Osteosarcoma (OS), the most prevalent bone malignancy, mainly affects children and adolescents. Despite recent advances in multimodal therapy, the overall survival rate for OS patients remains poor. Chinese herb medicine (CHM) is an alternative therapeutic option for multifaceted diseases such as malignant tumors. For centuries in China, polygonum cuspidatum, a classic CHM, has been used to treat several diseases, nevertheless, the mechanisms underlying its therapeutic effects have not been fully elucidated. Through network pharmacology and bioinformatic tools, we evaluated the pharmacological activity of polygonum cuspidatum. We found that it has a potential therapeutic effect on malignant tumors, which was subsequently verified by intragastric administration of polygonum cuspidatum to OS cell xenografted mice models. Next, to establish the action mechanism of polygonum cuspidatum, we built a disease/drug-target PPI network that was made up of 250 core treatment targets against OS using Cytoscape software. Enrichment evaluation for the above targets indicated that polygonum cuspidatum may exert its effects on the cell cycle and apoptosis of OS cells through inhibiting Akt/ERK/EGFR pathways. Finally, the above in silico results were experimentally validated via a series of molecular biological and cell functional analyses. Taken together, the findings show that polygonum cuspidatum has a significant potential for OS treatment, which provides a novel insight into the discovery of CHM-based drug against malignancies.

This study aimed to apply a physiologically based pharmacokinetic (PBPK) model to predict optimal dosing regimens of pazopanib (PAZ) for safe and effective administration when co-administered with CYP3A4 inhibitors, acid-reducing agents, food, and administered in patients with hepatic impairment. Here, we have successfully developed the population PBPK model and the predicted PK variables by this model matched well with the clinically observed data. Most ratios of prediction to observation were between 0.5 and 2.0. Suitable dosage modifications of PAZ have been identified using the PBPK simulations in various situations, i.e., 200 mg once daily (OD) or 100 mg twice daily (BID) when co-administered with the two CYP3A4 inhibitors, 200 mg BID when simultaneously administered with food or 800 mg OD when avoiding food uptake simultaneously. Additionally, the PBPK model also suggested that dosing does not need to be adjusted when co-administered with esomeprazole and administration in patients with wild hepatic impairment. Furthermore, the PBPK model also suggested that PAZ is not recommended to be administered in patients with severe hepatic impairment. In summary, the present PBPK model can determine the optimal dosing adjustment recommendations in multiple clinical uses, which cannot be achieved by only focusing on AUC linear change of PK.

This study aimed to build a mathematical model of physiologically based pharmacokinetic combined DPP-4 occupancy (PBPK-DO) in humans to provide some recommendations for dosing adjustment in patients with renal impairment. The PBPK-DO model was built using physicochemical and biochemical properties and binding kinetics data of TRE and OMA, and then validated by the clinically observed pharmacokinetics (PK) and pharmacodynamics (PD). Finally, the model was applied to determine dose adjustment in patients with renal impairment. The predicted PK and DPP-4 occupancy matched well with the clinically observed data, and all absolute average-folding errors (AAFEs) were within 2. The simulations showed that TRE and OMA were both suggested to only support dose reduction by half in patients with severe renal impairment based on this PBPK-DO model, which is different from the commendations only in terms of their AUC_0-336 changes. These simulation results were in good agreement with clinical recommendations about dosage adjustment in patients. The present PBPK-DO model can simultaneously predict PK and PD of TRE and OMA in humans and also provide valuable recommendations for dosing adjustment in renal impairment patients, which cannot be achieved by alone depending on PK change.

Backgrounds: Brain metastases occur in approximately 30% of patients with non-small-cell lung cancer (NSCLC). Therefore, the free drug concentration in cerebrospinal fluid (CSF) is strongly associated with the clinical efficacy.Purpose: The present study aimed to develop physiologically based pharmacokinetic (PBPK) models that can predict the steady-state trough concentration (C_trough) in plasma and CSF, as well as anaplastic lymphoma kinase (ALK) occupancy (AO), for three inhibitors: crizotinib (CRI), alectinib (ALE), and lorlatinib (LOR).Methods: To achieve this, population PBPK models were successfully developed and validated using multiple clinical pharmacokinetics (PK) and drug–drug interaction (DDI) studies, both in healthy subjects and patients.Results: The prediction-to-observation ratios for plasma AUC, C_max, and C_trough in heathy subjects and patients ranged between 0.5 and 2.0. In addition, PK profiles of CRI, ALE, and LOR in CSF aligned well with observed data. Moreover, the AUC and C_max ratios of the three inhibitors when co-administered with CYP3A4 inhibitors/inducers also matched with clinically observed values. Utilizing PK thresholds for effective plasma C_trough and AO values on wild-type and four ALK mutations in plasma and CSF, PBPK models were then combined with the mean and 95% confidence interval to predict optimal dosing regimens.Conclusions: Overall, these PBPK models provide valuable insights into determining appropriate dosing regimens for the three ALK inhibitors, understanding their effectiveness in brain metastasis therapy, and analyzing the underlying mechanisms of on-target resistance.

