Quantitative mass spectrometry imaging reveals mutation status-independent lack of imatinib in liver metastases of gastrointestinal stromal tumors

• Verfasst von: Abu Sammour, Denis [VerfasserIn]
• Verfasst von: Marsching, Christian [VerfasserIn]
• Verfasst von: Geisel, Alexander [VerfasserIn]
• Verfasst von: Erich, Katrin [VerfasserIn]
• Verfasst von: Schulz, Sandra [VerfasserIn]
• Verfasst von: Ramallo Guevara, Carina [VerfasserIn]
• Verfasst von: Rabe, Jan-Hinrich [VerfasserIn]
• Verfasst von: Marx, Alexander [VerfasserIn]
• Verfasst von: Findeisen, Peter [VerfasserIn]
• Verfasst von: Hohenberger, Peter [VerfasserIn]
• Verfasst von: Hopf, Carsten [VerfasserIn]
• Titel: Quantitative mass spectrometry imaging reveals mutation status-independent lack of imatinib in liver metastases of gastrointestinal stromal tumors
• Verf.angabe: Denis Abu Sammour, Christian Marsching, Alexander Geisel, Katrin Erich, Sandra Schulz, Carina Ramallo Guevara, Jan-Hinrich Rabe, Alexander Marx, Peter Findeisen, Peter Hohenberger & Carsten Hopf
• E-Jahr: 2019
• Jahr: 23 July 2019
• Umfang: 9 S.
• Fussnoten: Gesehen am 11.12.2019
• Titel Quelle: Enthalten in: Scientific reports
• Ort Quelle: [London] : Springer Nature, 2011
• Jahr Quelle: 2019
• Band/Heft Quelle: 9(2019) Artikel-Nummer 10698, 9 Seiten
• ISSN Quelle: 2045-2322
• DOI: doi:10.1038/s41598-019-47089-5
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1685166202

Abstract

Mass spectrometry imaging (MSI) is an enabling technology for label-free drug disposition studies at high spatial resolution in life science- and pharmaceutical research. We present the first extensive clinical matrix-assisted laser desorption/ionization (MALDI) quantitative mass spectrometry imaging (qMSI) study of drug uptake and distribution in clinical specimen, analyzing 56 specimens of tumor and corresponding non-tumor tissues from 27 imatinib-treated patients with the biopsy-proven rare disease gastrointestinal stromal tumors (GIST). For validation, we compared MALDI-TOF-qMSI with conventional UPLC-ESI-QTOF-MS-based quantification from tissue extracts and with ultra-high resolution MALDI-FTICR-qMSI. We introduced a novel generalized nonlinear calibration model of drug quantities based on computational evaluation of drug-containing areas that enabled better data fitting and assessment of the inherent method nonlinearities. Imatinib tissue spatial maps revealed striking inefficiency in drug penetration into GIST liver metastases even though the corresponding healthy liver tissues in the vicinity showed abundant imatinib levels beyond the limit of quantification (LOQ), thus providing evidence for secondary drug resistance independent of mutation status. Taken together, these findings underscore the important application of MALDI-qMSI in studying the spatial distribution of molecularly targeted therapeutics in oncology, namely to serve as orthogonal post-surgical approach to evaluate the contribution of anticancer drug disposition to resistance against treatment.