Population pharmacokinetics of free and liposome-encapsulated mitoxantrone in patients with relapsed/refractory lymphoma or small cell lung cancer.

OBJECTIVE: This study is aimed at investigating the pharmacokinetic (PK) characteristics of pegylated liposomal mitoxantrone (PLM) in patients with relapsed/refractory lymphoma or small cell lung cancer (SCLC) by constructing population pharmacokinetic (popPK) models for both liposome-encapsulated mitoxantrone and free mitoxantrone. METHODS: A total of 23 patients with relapsed/refractory lymphoma and 42 patients with SCLC were included. A popPK model was simultaneously developed utilizing a non-linear mixed effects model (NONMEM) to explore the PK profiles of liposome-encapsulated mitoxantrone and free mitoxantrone. Clearance (CL) and distribution volume (V) were calculated, and covariate analysis was employed to evaluate the influence of patient disease type, demographic information, and biochemical indicators of liver and kidney function on PK parameters. RESULTS: The concentration-time profiles for both liposome-encapsulated mitoxantrone and free mitoxantrone were described by a one-compartment model. The release (Rel) of liposome-encapsulated mitoxantrone to free mitoxantrone was determined to be 0.0191 L/h, and the V of liposome-encapsulated mitoxantrone was 2.32 L. The apparent CL of free mitoxantrone was estimated at 1.66 L/h. The apparent V of free mitoxantrone was 35.8 L in patients with relapsed/refractory lymphoma and 22.2 L for patients with SCLC. In patients with relapsed/refractory lymphoma, lower maximum concentration (Cmax) and higher apparent V of free mitoxantrone were observed compared with patients with SCLC. CONCLUSION: The popPK characteristics of both liposome-encapsulated and free mitoxantrone in patients with relapsed/refractory lymphoma or SCLC were effectively described by a one-compartment model.

Exploring the effect of Wuzhi capsule on the pharmacokinetics of regorafenib and its main metabolites in rat plasma using liquid chromatography-tandem mass spectrometry.

Regorafenib is a small-molecule tyrosine kinase inhibitor with severe hepatotoxicity. It undergoes metabolism mainly by CYP3A4 to generate active metabolites regorafenib-N-oxide (M2) and N-desmethyl-regorafenib-N-oxide (M5). Wuzhi capsule (WZC) is an herbal preparation derived from Schisandra sphenanthera and is potentially used to prevent regorafenib-induced hepatotoxicity. This study aims to explore the effect of WZC on the pharmacokinetics of regorafenib in rats. An efficient and sensitive liquid chromatography-tandem mass spectrometry method was developed to quantitatively determine regorafenib and its main metabolites in rat plasma. The proposed method was applied to the pharmacokinetic study of regorafenib in rats, with or without WZC. Coadministration of regorafenib with WZC resulted in a prolonged mean residence time (MRT) of the parent drug but had no statistically significant difference in other pharmacokinetic parameters. While for the main metabolites of regorafenib, WZC decreased the area under the curve and maximum concentration (Cmax ), delayed the time to reach Cmax , and prolonged the MRT of M2 and M5. These results indicate that WZC delayed and inhibited the metabolism of regorafenib to M2 and M5 by suppressing CYP3A4. Our study provides implications for the rational use of the WZC-regorafenib combination in clinical practice.

Molecular Subtypes Based on PANoptosis Genes and Characteristics of Immune Infiltration in Cutaneous Melanoma.

Cutaneous melanoma (CM) remains the most life-threatening form of skin cancer. Further risk stratification and search for new prognostic targets for CM are of positive clinical significance. PANoptosis is defined as an inflammatory programmed cell death mediated by the PANoptosome complex and cannot be characterized by pyroptosis, apoptosis or necroptosis alone. Although PANoptosis is closely associated with many diseases including cancer, it has not been reported in CM. Combined with GTEx and TCGA database, we extracted 14 PANoptosis-related genes (PAGs). The molecular subtypes of CM were then analyzed by PAGs and their associations with the immune microenvironment and immunotherapy reactivity were analyzed. LASSO and univariate Cox analysis was performed on PAGs-related differentially expressed genes to establish PAGs characteristics that could effectively predict the prognosis of CM patients. Immune infiltration, tumor mutation burden analysis, immunotherapy response and drug sensitivity analysis were used to further analyze the causes of prognostic differences. Our study provides a new perspective on the role of PANoptosis in CM.

