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Abstract Background Irinotecan (CPT-11) is a first-line treatment for advanced colorectal cancer (CRC). Four components (baicalin, baicalein, wogonin, and glycyrrhizic acid) derived from Huangqin Decoction (HQD) have been proven to enhance the anticancer activity of CPT-11 in our previous study. Objective This study aimed to determine the optimal combination of the four components for sensitizing CPT-11 as well as to explore the underlying mechanism. Methods The orthogonal design method was applied to obtain candidate combinations (Cmb1-9) of the four components. The influence of different combinations on the anticancer effect of CPT-11 was first evaluated in vitro by cell viability, wound healing ability, cloning formation, apoptosis, and cell cycle arrest. Then, a CRC xenograft mice model was constructed to evaluate the anticancer effect of the optimal combination in vivo. Potential mechanisms of the optimal combination exerting a sensitization effect combined with CPT-11 against CRC were analyzed by targeted metabolomics. Results In vitro experiments determined that Cmb8 comprised of baicalin, baicalein, wogonin, and glycyrrhizic acid at the concentrations of 17 μM, 47 μM, 46.5 μM and 9.8 μM respectively was the most effective combination. Importantly, the cell viability assay showed that Cmb8 exhibited synergistic anticancer activity in combination with CPT-11. In in vivo experiments, this combination (15 mg/kg of baicalin, 24 mg/kg of baicalein, 24 mg/kg of wogonin, and 15 mg/kg of glycyrrhizic acid) also showed a synergistic anticancer effect. Meanwhile, inflammatory factors and pathological examination of the colon showed that Cmb8 could alleviate the gastrointestinal damage induced by CPT-11. Metabolic profiling of the tumors suggested that the synergistic anticancer effect of Cmb8 might be related to the regulation of fatty acid metabolism. Conclusion The optimal combination of four components derived from HQD for the synergistic sensitization of CPT-11 against CRC was identified.

G protein-coupled receptor 35 (GPR35) has gained increasing attention as a promising target in treating inflammatory and gastrointestinal tract conditions, cardiovascular diseases, and cancer. Metabolites including kynurenic acid, lysophosphatidic acids, chemokine 17, and 5-hydroxyindole acetic acid have been suggested to be endogenous ligands of GPR35. However, little is known regarding the downstream metabolic characteristics upon GPR35 regulation. Herein, four GPR35 interventions in cell models, comprising GPR35 knock-down, over-expression, activation, or inhibition, were established through lentiviral transduction, or the use of a potent agonist (pamoic acid) or antagonist (ML194). Targeted metabolomics and pseudotargeted lipidomics were performed on these cell models to capture GPR35-associated metabolites and lipids. Levels of 75 metabolites and 204 lipids were significantly altered in response to one or more GPR35 interventions. Levels of metabolites involved in fatty acid β-oxidation and phosphatidylethanolamine metabolism were notably altered. This study reports the first exploration of the metabolic characteristics of GPR35, and may aid in understanding of the potential mechanisms and functions of GPR35 in various physiological and pathological conditions.

Die Dai et al. evaluate changes in the metabolomic and gut microbiome in response to experimental intestinal ischemia reperfusion (IIR) injury in rats. Their results provide further insight into how gut contents contribute to widespread injury in IIR patients.

Astragali radix (AR, the dried root of Astragalus) is a popular herbal remedy in both China and the United States. The commercially available AR is commonly classified into premium graded (PG) and ungraded (UG) ones only according to the appearance. To uncover novel sensitive and specific markers for AR grading, we took the integrated mass spectrometry-based untargeted and targeted metabolomics approaches to characterize chemical features of PG and UG samples in a discovery set (n=16 batches). A series of five differential compounds were screened out by univariate statistical analysis, including arginine, calycosin, ononin, formononetin, and astragaloside Ⅳ, most of which were observed to be accumulated in PG samples except for astragaloside Ⅳ. Then, we performed machine learning on the quantification data of five compounds and constructed a logistic regression prediction model. Finally, the external validation in an independent validation set of AR (n=20 batches) verified that the five compounds, as well as the model, had strong capability to distinguish the two grades of AR, with the prediction accuracy > 90%. Our findings present a panel of meaningful candidate markers that would significantly catalyze the innovation in AR grading.

