Material Basis Elucidation and Quantification of Dandelion through Spectrum-Effect Relationship Study between UHPLC Fingerprint and Antioxidant Activity via Multivariate Statistical Analysis.

The excessive expression of reactive oxygen species is closely connected to many diseases. Considerable studies have demonstrated dandelion as well as its ingredients exhibited antioxidant activity. However, specific material basis reflecting the antioxidant activity has not been comprehensively investigated. In this study, a spectrum-effect relationship study on dandelion between fingerprinting and antioxidant activity was analyzed in detail, while a UHPLC quantification method developed and completely validated for simultaneous determination of active ingredients in dandelion. With the establishment of dandelion fingerprints of different regions, 24 common peaks were characterized. The classic FRAP method and ABTS methods were then used to detect their antioxidant activity. Partial least squares regression analysis, bivariate correlation analysis and grey correlation method were used to accomplish the spectrum-effect relationship. Eventually, the ingredients with antioxidant activity which could be considered as candidate quality markers of dandelion were discovered through spectrum-effect relationship analysis. The six compounds including caftaric acid, chlorogenic acid, caffeic acid, chicoric acid, isochlorogenic acid A, and isochlorogenic acid C were quantitatively determined. The developed UHPLC assay method was accurate, precise, and reliable. The study has elucidated the antioxidant material basis of dandelion and provided a scientific basis for the quality control of dandelion.

Metabolomic profile perturbations of serum, lung, bronchoalveolar lavage fluid, spleen and feces in LPS-induced acute lung injury rats based on HPLC-ESI-QTOF-MS.

Acute lung injury (ALI) is a clinically common and serious disease, underscoring the urgent need for clarification of its pathogenesis. According to traditional Chinese medicine (TCM) theories on the "lung-spleen-intestine axis" and its correlation with ALI, a high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (HPLC-QTOF-MS) metabolomic platform was applied to identify biomarkers from five bio-samples of control and model rats challenged with intratracheally administered lipopolysaccharide (LPS) based on multivariate mathematical statistical analysis. As a result, 19, 24, 24, 15 and 29 altered metabolites were identified in serum, lung, bronchoalveolar lavage fluid (BALF), spleen and feces samples, respectively. Metabolic pathway analysis showed that linoleic acid, sphingolipid, glycerophospholipid and bile acid metabolism pathways were mainly altered by ALI. Additionally, ROC curves were applied to assess the specificity and sensitivity of the biomarkers. ALI characteristic metabolomic spectra were then established to differentiate the control from the model group with a similarity discriminative threshold of 0.7. Additionally, to compare the metabolomic profiles of the five bio-samples and establish metabolic similarities and differences among them, correlation analysis was conducted in order to delineate an objective law of endogenous linkage along the lung-spleen-intestine axis. Therefore, this study provides insights into the mechanisms involved in ALI from a metabolomics perspective, which can be applied in characterization of the mechanism and early disease detection. Graphical abstract.

A Novel Strategy for Targeted Lipidomics Based on LC-Tandem-MS Parameters Prediction, Quantification, and Multiple Statistical Data Mining: Evaluation of Lysophosphatidylcholines as Potential Cancer Biomarkers.

Lipid quantification is the ultimate goal in lipidomics studies challenged by the availability of standard compounds. A novel strategy for targeted lipidomics based on LC-MS/MS parameters prediction and multivariate statistical analysis was developed for the quantitation of lysophosphatidylcholines (LPCs) in this study. Multiple linear regression models were established with the acyl chain length and number of double bonds after the prediction correlation coefficients ( R2pred) were evaluated. Then related analytical parameters including collision energy, declustering potential, retention time, and response factor were successfully predicted for any given LPC. With this "model-prediction" strategy, sensitivity, accuracy, and coverage of targeted lipidomics were improved significantly, and 60 LPCs were determined simultaneously in plasma for the first time. An integrated evaluation method for multi-indexes, logistic regression-ROC analysis was also proposed after biomarkers were identified by Student's t test, univariate ROC curve, and PLS-DA. Then the developed workflow was successfully used to discover and evaluate multi-LPCs indexes (a set of LPCs biomarkers with the best discriminating ability) for differentiating lung, breast, colorectal, and gastric cancer from controls, and among different types of cancer. Finally, the multi-LPCs index for lung cancer was compared with the plasma before and after treatment to test its utility. The novel targeted lipidomics methodology for LPCs was expected to provide a new insight into quantitative lipidomics and further clinical application.

