PURPOSE: To study cancer associated with abnormal metabolism of phospholipids, of which several have been proposed as biomarkers for malignancy or to monitor response to anticancer therapy. We explored 3D (31) P magnetic resonance spectroscopic imaging (MRSI) at high magnetic field for in vivo assessment of individual phospholipids in two patient-derived breast cancer xenografts representing good and poor prognosis (luminal- and basal-like tumors). MATERIALS AND METHODS: Metabolic profiles from luminal-like and basal-like xenograft tumors were obtained in vivo using 3D (31) P MRSI at 11.7T and from tissue extracts in vitro at 14.1T. Gene expression analysis was performed in order to support metabolic differences between the two xenografts. RESULTS: In vivo (31) P MR spectra were obtained in which the prominent resonances from phospholipid metabolites were detected at a high signal-to-noise ratio (SNR >7.5). Metabolic profiles obtained in vivo were in agreement with those obtained in vitro and could be used to discriminate between the two xenograft models, based on the levels of phosphocholine, phosphoethanolamine, glycerophosphocholine, and glycerophosphoethanolamine. The differences in phospholipid metabolite concentration could partly be explained by gene expression profiles. CONCLUSION: Noninvasive metabolic profiling by 3D (31) P MRSI can discriminate between subtypes of breast cancer based on different concentrations of choline- and ethanolamine-containing phospholipids.
PURPOSE: To study cancer associated with abnormal metabolism of phospholipids, of which several have been proposed as biomarkers for malignancy or to monitor response to anticancer therapy. We explored 3D (31) P magnetic resonance spectroscopic imaging (MRSI) at high magnetic field for in vivo assessment of individual phospholipids in two patient-derived breast cancer xenografts representing good and poor prognosis (luminal- and basal-like tumors). MATERIALS AND METHODS: Metabolic profiles from luminal-like and basal-like xenograft tumors were obtained in vivo using 3D (31) P MRSI at 11.7T and from tissue extracts in vitro at 14.1T. Gene expression analysis was performed in order to support metabolic differences between the two xenografts. RESULTS: In vivo (31) P MR spectra were obtained in which the prominent resonances from phospholipid metabolites were detected at a high signal-to-noise ratio (SNR >7.5). Metabolic profiles obtained in vivo were in agreement with those obtained in vitro and could be used to discriminate between the two xenograft models, based on the levels of phosphocholine, phosphoethanolamine, glycerophosphocholine, and glycerophosphoethanolamine. The differences in phospholipid metabolite concentration could partly be explained by gene expression profiles. CONCLUSION: Noninvasive metabolic profiling by 3D (31) P MRSI can discriminate between subtypes of breast cancer based on different concentrations of choline- and ethanolamine-containing phospholipids.
Authors: Annette T Byrne; Denis G Alférez; Frédéric Amant; Daniela Annibali; Joaquín Arribas; Andrew V Biankin; Alejandra Bruna; Eva Budinská; Carlos Caldas; David K Chang; Robert B Clarke; Hans Clevers; George Coukos; Virginie Dangles-Marie; S Gail Eckhardt; Eva Gonzalez-Suarez; Els Hermans; Manuel Hidalgo; Monika A Jarzabek; Steven de Jong; Jos Jonkers; Kristel Kemper; Luisa Lanfrancone; Gunhild Mari Mælandsmo; Elisabetta Marangoni; Jean-Christophe Marine; Enzo Medico; Jens Henrik Norum; Héctor G Palmer; Daniel S Peeper; Pier Giuseppe Pelicci; Alejandro Piris-Gimenez; Sergio Roman-Roman; Oscar M Rueda; Joan Seoane; Violeta Serra; Laura Soucek; Dominique Vanhecke; Alberto Villanueva; Emilie Vinolo; Andrea Bertotti; Livio Trusolino Journal: Nat Rev Cancer Date: 2017-01-20 Impact factor: 60.716
Authors: Michael J Burns; Peter J Rayner; Gary G R Green; Louise A R Highton; Ryan E Mewis; Simon B Duckett Journal: J Phys Chem B Date: 2015-04-06 Impact factor: 2.991
Authors: Erwin Krikken; Wybe J M van der Kemp; Paul J van Diest; Thijs van Dalen; Hanneke W M van Laarhoven; Peter R Luijten; Dennis W J Klomp; Jannie P Wijnen Journal: NMR Biomed Date: 2019-03-29 Impact factor: 4.044