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Advances in liquid chromatography-mass spectrometry (LC-MS) instruments and analytical strategies have brought about great progress in targeted metabolomics analysis. This methodology is now capable of performing precise targeted measurement of dozens or hundreds of metabolites in complex biological samples. Classic targeted quantification assay using the multiple reaction monitoring (MRM) mode has been the foundation of high-quality metabolite quantitation. However, utilization of this strategy in biological studies has been limited by its relatively low metabolite coverage and throughput capacity. A number of methods for large-scale targeted metabolomics assay which have been developed overcome these limitations. These strategies have enabled extended metabolite coverage which is defined as targeting of large numbers of metabolites, while maintaining reliable quantification performance. These recently developed techniques thus bridge the gap between traditional targeted metabolite quantification and untargeted metabolomics profiling, and have proven to be powerful tools for metabolomics study. Although the LC-MRM-MS strategy has been used widely in large-scale metabolomics quantification analysis due to its fast scan speed and ideal analytic stability, there are still drawbacks which are due to the low resolution of the triple quadrupole instruments used for MRM assays. New approaches have been developed to expand the options for large-scale targeted metabolomics study, using high-resolution instruments such as parallel reaction monitoring (PRM). MRM and PRM-based techniques are now attractive strategies for quantitative metabolomics analysis and high-throughput biomarker discovery. Here we provide an overview of the major developments in LC-MS-based strategies for large-scale targeted metabolomics quantification in biological samples. The advantages of LC-MRM/PRM-MS based analytical strategies which may be used in multiplexed and high throughput quantitation for a wide range of metabolites are highlighted. In particular, PRM and MRM strategies are compared, and we summarize the work flow commonly used for large-scale targeted metabolomics analysis including sample preparation, LC separation and data analysis, as well as recent applications in biological studies.

Recent advances in mass spectrometers which have yielded higher resolution and faster scanning speeds have expanded their application in metabolomics of diverse diseases. Using a quadrupole-Orbitrap LC-MS system, we developed an efficient large-scale quantitative method targeting 237 metabolites involved in various metabolic pathways using scheduled, parallel reaction monitoring (PRM). We assessed the dynamic range, linearity, reproducibility, and system suitability of the PRM assay by measuring concentration curves, biological samples, and clinical serum samples. The quantification performances of PRM and MS1-based assays in Q-Exactive were compared, and the MRM assay in QTRAP 6500 was also compared. The PRM assay monitoring 237 polar metabolites showed greater reproducibility and quantitative accuracy than MS1-based quantification and also showed greater flexibility in postacquisition assay refinement than the MRM assay in QTRAP 6500. We present a workflow for convenient PRM data processing using Skyline software which is free of charge. In this study we have established a reliable PRM methodology on a quadrupole-Orbitrap platform for evaluation of large-scale targeted metabolomics, which provides a new choice for basic and clinical metabolomics study.

Lung cancer is the leading cause of cancer mortality, and early detection is key to improving survival. However, there are no reliable blood-based tests currently available for early-stage lung cancer diagnosis. Here, we performed single-cell RNA sequencing of different early-stage lung cancers and found that lipid metabolism was broadly dysregulated in different cell types, with glycerophospholipid metabolism as the most altered lipid metabolism–related pathway. Untargeted lipidomics was carried out in an exploratory cohort of 311 participants. Through support vector machine algorithm-based and mass spectrum–based feature selection, we identified nine lipids (lysophosphatidylcholines 16:0, 18:0, and 20:4; phosphatidylcholines 16:0–18:1, 16:0–18:2, 18:0–18:1, 18:0–18:2, and 16:0–22:6; and triglycerides 16:0–18:1–18:1) as the features most important for early-stage cancer detection. Using these nine features, we developed a liquid chromatography–mass spectrometry (MS)–based targeted assay using multiple reaction monitoring. This target assay achieved 100.00% specificity on an independent validation cohort. In a hospital-based lung cancer screening cohort of 1036 participants examined by low-dose computed tomography and a prospective clinical cohort containing 109 participants, the assay reached more than 90.00% sensitivity and 92.00% specificity. Accordingly, matrix-assisted laser desorption/ionization MS imaging confirmed that the selected lipids were differentially expressed in early-stage lung cancer tissues in situ. This method, designated as Lung Cancer Artificial Intelligence Detector, may be useful for early detection of lung cancer or large-scale screening of high-risk populations for cancer prevention.