The internal link of serum steroid hormones levels in insomnia, depression, and Alzheimer's disease rats: Is there an effective way to distinguish among these three diseases based on potential biomarkers?

Insomnia, depression, and Alzheimer's disease are all neurodegenerative diseases and are associated with the levels of steroid hormones. To investigate the internal connection and difference of steroid hormones among these three diseases and distinguish them from the perspective of biomarkers, an easy, quick, and efficient high-performance liquid chromatography with tandem mass spectrometry method was established and validated to determine six steroid hormones simultaneously in rat serum. The separation was accomplished on a SHIM-PACK XR-ODS chromatographic column with 0.1% v/v formic acid and methanol as the mobile phase and the detection was performed with electrospray ionization source in the positive ion mode. Based on the concentrations of steroid hormones, all the groups could be distinguished obviously from each other by using partial least square discriminant analysis. Meanwhile, 11-deoxycortisol, corticosterone, and cortisol were identified as potential biomarkers and 100% of samples were classified correctly by Bayes' discriminant function. These biomarkers were further screened by one-way analysis of variance and cortisol was significantly different among all these groups. Bayes' discriminant function was also built by cortisol and the classification accuracy was 87.2%. This workflow including determination of steroid hormones and discrimination among three neurological diseases would provide a basis for further clinical studies.

Highly Sensitive Quantification Method for Amine Submetabolome Based on AQC-Labeled-LC-Tandem-MS and Multiple Statistical Data Mining: A Potential Cancer Screening Approach.

The relationship between amine submetabolome and cancer has been increasingly investigated. However, no study was performed to evaluate the current methods of amine submetabolomics comprehensively, or to use such quantification results to provide an applicable approach for cancer screening. In this study, a highly sensitive and practical workflow for quantifying amine submetabolome, which was based on 6-aminoquinolyl- N-hydroxysuccinimidyl carbamate (AQC)-labeled-HPLC-MS/MS analysis combined with multiple statistical data processing approach, was established and optimized. Comparison and optimization of two analytical approaches, HILIC separation and precolumn derivatization, and three types of surrogate matrices of plasma were performed systematically. The detection sensitivities of AQC-labeled amines were increased by 50-1000-fold compared with the underivatization-HILIC method. Surrogate matrix was also used to verify the method after a large dilution factor was employed. In data analysis, the specific amino-index for each cancer sample was identified and validated by univariate receiver operating characteristic (ROC) curve analysis, partial least-squares discrimination analysis (PLS-DA), and multivariate ROC curve analysis. These amino indexes were innovatively quantified by multiplying the raised markers and dividing the reduced markers. As a result, the numerical intervals of amino indexes for healthy volunteers and cancer patients were provided, and their clinical value was also improved. Finally, the integrated workflow successfully differentiated the value of the amino index for plasma of lung, breast, colorectal, and gastric cancer samples from controls and among different types of cancer. Furthermore, it was also used to evaluate therapeutic effects. Taken together, the developed methodology, which was characterized by high sensitivity, high throughput, and high practicality, is suitable for amine submetabolomics in studying cancer biomarkers and could also be applied in many other clinical and epidemiological research.

Targeted Neurotransmitters Profiling Identifies Metabolic Signatures in Rat Brain by LC-MS/MS: Application in Insomnia, Depression and Alzheimer's Disease.