Reply to "A better interpretation of data regarding the opioid switching to methadone".

In our article ?Methadone switching for refractory cancer pain' (BMC palliative care, 2022) we explore the efficacy, safety and economics of methadone in treatment of patients with refractory cancer pain in China. Professor Mercadante provided a better interpretation of data regarding the opioid switching to methadone in the Matters Arising. In this article, we answered the questions in Mercadante et al.'s comments one by one.

Methadone switching for refractory cancer pain.

BACKGROUND: Methadone is commonly considered an alternative opioid treatment for refractory cancer pain. This study aims to investigate the efficacy, safety, and cost of methadone in the treatment of refractory cancer pain. METHODS: A retrospective study was conducted in patients who used methadone for refractory cancer pain from April 2016 to December 2020 at a cancer specialized hospital. Pain control, evaluated via pain score and breakthrough pain frequency, and adverse events of methadone were compared with analgesic regimens prior to methadone administration. The factors potentially affecting the switching outcome were analyzed via multivariate analysis. Moreover, the cost of pain control was estimated. RESULTS: Ninety patients received methadone for poor pain control (74.4%), intolerable adverse events (10.0%), or both (15.6%) after prior opioid treatments. Sixty-four patients (71.1%) were successfully switched to methadone with median pain score significantly decreased from 4.0 to 2.0 (p < 0.001) and median daily frequency of breakthrough pain from 3.0 to 0.0 (p < 0.001) at a maintained median conversion ratio of 6.3 [interquartile range (IQR): 4.0-10.0] to prior opioid treatment. Similar adverse event profiles of constipation, nausea, vomiting, and dizziness were observed between methadone and prior opioid regimens. The median daily cost of analgesic regimens was significantly reduced from $19.5 (IQR: 12.3-46.2) to $10.8 (IQR: 7.1-18.7) (p < 0.01) after switching to methadone. The 3-day switch method significantly improved the rate of successful switching compared with the stop and go method (odds ratio = 3.37, 95% CI: 1.30-8.76, p = 0.013). CONCLUSION: Methadone is an effective, safe, and cost-saving treatment for patients with refractory cancer pain.

Spectrum-Effect Relationship-Based Strategy Combined with Molecular Docking to Explore Bioactive Flavonoids from Sceptridium ternatum.

Sceptridium ternatum is a herbaceous plant with significant potential for pharmaceutical and cosmetic applications. In this study, we established a spectrum-effect relationship-based strategy to investigate the bioactive basis and tissue distribution in S. ternatum. First, a phytochemical analysis on the ethanol extracts from roots, stems, and leaves of S. ternatum was performed using the colorimetric method, high-performance liquid chromatography-ultraviolet (HPLC-UV), and high-performance liquid chromatography-electrospray ionization quadrupole time-of-flight mass spectrometry (HPLC-ESI-Q-TOF-MS/MS). Then, radical scavenging assays and the lipopolysaccharide-stimulated RAW 264.7 cell model were used to estimate the antioxidant and anti-inflammatory activities, respectively. Spectrum-effect relationship analysis and molecular docking were further employed to evaluate the correlation between the phytochemical profile and anti-inflammatory activity. Our results demonstrate that S. ternatum leaves contained the most abundant flavonoids and exerted the best biological activities. Their IC50 values for scavenging 2,2'-azino-bis (3-ethylbenzthiazoline-6-sulfonic acid) and 1,1-diphenyl-2-picrylhydrazyl radicals were 2.43 ± 0.13 and 5.36 ± 0.54 mg/mL, respectively. In lipopolysaccharide-stimulated RAW 264.7 cells, the leaf extract caused the greatest reduction in nitric oxide production (38.15%) and interleukin-6 release (110.86%). Spectrum-effect relationship analysis and molecular docking indicated that quercetin 3-O-rhamnoside-7-O-glucoside possessed high anti-inflammatory activity by binding with interleukin-6. In conclusion, S. ternatum is a rich source of bioactive flavonoids with potential for exploitation in the prevention and treatment of oxidative stress and inflammation-related pathologies.

