An optimal combination of four active components in Huangqin decoction for the synergistic sensitization of irinotecan against colorectal cancer.

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.

A new chemical derivatization reagent sulfonyl piperazinyl for the quantification of fatty acids using LC-MS/MS.

In our previous study, a chemical derivatization reagent named 5-(dimethylamino) naphthalene-1-sulfonyl piperazine (Dns-PP) was developed to enhance the chromatographic retention and the mass spectrometric response of free fatty acids (FFAs) in reversed-phase liquid chromatography coupled with electrospray ionization-mass spectrometry (RPLC-ESI-MS). However, Dns-PP exhibited strong preferences for long-chain FFAs, with limited improvement for short- or medium-chain FFAs. In this study, a new series of labeling reagents targeting FFAs were designed, synthesized, and evaluated. Among these reagents, Tmt-PP (N2, N2, N4, N4-tetramethyl-6-(4-(piperazin-1-ylsulfonyl) phenyl)-1,3,5-triazine-2,4-diamine) exhibited the best MS response and was selected for further evaluations. We compared Tmt-PP with Dns-PP and four commonly used carboxyl labeling reagents from existing studies, demonstrating the advantages of Tmt-PP. Further comparisons between Tmt-PP and Dns-PP in measuring FFAs from biological samples revealed that Tmt-PP labeling enhanced the MS response for about 80 % (30/38) of the measured FFAs, particularly for short- and medium-chain FFAs. Moreover, Tmt-PP labeling significantly improved the chromatographic retention of short-chain FFAs. To ensure accurate quantification, we developed a stable isotope-labeled Tmt-PP (i.e., d12-Tmt-PP) to react with chemical standards and serve as one-to-one internal standards (IS). The method was validated for accuracy, precision, sensitivity, linearity, stability, extraction efficiency, as well as matrix effect. Overall, this study introduced a new chemical derivatization reagent Tmt-PP (d12-Tmt-PP), providing a sensitive and accurate option for quantifying FFAs in biological samples.

A chemical derivatization-based pseudotargeted LC-MS/MS method for high coverage determination of dipeptides.

Dipeptides (DPs) have attracted more and more attention in many research fields due to their important biological functions and promising roles as disease biomarkers. However, the determination of DPs in biological samples is very challenging owing to the limited availability of commercial standards, high structure diversity, distinct physical and chemical characteristics, wide concentration range, and the extensive existence of isomers. In this study, a pseudotargeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) method coupled with chemical derivatization for the simultaneous analysis of 400 DPs and their constructing amino acids (AAs) in biospecimens is established. Dansyl chloride (Dns-Cl) chemical derivatization was introduced to provide characteristic MS fragments for annotation and improve the chromatographic separation of DP isomers. A retention time (RT) prediction model was constructed using 83 standards (63 DPs and 20 AAs) based on their quantitative structural retention relationship (QSRR) after the Dns-Cl labeling, which largely facilitated the annotation of the DPs without standards. Finally, we applied this method to investigate the profile change of DPs in a cisplatin-induced acute kidney injury (AKI) rat model. The established workflow provides a platform to profile DPs and expand our understanding of these little-studied metabolites.

High-Coverage Strategy for Multi-Subcellular Metabolome Analysis Using Dansyl-Labeling-Based LC-MS/MS.

Subcellular compartmentalization ensures orderly and efficient intracellular metabolic activities in eukaryotic life. Investigation of the subcellular metabolome could provide in-depth insight into cellular biological activities. However, the sensitive measurement of multi-subcellular metabolic profiles is still a significant challenge. Herein, we present a comprehensive subcellular fractionation, characterization, and metabolome analysis strategy. First, six subcellular fractions including nuclei, mitochondria, lysosomes, peroxisomes, microsomes, and cytoplasm were generated from a single aliquot of liver homogenate. Then, a dansyl-labeling-assisted liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for measuring 151 amino/phenol- or carboxyl-containing metabolites in the subcellular fractions was established and validated. Last, the strategy was applied to a rat model of carbon tetrachloride (CCl4)-induced acute liver injury (ALI). The metabolic profile of individual organelles was compared with that of the liver. Interestingly, many unique changes were observed specifically in organelles, while the liver failed to capture these changes. This result indicates that metabolic investigation at the tissue level might lead to erroneous results due to the leveling effect. Our study demonstrates a feasible approach for the broad-spectrum-targeted metabolic profiling of multi-subcellular fractions, which can be of great use in driving our further understanding of intracellular metabolic activities in various physical and pathological conditions.