Epidemiological, cross-sectional, and prospective studies have suggested that insomnia, Alzheimer's disease (AD) and depression are mutually interacting conditions and frequently co-occur. The monoamine and amino acid neurotransmitter systems in central nervous system were involved in the examination of neurobiological processes of this symptom complex. However, few studies have reported systematic and contrastive discussion of different neurotransmitters (NTs) changing in these neurological diseases. Thus, it is necessary to establish a reliable analytical method to monitoring NTs and their metabolite levels in rat brain tissues for elucidating the differences in pathophysiology of these neurological diseases. A rapid, sensitive and reliable LC-MS/MS method was established for simultaneous determination of the NTs and their metabolites, including tryptophan (Trp), tyrosine (Tyr), serotonin (5-HT), 5-hydroxyindolacetic acid (5-HIAA), dopamine (DA), acetylcholine (ACh), norepinephrine (NE), glutamic acid (Glu), and γ-aminobutyric acid (GABA) in rat brain tissues. The mobile phase consisting of methanol and 0.01% formic acid in water was performed on an Inertsil EP C18 column, and the developed method was validated well. Results demonstrated that there were significant differences for 5-HT, DA, NE, Trp, Tyr and ACh between model and control group in all three models, and a Bayes linear discriminant function was established to distinguish these three kinds of nervous system diseases by DA, Tyr and ACh for their significant differences among control and three model groups. It could be an excellent strategy to provide perceptions into the similarity and differentia of mechanisms from the point of NTs' changing in brain directly and a new method to distinguish insomnia, depression and AD from view of essence.

Metabolomics Strategy Using High Resolution Mass Spectrometry Reveals Novel Biomarkers and Pain-Relief Effect of Traditional Chinese Medicine Prescription Wu-Zhu-Yu Decoction Acting on Headache Modelling Rats.

Headache is a common episodic or chronic neurologic disorder. Treatment options and diagnosis are restricted by an incomplete understanding of disease pathology and the lack of diagnostic markers. Wu-Zhu-Yu decoction (WZYD), a traditional Chinese medicine (TCM) formula containing four TCM herbs, is commonly used in the treatment of headache in China. To deeply understand more about headache and investigate the pain-relief mechanism of WZYD, a comprehensive metabolomics study combined with multivariate data processing strategy was carried out. An LC-high resolution mass spectrometry-based metabolomics approach was applied to characterize metabolic biomarker candidates. Multiple pattern recognition including principal component analysis-discriminant analysis, partial least squares-discriminant analysis and hierarchical cluster analysis were used to determine groups and confirm important variables. A total of 17 potential biomarkers were characterized and related metabolic pathways were identified. The study demonstrated that the established metabolomics strategy is a powerful approach for investigating the mechanism of headache attack and WZYD. In addition, the approach may highlight biomarkers and metabolic pathways and can capture subtle metabolite changes from headache, which may lead to an improved mechanism understanding of central nervous system diseases and TCM treatment.

Qualitative screening of absorbed indoloquinazoline alkaloids and their metabolites in rat plasma after the oral administration of Wu-Zhu-Yu decoction by high-resolution mass spectrometry with multiple data mining algorithms.

A rapid and sensitive liquid chromatography with high-resolution mass spectrometry method with multiple data processing algorithms was developed and applied for the metabolite profiling of evodiamine and its analogous alkaloids in rat plasma after the administration of Wu-Zhu-Yu decoction. All samples were purified using hydrophilic-lipophilic balanced solid-phase extraction cartridges and analyzed by a Sciex TripleTOF 5600(+) mass spectrometer with a 35 min liquid chromatography gradient elution. High-resolution full-scan mass spectrometry and information-dependent acquisition tandem mass spectrometry data were analyzed using multiple data processing approaches. The results indicated that the detected eight prototype alkaloids could be metabolized to 58 metabolites through both phase I and phase II reactions. Oxidation was demonstrated to be the principle metabolic pathway of the parent compounds. The study contributes to the understanding of the absorption and metabolism of the alkaloids in Wu-Zhu-Yu decoction and provides a detailed analysis of scientific data.

Comprehensive Qualitative Ingredient Profiling of Chinese Herbal Formula Wu-Zhu-Yu Decoction via a Mass Defect and Fragment Filtering Approach Using High Resolution Mass Spectrometry.