Comprehensive evaluation of the antioxidant capacity of Sceptridium ternatum using multiple colorimetric methods and 1,1-diphenyl-2-picrylhydrazyl-high-performance liquid chromatography analysis.

Sceptridium ternatum is a medicinal herb with multiple health benefits. However, its antioxidant activity and active components have not been clarified. In this study, the antioxidant capacity of S. ternatum was comprehensively investigated using multiple colorimetric methods and 1,1-diphenyl-2-picrylhydrazyl-high-performance liquid chromatography analysis. First, the phenolic content, flavonoid content, and radical scavenging ability of S. ternatum were parallelly determined using colorimetric methods performed in 96-well microplates. The flavonoid content, rather than the phenolic content, was highly correlated with its antioxidant activity. Sceptridium ternatum was shown to be a rich source of flavonoids, with a highest flavonoid yield of 3.44 ± 0.11 mg/g. Subsequently, 1,1-diphenyl-2-picrylhydrazyl-high-performance liquid chromatography experiment and quadrupole time-of-flight mass spectrometry analyses were carried out for rapid screening of the individual antioxidants. A total of 14 O-glycosyl flavonoids with quercetin or kaempferol aglycone have been characterized. Particularly, quercetin 3-O-rhamnoside-7-O-glucoside exhibited the most potent antioxidant ability. Its half-maximal effective concentrations for scavenging 1,1-diphenyl-2-picrylhydrazyl and 2,2'-azino-bis (3-ethylbenzthiazoline-6-sulfonic acid) radicals were 70.55 ± 2.69 and 106.90 ± 1.76 µg/mL, respectively, which were comparable with those of l-ascorbic acid. Our results indicated that the combined colorimetric and chromatographic methods provided a practical strategy for the discovery of bioactive compounds from natural products.

Asiatic acid enhances intratumor delivery and the antitumor effect of pegylated liposomal doxorubicin by reducing tumor-stroma collagen.

Tumor-targeted drug delivery systems (Tt-DDSs) are proposed as a promising strategy for cancer care. However, the dense collagen network in tumors stroma significantly reduces the penetration and efficacy of Tt-DDS. In order to investigate the effect of asiatic acid (AA) on antitumor effect of pegylated liposomal doxorubicin (PLD) by attenuating stroma-collagen, colon cancer xenograft mice (SW620 cell line) were treated by PLD, AA, or combined regimes, respectively; the collagen levels were estimated by Sirius red/fast green dual staining and immunohistochemistry (IHC) staining; the intratumor exposure of doxorubicin was visualized by ex vivo fluorescence imaging and quantified by HPLC/MS analysis. In addition, the impact of AA on collagen synthesis of fibroblast cell (HFL-1) and cytotoxic effect of PLD and doxorubicin to cancer cell (SW620) were studied in vitro. In the presence of AA (4 mg/kg), the intratumor collagen level was restricted in vivo (reduced by 22%, from 4.14% ± 0.30% to 3.24% ± 0.25%, P = 0.051) and in vitro. Subsequently, doxorubicin level was increased by ~30%. The antitumor activity of PLD was significantly improved (57.3% inhibition of tumor growth and 44% reduction in tumor weight) by AA combination. Additionally, no significant improvement in cytotoxic effect of PLD or doxorubicin induced by AA was observed. In conclusion, AA is a promising sensitizer for tumor treatment by enhancing intratumor drug exposure via stromal remodeling.

Long non-coding RNA NEAT1 promotes hepatocellular carcinoma cell proliferation through the regulation of miR-129-5p-VCP-IκB.