Stepwise solid phase extraction integrated with chemical derivatization for all-in-one injection LC-MS/MS analysis of metabolome and lipidome.

The metabolome and lipidome are critical components in illustrating biological processes and pathological mechanisms. Generally, two or more independent methods are required to analyze the two compound panels due to their distinct chemical properties and polarity differences. Here, a novel strategy integrating stepwise solid-phase extraction (SPE) and dansyl chemical derivatization was proposed for all-in-one injection LC-MS/MS analysis of serum metabolome and lipidome. In this workflow, a stepwise elution procedure was firstly optimized to separate the metabolome and lipidome fractions using an Ostro plate. Dansyl chemical derivatization was then applied to label amine/phenol, carboxyl, and carbonyl-containing sub-metabolomes. Our results demonstrated that the dansyl labeling could significantly improve chromatographic separation, enhance the MS response, and overcome the matrix effect of co-eluting lipids. Ultimately, an all-in-one injection LC-MS/MS method measuring 256 lipids (covering 20 subclasses) and 212 metabolites (including amino acids, bile acids, fatty acids, acylcarnitines, indole derivatives, ketones and aldehydes, nucleic acid metabolism, polyamines, etc.) was established. This method was applied to investigate the metabolic changes in cisplatin-induced nephrotoxicity in rats and the results were compared with previous untargeted metabolomics. The presented strategy could predominantly improve the analytical coverage and throughput and can be of great use in discovering reliable potential biomarkers in various applications.

Rapid Screening of Proanthocyanidins from the Roots of Ephedra sinica Stapf and its Preventative Effects on Dextran-Sulfate-Sodium-Induced Ulcerative Colitis.

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.

Integrated multi-omics reveal important roles of gut contents in intestinal ischemia-reperfusion induced injuries in rats.

Intestinal ischemia-reperfusion (IIR) is a life-threatening clinical event with damaging signals whose origin and contents are unclear. Here we observe that IIR significantly affect the metabolic profiles of most organs by unbiased organ-wide metabolic analysis of gut contents, blood, and fifteen organs in rats (n = 29). Remarkably, correlations between gut content metabolic profiles and those of other organs are the most significant. Gut contents are also the only ones to show dynamic correlations during IIR. Additionally, according to targeted metabolomics analysis, several neurotransmitters are considerably altered in the gut during IIR, and displayed noteworthy correlations with remote organs. Likewise, metagenomics analysis (n = 35) confirm the effects of IIR on gut microbiota, and identify key species fundamental to the changes in gut metabolites, particularly neurotransmitters. Our multi-omics results establish key roles of gut contents in IIR induced remote injury and provide clues for future exploration.

Discovery of Synergistic Drug Combinations for Colorectal Cancer Driven by Tumor Barcode Derived from Metabolomics "Big Data".

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.

Inflammatory-Dependent Bidirectional Effect of Bile Acids on NLRP3 Inflammasome and Its Role in Ameliorating CPT-11-Induced Colitis.

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.

Subcellular metabolomics: Isolation, measurement, and applications.

Metabolomics, a technique that profiles global small molecules in biological samples, has been a pivotal tool for disease diagnosis and mechanism research. The sample type in metabolomics covers a wide range, including a variety of body fluids, tissues, and cells. However, little attention was paid to the smaller, relatively independent partition systems in cells, namely the organelles. The organelles are specific compartments/places where diverse metabolic activities are happening in an orderly manner. Metabolic disorders of organelles were found to occur in various pathological conditions such as inherited metabolic diseases, diabetes, cancer, and neurodegenerative diseases. However, at the cellular level, the metabolic outcomes of organelles and cytoplasm are superimposed interactively, making it difficult to describe the changes in subcellular compartments. Therefore, characterizing the metabolic pool in the compartmentalized system is of great significance for understanding the role of organelles in physiological functions and diseases. So far, there are very few research articles or reviews related to subcellular metabolomics. In this review, subcellular fractionation and metabolite analysis methods, as well as the application of subcellular metabolomics in the physiological and pathological studies are systematically reviewed, as a practical reference to promote the continued advancement in subcellular metabolomics.

Network-driven targeted analysis reveals that Astragali Radix alleviates doxorubicin-induced cardiotoxicity by maintaining fatty acid homeostasis.