The Wu-Zhu-Yu decoction is a traditional Chinese medicine formula for the treatment of headache. To reveal its material basis, a rapid and reliable liquid chromatography-high resolution mass spectrometry method was established for comprehensive profiling of the chemical ingredients in the Wu-Zhu-Yu decoction. The method was used on a quadrupole time-of-flight mass spectrometer along with an advanced data processing procedure consisting of mass accuracy screening, mass defect filtering and fragment filtering. After eliminating interference with a filtering approach, the MS data profiling was made more distinct and accurate. With the optimized conditions of only 35 min LC separation and single sample injection of each positive or negative ion mode, a total of 168 compounds were characterized, including 23 evodiamine and its analogous alkaloids, 12 limonoids, 17 gingerols, 38 ginsenosides, 15 flavonoids, 16 organic acids, 14 alkaloids, 5 saponins, 3 2,2-dimethylchromenes and 25 other compounds. The fragmentation patterns of representative compounds were illustrated as well. Integrative qualitative analysis of the Wu-Zhu-Yu decoction by high resolution mass spectrometry was accomplished and reported for the first time. The study demonstrated that the established method was a powerful and reliable strategy for comprehensive detection and would be widely applicable for identification of complicated components from herbal prescriptions, and may provide a basis for chemical analysis of other complex mixtures.

Polyamine Metabolites Profiling for Characterization of Lung and Liver Cancer Using an LC-Tandem MS Method with Multiple Statistical Data Mining Strategies: Discovering Potential Cancer Biomarkers in Human Plasma and Urine.

Polyamines, one of the most important kind of biomarkers in cancer research, were investigated in order to characterize different cancer types. An integrative approach which combined ultra-high performance liquid chromatography-tandem mass spectrometry detection and multiple statistical data processing strategies including outlier elimination, binary logistic regression analysis and cluster analysis had been developed to discover the characteristic biomarkers of lung and liver cancer. The concentrations of 14 polyamine metabolites in biosamples from lung (n = 50) and liver cancer patients (n = 50) were detected by a validated UHPLC-MS/MS method. Then the concentrations were converted into independent variables to characterize patients of lung and liver cancer by binary logic regression analysis. Significant independent variables were regarded as the potential biomarkers. Cluster analysis was engaged for further verifying. As a result, two values was discovered to identify lung and liver cancer, which were the product of the plasma concentration of putrescine and spermidine; and the ratio of the urine concentration of S-adenosyl-l-methionine and N-acetylspermidine. Results indicated that the established advanced method could be successfully applied to characterize lung and liver cancer, and may also enable a new way of discovering cancer biomarkers and characterizing other types of cancer.

Characterization of multiple constituents in Kai-Xin-San prescription and rat plasma after oral administration by liquid chromatography with quadrupole time-of-flight tandem mass spectrometry.

A sensitive and reliable ultra high performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry method was established to separate and identify the chemical constituents of Kai-Xin-San prescription, a classic traditional Chinese medicine formula that plays an important role in the treatment of Alzheimer's disease. The detection was performed on an Agilent 6520 Accurate-Mass quadrupole time-of-flight mass spectrometer equipped with an electrospray ionization source in negative modes. With the optimized conditions, a total of 54 compounds were identified or tentatively characterized. Out of the 54 compounds, six compounds were identified by comparing the retention time and mass spectrometry data with reference standards, the rest were characterized by analyzing mass spectrometry data and retrieving the literature data. Results indicated ginsenosides, polygala saponins, terpenoids, and oligosaccharide esters were the major effective constituents in Kai-Xin-San prescription. There were 26 prototype ingredients that were assigned for identification in rat plasma. It is also concluded that the developed ultra high performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry method with high sensitivity and resolution is suitable for identifying and characterizing the chemical constituents of Kai-Xin-San prescription, and the analysis provides a helpful chemical basis for further research on Kai-Xin-San prescription and the clinical diagnostics of Alzheimer's disease.

Combination of the advantages of chromatographic methods based on active components for the quality evaluation of licorice.

