Registro de lexicografia hispanica

Gillet, Joseph E.; Romera-Navarro, M.

doi:10.2307/470995

Cited by 2 publications

(3 citation statements)

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“…data independent acquisition, DIA). (21) In a cycle time of about 1.8 sec, one survey scan and thirty-four 26 Da SWATH scans were performed. These 26 Da-wide scan events sequentially cover the mass range of 400 -1250 Da, with a 1 Da for the window overlap.…”

Section: Proteomics Sample Preparation and Mass Spectrometry Analysismentioning

confidence: 99%

Multiomic Profiling of Tyrosine Kinase Inhibitor-Resistant K562 Cells Suggests Metabolic Reprogramming To Promote Cell Survival

et al. 2019

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Resistance to chemotherapy can occur through a wide variety of mechanisms. Resistance to tyrosine kinase inhibitors (TKIs) often arises from kinase mutations-however, "off-target" resistance occurs but is poorly understood. Previously, we established cell line resistance models for three TKIs used in chronic myeloid leukemia treatment, and found that resistance was not attributed entirely to failure of kinase inhibition. Here, we performed global, integrated proteomic and transcriptomic profiling of these cell lines to describe mechanisms of resistance at the protein and gene expression level. We used whole transcriptome sequencing and SWATH-based dataindependent acquisition mass spectrometry (DIA-MS), which does not require isotopic labels and provides quantitative measurements of proteins in a comprehensive, unbiased fashion. The proteomic and transcriptional data were correlated to generate an integrated understanding of the gene expression and protein alterations associated with TKI resistance. We defined mechanisms of resistance and two novel markers, CA1 and alpha-synuclein, that were common to all TKIs tested. Resistance to all of the TKIs was associated with oxidative stress responses, hypoxia signatures, and apparent metabolic reprogramming of the cells. Metabolite profiling and glucose-dependence experiments showed that resistant cells had routed their metabolism through glycolysis (particularly through the pentose phosphate pathway) and exhibited disruptions in mitochondrial metabolism. These experiments are the first to report a global, integrated proteomic, transcriptomic and metabolic analysis of TKI resistance. These data suggest that although the mechanisms are complex, targeting metabolic pathways along with TKI treatment may overcome pan-TKI resistance.

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Section: Proteomics Sample Preparation and Mass Spectrometry Analysismentioning

confidence: 99%

Multiomic Profiling of Tyrosine Kinase Inhibitor-Resistant K562 Cells Suggests Metabolic Reprogramming To Promote Cell Survival

et al. 2019

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“…107 Targeted proteomics approaches like selected reaction monitoring (SRM), also known as multiple reaction monitoring (MRM), parallel reaction monitoring (PRM), and data-independent acquisition (DIA) combined with targeted data extraction of the MS/MS spectra [e.g., sequential windowed acquisition of all theoretical product ion mass spectra (SWATH)], are developing rapidly. 134 Reproducible and accurate quantification of target peptides or proteins across many samples have been made possible by SRM-and PRM-based analysis. Although both SRM and PRM have not been demonstrated with sample multiplexing to date, it is possible to ensure reliable quantification for ~500 peptides/125 proteins in a single analysis.…”

Section: Other Multiplexing Approachesmentioning

confidence: 99%

“…Also, SRM-based quantification has been shown to be at least 10-fold higher in sensitivity than DIA-based targeted quantification. 134…”

Section: Other Multiplexing Approachesmentioning

confidence: 99%

Sample Multiplexing Strategies in Quantitative Proteomics

Arul

Robinson

2018

Anal. Chem.

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Proteomics increasingly contributes to our understanding of the roles that proteins play in biology and a wide range of applications including the microbiome, bioremediation, 1 and diseases such as cancer, 2 Alzheimer's, 3 diabetes, 4 cardiovascular disease, 5 obesity, 6 and many aspects of human health. 7,8 The size of the human genome, ~20300 protein coding genes, results in an estimated three billion proteoforms 9 that potentially exist in biological samples subject to proteomic analysis. The traditional approach of bottom-up proteomics requires digestion of proteins into peptides which further increases sample complexity. Despite this added complexity, however, peptides that "fly" well into the mass spectrometer are easily fragmented and detected and can be sequenced routinely using numerous data acquisition and analysis pipelines. To provide proteome depth across a dynamic range of 10-12 orders of magnitude requires sophisticated analytical instrumentation and extensive sample fractionation techniques. Quite impressively, this level of analyte multiplexing in single experiments has been taken advantage of in numerous studies over the last 15 years. Many biological questions of interest, however, seek to determine differences in protein concentrations across two or more conditions, multiple time points, and in various tissues. This leads to a desire to increase the overall sample throughput in bottom-up proteomics. Mass spectrometry (MS)-based proteomics and protein microarray technology have made high throughput protein quantification possible. Microarray-based technology for proteomics includes full-length protein, peptide, antibody, reverse-phase, and tissue arrays 10 that detect tens to thousands of proteins with fluorescent detection. Array-based approaches have advantages of multiplexing samples to simultaneously screen interactions among several biomolecules with linearity. 11 Despite the advantages array-based approaches offer, they also suffer from intense experimental design, chip customization, protein immobilization in native state, normalization, nonspecific binding, cross reactivity, 12 lack of *

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Registro de lexicografia hispanica

Cited by 2 publications

References 0 publications

Multiomic Profiling of Tyrosine Kinase Inhibitor-Resistant K562 Cells Suggests Metabolic Reprogramming To Promote Cell Survival

Multiomic Profiling of Tyrosine Kinase Inhibitor-Resistant K562 Cells Suggests Metabolic Reprogramming To Promote Cell Survival

Sample Multiplexing Strategies in Quantitative Proteomics

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