuated phagocytosis and bactericidal activities of macrophages to H. pylori. Furthermore, we identified that Jagged1, one of Notch signaling ligands, was both upregulated in mRNA and protein level in activated macrophages induced by H. pylori. Clinical specimens showed that the number of Jagged1+ macrophages in the stomach mucosa from H. pylori-infected patients was significantly higher than that in healthy control. The overexpression of Jagged1 promoted bactericidal activities of macrophages against H. pylori and siRNA-Jagged1 presented the opposite effect. Besides, the addition of exogenous rJagged1 facilitated the pro-inflammatory mediators of macrophages against H. pylori, but the treatment of anti-Jagged1 neutralizing antibody attenuated it. Taken together, these results suggest that Jagged1 is a promoting molecule for macrophages against H. pylori, which will provide insight for exploring Jagged1 as a novel therapeutic target for the control of H. pylori infection.

Binary Eluent Based Vortex-Assisted Matrix Solid-Phase Dispersion for the Extraction and Determination of Multicomponent from Musk by Gas Chromatography-Mass Spectrometry.

A green, flexible, and effective strategy was proposed to quantify four target compounds (muscone, ethyl palmitate, ethyl oleate, and ethylparaben) from musk by binary eluent based vortex-assisted matrix solid-phase dispersion (MSPD) extraction coupled with GC/MS. Single-factor tests and orthogonal design were employed to optimize the MSPD parameters. In addition, the binary eluent system, methanol, and ethyl acetate 3 : 7 (v/v) were used to extract the target analytes. Finally, C 18 was applied as the easily available dispersant and the sample powder was ground for 2 min. Thereafter, the mixture was rapidly extracted with the binary eluents under whirling for 3 min. Eventually, the analysis of the samples was completed within 12 min by GC/MS. All correlation coefficients (r) of four targets were more than 0.9991. The recoveries of all target compounds ranged from 92.8% to 101% while their RSDs were less than 6.94%. There was no significant matrix interference for the analysis. Thus, the combination of vortex-assisted MSPD with GC/MS was considered as a novel, rapid, and environmentally friendly quantitative approach for musk samples.

A strategy for intelligent chemical profiling-guided precise quantitation of multi-components in traditional Chinese medicine formulae-QiangHuoShengShi decoction.

Due to the tremendous clinical value, more and more Traditional Chinese Medicines (TCMs) and their formulae are attracted by world's attention. QiangHuoShengShi (QHSS) decoction is one of classic TCM formulae, which is clinically used for treating various rheumatic diseases. However, the phytochemical constituents of QHSS have rarely been reported. A simple, intelligent, and comprehensive strategy was developed to characterize the phytochemical-fingerprint and quantify the chemical-markers for precise quality evaluation of QHSS. Firstly, a new deep-learning assisted mass defect filter (MDF) method was built for rapid and accurate classification of mass spectrum (MS) ions acquired by ultra-high performance liquid chromatography quadrupole time of flight tandem mass spectrometry (UHPLC-Q-TOF/MS). Subsequently, herb species-specific chemical-category and characteristic identification were used for further characterization of multi-components. As the result, seven major types of compounds in QHSS were intelligently differentiated and 183 phytochemical compounds were tentatively identified. Finally, a sensitive scheduled multiple reaction monitoring (sMRM) detection method was applied to precisely quantify 37 target analytes in QHSS decoction. This integrated strategy would provide an alternative method for chemical-material basis study of more herbal medicine or natural products.

A Metabolomics Coupled With Chemometrics Strategy to Filter Combinatorial Discriminatory Quality Markers of Crude and Salt-Fired Eucommiae Cortex.

Eucommiae Cortex is commonly used for treating various diseases in a form of the crude and salt-fired products. Generally, it is empirical to distinguish the difference between two types of Eucommiae Cortex. The metabolomics coupled with chemometrics strategy was proposed to filter the combinatorial discriminatory quality markers for precise distinction and further quality control of the crude and salt-fired Eucommiae Cortex. The metabolomics data of multiple batches of Eucommiae Cortex samples was obtained by ultra-high performance liquid chromatography coupled with mass spectrometry (UHPLC-MS). Orthogonal partial least-squares discriminant analysis was utilized to filter candidate markers for characterizing the obvious difference of the crude and salt-fired Eucommiae Cortex. The accuracy of combinatorial markers was validated by random forest and partial least squares regression. Finally, eleven combinatorial discriminatory quality markers from 67 identified compounds were rapidly screened, identified, and determined for distinguishing the difference between crude and salt-fired Eucommiae Cortex. It was demonstrated that UHPLC-MS based metabolomics with chemometrics was a powerful strategy to screen the combinatorial discriminatory quality markers for distinguishing the crude and salt-fired Eucommiae Cortex and to provide the reference for precise quality control of Eucommiae Cortex.