A rapid, improved and comprehensive method including high-performance thin-layer chromatography, fingerprint technology and single standard to determine multiple components was developed and validated for the quality evaluation of licorice. In this study, a newly developed high-performance thin-layer chromatography method was first used for authentication of licorice, which achieved simultaneous identification of multiple bands including five bands for known bioactive components by comparing their retention factor values and colors with the standards. For fingerprint analysis, 8 of 16 common peaks were identified. Simultaneously, similarity analysis which showed very similar patterns and hierarchical clustering analysis were performed to discriminate and classify the 27 batches of samples. Additionally, the single standard to determine multiple components method was first successfully achieved to quantify the eight important active markers in licorice including liquiritin apioside, liquiritin, isoliquiritin apioside, isoliquritin, neoisoliquiritin, liquiritigenin, isoliquiritigenin and glycyrrhizic acid. The easily available glycyrrhizic acid was selected as the reference substance to calculate relative response factors. Compared with the normal external standard method, this alternative method can be used to determine the multiple indices effectively and accurately. The validation result showed that the developed method was specific, accurate, precise, robust and reliable for the overall quality assessment of licorice.

Ultra-fast LC-ESI-MS/MS method for the simultaneous determination of six highly toxic Aconitum alkaloids from Aconiti kusnezoffii radix in rat plasma and its application to a pharmacokinetic study.

A fast, sensitive, and efficient ultra-fast LC-ESI-MS/MS method was developed for the simultaneous quantitation of six highly toxic Aconitum alkaloids, that is, aconitine, mesaconitine, hypaconitine, benzoylaconine, benzoylmesaconine, and benzoylhypaconine, in rat plasma after oral administration of crude ethanol extracts from Aconiti kusnezoffii radix by ultrasonic extraction, reflux extraction for 1 h, and reflux extraction for 3 h, respectively. The separation of six Aconitum alkaloids and aminopyrine (internal standard) was performed on an InertSustain® C18 column, and the quantification of the analytes was performed on a 4000Q ultra-fast LC-MS/MS system with turbo ion spray source in the positive ion and multiple-reaction monitoring mode. Absolute recoveries ranged within 65.06-85.1% for plasma samples. The intra- and interday precision and accuracy of analytes were satisfactory. The methods were validated with sensitivity reaching the lower LOQ for aconitine, mesaconitine, hypaconitine, benzoylaconine, benzoylmesaconine, and benzoylhypaconine, which were 0.025, 0.025, 0.050, 0.025, 0.025, and 0.100 ng/mL, respectively. The method was successfully applied to a pharmacokinetic study of six Aconitum alkaloids in rat plasma after oral administration of crude ethanol extracts from the raw root of Aconitum kusnezoffii Reichb. by three different extraction processes.

Quality assessment of Cinnamomi Ramulus by the simultaneous analysis of multiple active components using high-performance thin-layer chromatography and high-performance liquid chromatography.

A novel and improved method for the quality assessment of Cinnamomi Ramulus was developed and completely validated. The method was established using fingerprint technology and simultaneous quantitative determination of six main marker compounds including coumarin, cinnamic alcohol, cinnamic acid, 2-methoxy cinnamic acid, cinnamaldehyde, and 2-methoxy cinnamaldehyde in the herbal medicine for the first time. A newly developed high-performance thin-layer chromatography method, which achieved simultaneous definition of five marker components by comparing the colors and retardation factor values of the bands in high-performance thin-layer chromatography, was first used for the authentication of Cinnamomi Ramulus. The fingerprints of 26 batches of herbal samples from different regions of China showed very similar chromatographic patterns that were evaluated by similarity analysis and hierarchical clustering analysis. In addition, six marker compounds were simultaneously determined using single standard to determine multiple components by the relative response factors. Compared with the external standard method, the new quantitative method was validated to determine multiple compounds in 26 batches of Cinnamomi Ramulus samples. All results demonstrated that the simple and rapid method could be effectively utilized for the quality control of Cinnamomi Ramulus.