Irinotecan (CPT-11) in combination with 5-fluorouracil and leucovorin is a first-line chemotherapy regimen for the treatment of colorectal cancer; however, its clinical application is limited by the dose-limiting gastrointestinal toxicity of colitis. In our previous studies, several bile acids (BAs) were found significantly elevated in the colon of the CPT-11-induced rat colitis model. On the other hand, NLRP3 inflammasome has been reported to play important roles in mediating colitis. Interestingly, BA was stated to activate the NLRP3 inflammasome in some studies, while in some other reports, it showed an inhibitory effect. We assumed that the inflammatory status in different circumstances might have contributed to the controversial findings. In this study, we first discovered, under non-inflammatory conditions, that supplementing BA could activate the NLRP3 inflammasome in THP-1-differentiated macrophages and promote inflammation. In lipopolysaccharide (LPS)-induced inflammatory macrophages, however, BA inhibited the NLRP3 inflammasome and reduced inflammation. Further experiments demonstrated that Takeda G protein-coupled receptor 5 (TGR5) is essential in mediating the inhibitory effect of BA, while phospho-SP1 (p-SP1) is key to the activation. Furthermore, we applied the above findings to ameliorate CPT-11-caused colitis in rats by inhibiting SP1 with mithramycin A (MitA) or activating TGR5 using oleanolic acid (OA). Our findings may shed light on the discovery of effective interventions for reducing dose-limiting chemotherapy-induced colitis.

Intestinal toxicity induced by chemotherapeutics has become an important reason for the interruption of therapy and withdrawal of approved agents. In this study, we demonstrated that chemotherapeutics-induced intestinal damage were commonly characterized by the sharp upregulation of tryptophan (Trp)−kynurenine (KYN)−kynurenic acid (KA) axis metabolism. Mechanistically, chemotherapy-induced intestinal damage triggered the formation of an interleukin-6 (IL-6)−indoleamine 2,3-dioxygenase 1 (IDO1)−aryl hydrocarbon receptor (AHR) positive feedback loop, which accelerated kynurenine pathway metabolism in gut. Besides, AHR and G protein-coupled receptor 35 (GPR35) negative feedback regulates intestinal damage and inflammation to maintain intestinal integrity and homeostasis through gradually sensing kynurenic acid level in gut and macrophage, respectively. Moreover, based on virtual screening and biological verification, vardenafil and linagliptin as GPR35 and AHR agonists respectively were discovered from 2388 approved drugs. Importantly, the results that vardenafil and linagliptin significantly alleviated chemotherapy-induced intestinal toxicity in vivo suggests that chemotherapeutics combined with the two could be a promising therapeutic strategy for cancer patients in clinic. This work highlights GPR35 and AHR as the guardian of kynurenine pathway metabolism and core component of defense responses against intestinal damage.

FOLFOX (oxaliplatin, fluorouracil and calcium folinate) is the first-line chemotherapy regimen for colon cancer therapy in the clinic. It provides superior efficacy than oxaliplatin alone, but the underlying mechanism remains unclear. In the present study, pharmacomicrobiomics integrated with metabolomics was conducted to uncover the role of the gut microbiome behind this. First, in vivo study demonstrated that FOLFOX exhibited better efficacy than oxaliplatin alone in colon cancer animal models. Second, 16S rDNA gene sequencing analysis showed that the abundance of Akkermansia muciniphila (A. muciniphila) remarkably increased in the FOLFOX treated individuals and positively correlated with the therapeutic effect. Third, further exploration confirmed A. muciniphila colonization significantly enhanced the anti-cancer efficacy of FOLFOX. Last, metabolomics analysis suggested dipeptides containing branched-chain amino acid (BCAA) might be responsible for gut bacteria mediated FOLFOX efficacy. In conclusion, our study revealed the key role of A. muciniphila in mediating FOLFOX efficacy, and manipulating A. muciniphila might serve as a novel strategy for colon cancer therapy.

Colorectal cancer (CRC) is one of the most commonly diagnosed cancers with high mortality worldwide. Type 2 diabetes mellitus (T2D), known as a risk factor of CRC, can promote the deterioration of CRC, but the underlying mechanism is elusive. In this study, we aimed to reveal the relationship between CRC and T2D from the perspective of small-molecule metabolism. First, a list of common dysregulated metabolites in CRC and T2D was obtained by retrieving existing metabolomics publications. Among these metabolites, oleic acid (OA) was found to be able to promote the proliferation and migration of colon carcinoma cell HCT116. Further experiments proved that insulin could significantly strengthen this promotion and showed a synergistic effect with OA. Mechanism study found that OA and insulin acted synergistically through the extracellular signal-regulated kinase (ERK)1/2/c-Myc/cyclin D1 pathway. In addition, the combination of ERK1/2 inhibitor SCH772984 and cyclin-dependent kinase (CDK)4/6 inhibitor palbociclib showed a remarkable inhibitory effect on tumor growth in vivo. Taken together, the current study found that OA plays an important role in CRC development by using a functional metabolomics approach. More importantly, insulin and OA were confirmed to synergistically promote the deterioration of CRC in vitro and in vivo via ERK1/2/c-Myc/cyclin D1 pathway. Our findings may shed light on CRC treatment among the T2D population.

