Single-sample, multi-omic mass spectrometry for investigating mechanisms of drug toxicity
Mahmud, I.; Chan, W.-K.; Yannell, K.; Simmermaker, C.; Van de Bittner, G.; Wu, L.; Chan, D.; Mohsin, S. B.; Liu, Y.; Sausen, J.; Weinstein, J. N.; Lorenzi, P. L.
Show abstract
Poor therapeutic index is a principal cause of drug attrition during development. A case in point is L-asparaginase (ASNase), an enzyme-drug approved for treatment of pediatric acute lymphoblastic leukemia (ALL) but too toxic for adults. To elucidate potentially targetable mechanisms for mitigation of ASNase toxicity, we performed multi-omic profiling of the response to sub-toxic and toxic doses of ASNase in mice. We collected whole blood samples longitudinally, processed them to plasma, and extracted metabolites, lipids, and proteins from a single 20-{micro}L plasma sample. We analyzed the extracts using multiple reaction monitoring (MRM) of 500+ water soluble metabolites, 750+ lipids, and 375 peptides on a triple quadrupole LC-MS/MS platform. Metabolites, lipids, and peptides that were modulated in a dose-dependent manner appeared to converge on antioxidation, inflammation, autophagy, and cell death pathways, prompting the hypothesis that inhibiting those pathways might decrease ASNase toxicity while preserving anticancer activity. Overall, we provide here a streamlined, three-in-one LC-MS/MS workflow for targeted metabolomics, lipidomics, and proteomics and demonstrate its ability to generate new insights into mechanisms of drug toxicity.
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Optimized Mass Spectrometry Detection of Thyroid Hormones and Polar Metabolites in Rodent Cerebrospinal Fluid 95%
- High-throughput UHPLC-MS to screen metabolites in feces for gut metabolic health 95%
- An Optimised Monophasic Faecal Extraction Method for LC-MS Analysis and its Application in Gastrointestinal Disease 95%
Similar papers in this journal
- UCL-MetIsoLib: A Public High-Resolution Tandem Mass Spectrometry Library for HILIC-Based Isomer-Resolved Profiling of Glycolysis, Central Carbon Metabolism, and Beyond in Urine, Plasma, Tissues, Cells, and Patient-Derived Organoids 96%
- Comprehensive Metabolomic Analysis of Human Heart Tissue Enabled by Parallel Metabolite Extraction and High-Resolution Mass Spectrometry 95%
- Assessment of a 60-biomarker health surveillance panel (HSP) on whole blood from remote sampling devices by targeted LC/MRM-MS and discovery DIA-MS analysis 95%
Similar papers in this journal
- Untargeted metabolomics of COVID-19 patient serum reveals potential prognostic markers of both severity and outcome 95%
- Meta-analysis of targeted metabolomics data from heterogeneous biological samples provides insights into metabolite dynamics 95%
- An untargeted metabolomics strategy to measure differences in metabolite uptake and excretion by mammalian cell lines 95%
Similar papers in this journal
- Metabolic snapshot of plasma samples reveals new pathways implicated in SARS-CoV-2 pathogenesis 95%
- Development and Validation of a Novel LC-MS/MS Based Proteomics Method for Quantitation of Retinol Binding Protein 4 (RBP4) and Transthyretin (TTR) 95%
- Development and Application of Multidimensional Lipid Libraries to Investigate Lipidomic Dysregulation Related to Smoke Inhalation Injury Severity 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.