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Dataset describing the development, optimization and application of SRM/MRM based targeted proteomics strategy for quantification of potential biomarkers of EGFR TKI sensitivity.

ABSTRACT: The data presented here describes the use of targeted proteomic assays to quantify potential biomarkers of Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) sensitivity in lung adenocarcinoma and is related to the research article: "Quantitative targeted proteomic analysis of potential markers of tyrosine kinase inhibitor (TKI) sensitivity in EGFR mutated lung adenocarcinoma" [1]. This article describes the data associated with liquid chromatography coupled to multiple reaction monitoring (LC-MRM) method development which includes selection of an optimal transition list, retention time prediction and building of reverse calibration curves. Sample preparation and optimization which includes phosphotyrosine peptide enrichment via a combination of pan-phosphotyrosine antibodies is described. The dataset also consists of figures, tables and Excel files describing the quantitative results of testing these optimized methods in two lung adenocarcinoma cell lines with EGFR mutations.

SUBMITTER: Awasthi S

PROVIDER: S-EPMC5997585 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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Dataset describing the development, optimization and application of SRM/MRM based targeted proteomics strategy for quantification of potential biomarkers of EGFR TKI sensitivity.

Awasthi Shivangi S Maity Tapan T Oyler Benjamin L BL Zhang Xu X Goodlett David R DR Guha Udayan U

Data in brief 20180502

The data presented here describes the use of targeted proteomic assays to quantify potential biomarkers of Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) sensitivity in lung adenocarcinoma and is related to the research article: "Quantitative targeted proteomic analysis of potential markers of tyrosine kinase inhibitor (TKI) sensitivity in EGFR mutated lung adenocarcinoma" [1]. This article describes the data associated with liquid chromatography coupled to multiple reac ...[more]

PMID: 29900338

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Project description:Enhanced in-source fragmentation/annotation (EISA) has recently been shown to produce fragment ions that match tandem mass spectrometry data across a wide range of small molecules. EISA has been developed to facilitate data-dependent acquisition (DDA), data-independent acquisiton (DIA), and multiple-reaction monitoring (MRM), enabling molecular identifications in untargeted metabolomics and targeted quantitative single-quadrupole MRM (Q-MRM) analyses. Here, EISA has been applied to peptide-based proteomic analysis using optimized in-source fragmentation to generate fragmentation patterns for a mixture of 38 peptides, which were comparable to the b- and y-type fragment ions typically observed in tandem MS experiments. The optimal in-source fragmentation conditions at which high-abundance peptide fragments and precursor ions coexist were compared with automated data-dependent acquisition (DDA) in the same quadrupole time-of-flight (QTOF-MS) mass spectrometer, generating a significantly higher fragment percentage of peptides from both singly and doubly charged b- and y-type fragment (b+, y+, b2+, and y2+) ions. Higher fragment percentages were also observed for these fragment ion series over linear ion trap instrumentation. An XCMS-EISA annotation/deconvolution program was developed, making use of the retention time and peak shape continuity between precursor fragment ions, to perform automated proteomic data analysis on the enhanced in-source fragments. Post-translational modification (PTM) characterization on peptides was demonstrated with EISA, producing fragment ions corresponding to a neutral loss of phosphoric acid with greater intensity than observed with DDA on a QTOF-MS. Moreover, Q-MRM demonstrated the ability to use EISA for peptide quantification. The availability of more sophisticated in-source fragmentation informatics, beyond XCMS-EISA, will further enable EISA for sensitive autonomous identification and Q-MRM quantitative analyses in proteomics.

Project description:PurposeWe aimed to evaluate whether the addition of pemetrexed is effective in improving progression-free survival (PFS) in epidermal growth factor receptor (EGFR)-mutated patients with or without concomitant alterations.Materials and methodsThis multicenter clinical trial was conducted in China from June 15, 2018, to May 31, 2019. A total of 92 non-small cell lung cancer (NSCLC) patients harboring EGFR-sensitive mutations were included and divided into concomitant and non-concomitant groups. Patients in each group were randomly treated with EGFR-tyrosine kinase inhibitor (TKI) monotherapy or EGFR-TKI combined with pemetrexed in a ratio of 1:1. PFS was recorded as the primary endpoint.ResultsThe overall median PFS of this cohort was 10.1 months. There were no significant differences in PFS between patients with and without concomitant and between patients received TKI monotherapy and TKI combined with pemetrexed (p=0.210 and p=0.085, respectively). Stratification analysis indicated that patients received TKI monotherapy had a significantly longer PFS in non-concomitant group than that in concomitant group (p=0.002). In concomitant group, patients received TKI combined with pemetrexed had a significantly longer PFS than patients received TKI monotherapy (p=0.013). Molecular dynamic analysis showed rapidly emerging EGFR T790M in patients received TKI monotherapy. EGFR mutation abundance decreased in patients received TKI combined chemotherapy, which supports better efficacy for a TKI combined chemotherapy as compared to TKI monotherapy. A good correlation between therapeutic efficacy and a change in circulating tumor DNA (ctDNA) status was found in 66% of patients, supporting the guiding role of ctDNA minimal residual disease (MRD) in NSCLC treatment.ConclusionEGFR-TKI monotherapy is applicable to EGFR-sensitive patients without concomitant alterations, while a TKI combined chemotherapy is applicable to EGFR-sensitive patients with concomitant alterations. CtDNA MRD may be a potential biomarker for predicting therapeutic efficacy.

Dataset Information

Dataset describing the development, optimization and application of SRM/MRM based targeted proteomics strategy for quantification of potential biomarkers of EGFR TKI sensitivity.

Publications

Dataset describing the development, optimization and application of SRM/MRM based targeted proteomics strategy for quantification of potential biomarkers of EGFR TKI sensitivity.

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