Background: Soft tissue sarcomas (STSs) are rare, highly malignant mesenchymal tumours, comprising approximately 1% of all adult cancers and about 15% of paediatric solid tumours. STSs exhibit considerable genomic complexity with diverse subtypes, posing significant clinical challenges. Objectives: This study aims to characterise the molecular signature of primary STS through liquid biopsies and the untargeted metabolomic profiling of 75 patients, providing deep insights into cellular processes and potential therapeutic targets. Methods: This study analysed serum samples using nuclear magnetic resonance (NMR) spectroscopy for metabolomic profiling. Multivariate data analysis and machine learning classifiers were employed to identify biomarkers. Results: A panel of eleven significant deregulated metabolites were discovered in serum samples of patients with STS, with potential implications for cancer diagnosis and treatment. Conclusions: Choline decrease emerged as a marker for cancer progression, highlighting the potential of targeting its metabolism for therapeutic approaches in STS. The NMR analysis protocol proved effective for determining circulating biomarkers from liquid biopsies, making it suitable for rare disease research.
Untargeted Metabolomics and Liquid Biopsy Investigation of Circulating Biomarkers in Soft Tissue Sarcoma / Grasso D, Marzocchi B, Scoccianti G, Palchetti I, Campanacci DA, Antonuzzo L, Scolari F, Pillozzi S, Bernini A.. - In: CANCERS. - ISSN 2072-6694. - ELETTRONICO. - (2025), pp. 0-0.
Untargeted Metabolomics and Liquid Biopsy Investigation of Circulating Biomarkers in Soft Tissue Sarcoma
Marzocchi B;Scoccianti G;Palchetti I;Campanacci DA;Antonuzzo L;Scolari F;Pillozzi S;
2025
Abstract
Background: Soft tissue sarcomas (STSs) are rare, highly malignant mesenchymal tumours, comprising approximately 1% of all adult cancers and about 15% of paediatric solid tumours. STSs exhibit considerable genomic complexity with diverse subtypes, posing significant clinical challenges. Objectives: This study aims to characterise the molecular signature of primary STS through liquid biopsies and the untargeted metabolomic profiling of 75 patients, providing deep insights into cellular processes and potential therapeutic targets. Methods: This study analysed serum samples using nuclear magnetic resonance (NMR) spectroscopy for metabolomic profiling. Multivariate data analysis and machine learning classifiers were employed to identify biomarkers. Results: A panel of eleven significant deregulated metabolites were discovered in serum samples of patients with STS, with potential implications for cancer diagnosis and treatment. Conclusions: Choline decrease emerged as a marker for cancer progression, highlighting the potential of targeting its metabolism for therapeutic approaches in STS. The NMR analysis protocol proved effective for determining circulating biomarkers from liquid biopsies, making it suitable for rare disease research.| File | Dimensione | Formato | |
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