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The proposed DIA workflow yields optimum time efficiency and data reliability and provides a good choice for proteomic analysis in biological and clinical studies, and these dysregulated proteins might be potential biomarkers for ccRCC diagnosis.

Objective: To analyze the proteome of preoperative cerebrospinal fluid (CSF) in older orthopedic patients with or without postoperative delirium (POD) using untargeted proteomics.Methods: A prospective cohort study was conducted. Eighty hip fracture patients aged ≥65 years were recruited. After successful spinal anesthesia, CSF was collected. The patients were divided into POD and No-POD groups based on the Confusion Assessment Method, and patients with POD were graded using the Memorial Delirium Assessment Scale (MDAS). Thirty No-POD patients were matched to 10 POD patients by age (±2 years) and Mini-Mental State Examination score (±2 scores). Label-free proteomic analysis was performed using a liquid chromatography coupled to mass spectrometry (LC-MS) workflow. Validation was performed using mass-spectrometry-based parallel reaction monitoring (PRM) for the 30 No-POD and 10 POD patients, as well as for an additional 5 POD patients. Bioinformatics were used to investigate possible relevant pathological mechanisms.Results: The incidence of POD in older orthopedic patients was 18.8% in our cohort of 80 patients. Proteomics results revealed 63 dysregulated CSF proteins, and PRM analysis validated these results. The preoperative CSF levels of both V-set and transmembrane domain-containing protein 2B (VSTM2B) and coagulation factor V (FA5) were positively correlated with MDAS scores on postoperative day 1 (r > 0.8, p < 0.05). Bioinformatic analysis revealed that several nervous-system-related pathways are relevant to POD development. Conclusion:We identified and validated several novel CSF proteins that are dysregulated in POD, and revealed several pathways that are relevant to POD development. Our results not only provide risk biomarkers for POD, but also give clues for further investigations into the pathological mechanisms of delirium. Clinical trial registration: This study was registered in the Chinese Clinical Trial Registry (ChiCTR1900021533).

B12 belongs to the coumarin class of compounds that have been shown to have various physiological and pharmacological activities including anti-inflammatory, antibacterial, and antioxidant. In the present study, we characterised the neuroprotective effects of B12 against H 2 O 2 -induced neuronal cell damage in SH-SY5Y cells. Protein expression profiling in combination with pathway analysis was deployed to investigate the molecular events associated with the neuroprotective effects in human neuronal cells using a label-free quantitative proteomics approach. A total of 22 proteins were significantly differentially expressed in H 2 O 2 -damaged cells with or without B12 treatment. Bioinformatics analysis using the Cytoscape platform indicated that poly pyrimidine tract binding protein 1 (PTBP1) was highly associated with the protective effect, and western blotting verified that PTBP1 was up-regulated in H 2 O 2 + B12 treatment group, compared with the H 2 O 2 treated group. PTBP RNAi experiments knocked down PTBP expression, which cancelled out the protective effect of B12 on cell viability. Thus, we infer that B12 neuroprotective activity involves up-regulation of PTBP1 and its associated signalling networks following H 2 O 2 -induced apoptosis in SH-SY5Y cells. B12 or related compounds may prove to be useful therapeutic agents for the treatment of neurodegenerative diseases such as Alzheimer's and Parkinson's.Neurodegenerative diseases such as Parkinson's (PD) and Alzheimer's (AD) are characterized by the progressive loss of specific neuronal cell populations, and are associated with the formation of protein aggregates 1-3 . A common feature of these diseases is a connection with oxidative stress, which leads to the dysfunction or death of neuronal cells and contributes to disease pathogenesis 3 . Oxidative damage is generated following cell lysis and a burst of oxidative activity that results in an accumulation of oxygen free radicals that attack proteins, nucleic acids, and lipid membranes, thereby disrupting cellular function and integrity 4 . Hydrogen peroxide (H 2 O 2 ) is among the main reactive oxygen species (ROS) and is produced in redox processes 5,6 . Oxidative stress manifests its toxic effects through different pathways, and knowledge of these pathways could assist the development of a number of potential therapeutic strategies that target neurodegenerative diseases 4 .Proteomics, the collective study of all expressed proteins in cells, tissues, or biological fluids at a given time or under given conditions, reveals information on not only the individual components (proteins), but also their interplay in complexes, signalling pathways, and network modules associated with specific biochemical functions [7][8][9] . Proteomics studies generally involve high-throughput experimental platforms such as liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) 10-12 that measures the abundance of proteins or peptides in different biological conditions by assaying thousands of proteins from comp...