Recent advances in chemical protein synthesis: method developments and biological applications

Glioblastoma multiforme (GBM) is the most frequent and deadly human brain cancer. Early diagnosis through non-invasive biomarkers may render GBM more easily treatable, improving the prognosis of this currently incurable disease. We suggest the use of serum extracellular vesicle (sEV)-derived circular RNAs (circRNAs) as highly stable minimally invasive diagnostic biomarkers for GBM diagnosis. EVs were isolated by size exclusion chromatography from sera of 23 GBM and 5 grade 3 glioma (GIII) patients, and 10 unaffected controls (UC). The expression of two candidate circRNAs (circSMARCA5 and circHIPK3) was assayed by droplet digital PCR. CircSMARCA5 and circHIPK3 were significantly less abundant in sEVs from GBM patients with respect to UC (fold-change (FC) of -2.15 and -1.92, respectively) and GIII (FC of -1.75 and -1.4, respectively). Receiver operating characteristic curve (ROC) analysis, based on the expression of sEV-derived circSMARCA5 and circHIPK3, allowed us to distinguish GBM from UC (area under the curve (AUC) 0.823 (0.667-0.979) and 0.855 (0.704 to 1.000), with a 95% confidence interval (CI), respectively). Multivariable ROC analysis, performed by combining the expression of sEV-derived circSMARCA5 and circHIPK3 with preoperative neutrophil to lymphocyte (NLR), platelet to lymphocyte (PLR) and lymphocyte to monocyte (LMR) ratios, three known diagnostic and prognostic GBM markers, allowed an improvement in the GBM diagnostic accuracy (AUC 0.901 (0.7912 to 1.000), 95% CI). Our data suggest sEV-derived circSMARCA5 and circHIPK3 as good diagnostic biomarkers for GBM, especially when associated with preoperative NLR, PLR and LMR.

https://www.mdpi.com/1424-8247/14/7/618/pdf

Serum Extracellular Vesicle-Derived circHIPK3 and circSMARCA5 Are Two Novel Diagnostic Biomarkers for Glioblastoma Multiforme.

Gold Nanoparticles-Based Photothermal Therapy for Breast Cancer.

Abstract The stimuli-responsive nanofibers prepared by electrospinning have become an ideal stimuli-responsive material due to their large specific surface area and porosity, which can respond extremely quickly to external environmental incitement. As an intelligent drug delivery platform, stimuli-responsive nanofibers can efficiently load drugs and then be stimulated by specific conditions (light, temperature, magnetic field, ultrasound, pH or ROS, etc.) to achieve slow, on-demand or targeted release, showing great potential in areas such as drug delivery, tumor therapy, wound dressing, and tissue engineering. Therefore, this paper reviews the recent trends of stimuli-responsive electrospun nanofibers as intelligent drug delivery platforms in the field of biomedicine. 

Stimuli-responsive electrospun nanofibers for drug delivery, cancer therapy, wound dressing, and tissue engineering

In some malignant tumors, a high neutrophil-to-lymphocyte ratio (NLR) is connected with unfavorable prognosis. Nevertheless, the prognostic value of the NLR in gliomas remains disputed. The clinical significance of the NLR in gliomas was investigated in our study. The databases, PubMed, Embase, and the Cochrane Library, were searched using words like “glioma,” “glioblastoma,” “neutrophil-to-lymphocyte ratio,” and others through May 2019. We evaluated the significance of NLR on overall survival (OS) of patients with gliomas in our study. Finally, 16 cohorts with 2275 patients were analyzed. The pooled analysis revealed that an elevated NLR was connected with unfavorable OS (hazards ratio (HR): 1.43, 95% confidence interval (CI): 1.27–1.62) outcomes of patients with gliomas. A high NLR can be considered a high-risk prognostic factor in gliomas, and more adjuvant chemotherapy should be recommended for high-risk patients.

/pdf/prognostic-impact-of-neutrophil-to-lymphocyte-ratio-in-2cj91e98rw.pdf

Prognostic impact of neutrophil-to-lymphocyte ratio in gliomas: a systematic review and meta-analysis.

The neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) have been recognized as inflammatory markers and used as prognostic makers in various cancers. The present study sought to investigate the prognostic role of NLR and PLR in Chinese patients with glioma. Clinical data, including NLR, PLR and overall survival (OS), were collected from 112 patients who underwent surgery to treat primary glioma. Kaplan-Meier survival analysis as well as uni- and multivariate Cox regression were performed to examine potential associations of preoperative NLR and PLR with OS. Among all patients, mean NLR was 3.80±1.48 and mean PLR was 183.60±81.38. NLR increased with increasing WHO tumor grade (p 0.05). Patients with NLR ≥ 4 had significantly shorter mean OS (20.75±7.68 months) than patients with NLR 200), tumor size (≥ 5 cm), WHO grade (III/IV), and Karnofsky Performance Status ( 4 as an independent predictor of OS (HR 1.932, 95 % CI 1.011 to 3.694, p = 0.046). Our results suggest that at least in Chinese patients, increased preoperative NLR and PLR are associated with worse OS, and NLR may be an independent risk factor to identify glioma patients with poor prognosis. These results should be validated and extended in larger clinical studies.

Prognostic significance of preoperative neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in patients with glioma.