Proanthocyanidins (PACs) have been proven to exert antioxidant and anti-inflammatory effects. In this study, ultra-performance liquid chromatography (UPLC) coupled with linear ion trap-Orbitrap (LTQ-Orbitrap) high-resolution mass spectrometry was first employed to systematically screen PACs from the roots of Ephedra sinica Stapf, and its ethyl acetate extract (ERE) was found to contain PAC monomers and A-type dimeric proanthocyanidins, which were tentatively identified through characteristic fragmentation patterns. In vitro, the antioxidant activity of ERE was tested through 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2, 2-azino-bis-3-ethylbenzothiazoline-6-sulfonic acid (ABTS) assays. In addition, ERE could inhibit the production of nitric oxide (NO) in lipopolysaccharide (LPS)-induced RAW 264.7 cells. In vivo, the preventative effects on dextran-sulfate-sodium-induced ulcerative colitis in mice was investigated. Mice were administered with ERE for 21 days, and during the last 7 days of the treatment period dextran sulfate sodium (DSS) was used to induce experimental colitis. The results showed that ERE treatment alleviated DSS-induced colitis, which was characterized by decreases in disease activity index (DAI) scores, spleen index and colon levels of TNF-α and IL-6, mitigation in pathological damage and oxidative stress and increases in colon length and IL-10 levels. In conclusion, supplementation of PACs derived from ERE may offer a new strategy for the treatment of ulcerative colitis. Moreover, our research will greatly facilitate better utilization of Ephedra plants.

Pharmacometabolomics has been already successfully used in toxicity prediction for one specific adverse effect. However in clinical practice, two or more different toxicities are always accompanied with each other, which puts forward new challenges for pharmacometabolomics. Gastrointestinal toxicity and myelosuppression are two major adverse effects induced by Irinotecan (CPT-11), and often show large individual differences. In the current study, a pharmacometabolomic study was performed to screen the exclusive biomarkers in predose serums which could predict late-onset diarrhea and myelosuppression of CPT-11 simultaneously. The severity and sensitivity differences in gastrointestinal toxicity and myelosuppression were judged by delayed-onset diarrhea symptoms, histopathology examination, relative cytokines and blood cell counts. Mass spectrometry-based non-targeted and targeted metabolomics were conducted in sequence to dissect metabolite signatures in predose serums. Eventually, two groups of metabolites were screened out as predictors for individual differences in late-onset diarrhea and myelosuppression using binary logistic regression, respectively. This result was compared with existing predictors and validated by another independent external validation set. Our study indicates the prediction of toxicity could be possible upon predose metabolic profile. Pharmacometabolomics can be a potentially useful tool for complicating toxicity prediction. Our findings also provide a new insight into CPT-11 precision medicine. KEY WORDS: Irinotecan, Individual differences, Complicating toxicity, Prediction, Metabolomics, Gastrointestinal toxicity, Biomarkers, Diarrhea

The accumulation of cancer metabolomics data in the past decade provides exceptional opportunities for deeper investigations into cancer metabolism. However, integrating a large amount of heterogeneous metabolomics data to draw a full picture of the metabolic reprogramming and to discover oncometabolites of certain cancers remains challenging. In this study, a tumor barcode constructed based upon existing metabolomics “big data” using the Bayesian vote-counting method is proposed to identify oncometabolites in colorectal cancer (CRC). Specifically, a panel of oncometabolites of CRC was generated from 39 clinical studies with 3202 blood samples (1332 CRC vs. 1870 controls) and 990 tissue samples (495 CRC vs. 495 controls). Next, an oncometabolite-protein network was constructed by combining the tumor barcode and its involved proteins/enzymes. The effect of anti-cancer drugs or drug combinations was then mapped into this network by the random walk with restart process. Utilizing this network, potential Irinotecan (CPT-11)-sensitizing agents for CRC treatment were discovered by random forest and Xgboost. Finally, a compound named MK-2206 was highlighted and its synergy with CPT-11 was validated on two CRC cell lines. To summarize, we demonstrate in the present study that the metabolomics “big data”-based tumor barcodes and the subsequent network analyses are potentially useful for drug combination discovery or drug repositioning.

