title: Prognostic Metabolite Biomarkers for Soft Tissue Sarcomas Discovered by Mass Spectrometry Imaging.
abstract: Metabolites can be an important read-out of disease. The identification and validation of biomarkers in the cancer metabolome that can stratify high-risk patients is one of the main current research aspects. Mass spectrometry has become the technique of choice for metabolomics studies, and mass spectrometry imaging (MSI) enables their visualization in patient tissues. In this study, we used MSI to identify prognostic metabolite biomarkers in high grade sarcomas; 33 high grade sarcoma patients, comprising osteosarcoma, leiomyosarcoma, myxofibrosarcoma, and undifferentiated pleomorphic sarcoma were analyzed. Metabolite MSI data were obtained from sections of fresh frozen tissue specimens with matrix-assisted laser/desorption ionization (MALDI) MSI in negative polarity using 9-aminoarcridine as matrix. Subsequent annotation of tumor regions by expert pathologists resulted in tumor-specific metabolite signatures, which were then tested for association with patient survival. Metabolite signals with significant clinical value were further validated and identified by high mass resolution Fourier transform ion cyclotron resonance (FTICR) MSI. Three metabolite signals were found to correlate with overall survival (m/z 180.9436 and 241.0118) and metastasis-free survival (m/z 160.8417). FTICR-MSI identified m/z 241.0118 as inositol cyclic phosphate and m/z 160.8417 as carnitine. Graphical Abstract ᅟ.
authors.affiliation: Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands.
authors.forename: Sha
authors.initials: S
authors.lastname: Lou
authors.affiliation: Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands.|Maastricht MultiModal Molecular Imaging institute (M4I), Maastricht University, Maastricht, The Netherlands.
authors.forename: Benjamin
authors.initials: B
authors.lastname: Balluff
authors.affiliation: Department of Pathology, Leiden University Medical Center, Leiden, The Netherlands.
authors.forename: Arjen H G
authors.initials: AHG
authors.lastname: Cleven
authors.affiliation: Department of Pathology, Leiden University Medical Center, Leiden, The Netherlands.
authors.forename: Judith V M G
authors.initials: JVMG
authors.lastname: Bovée
authors.affiliation: Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands. L.A.Mcdonnell@lumc.nl.|Department of Pathology, Leiden University Medical Center, Leiden, The Netherlands. L.A.Mcdonnell@lumc.nl.|Fondazione Pisana per la Scienza ONLUS, Pisa, Italy. L.A.Mcdonnell@lumc.nl.
authors.forename: Liam A
authors.initials: LA
authors.lastname: McDonnell
mesh_terms: D000368:Aged; D014408:Biomarkers, Tumor / Q000032:analysis / Q000378:metabolism*; D005260:Female; D005583:Fourier Analysis; D006801:Humans; D008297:Male; D055442:Metabolome; D055432:Metabolomics / Q000379:methods; D008875:Middle Aged; D011379:Prognosis; D012509:Sarcoma / Q000000981:diagnostic imaging* / Q000378:metabolism* / Q000401:mortality; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization / Q000379:methods*; D016019:Survival Analysis; D057188:Workflow
chemical_list: D014408:Biomarkers, Tumor
keywords: Biomarker discovery; High grade sarcoma; Leiomyosarcoma; MALDI-MSI; Metabolites; Myxofibrosarcoma; Osteosarcoma; Prognosis; Soft tissue sarcoma; Undifferentiated pleomorphic sarcoma