Long non-coding RNA nuclear-enriched abundant transcript 1 (NEAT1) plays an important role in the pathogenesis and development of several types of cancer. However, the functional mechanism of NEAT1 in hepatocellular carcinoma (HCC) remains unclear. NEAT1 and microRNA (miR)-129-5p expression in HCC tissues and cell lines was quantified by means of quantitative PCR. The effects of NEAT1 expression inhibition or upregulation in HCC cell lines were analyzed in terms of cell viability and apoptosis. Biological software was used to predict the binding sites of NEAT1 and miR-129-5p. The expression of the miR-129-5p target molecules valosin-containing protein (VCP) and IκB was detected using Western blotting. The effect of NEAT1 on tumor growth was observed in mouse models of transplanted hepatoma. In the present study, it was concluded that the expression of NEAT1 was significantly increased in the HCC tissues and cell lines. Meanwhile, after downregulating NEAT1 expression in HepG2/Huh7 cell lines, the cell viability was significantly lowered, whereas the corresponding rate of apoptosis was significantly increased. Additionally, it was found that the NEAT1 and miR-129-5p expression showed a negative correlation in HCC tissues. It was further proved that there was a certain negative regulatory mechanism between NEAT1 and miR-129-5p, which was related to the expression of VCP and IκB. The mouse model experiments confirmed that the interference with NEAT1 expression inhibited tumor growth. The study concluded that the overexpression of NEAT1 inhibited the expression of miR-129-5p by regulating VCP/IκB, thereby promoting the proliferation of HCC cells. This study provides new insights into the pathogenesis of HCC, as well as identifying new target genes for diagnosis and treatment.NEW & NOTEWORTHY The results provide strong evidence that upregulated NEAT1 promotes the proliferation of cancer cells in hepatocellular carcinoma (HCC) and this regulatory mechanism depends on the microRNA (miR)-129-5p-valosin-containing protein-IκB axis. The study also indicates that NEAT1 could be a potential therapeutic target for HCC.

Construction and validation of a mitochondria-associated genes prognostic signature and immune microenvironment characteristic of sepsis.

BACKGROUND: Sepsis is a common critical condition seen in clinical settings, with mitochondrial dysfunction playing an important role in the progression of sepsis. However, a mitochondrial prognosis model related to sepsis has not been established yet, and the relationship between the sepsis immune microenvironment and mitochondria remains unclear. METHODS: Sepsis prognostic mitochondria-associated genes (MiAGs) were screened by univariate Cox, multivariate Cox, and LASSO analysis from the GEO dataset. Consensus Cluster was used to analyze MiAGs-based molecular subtypes for sepsis. The ESTIMATE and ssGSEA algorithms were used to analyze the situation of sepsis immune cell infiltration and its relation to MiAGs. Further, MiAGs score was calculated to construct a sepsis prognosis risk model to predict the prognosis of sepsis patients. Clinical blood samples were used to investigate the expression level of selected MiAGs in sepsis. Single-cell sequencing analysis, mitochondrial membrane potential (MMP), reactive oxygen species (ROS), and ATP detection were used to verify the influence of MiAGs on mitochondrial dysfunction in sepsis. RESULTS: A total of 5 MiAGs of sepsis were screened. Based on MiAGs, sepsis MiAGs subtypes were analyzed, where Cluster A had a better prognosis than Cluster B, and there were significant differences in immune infiltration between the two clusters. The sepsis mitochondrial prognosis model suggested that the high MiAG score group had a shorter survival time compared to the low MiAG score group. Significant differences were also observed in the immune microenvironment between the high and low MiAG score groups. Prognostic analysis and the Nomogram indicated that the MiAG score is an independent prognostic factor in sepsis. Single-cell sequencing analysis exhibited the possible influence of MiAGs on the mitochondrial function of monocytes. Finally, the downregulation of the COX7B could effectively improve mitochondrial function in the LPS-stimulated sepsis model. CONCLUSION: Our findings suggest that MiAGs can be used to predict the prognosis of sepsis and that regulating the mitochondrial prognostic gene COX7B can effectively improve the mitochondrial function of immune cells in sepsis.