This study centers on automatic sleep staging with a single channel electroencephalography (EEG), with some significant findings for sleep staging. In this study, we proposed a deep learning-based network by integrating attention mechanism and bidirectional long short-term memory neural network (AT-BiLSTM) to classify wakefulness, rapid eye movement (REM) sleep and non-REM (NREM) sleep stages N1, N2 and N3. The AT-BiLSTM network outperformed five other networks and achieved an accuracy of 83.78%, a Cohen’s kappa coefficient of 0.766 and a macro F1-score of 82.14% on the PhysioNet Sleep-EDF Expanded dataset, and an accuracy of 81.72%, a Cohen’s kappa coefficient of 0.751 and a macro F1-score of 80.74% on the DREAMS Subjects dataset. The proposed AT-BiLSTM network even achieved a higher accuracy than the existing methods based on traditional feature extraction. Moreover, better performance was obtained by the AT-BiLSTM network with the frontal EEG derivations than with EEG channels located at the central, occipital or parietal lobe. As EEG signal can be easily acquired using dry electrodes on the forehead, our findings might provide a promising solution for automatic sleep scoring without feature extraction and may prove very useful for the screening of sleep disorders.

Background: Obstructive sleep apnea (OSA), a highly prevalent sleep disorder, is closely related to cardiovascular disease (CVD). Our previous work demonstrated that Shannon entropy of the degree distribution (EDD), obtained from the network domain of heart rate variability (HRV), might be a potential indicator for CVD. Method: To investigate the potential association between OSA and EDD, OSA patients and healthy controls (HCs) were identified from a sleep study database. Then EDD was calculated from electrocardiogram (ECG) signals during sleep, followed by cross-sectional comparisons between OSA patients and HCs, and longitudinal comparisons from baseline to follow-up visits. Furthermore, for OSA patients, the association between EDD and OSA severity, measured by apnea-hypopnea index (AHI), was also analyzed. Results: Compared with HCs, OSA patients had significantly increased EDD during sleep. A positive correlation between EDD and the severity of OSA was also observed. Although the value of EDD became larger with aging, it was not OSA-specified. Conclusion: Increased EDD derived from ECG signals during sleep might be a potential dynamic biomarker to identify OSA patients from HCs, which may be used in screening OSA with high risk before polysomnography is considered.

Cytochrome P450 1A2 (CYP1A2) is one of the major CYP450 enzymes (CYPs) in the liver, and participates in the biotransformation of various xenobiotics and endogenous signaling molecules. The expression and activity of CYP1A2 show large individual differences, due to genetic and environmental factors. In order to discover non-invasive serum biomarkers associated with hepatic CYP1A2, mass spectrometry-based, untargeted metabolomics were first conducted, in order to dissect the metabolic differences in the serum and liver between control rats and β-naphthoflavone (an inducer of CYP1A2)-treated rats. Real-time reverse transcription polymerase chain reaction and pharmacokinetic analysis of phenacetin and paracetamol were performed, in order to determine the changes of mRNA levels and activity of CYP1A2 in these two groups, respectively. Branched-chain amino acids phenylalanine and tyrosine were ultimately focalized, as they were detected in both the serum and liver with the same trends. These findings were further confirmed by absolute quantification via a liquid chromatography–tandem mass spectrometry (LC-MS/MS)-based targeted metabolomics approach. Furthermore, the ratio of phenylalanine to tyrosine concentration was also found to be highly correlated with CYP1A2 activity and gene expression. This study demonstrates that metabolomics can be a potentially useful tool for biomarker discovery associated with CYPs. Our findings contribute to explaining interindividual variations in CYP1A2-mediated drug metabolism.

Saikosaponin d (SSd) is one of the main active ingredients in Radix Bupleuri. In our study, network pharmacology databases and metabolomics were used in combination to explore the new targets and reveal the in-depth mechanism of SSd. A total of 35 potential targets were chosen through database searching (HIT and TCMID), literature mining, or chemical similarity predicting (Pubchem). Out of these obtained targets, Neuropilin-1 (NRP-1) was selected for further research based on the degree of molecular docking scores and novelty. Cell viability and wound healing assays demonstrated that SSd combined with NRP-1 knockdown could significantly enhance the damage of HepG2. Metabolomics analysis was then performed to explore the underlying mechanism. The overall difference between groups was quantitatively evaluated by the metabolite deregulation score (MDS). Results showed that NRP-1 knockdown exhibited the lowest MDS, which demonstrated that the metabolic profile experienced the slightest interference. However, SSd alone, or NRP-1 knockdown in combination with SSd, were both significantly influenced. Differential metabolites mainly involved short- or long-chain carnitines and phospholipids. Further metabolic pathway analysis revealed that disturbed lipid transportation and phospholipid metabolism probably contributed to the enhanced anti-hepatoma effect by NRP-1 knockdown in combination with SSd. Taken together, in this study, we provided possible interaction mechanisms between SSd and its predicted target NRP-1.