ETHNOPHARMACOLOGICAL RELEVANCE: Astragali Radix (AR) is a popular traditional Chinese medicine that has been used for more than 2000 years. It is a well-known tonic for weak people with chronic diseases, such as heart failure and cerebral ischemia. Previous studies have reported that AR could support the "weak heart" of cancer patients who suffered from doxorubicin (DOX)-induced cardiotoxicity (DIC). However, the underlying mechanism remains unclear. AIM OF THE STUDY: This study aimed to uncover the critical pathways and molecular determinants for AR against DIC by fully characterizing the network-based relationship. MATERIALS AND METHODS: We integrated ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) profiling, database and literature searching, and the human protein-protein interactome to discover the specific network module associated with AR against DIC. To validate the network-based findings, a low-dose, long-term DIC mouse model and rat cardiomyoblast H9c2 cells were employed. The levels of potential key metabolites and proteins in hearts and cells were quantified by the LC-MS/MS targeted analysis and western blotting, respectively. RESULTS: We constructed one of the most comprehensive AR component-target network described to date, which included 730 interactions connecting 64 unique components and 359 unique targets. Relying on the network-based evaluation, we identified fatty acid metabolism as a putative critical pathway and peroxisome proliferator-activated receptors (PPARα and PPARγ) as potential molecular determinants. We then confirmed that DOX caused the accumulation of fatty acids in the mouse failing heart, while AR promoted fatty acid metabolism and preserved heart function. By inhibiting PPARγ in H9c2 cells, we further found that AR could alleviate DIC by activating PPARγ to maintain fatty acid homeostasis. CONCLUSIONS: Our findings imply that AR is a promising drug candidate that treats DIC by maintaining fatty acid homeostasis. More importantly, the network-based method developed here could facilitate the mechanism discovery of AR therapy and help catalyze innovation in its clinical application.

Twins labeling derivatization-based LC-MS/MS strategy for absolute quantification of paired prototypes and modified metabolites.

Modified metabolites play significant roles in disease occurrence, progression and diagnosis. Sensitive and accurate analytical methods for the quantification of these metabolites are therefore of great importance. In this study, a liquid chromatography tandem mass spectrometry (LC-MS/MS) method was developed for the simultaneous measurement of 13 pairs of prototypes and their modified forms covering nucleobases, nucleosides and amino acids. In order to improve the quantification sensitivity and accuracy, two structure analogs named N-dimethyl-amino naphthalene-1-sulfonyl chloride (Dns-Cl) and N-diethyl-amino naphthalene-1-sulfonyl chloride (Dens-Cl) were introduced for twins labeling derivatization. Dns-labeling was utilized to react with target analytes while the Dens-labeling of standard compounds provided one-to-one internal standards. With the introduce of naphthalene and easily ionizable moiety tertiary ammonium, chromatography retention and separation of these polar metabolites were notably improved on C18 columns and the detection sensitivity was increased up to 400 folds. The method is sensitive with the lower limit of quantification (LLOQ) values of 0.002-0.5 µg/mL. Comparisons of the performance of twins labeling derivatization and traditional chemical isotope labeling (CIL) derivatization verified the ability of our method in the absolute quantification. The established method was applied to human lung adenocarcinoma cell line A549 and its cisplatin resistant derivative A549/DDP. Significant shifts in 12 metabolites as well as 9 modified-to-prototypical ratios in A549/DDP were observed, demonstrating the utility of our method and the potential role of modified metabolites in mediating anticancer drug resistance. The method can be easily extended to determine other types of modified metabolites in various biological matrices, which will greatly expand our knowledge on these metabolites.

3' untranslated region variants in DEFA5 gene associated with susceptibility to IgA nephropathy in the Chinese Han population.

Aim: To evaluate the association between single-nucleotide polymorphisms in the 3' untranslated region of the DEFA5 gene and IgA nephropathy (IgAN) risk, the authors performed an association study in the Chinese Han population. Materials & methods: The authors recruited 426 IgAN patients and 498 controls. The MassARRAY platform (Agena Bioscience, Inc., CA, USA) was used to genotype single-nucleotide polymorphisms in DEFA5. Odds ratios and 95% CIs were calculated through logistic regression analysis. Results: The authors observed that rs12716641 significantly reduced IgAN risk in the allele (odds ratio: 0.77; p = 0.026) and genotype (odds ratio: 0.75; p = 0.039) models. Stratification analysis revealed that several genotypes of rs12716641 played a protective role against IgAN. Conclusion: The authors' results revealed that single-nucleotide polymorphisms in the 3' untranslated region of DEFA5 were associated with IgAN risk.

Predicting the grades of Astragali radix using mass spectrometry-based metabolomics and machine learning.

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.

Metabolic network-based identification of plasma markers for non-small cell lung cancer.

