Project description:PurposeThis work aims to identify differential metabolites and predicting molecular subtypes of breast cancer (BC).MethodsPlasma samples were collected from 96 BC patients and 79 normal participants. Metabolic profiles were determined by liquid chromatography-mass spectrometry and gas chromatography-mass spectrometry based on multivariate statistical data analysis.ResultsWe observed 64 differential metabolites between BC and normal group. Compared to human epidermal growth factor receptor 2 (HER2)-negative patients, HER2-positive group showed elevated aerobic glycolysis, gluconeogenesis, and increased fatty acid biosynthesis with reduced Krebs cycle. Compared with estrogen receptor (ER)-negative group, ER-positive patients showed elevated alanine, aspartate and glutamate metabolism, decreased glycerolipid catabolism, and enhanced purine metabolism. A panel of 8 differential metabolites, including carnitine, lysophosphatidylcholine (20:4), proline, alanine, lysophosphatidylcholine (16:1), glycochenodeoxycholic acid, valine, and 2-octenedioic acid, was identified for the classification of BC subtypes. These markers showed potential diagnostic value with average area under the curve at 0.925 (95% CI 0.867-0.983) for the training set (n=51) and 0.893 (95% CI 0.847-0.939) for the test set (n=45).ConclusionHuman plasma metabolomics is useful in identifying differential metabolites and predicting breast cancer subtypes.
Project description:IntroductionUnderstanding the pharmacokinetics (PK) of antimicrobial drugs in pregnant women is crucial to provide effective and safe treatment. This study is part of a series that systematically reviews literature on the PK and analyzes if, based on the changed PK, evidence-based dosing regimens have been developed for adequate target attainment in pregnant women. This part focusses on antimicrobials other than penicillins and cephalosporins.MethodsA literature search was conducted in PubMed according to the PRISMA guidelines. Search strategy, study selection, and data extraction were independently performed by two investigators. Studies were labeled as relevant when information on the PK of antimicrobial drugs in pregnant women was available. Extracted parameters included bioavailability for oral drugs, volume of distribution (Vd) and clearance (CL), trough and peak drug concentrations, time of maximum concentration, area under the curve and half-life, probability of target attainment, and minimal inhibitory concentration (MIC). In addition, if developed, evidence-based dosing regimens were also extracted.ResultsOf the 62 antimicrobials included in the search strategy, concentrations or PK data during pregnancy of 18 drugs were reported. Twenty-nine studies were included, of which three discussed aminoglycosides, one carbapenem, six quinolones, four glycopeptides, two rifamycines, one sulfonamide, five tuberculostatic drugs, and six others. Eleven out of 29 studies included information on both Vd and CL. For linezolid, gentamicin, tobramycin, and moxifloxacin, altered PK throughout pregnancy, especially in second and third trimester, has been reported. However, no target attainment was studied and no evidence-based dosing developed. On the other hand, the ability to reach adequate targets was assessed for vancomycin, clindamycin, rifampicin, rifapentine, ethambutol, pyrazinamide, and isoniazid. For the first six mentioned drugs, no dosage adaptations during pregnancy seem to be needed. Studies on isoniazid provide contradictory results.ConclusionThis systematic literature review shows that a very limited number of studies have been performed on the PK of antimicrobials drugs-other than cephalosporins and penicillins-in pregnant women.
Project description:The ProteomeTools project aims to derive molecular and digital tools from the human proteome to facilitate biomedical and life science research. Here, we describe the third iteration of the generation and multimodal LC-MS/MS analysis of >305,000 synthetic non-tryptic peptides representing HLA Class I & II ligands as well as peptides derived from the N-terminal proteases LysN and ApsN. This resource will be extended to 1.4 million peptides and all data will be made available to the public in ProteomicsDB.
Project description:1) We identified the genes whose expression was up- and down-regulated by the adhesion to bone marrow stromal cells in human multiple myeloma cell line RPMI8226. 2) We identified the genes whose expression was up- and down-regulated by the PI3K inhibitor PF-04691502 in human multiple myeloma cell line RPMI8226. We isolated mRNA from the multiple myeloma cell line RPMI8226 under drug-resistant conditions, and subjected them to gene expression profiling using an Agilent GeneChip Array.
Project description:The ProteomeTools project aims to derive molecular and digital tools from the human proteome to facilitate biomedical and life science research. Here, we describe the third iteration of the generation and multimodal LC-MS/MS analysis of >305,000 synthetic non-tryptic peptides representing HLA Class I & II ligands as well as peptides derived from the N-terminal proteases LysN and ApsN. This resource will be extended to 1.4 million peptides and all data will be made available to the public in ProteomicsDB.