Simultaneous quantitation of polygalaxanthone III and four ginsenosides by ultra-fast liquid chromatography with tandem mass spectrometry in rat and beagle dog plasma after oral administration of Kai-Xin-San: application to a comparative pharmacokinetic study.

A fast, selective, and quantitative ultra-fast liquid chromatography with tandem mass spectrometry method has been developed and validated for the simultaneous quantitation of polygalaxanthone III, ginsenoside Rb1, ginsenoside Rd, ginsenoside Re, and ginsenoside Rg1 in the plasma of rat and beagle dog after oral administration of Kai-Xin-San. After addition of the internal standard, salidroside, the plasma samples were extracted by liquid-liquid extraction and separated on a Venusil MP C18 column with methanol/0.01% acetic acid water as mobile phase. The tandem mass spectrometric detection was performed in the multiple reaction monitoring with turbo ion spray source in a switching ionization mode. The method was examined, and found to be precise and accurate with the linearity range of the compounds. The intra- and interday precision and accuracy of the analytes were well within acceptance criteria (±15%). The mean extraction recoveries of analytes and internal standard were all >75.0%. The validated method has been successfully applied to comparing pharmacokinetic profiles of analytes in rat and beagle dog plasma. The results indicated that no significant differences were observed in pharmacokinetic parameters of ginsenoside Rg1, while the others had significant differences, which may due to the different mechanisms of absorption and metabolism.

Cytotoxic xanthones from Garcinia pedunculata fruits.

Eight previously undescribed and seven known xanthones were isolated from the fruits of Garcinia pedunculata Roxb. The structures were identified by a variety of spectroscopic methods as well as by comparison with the literature. The isolates showed appreciable cytotoxicity against three human tumor cell lines (HepG2, A549, and MCF-7). Pedunculaxanthone G exhibited inhibitory activities with IC50 values of 12.41, 16.51, and 15.45 µM against the cancer cell lines and induced cell apoptosis in HepG2 cells.

A multilocus-dendritic boronic acid functionalized magnetic nanoparticle for capturing circulating tumor cells in the peripheral blood of mice with metastatic breast cancer.

BACKGROUND: Dynamic fluctuation of circulating tumor cells (CTCs) can serve as an indicator of tumor progression. However, the sensitive isolation of CTCs remains extremely challenging due to their rarity and heterogeneity. Against this dilemma, dendritic boronic acid-modified magnetic nanoparticles (MNPs) were prepared in this study, and polyethyleneimine (PEI) was utilized as a scaffold to significantly increase the number of boronic acid moieties. Then the novel developed material was applied to monitor the number of CTCs in mice with metastatic breast cancer to evaluate the therapeutic effects of matrine (Mat), doxorubicin (Dox), and Mat in combination with Dox. RESULTS: Compared to the low binding capacity of a single boronic acid ligand, dendritic boronic acid shows enhanced sensitivity in binding to sialic acid (SA), which is overexpressed in CTCs. The results showed that the capture efficiency of this modified material could achieve 94.7% and successfully captured CTCs in blood samples from mice with metastatic breast cancer. The CTC counts were consistent with the results of the pathologic examination, demonstrating the reliability and utility of the method. SIGNIFICANCE: The dendritic boronic acid nanomaterials prepared in this study showed high specificity, sensitivity, and accuracy for cancer cell capture. The approach is expected to provide new insights into cancer diagnosis, personalized therapy, and optimization of treatment regimens.

FD-DE: Differential Evolution with fitness deviation based adaptation in parameter control.

Differential Evolution (DE) is arguably one of the most powerful stochastic optimization algorithms for different optimization applications, however, even the state-of-the-art DE variants still have many weaknesses. In this study, a new powerful DE variant for single-objective numerical optimization is proposed, and there are several contributions within it: First, an enhanced wavelet basis function is proposed to generate scale factor F of each individual in the first stage of the evolution; Second, a hybrid trial vector generation strategy with perturbation and t-distribution is advanced to generate different trial vectors regarding different stages of the evolution; Third, a fitness deviation based parameter control is proposed for the adaptation of control parameters; Fourth, a novel diversity indicator is proposed and a restart scheme can be launched if necessary when the quality of the individuals is detected bad. The novel algorithm is validated using a large test suite containing 130 benchmarks from the universal test suites on single-objective numerical optimization, and the results approve the big improvement in comparison with several well-known state-of-the-art DE variants. Moreover, our algorithm is also validated under real-world optimization applications, and the results also support its superiority.