Evaluation of omadacycline regimens for community-acquired bacterial pneumonia patients infected with Staphylococcus Aureus by pharmacokinetic/pharmacodynamic analysis.

Omadacycline is an FDA-approved agent for community-acquired bacterial pneumonia (CABP). The purpose of this study is to evaluate the effectiveness of omadacycline for treating CABP patients infected with Staphylococcus aureus, including Methicillin-Resistant Staphylococcus aureus (MRSA) and Methicillin-Susceptible Staphylococcus aureus (MSSA), using pharmacokinetic/pharmacodynamic (PK/PD) analysis. Monte Carlo simulations (MCSs) were performed by utilizing omadacycline pharmacokinetic (PK) parameters, minimum inhibitory concentration (MIC) data, and in vivo PK/PD targets to calculate the probability of target attainment (PTA) and cumulative fraction of response (CFR) values for different dose regimens against MRSA and MSSA in CABP patients. A dosage regimen with a PTA or CFR expectation value greater than 90% was considered optimal. For all recommended dose regimens, PTA values for MRSA MIC ≤1 and MSSA MIC ≤4 on days 1, 4, and 7 were greater than 90%. Based on the MIC distribution of Staphylococcus aureus, all dose regimens had CFR values greater than 90% for both MRSA and MSSA. CFR values for different bacterial strains were still greater than 90% within the range of PK/PD target values less than 40, although they gradually decreased with increasing PK/PD target values. PK/PD modeling demonstrated that all recommended dose regimens of omadacycline are highly effective against CABP patients infected with MRSA and MSSA. The study provides theoretical support for the efficacy of omadacycline in different dose regimens.

Cost-effectiveness analysis of tislelizumab plus chemotherapy as the first-line treatment for advanced or metastatic oesophageal squamous cell carcinoma in China.

OBJECTIVE: We aimed to investigate the cost-effectiveness of tislelizumab plus chemotherapy compared to chemotherapy alone as a first-line treatment for advanced or metastatic oesophageal squamous cell carcinoma (OSCC). METHODS: A partitioned survival model was developed to evaluate the cost-effectiveness of tislelizumab plus chemotherapy versus chemotherapy alone in patients with advanced or metastatic OSCC over a 10-year lifetime horizon from the perspective of the Chinese healthcare system. Costs and utilities were derived from the drug procurement platform and published literature. The model outcomes comprised of costs, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratio (ICER). One-way and probabilistic sensitivity analyses were conducted to address uncertainty and ensure the robustness of the model. RESULTS: Tislelizumab plus chemotherapy yielded an additional 0.337 QALYs and incremental costs of $7,117.007 compared with placebo plus chemotherapy, generating an ICER of $21,116.75 per QALY, which was between 1 time ($12,674.89/QALY) and 3 times GDP ($38,024.67/QALY) per capita. In one-way sensitivity analysis, the ICER is most affected by the cost of oxaliplatin, paclitaxel and tislelizumab. In the probabilistic sensitivity analysis, when the willingness-to-pay threshold was set as 1 or 3 times GDP per capita, the probability of tislelizumab plus chemotherapy being cost-effective was 1% and 100%, respectively. CONCLUSION: Tislelizumab plus chemotherapy was probably cost-effective compared with chemotherapy alone as the first-line treatment for advanced or metastatic OSCC in China.

Involvement of mitogen-activated protein kinase in signal transducer and activator of transcription-1 mediated differentiation induced by bortezomib in acute myeloid leukemia cells.