Dengue virus (DENV) is the most widespread arbovirus with an estimated 100 million infections occurring every year. Endemic in the tropical and subtropical areas of the world, dengue fever/dengue hemorrhagic fever (DF/DHF) is emerging as a major public health concern. The complex array of concurrent host physiologic changes has hampered a complete understanding of underlying molecular mechanisms of dengue pathogenesis.Systems level characterization of serum metabolome and lipidome of adult DF patients at early febrile, defervescence, and convalescent stages of DENV infection was performed using liquid chromatography- and gas chromatography-mass spectrometry. The tractability of following metabolite and lipid changes in a relatively large sample size (n = 44) across three prominent infection stages allowed the identification of critical physiologic changes that coincided with the different stages. Sixty differential metabolites were identified in our metabolomics analysis and the main metabolite classes were free fatty acids, acylcarnitines, phospholipids, and amino acids. Major perturbed metabolic pathways included fatty acid biosynthesis and β-oxidation, phospholipid catabolism, steroid hormone pathway, etc., suggesting the multifactorial nature of human host responses. Analysis of phospholipids and sphingolipids verified the temporal trends and revealed association with lymphocytes and platelets numbers. These metabolites were significantly perturbed during the early stages, and normalized to control levels at convalescent stage, suggesting their potential utility as prognostic markers.DENV infection causes temporally distinct serum metabolome and lipidome changes, and many of the differential metabolites are involved in acute inflammatory responses. Our global analyses revealed early anti-inflammatory responses working in concert to modulate early pro-inflammatory processes, thus preventing the host from development of pathologies by excessive or prolonged inflammation. This study is the first example of how an omic- approach can divulge the extensive, concurrent, and dynamic host responses elicited by DENV and offers plausible physiological insights to why DF is self limiting.

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As an anticancer agent, irinotecan (CPT-11) has been widely applied in clinical, especially in the treatment of colorectal cancer. However, its clinical use has long been limited by the side effects and potential tissue toxicity. To discriminate the target toxic tissues and dissect the specific response of target tissues after CPT-11 administration in rats, untargeted metabolomic study was conducted. First, differential metabolites between CPT-11 treated group and control group in each tissue were screened out. Then, based on fold changes of these differential metabolites, principal component analysis and hierarchical cluster analysis were performed to visualize the degree and specificity of the influences of CPT-11 on the metabolic profiles of nine tissues. Using this step-wise method, ileum, jejunum, and liver were finally recognized as target toxic tissues. Furthermore, tissue specific responses of liver, ileum, and jejunum to CPT-11 were dissected and specific differential metabolites were screened out. Perturbations in Krebs cycle, amino acid, purine and bile acid metabolism were observed in target toxic tissues. In conclusion, our study put forward a new approach to dissect target toxic tissues and tissue specific responses of CPT-11 using metabolomics. [ABSTRACT FROM AUTHOR]

A sensitive and specific liquid chromatography–electrospray ionization mass spectrometry method is developed and validated for the identification and quantitation of azithromycin in human plasma. After the addition of the internal standard and 1.0M sodium hydroxide solution, plasma samples are extracted with a methylene chloride–ethyl acetate mixture (20:80, v/v). The organic layer is evaporated under a stream of nitrogen at 40°C. The residue is reconstituted with 200 µL of the mobile phase. The compounds are separated on a prepacked Shimadzu Shim-pack VP-ODS C18 (5 µm, 150 mm × 2.0 mm) column using a mixture of acetonitrile–water (65:35) (0.5% triethylamine, pH was adjusted to 6.2 with acetic acid) as the mobile phase. Detection is performed on a single quadrupole mass spectrometer by selected ion monitoring mode via electrospray ionization source. The method is fully validated and linear calibration curves are obtained in the concentration ranges from 5 to 2000 ng/mL. The intra- and inter-batch relative standard deviations at four different concentration levels are all < 10%. The limit of detection and quantitation are 2 ng/mL and 5 ng/mL, respectively. The proposed method enables the unambiguous identification and quantitation of azithromycin for pharmacokinetic, bioavailability, or bioequivalence studies. [ABSTRACT FROM AUTHOR]