Gastric cancer (GC) remains a global health challenge with limited therapeutic options, highlighting the need for novel treatments. Traditional Mongolian medicine Ana Gaqi Nari (AGN) offers promising anti-cancer potential, but its molecular mechanisms remain poorly understood. Multi-omics approaches provide an unprecedented opportunities to decode complex herbal formulations and bridge traditional knowledge with modern systems biology. To elucidate AGN's molecular mechanisms in GC treatment using an integrative strategy combining network pharmacology, multi-omics analyses, and experimental validation, while identifying bioactive compounds and therapeutic targets. We employed integrative multi-omics approaches to predict AGN's bioactive components and targets, followed by molecular docking and binding assays. In vitro and in vivo models assessed AGN's effects on apoptosis, pyroptosis, and pro-survival pathways. Multi-omics profiling characterized AGN's impact on GC metabolism and inflammation. Xenograft studies compared AGN's efficacy and safety to standard chemotherapy. Multi-omics analysis identified piperine as AGN's primary bioactive compound, exhibitING strong binding to d-amino acid oxidase (DAO) (-10.3 kcal/mol), a novel GC target associated with poor prognosis. AGN demonstrated dual anti-cancer effects by inducing both apoptosis and pyroptosis while suppressing pro-survival AKT/ERK signaling. AGN remodeled amino acid and lipid metabolism, disrupting GC's metabolic plasticity, and antagonized IL-17A-mediated inflammation. In xenograft models, AGN showed dose-dependent tumor suppression comparable to standard chemotherapy with superior safety profiles. DAO and IL-17A emerged as potential biomarkers for patient stratification. This study reveals AGN as a multi-target GC therapy DAO modulation, IL-17A suppression, metabolic reprogramming, and programmed cell death induction. By integrating multi-omics and ethnopharmacology, we provide a framework for modernizing traditional herbal medicines into evidence-based therapies, positioning AGN as a potential candidate for precision GC treatment.

Liver cancer is one of the most common and highly lethal malignancies worldwide, and current therapeutic strategies remain limited, posing significant clinical challenges. Thermal processing of natural products is not only used for the extraction of active constituents, but may also induce structural reconstruction and bioactivity transformation of endogenous components. Recent studies have demonstrated that certain natural products can generate carbon dots (CDs) with specific biological activities under high-temperature conditions, suggesting that these nanoparticles may serve as novel active components formed during thermal processing. Phellinus igniarius, a traditional medicinal fungus, possesses anti-inflammatory and immunomodulatory activities. However, the formation of carbon dots during its thermal processing and their biological functions have not been systematically investigated. In this study, Phellinus igniarius-derived carbon dots (PI-CDs) were synthesized using a hydrothermal method, and their antitumor activities and underlying mechanisms were systematically evaluated both in vitro and in vivo . The results showed that PI-CDs exhibited uniform nanoscale morphology with good dispersibility. In vitro experiments demonstrated that PI-CDs significantly inhibited the viability, migration, and invasion of liver cancer cells in a concentration-dependent manner. Transcriptomic analysis revealed significant enrichment of MAPK signaling and apoptosis-related pathways, which was further supported by increased phosphorylation of p38 and JNK. Mechanistically, PI-CDs induced intracellular reactive oxygen species (ROS) accumulation, promoted mitochondrial membrane depolarization, and triggered apoptotic cell death. Furthermore, PI-CDs effectively suppressed tumor growth in vivo xenograft model without obvious systemic toxicity. Collectively, these findings suggest that PI-CDs exert antitumor effects through oxidative stress-associated MAPK signaling and mitochondria-dependent apoptosis. This study demonstrates that carbon dots generated from the medicinal fungus Phellinus igniarius possess significant anti-liver cancer activity and reveals a ROS/MAPK-associated mechanism underlying their biological effects. More importantly, our findings highlight thermal processing as a promising strategy for transforming traditional medicinal resources into functional nanomaterials with intrinsic therapeutic potential, thereby providing a new perspective for the development of natural product-derived nanomedicines for cancer treatment.