On the Relevance of Soft Tissue Sarcomas Metabolic Landscape Mapping

Soft tissue sarcomas (STS) prognosis is disappointing, with current treatment strategies being based on a fit for all principle and not taking distinct sarcoma subtypes specificities and genetic/metabolic differences into consideration. The paucity of precision therapies in STS reflects the shortage of studies that seek to decipher the sarcomagenesis mechanisms. There is an urge to improve STS diagnosis precision, refine STS classification criteria, and increase the capability of identifying STS prognostic biomarkers. Single-omics and multi-omics studies may play a key role on decodifying sarcomagenesis. Metabolomics provides a singular insight, either as a single-omics approach or as part of a multi-omics strategy, into the metabolic adaptations that support sarcomagenesis. Although STS metabolome is scarcely characterized, untargeted and targeted metabolomics approaches employing different data acquisition methods such as mass spectrometry (MS), MS imaging, and nuclear magnetic resonance (NMR) spectroscopy provided important information, warranting further studies. New chromatographic, MS, NMR-based, and flow cytometry-based methods will offer opportunities to therapeutically target metabolic pathways and to monitorize the response to such metabolic targeting therapies. Here we provide a comprehensive review of STS omics applications, comprising a detailed analysis of studies focused on the metabolic landscape of these tumors.

Automated summary

The prognosis of soft tissue sarcomas (STS) is disappointing due to the lack of individualized treatment strategies and the neglect of specificities and genetic/metabolic differences among sarcoma subtypes. There is a need for more studies to decipher the mechanisms of sarcomagenesis, improve STS diagnosis precision, refine STS classification criteria, and identify prognostic biomarkers. Metabolomics, either as a single-omics approach or as part of a multi-omics strategy, provides valuable insights into the metabolic adaptations that support sarcomagenesis. Further studies employing various data acquisition methods have provided important information for the characterization of the STS metabolome. New methods based on chromatography, mass spectrometry (MS), nuclear magnetic resonance (NMR) spectroscopy, and flow cytometry will offer opportunities to target metabolic pathways therapeutically and monitor the response to such therapies.