Heat-Generating Mn0.5Zn0.5Fe2O4/MWCNTs Nanocomposites for Enhancing Hyperthermia Efficacy in Magnetic Hyperthermia Applications

Crizotinib is used for the treatment of c‐ros oncogene 1–positive advanced non–small‐cell lung cancer. Triazole antifungal agents are widely used for invasive fungal infections in clinical practice. To predict the potential influence of different triazoles (voriconazole, fluconazole, and itraconazole) on the pharmacokinetics of crizotinib by modeling and simulation the physiologically based pharmacokinetic models were established and validated in virtual cancer subjects through Simcyp software based on the essential physicochemical properties and pharmacokinetic data collected. The validated physiologically based pharmacokinetic models were applied to predict the drug‐drug interactions between crizotinib and different triazoles (voriconazole, fluconazole, or itraconazole) in patients with cancer. Crizotinib and triazole antifungal agents were administered orally. The predicted plasma concentration vs time profiles of crizotinib, voriconazole, fluconazole, and itraconazole showed good agreement with observed, respectively. The geometric mean area under the plasma concentration–time curve (AUC) of crizotinib was increased by 84%, 58%, and 79% when coadministered with voriconazole, fluconazole, or itraconazole at multiple doses, respectively. The drug‐drug interaction results showed increased pharmacokinetic exposure (maximum plasma concentration and area under the plasma concentration–time curve) of crizotinib when coadministrated with different triazoles (voriconazole > itraconazole > fluconazole). Among the 3 triazoles, voriconazole exhibited the most significant influence on the pharmacokinetic exposure of crizotinib. In clinic, adverse drug reactions and toxicity related to crizotinib should be carefully monitored, and therapeutic drug monitoring for crizotinib is recommended to guide dosing and optimize treatment when coadministered with voriconazole, fluconazole, or itraconazole.

Use of Modeling and Simulation to Predict the Influence of Triazole Antifungal Agents on the Pharmacokinetics of Crizotinib

The design of experiments (DoE) method was employed to optimize the adsorption processes of seven psychoactive substances in magnetic solid phase extraction. Fe3O4/GO/ZIF-8 was utilized as an adsorbent for the efficient extraction of psychoactive substances from environmental water samples. The analytes were ephedrine, methylephedrine, amphetamine, methamphetamine, morphine, papaverine, and thebaine, which were determined by ultrahigh performance liquid chromatography-tandem mass spectrometry. Plackett-Burman design was employed to identify the significant factors responsible for adsorption, and Box-Behnken design was used for further optimization to obtain the optimum values for each variable. The predicted and experimental values were found to be in good agreement. The coefficient of determination (R2) values of 0.9500-0.9976 indicated that the model was significant. The linear ranges were 1-100 ng mL-1, and the correlation coefficient was good (r2 ≥ 0.995). The EF with values of about 2.5 was obtained with recoveries in the range of 74.92-94.47%. The limits of detection (LOD) and limits of quantification (LOQ) were 0.086-0.353 ng mL-1 and 0.286-1.175 ng mL-1, respectively. The intra-day and inter-day RSDs were in the range of 0.17-1.87% and 0.06-2.21%, respectively. By using the DoE method, the errors associated with inferring the influence and interaction between various factors can be reduced. The combination of MSPE and DoE improves the recovery, precision, and simultaneous detectability of the target analytes. It has a high potential for psychoactive substance analysis in environmental water.

Design of experiments (DoE) to develop and to optimize extraction of psychoactive substances.

Background: Bruton’s tyrosine kinase (BTK) inhibitors are commonly used in the targeted therapy of B-cell malignancies. It is reported that myelosuppression and fungal infections might occur during antitumor therapy of BTK inhibitors, therefore a combination therapy with triazole antifungals is usually required. Objective: To evaluate the influence of different triazoles (voriconazole, fluconazole, itraconazole) on the pharmacokinetics of BTK inhibitors (zanubrutinib, acalabrutinib) and to quantify the drug-drug interactions (DDIs) between them. Methods: The physiologically-based pharmacokinetic (PBPK) models were developed based on pharmacokinetic parameters and physicochemical data using Simcyp® software. These models were validated using clinically observed plasma concentrations data which based on existing published studies. The successfully validated PBPK models were used to evaluate and predict potential DDIs between BTK inhibitors and different triazoles. BTK inhibitors and triazole antifungal agents were simulated by oral administration. Results: Simulated plasma concentration-time profiles of the zanubrutinib, acalabrutinib, voriconazole, fluconazole, and itraconazole are consistent with the clinically observed profiles which based on existing published studies, respectively. The exposures of BTK inhibitors increase by varying degrees when co-administered with different triazole antifungals. At multiple doses regimen, voriconazole, fluconazole and itraconazole may increase the area under plasma concentration-time curve (AUC) of zanubrutinib by 127%, 81%, and 48%, respectively, and may increase the AUC of acalabrutinib by 326%, 119%, and 264%, respectively. Conclusion: The PBPK models sufficiently characterized the pharmacokinetics of BTK inhibitors and triazole antifungals, and were used to predict untested clinical scenarios. Voriconazole exhibited the greatest influence on the exposures of BTK inhibitors. The dosage of zanubrutinib or acalabrutinib need to be reduced when co-administered with moderate CYP3A inhibitors.

Use of modeling and simulation to predict the influence of triazole antifungal agents on the pharmacokinetics of zanubrutinib and acalabrutinib

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