In this paper we report a new myeloid differentiation effect of bortezomib (BTZ) in acute myeloid leukemia (AML) cell lines and primary patient-derived AML cells; this effect was assayed by investigating growth-inhibition, cell morphology, differentiation markers, and nitro-blue tetrazolium reduction. We show that BTZ induces the phosphorylation of several mitogen-activated protein (MAP) kinases, including MEK/ERK, c-Jun N-terminal kinase (JNK), and p38 MAPK. BTZ-induced cell differentiation is almost completely reversed by PD98059, an inhibitor of MEK, which also attenuates the increase in phospho-JNK p46. However, p38 activation does not appear to be required for the differentiation induced by BTZ. Furthermore, the differentiation effect of BTZ is associated with increased protein level of signal transducer and activator of transcription-1 (STAT1), a molecular determinant of myeloid differentiation, due to effects on both its synthesis and degradation. In short, this study reveals that BTZ activates the MEK/ERK cascade, which further up-regulates the expression and activity of the key myeloid transcription factor STAT1, thus promoting myeloid differentiation. These findings contribute to an unexpected potential mechanism for the antitumor activity of BTZ in AML.

A Prognostic Cuproptosis-Related LncRNA Signature for Colon Adenocarcinoma.

Background: Cuproptosis, a recently discovered form of cell death, is caused by copper levels exceeding homeostasis thresholds. Although Cu has a potential role in colon adenocarcinoma (COAD), its role in the development of COAD remains unclear. Methods: In this study, 426 patients with COAD were extracted from the Cancer Genome Atlas (TCGA) database. The Pearson correlation algorithm was used to identify cuproptosis-related lncRNAs. Using the univariate Cox regression analysis, the least absolute shrinkage and selection operator (LASSO) was used to select cuproptosis-related lncRNAs associated with COAD overall survival (OS). A risk model was established based on the multivariate Cox regression analysis. A nomogram model was used to evaluate the prognostic signature based on the risk model. Finally, mutational burden and sensitivity analyses of chemotherapy drugs were performed for COAD patients in the low- and high-risk groups. Result: Ten cuproptosis-related lncRNAs were identified and a novel risk model was constructed. A signature based on ten cuproptosis-related lncRNAs was an independent prognostic predictor for COAD. Mutational burden analysis suggested that patients with high-risk scores had higher mutation frequency and shorter survival. Conclusion: Constructing a risk model based on the ten cuproptosis-related lncRNAs could accurately predict the prognosis of COAD patients, providing a fresh perspective for future research on COAD.

Development of anoikis-related long non-coding RNA signature associated with prognosis and immune landscape in cutaneous melanoma patients.

BACKGROUND: Anoikis is involved in many critical biological processes in tumors; however, function in CM is still unknown. In this study, the relevance between Anoikis-related lncRNAs (ARLs) and the clinicopathological characteristics of patients with CM was comprehensively assessed. METHODS: Through analysis of TCGA dataset, ARLs were identified by using TCGA dataset. Based on the ARLs, a risk model was established to anticipate the prognosis of patients with CM, besides, the prediction accuracy of the model was evaluated. The immune infiltration landscape of patients with CM was assessed comprehensively, and the correlation between ARLs and immunity was elucidated. Immunotherapy and drug sensitivity analyses were applied to analyze the treatment response in patients with CM with diverse risk scores. Different subgroups were distinguished among the patients using consensus cluster analysis. RESULTS: A risk model based on six ARLs was set up to obtain an accurate prediction of the prognosis of patients with CM. There were distinctions in the immune landscape among CM patients with diverse risk scores and subgroups. Six prognosis-related ARLs were highly correlated with the number of immune cells. Patients with CM with different risk scores have various sensitivities to immunotherapy and antitumor drug treatments. CONCLUSION: Our newly risk model associated with ARLs has considerable prognostic value for patients with CM. Not only has the risk model high prediction accuracy but it also indicates the immune status of CM patients, which will provide a new direction for the individualized therapy of patients with CM.

Identification and experimental validation of mitochondria-related genes biomarkers associated with immune infiltration for sepsis.

