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On the Relevance of Soft Tissue Sarcomas Metabolic Landscape Mapping
Miguel Esperança-Martins1,2,3, Iola F Duarte4, Mara Rodrigues2
1Medical Oncology Department, Centro Hospitalar Universitário Lisboa Norte, 1649-028 Lisboa, Portugal.
Abstract:
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.
Insights
Soft tissue sarcomas (STS) lack personalized therapies due to limited understanding of their development. This review highlights metabolomics
Area of Science:
- Oncology
- Biochemistry
- Genomics
Background:
- Soft tissue sarcomas (STS) have a poor prognosis, with current treatments lacking personalization and failing to account for specific subtype and metabolic differences.
- The limited availability of precision therapies for STS is attributed to a scarcity of research into sarcomagenesis mechanisms.
- There is a critical need to enhance STS diagnostic accuracy, refine classification, and identify prognostic biomarkers.
Purpose of the Study:
- To review the application of omics technologies in soft tissue sarcomas.
- To analyze the metabolic landscape of STS through a detailed examination of existing studies.
- To underscore the potential of metabolomics in understanding and treating STS.
Main Methods:
- Comprehensive literature review of single-omics and multi-omics studies in STS.
- Analysis of metabolomics approaches including mass spectrometry (MS), MS imaging, and nuclear magnetic resonance (NMR) spectroscopy.
- Evaluation of emerging methods like advanced chromatography and flow cytometry for metabolic pathway analysis.
Main Results:
- Metabolomics offers unique insights into the metabolic adaptations supporting sarcomagenesis, whether as a standalone or integrated multi-omics approach.
- Current metabolomic characterization of STS is limited, but existing studies using MS and NMR have yielded valuable data.
- New analytical techniques promise to enable therapeutic targeting of metabolic pathways and monitoring of treatment response.
Conclusions:
- Omics studies, particularly metabolomics, are crucial for deciphering sarcomagenesis and improving STS diagnosis and classification.
- Further research into the STS metabolome is warranted to identify novel biomarkers and therapeutic targets.
- Advancements in metabolomic technologies will facilitate the development of personalized treatment strategies for STS.