Project description:Recently, many studies have shown that lncRNA can mediate the regulation of TF-gene in drug sensitivity. However, there is still a lack of systematic identification of lncRNA-TF-gene regulatory triplets for drug sensitivity. In this study, we propose a novel analytic approach to systematically identify the lncRNA-TF-gene regulatory triplets related to the drug sensitivity by integrating transcriptome data and drug sensitivity data. Totally, 1570 drug sensitivity-related lncRNA-TF-gene triplets were identified, and 16 307 relationships were formed between drugs and triplets. Then, a comprehensive characterization was performed. Drug sensitivity-related triplets affect a variety of biological functions including drug response-related pathways. Phenotypic similarity analysis showed that the drugs with many shared triplets had high similarity in their two-dimensional structures and indications. In addition, Network analysis revealed the diverse regulation mechanism of lncRNAs in different drugs. Also, survival analysis indicated that lncRNA-TF-gene triplets related to the drug sensitivity could be candidate prognostic biomarkers for clinical applications. Next, using the random walk algorithm, the results of which we screen therapeutic drugs for patients across three cancer types showed high accuracy in the drug-cell line heterogeneity network based on the identified triplets. Besides, we developed a user-friendly web interface-DrugSETs (http://bio-bigdata.hrbmu.edu.cn/DrugSETs/) available to explore 1570 lncRNA-TF-gene triplets relevant with 282 drugs. It can also submit a patient's expression profile to predict therapeutic drugs conveniently. In summary, our research may promote the study of lncRNAs in the drug resistance mechanism and improve the effectiveness of treatment.
Project description:Myasthenia gravis (MG) is a devastating acquired autoimmune disease. Previous studies have observed that disturbances of gut microbiome may attribute to the development of MG through fecal metabolomic signatures in humans. However, whether there were differential gut microbial and fecal metabolomic phenotypes in different subtypes of MG remains unclear. Here, our objective was to explore whether the microbial and metabolic signatures of ocular (OMG) and generalized myasthenia gravis (GMG) were different, and further identify the shared and distinct markers for patients with OMG and GMG. In this study, 16S ribosomal RNA (rRNA) gene sequencing and gas chromatography-mass spectrometry (GC/MS) were performed to capture the microbial and metabolic signatures of OMG and GMG, respectively. Random forest (RF) classifiers was used to identify the discriminative markers for OMG and GMG. Compared with healthy control (HC) group, GMG group, but not OMG group, showed a significant decrease in α-phylogenetic diversity. Both OMG and GMG groups, however, displayed significant gut microbial and metabolic disorders. Totally, we identified 20 OTUs and 9 metabolites specific to OMG group, and 23 OTUs and 7 metabolites specific to GMG group. Moreover, combinatorial biomarkers containing 15 discriminative OTUs and 2 differential metabolites were capable of discriminating OMG and GMG from each other, as well as from HCs, with AUC values ranging from 0.934 to 0.990. In conclusion, different subtypes of MG harbored differential gut microbiota, which generated discriminative fecal metabolism.
Project description:The mechanisms driving SARS-CoV-2 susceptibility remain poorly understood, especially the factors determining why unvaccinated individuals remain uninfected despite high-risk exposures. To understand lipid and metabolite profiles related with COVID-19 susceptibility and disease progression. We collected samples from an exceptional group of unvaccinated healthcare workers heavily exposed to SARS-CoV-2 but not infected ('non-susceptible') and subjects who became infected during the follow-up ('susceptible'), including non-hospitalized and hospitalized patients with different disease severity providing samples at early disease stages. Then, we analyzed their plasma metabolomic profiles using mass spectrometry coupled with liquid and gas chromatography. We show specific lipids profiles and metabolites that could explain SARS-CoV-2 susceptibility and COVID-19 severity. More importantly, non-susceptible individuals show a unique lipidomic pattern characterized by the upregulation of most lipids, especially ceramides and sphingomyelin, which could be interpreted as markers of low susceptibility to SARS-CoV-2 infection. This study strengthens the findings of other researchers about the importance of studying lipid profiles as relevant markers of SARS-CoV-2 pathogenesis.
Project description:Fibrosis is a pathological process involving the abnormal deposition of connective tissue, resulting from improper tissue repair in response to sustained injury caused by hypoxia, infection, or physical damage. It can impact any organ, leading to their dysfunction and eventual failure. Additionally, tissue fibrosis plays an important role in carcinogenesis and the progression of cancer.Early and accurate diagnosis of organ fibrosis, coupled with regular surveillance, is essential for timely disease-modifying interventions, ultimately reducing mortality and enhancing quality of life. While extensive research has already been carried out on the topics of aberrant wound healing and fibrogenesis, we lack a thorough understanding of how their relationship reveals itself through modern imaging techniques.This paper focuses on fibrosis of the genito-urinary system, detailing relevant imaging technologies used for its detection and exploring future directions.