Key result
Quantitative mass spectrometry-based proteomics has the potential to address unmet clinical needs in sarcoma by aiding diagnosis, improving disease classification, and identifying novel biomarkers.
Why the study?
Sarcoma clinical management faces challenges including diagnostic uncertainties, limited biomarkers, heterogeneity, and lack of effective treatments, which sarcoma proteomics has the potential to address.
Quantitative proteomics has the potential to address unmet clinical needs in sarcoma by aiding diagnosis, improving disease classification, and identifying prognostic and therapeutic biomarkers.
May support proteomics for sarcoma diagnostics and biomarkers; leaves open prospective validation before clinical adoption.
Sarcoma is a rare and complex disease comprising over 80 malignant subtypes that is frequently characterized by poor prognosis. Challenges in clinical management include uncertainties in diagnosis and disease classification, limited prognostic and predictive biomarkers, incompletely understood disease heterogeneity among and within subtypes, lack of effective treatment options, and limited progress in identifying new drug targets and novel therapeutics. Proteomics refers to the study of the entire complement of proteins expressed in specific cells or tissues. Advances in proteomics have included the development of quantitative mass spectrometry (MS)-based technologies which enable analysis of large numbers of proteins with relatively high throughput, enabling proteomics to be studied on a scale that has not previously been possible. Cellular function is determined by the levels of various proteins and their interactions, so proteomics offers the possibility of new insights into cancer biology. Sarcoma proteomics therefore has the potential to address some of the key current challenges described above, but it is still in its infancy. This review covers key quantitative proteomic sarcoma studies with findings that pertain to clinical utility. Proteomic methodologies that have been applied to human sarcoma research are briefly described, including recent advances in MS-based proteomic technology. We highlight studies that illustrate how proteomics may aid diagnosis and improve disease classification by distinguishing sarcoma histologies and identify distinct profiles within histological subtypes which may aid understanding of disease heterogeneity. We also review studies where proteomics has been applied to identify prognostic, predictive and therapeutic biomarkers. These studies traverse a range of histological subtypes including chordoma, Ewing sarcoma, gastrointestinal stromal tumors, leiomyosarcoma, liposarcoma, malignant peripheral nerve sheath tumors, myxofibrosarcoma, rhabdomyosarcoma, synovial sarcoma, osteosarcoma, and undifferentiated pleomorphic sarcoma. Critical questions and unmet needs in sarcoma which can potentially be addressed with proteomics are outlined.
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Connolly et al. (2023) conducted a review in Sarcoma. Quantitative proteomics was evaluated. Quantitative mass spectrometry-based proteomics has the potential to address unmet clinical needs in sarcoma by aiding diagnosis, improving disease classification, and identifying novel biomarkers.
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