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Cisplatin resistance in cell models: evaluation of metallomic and biological predictive biomarkers to address early therapy failure

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Abstract

Cisplatin, one of the most extensively used metallodrugs in cancer treatment, presents the important drawback of patient resistance. This resistance is the consequence of different processes including those preventing the formation of DNA adducts and/or their quick removal. Thus, a tool for the accurate detection and quantitation of cisplatin-induced adducts might be valuable for predicting patient resistance. To prove the validity of such an assumption, highly sensitive plasma mass spectrometry (ICP-MS) strategies were applied to determine DNA adduct levels and intracellular Pt concentrations. These two metal-relative parameters were combined with an evaluation of biological responses in terms of genomic stability (with the Comet assay) and cell cycle progression (by flow cytometry) in four human cell lines of different origins and cisplatin sensitivities (A549, GM04312, A2780 and A2780cis), treated with low cisplatin doses (5, 10 and 20 μM for 3 hours). Cell viability and apoptosis were determined as resistance indicators. Univariate linear regression analyses indicated that quantitation of cisplatin-induced G–G intra-strand adducts, measured 1 h after treatment, was the best predictor for viability and apoptosis in all of the cell lines. Multivariate linear regression analyses revealed that the prediction improved when the intracellular Pt content or the Comet data were included in the analysis, for all sensitive cell lines and for the A2780 and A2780cis cell lines, respectively. Thus, a reliable cisplatin resistance predictive model, which combines the quantitation of adducts by HPLC-ICP-MS, and their repair, with the intracellular Pt content and induced genomic instability, might be essential to identify early therapy failure.

Graphical abstract: Cisplatin resistance in cell models: evaluation of metallomic and biological predictive biomarkers to address early therapy failure

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Publication details

The article was received on 19 Jan 2017, accepted on 07 Apr 2017 and first published on 10 Apr 2017


Article type: Paper
DOI: 10.1039/C7MT00014F
Citation: Metallomics, 2017, Advance Article
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    Cisplatin resistance in cell models: evaluation of metallomic and biological predictive biomarkers to address early therapy failure

    M. Espina, M. Corte-Rodríguez, L. Aguado, M. Montes-Bayón, M. I. Sierra, P. Martínez-Camblor, E. Blanco-González and L. M. Sierra, Metallomics, 2017, Advance Article , DOI: 10.1039/C7MT00014F

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