Accurate determination for lipidomics based on LC-tandem-MS parameters modeling, prediction, and database: Monitoring the progression of hepatocellular carcinoma.

The unavailability of adequate lipid reference standards is a major challenge for accurate quantitative analysis of lipidomics. Based on the discovery of regularity and predictability for lipids in chromatography-mass spectrometry behaviors, "target compound-structure correlation-analytical parameter database" protocol and "modeling-prediction" strategy were carried out to calculate the relative coefficients of analytical parameters within each subclass. Then the relevant LC-tandem-MS parameters of unknown lipids were predicted and a quantification parameter database for 4081 lipids was established and validated. Reference standards-independent accurate determination for lipidomics was achieved with the parameter's database and applied to monitor the change of lipid metabolism in the plasma of whole course of health-hepatitis-cirrhosis-hepatocellular carcinoma (HCC). Combined Student's t test, orthogonal partial least squares discrimination analysis (OPLS-DA) and binary logistic regression-ROC analysis, lipid biomarkers for differentiating health from each disease and differentiating different stages of disease were identified and the pathogenesis of HCC was preliminarily clarified. The established methodology would shed light on comprehensive and accurate quantitative lipidomics and exploring the pathomechanism and potential therapeutic targets of HCC.

Induction of P-glycoprotein expression by dandelion in tumor and heart tissues: Impact on the anti-tumor activity and cardiotoxicity of doxorubicin.

BACKGROUND: Previously, we have investigated the anti-tumor activity and mechanism through which dandelion acts against triple-negative breast cancer (TNBC). However, traditional Chinese medicine is mostly accepted as an adjunct therapy during chemotherapy in clinical practice. So far, little is known about the effects of dandelion in conjunction with chemotherapeutic drugs. PURPOSE: To investigate the effects of dandelion on the anti-tumor activity and cardiotoxicity of doxorubicin (DOX), and to further explore the molecular mechanisms through which these effects occur. STUDY DESIGN: At the beginning of this study, dandelion was observed to alleviate DOX-induced cardiotoxicity and reduce the anti-tumor activity of DOX. Subsequently, we investigated whether the resistance to DOX mediated by P-glycoprotein was involved in the above effects. METHODS: The cardioprotective effect of dandelion was investigated on DOX-treated mice by histological analysis, myocardial enzyme assays, and an untargeted metabolomics study based on LC-Q-TOF/MS. TNBC cell lines and 4T1 tumor-bearing mice were employed to investigate the combined anti-tumor activity. Laser scanning confocal microscope and a flow cytometry analysis were employed to measure the intracellular accumulation of DOX. A specific, sensitive, and rapid LC-MS/MS method was developed to detect the efflux of DOX from cells. Expression of P-glycoprotein in mouse tumor and heart tissues was detected via Western blotting analysis. RESULTS: Dandelion was found to significantly alleviate DOX-induced cardiotoxicity, as was evidenced by improved cardiomyocyte morphology, decreased LDH and CK-MB release, and adjusted metabolic biomarker levels. However, in vitro and in vivo studies showed that dandelion could reduce the anti-tumor activity of DOX. This counteraction was achieved by activating of the drug efflux transporter P-glycoprotein, thereby promoting the efflux of DOX from cells and reducing the intracellular accumulation of DOX. Moreover, the activation of P-glycoprotein by dandelion in mouse heart tissue was also observed, thus suggesting that the decrease of cardiac DOX accumulation plays an important role in the cardioprotective effect of dandelion. CONCLUSION: Dandelion can activate the P-glycoprotein in heart and tumor tissues, which ameliorates DOX-induced cardiotoxicity but attenuates DOX cytotoxicity toward TNBC. Our findings have important implications for the correct clinical use of dandelion.