Metabolic markers, offering sensitive information on biological dysfunction, play important roles in diagnosing and treating cancers. However, the discovery of effective markers is limited by the lack of well-established metabolite selection approaches. Here, we propose a network-based strategy to uncover the metabolic markers with potential clinical availability for non-small cell lung cancer (NSCLC). First, an integrated mass spectrometry-based untargeted metabolomics was used to profile the plasma samples from 43 NSCLC patients and 43 healthy controls. We found that a series of 39 metabolites were altered significantly. Relying on the human metabolic network assembled from Kyoto Encyclopedia of Genes and Genomes (KEGG) database, we mapped these differential metabolites to the network and constructed an NSCLC-related disease module containing 23 putative metabolic markers. By measuring the PageRank centrality of molecules in this module, we computationally evaluated the network-based importance of the 23 metabolites and demonstrated that the metabolism pathways of aromatic amino acids and long-chain fatty acids provided potential molecular targets of NSCLC (i.e., IL4l1 and ACOT2). Combining network-based ranking and support-vector machine modeling, we further found a panel of eight metabolites (i.e., pyruvate, tryptophan, and palmitic acid) that showed a high capability to differentiate patients from controls (accuracy > 97.7%). In summary, we present a meaningful network method for metabolic marker discovery and have identified eight strong candidate metabolites for NSCLC diagnosis.

Akkermansia Muciniphila Potentiates the Antitumor Efficacy of FOLFOX in Colon Cancer.

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.

Absolute Quantification of Acylcarnitines Using Integrated Tmt-PP Derivatization-Based LC-MS/MS and Quantitative Analysis of Multi-Components by a Single Marker Strategy.

Acylcarnitines (ACs) play important roles in the fatty acid ß-oxidation and are considered as diagnostic markers for many diseases. Accurate determination of ACs remains challenging due to their low abundance, high structure diversity, and limited availability of standard compounds. In this study, microwave-assisted Tmt-PP (p-[3,5-(dimethylamino)-2,4,6-triazine] benzene-1-sulfonyl piperazine) derivatization was utilized to facilitate the liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) determination of ACs. The result indicated that Tmt-PP labeling enables the prediction of the retention time and MS response of ACs and enhances their MS response up to 4 times. The introduction of the microwave during the derivatization procedure greatly improved the reaction efficiency, demonstrated by the shortened reaction time from 90 to 1 min. Furthermore, we applied a strategy named quantitative analysis of multi-components by a single marker (QAMS) for the assay of 26 ACs with only 5 AC standards, solving the standard availability issue to a large extent. The established workflow was applied to discover dysregulated ACs in xenograft colon cancer mice, and the quantification results were highly comparable with traditional methods where there were the corresponding standards for each AC. Our study demonstrated that chemical derivatization-based LC-MS/MS integrated with the QAMS strategy is robust for the identification and quantification of ACs and has great potential in targeted metabolomics study.

Oleic Acid and Insulin as Key Characteristics of T2D Promote Colorectal Cancer Deterioration in Xenograft Mice Revealed by Functional Metabolomics.

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.

Tryptophan Pathway-Targeted Metabolomics Study on the Mechanism and Intervention of Cisplatin-Induced Acute Kidney Injury in Rats.

Cisplatin is a chemotherapeutic agent widely employed in the treatment of various solid tumors. However, its use is often restricted by acute kidney injury (AKI) which is the dose-limiting adverse effect of cisplatin. While numerous studies aiming to alleviate the AKI have been conducted, there are no effective remedies in clinical practice. In this paper, a targeted metabolomics study was performed to reveal the potential relationship between tryptophan metabolism and cisplatin-induced AKI. A chemical derivatization integrated liquid chromatography coupled tandem mass spectrometry (LC-MS/MS) approach was utilized to quantify 29 metabolites in the tryptophan pathway in rat kidney medulla and cortex after cisplatin administration. Results showed that tryptophan metabolism was remarkably disturbed both in the medulla and cortex after cisplatin administration. We also found that the tryptophan pathway in the medulla was more sensitive to cisplatin exposure compared with the cortex. Among these metabolites, indoxyl sulfate was focused for further study because it accumulated most significantly in the kidney cortex and medulla in a dose-dependent manner. A function verification study proved that chlormethiazole, a widely used CYP2E1 inhibitor, could reduce the production of indoxyl sulfate in the liver and attenuate cisplatin-induced AKI in rats. In conclusion, our study depicted the tryptophan pathway in cisplatin-induced AKI for the first time and demonstrated tryptophan metabolism is closely associated with the renal toxicity caused by cisplatin, which can be of great use for the discovery of renal toxicity attenuating remedies.