Background: Sepsis remains a complex condition with incomplete understanding of its pathogenesis. Further research is needed to identify prognostic factors, risk stratification tools, and effective diagnostic and therapeutic targets. Methods: Three GEO datasets (GSE54514, GSE65682, and GSE95233) were used to explore the potential role of mitochondria-related genes (MiRGs) in sepsis. WGCNA and two machine learning algorithms (RF and LASSO) were used to identify the feature of MiRGs. Consensus clustering was subsequently carried out to determine the molecular subtypes for sepsis. CIBERSORT algorithm was conducted to assess the immune cell infiltration of samples. A nomogram was also established to evaluate the diagnostic ability of feature biomarkers via "rms" package. Results: Three different expressed MiRGs (DE-MiRGs) were identified as sepsis biomarkers. A significant difference in the immune microenvironment landscape was observed between healthy controls and sepsis patients. Among the DE-MiRGs, NDUFB3 was selected to be a potential therapeutic target and its significant elevated expression level was confirmed in sepsis using in vitro experiments and confocal microscopy, indicating its significant contribution to the mitochondrial quality imbalance in the LPS-simulated sepsis model. Conclusion: By digging the role of these pivotal genes in immune cell infiltration, we gained a better understanding of the molecular immune mechanism in sepsis and identified potential intervention and treatment strategies.

Population pharmacokinetics and toxicity correlation analysis of free and liposome-encapsulated doxorubicin in Chinese patients with advanced breast cancer.

PURPOSE: The objective of this study was to investigate the pharmacokinetic characteristics of pegylated liposomal doxorubicin (PLD) in Chinese female patients with advanced breast cancer by constructing population pharmacokinetic (popPK) models of liposome-encapsulated and free doxorubicin. Additionally, the relationship between pharmacokinetic parameters and drug-related adverse events (AEs) was explored through toxicity correlation analysis. METHODS: A total of 20 patients with advanced breast cancer were selected from a PLD bioequivalence study. All patients received a single intravenous dose of 50 mg/m2 PLD. Plasma concentrations were measured using liquid chromatography-tandem mass spectrometry (LC-MS/MS). A popPK model was simultaneously built to characterize the pharmacokinetic profiles of liposome-encapsulated and free doxorubicin by non-linear mixed effects model (NONMEM). PLD-related toxicities were graded according to the common terminology criteria for adverse events (CTCAE) v5.0. The Spearman correlation analysis was conducted to explore the relationship between pharmacokinetic parameters and drug-related AEs of both liposome-encapsulated doxorubicin and free doxorubicin. RESULTS: The concentration-time profiles of both liposome-encapsulated doxorubicin and free doxorubicin were well described by a one-compartment model. The most common AEs to PLD were nausea, vomiting, neutropenia, leukopenia, and stomatitis, most of which were grade I-II. The toxicity correlation analysis results indicated that stomatitis was related to the Cmax of liposome-encapsulated doxorubicin (P < 0.05). No other AEs were found to be correlated with the pharmacokinetic parameters of either free or liposome-encapsulated doxorubicin. CONCLUSION: A one-compartment model adequately described the popPK characteristics of both liposome-encapsulated and free doxorubicin in Chinese female patients with advanced breast cancer. Most AEs to PLD were mild. Additionally, the occurrence of mucositis may be positively correlated with the Cmax of liposome-encapsulated doxorubicin.

Population Pharmacokinetics of Anlotinib, a Multiple Receptor Tyrosine Kinase Inhibitor, in Chinese Patients With Malignant Tumors.

The objective of this study was to investigate the pharmacokinetic behavior of anlotinib in Chinese patients with malignant tumors using the population approach. A total of 407 anlotinib plasma concentrations from 16 patients were analyzed in this study. Anlotinib was administered orally 12 or 16 mg in the single-dose phase and 12 mg once daily in the multiple-dose phase. A population pharmacokinetic model was established using nonlinear mixed-effects model method. The potential influence of demographic and pathophysiological factors on oral anlotinib pharmacokinetics was investigated in a covariate analysis. The final model was evaluated using goodness-of-fit plots, visual predictive check, and bootstrap methods. The pharmacokinetic profile of anlotinib was best described by a 1-compartment model with first-order absorption and first-order elimination. The population estimates of the apparent total clearance, apparent volume of distribution, and absorption rate constant were 8.91 L/h, 1950 L, and 0.745/h, respectively. Body weight was identified as a significant covariate on apparent volume of distribution. Patients with low body weight tended to show higher exposure to anlotinib than those with high body weight. However, these differences were not clinically significant based on the simulations of the individual body weight effects. Taken together, this population pharmacokinetic model adequately described the pharmacokinetics of anlotinib in patients with malignant tumors and supports the same starting dose among them.

