A high-throughput processing service for retention time alignment of complex proteomics and metabolomics LC-MS data

Ahmad, Isthiaq; Suits, Frank; Hoekman, Berend; Swertz, Morris A.; Byelas, Heorhiy; Dijkstra, Martijn; Hooft, Rob; Katsubo, Dmitry; Breukelen, Bas van; Bischoff, Rainer; Horvatovich, Péter

doi:10.1093/bioinformatics/btr094

Cited by 10 publications

(5 citation statements)

References 13 publications

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“…The aligned chromatograms of trastuzumab and pertuzumab show highly similar, characteristic profiles. LC-UV trace similarity was quantified by measuring the area under the curve of the overlap between two traces divided by the geometric mean of the area under the curve of the two individual traces (Ahmad et al, 2011;Suits et al, 2008). Figure 5 shows a heatmap of the similarity scores between all possible pairs of chromatograms following hierarchical clustering (Figure S2, supporting information).…”

Section: Figure 3amentioning

confidence: 99%

Biotransformation of Trastuzumab and Pertuzumab in Breast Cancer Patients Assessed by Affinity Enrichment and Ion-Exchange Chromatography

Olaleye

Spanov

Bults³

et al. 2022

Drug Metab Dispos

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Therapeutic proteins (TPs) are known to be heterogeneous due to modifications that occur during the production process and storage. Modifications may also occur in TPs after their administration to patients due to in vivo biotransformation. Ligand binding assays, which are widely used in the bioanalysis of TPs in body fluids, are typically unable to distinguish such modifications. Liquid chromatography coupled to mass spectrometry (LC-MS) is being increasingly used to study modifications in TPs but its use to study in vivo biotransformation has been limited until now. We present a novel approach that combines affinity enrichment using Affimer reagents® with ionexchange chromatography (IEX) to analyze charge variants of the TPs trastuzumab and pertuzumab in plasma of patients undergoing therapy for HER2-positive breast cancer. Affimer reagents® were immobilized via engineered Cys tags to maleimide beads and the TPs were eluted under acidic conditions followed by rapid neutralization. The enriched TPs were analyzed by cation-exchange chromatography (IEX) using pH-gradient elution resulting in the separation of about 20 charge variants for trastuzumab and about 5 charge variants for pertuzumab. A comparison between in vitro stressed TPs spiked into plasma and TPs enriched from patient plasma showed that the observed profiles were highly similar. This indicates that in vitro stress testing in plasma can mimic the situation in patient plasma, as far as the generation of charge variants is concerned.

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Section: Figure 3amentioning

confidence: 99%

Biotransformation of Trastuzumab and Pertuzumab in Breast Cancer Patients Assessed by Affinity Enrichment and Ion-Exchange Chromatography

Olaleye

Spanov

Bults³

et al. 2022

Drug Metab Dispos

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“…This image representation can also be used to identify critical issues with the alignment. For example, when the similarity matrix after alignment contains highly dissimilar samples or groups of samples with low similarity scores, it suggests problems have occurred during the sample collection, sample preparation, or LC-MS/MS measurement, and thus the dissimilar chromatograms cannot be confidently processed with the rest of the data [35].…”

Section: Retention Time Alignmentmentioning

confidence: 99%

Pipelines and Systems for Threshold Avoiding Quantification of LC-MS/MS data

Horvatovich

Brotons

Eriksson

et al. 2021

Preprint

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The accurate processing of complex LC-MS/MS data from biological samples is a major challenge for metabolomics, proteomics and related approaches. Here we present the Pipelines and Systems for Threshold Avoiding Quantification (PASTAQ) LC-MS/MS pre-processing toolset, which allows highly accurate quantification of data-dependent acquisition (DDA) LC-MS/MS datasets. PASTAQ performs compound quantification using single-stage (MS1) data and implements novel algorithms for high-performance and accurate quantification, retention time alignment, feature detection, and linking annotations from multiple identification engines. PASTAQ offers straightforward parametrization and automatic generation of quality control plots for data and pre-processing assessment. This design results in smaller variance when analyzing replicates of proteomes mixed with known ratios, and allows the detection of peptides over a larger dynamic concentration range compared to widely used proteomics preprocessing tools. The performance of the pipeline is also demonstrated in a biological human serum dataset for the identification of gender related proteins.

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“…A survey of web-based methods is provided by Tohge & Fernie (2009). More recent web-based applications for metabolomics include the retention time alignment methods Warp2D (Ahmad et al, 2011) and ChromA (Hoffmann & Stoye, 2009), which are applicable to GC-MS or LC-MS data, and Chromaligner (Wang et al, 2010), which aligns GC and LC data with single-dimension detectors like FID.…”

Section: Introductionmentioning

confidence: 99%