Integrated Transcriptomics and Reverse Pharmacophore Mapping-based Network Pharmacology to Explore the Mechanisms of Natural Compounds against Doxorubicin-induced Cardiotoxicity.

BACKGROUND: Doxorubicin-Induced Cardiotoxicity (DIC) has greatly limited the clinical benefits of this frontline drug in oncotherapy. Drug combination with Natural Compounds (NCs) that possess potency against DIC is considered as a promising intervention strategy. However, the Mechanisms of Action (MoAs) underlying such drug interactions remain poorly understood. The aim of this study was to systematically pursuit of the molecular mechanisms of NCs against DIC. METHODS: First, the gene expression signatures of DIC were characterized from transcriptomics datasets with doxorubicin-treated and untreated cardiomyocytes using differentially expressed gene identification, functional enrichment analysis, and protein-protein interaction network analysis. Secondly, reverse pharmacophore mapping-based network pharmacology was employed to illustrate the MoAs of 82 publicly reported NCs with anti-DIC potency. Cluster analysis based on their enriched pathways was performed to gain systematic insights into the anti-DIC mechanisms of the NCs. Finally, the typical compounds were validated using Gene Set Enrichment Analysis (GSEA) of the relevant gene expression profiles from a public gene expression database. RESULTS: Based on their anti-DIC MoAs, the 82 NCs could be divided into four groups, which corresponded to ten MoA clusters. GSEA and literature evidence on these compounds were provided to validate the MoAs identified through this bioinformatics analysis. The results suggested that NCs exerted potency against DIC through both common and different MoAs. CONCLUSION: This strategy integrating different types of bioinformatics approaches is expected to create new insights for elucidating the MoAs of NCs against DIC.

A Novel Risk Model Based on Autophagy-Related LncRNAs Predicts Prognosis and Indicates Immune Infiltration Landscape of Patients With Cutaneous Melanoma.

Cutaneous melanoma (CM) is a malignant tumor with a high incidence rate and poor prognosis. Autophagy plays an essential role in the development of CM; however, the role of autophagy-related long noncoding RNAs (lncRNAs) in this process remains unknown. Human autophagy-related genes were extracted from the Human Autophagy Gene Database and screened for autophagy-related lncRNAs using Pearson correlation. Multivariate Cox regression analysis was implemented to identify ten autophagy-related lncRNAs associated with prognosis, and a risk model was constructed. The Kaplan-Meier survival curve showed that the survival probability of the high-risk group was lower than that of the low-risk group. A novel predictive model was constructed to investigate the independent prognostic value of the risk model. The nomogram results showed that the risk score was an independent prognostic signature that distinguished it from other clinical characteristics. The immune infiltration landscape of the low-risk and high-risk groups was further investigated. The low-risk groups displayed higher immune, stromal, and ESTIMATE scores and lower tumor purity. The CIBERSORT and single sample gene set enrichment analysis (ssGSEA) algorithms indicated a notable gap in immune cells between the low- and high-risk groups. Ten autophagy-related lncRNAs were significantly correlated with immune cells. Finally, Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) results demonstrated that autophagy-related lncRNA-mediated and immune-related signaling pathways are crucial factors in regulating CM. Altogether, these data suggest that constructing a risk model based on ten autophagy-related lncRNAs can accurately predict prognosis and indicate the tumor microenvironment of patients with CM. Thus, our study provides a new perspective for the future clinical treatment of CM.