Clinical implications and molecular features of extracellular matrix networks in soft tissue sarcomas.

PURPOSE: The landscape of extracellular matrix (ECM) alterations in soft tissue sarcomas (STS) remains poorly characterised. We aimed to investigate the tumour ECM and adhesion signalling networks present in STS and their clinical implications. EXPERIMENTAL DESIGN: Proteomic and clinical data from 321 patients across 11 histological subtypes were analysed to define ECM and integrin adhesion networks. Subgroup analysis was performed in leiomyosarcomas (LMS), dedifferentiated liposarcomas (DDLPS) and undifferentiated pleiomorphic sarcomas (UPS). RESULTS: This analysis defined subtype-specific ECM profiles including enrichment of basement membrane proteins in LMS and ECM proteases in UPS. Across the cohort, we identified three distinct co-regulated ECM networks which are associated with tumour malignancy grade and histological subtype. Comparative analysis of LMS cell line and patient proteomic data identified the LCP1 cytoskeletal protein as a prognostic factor in LMS. Characterisation of ECM network events in DDLPS revealed three subtypes with distinct oncogenic signalling pathways and survival outcomes. Evaluation of the DDLPS subtype with the poorest prognosis nominates ECM remodelling proteins as candidate anti-stromal therapeutic targets. Finally, we define a proteoglycan signature which is an independent prognostic factor for overall survival in DDLPS and UPS. CONCLUSIONS: STS comprise heterogeneous ECM signalling networks and matrix-specific features have utility for risk stratification and therapy selection which could in future guide precision medicine in these rare cancers.

Proteomic features of soft tissue tumours in adolescents and young adults.

BACKGROUND: Adolescents and young adult (AYA) patients with soft tissue tumours including sarcomas are an underserved group with disparities in treatment outcomes. METHODS: To define the molecular features between AYA and older adult (OA) patients, we analysed the proteomic profiles of a large cohort of soft tissue tumours across 10 histological subtypes (AYA n = 66, OA n = 243), and also analysed publicly available functional genomic data from soft tissue tumour cell lines (AYA n = 5, OA n = 8). RESULTS: Biological hallmarks analysis demonstrates that OA tumours are significantly enriched in MYC targets compared to AYA tumours. By comparing the patient-level proteomic data with functional genomic profiles from sarcoma cell lines, we show that the mRNA splicing pathway is an intrinsic vulnerability in cell lines from OA patients and that components of the spliceosome complex are independent prognostic factors for metastasis free survival in AYA patients. CONCLUSIONS: Our study highlights the importance of performing age-specific molecular profiling studies to identify risk stratification tools and targeted agents tailored for the clinical management of AYA patients.

Soft tissue tumours are cancers that develop in the connective and supporting tissues of the body, such as muscle or fat. These tumours arise in patients across the entire age range. However, improvements in survival outcomes in adolescent and young adult (AYA) patients have lagged behind outcomes in older adults (OA) and children. To better understand the biology of AYA patients with soft tissue tumours, we analysed protein profiles across 10 different types. We identified biological differences between AYA and OA patients and report an age-specific signature that can potentially be used to help predict which AYA patients are more likely to have aggressive cancers that will spread to other parts of the body. Our study highlights the importance of performing age-specific studies to identify new tools to predict patient outcomes and potentially find more suitable treatments.

The proteomic landscape of soft tissue sarcomas.

Soft tissue sarcomas (STS) are rare and diverse mesenchymal cancers with limited treatment options. Here we undertake comprehensive proteomic profiling of tumour specimens from 321 STS patients representing 11 histological subtypes. Within leiomyosarcomas, we identify three proteomic subtypes with distinct myogenesis and immune features, anatomical site distribution and survival outcomes. Characterisation of undifferentiated pleomorphic sarcomas and dedifferentiated liposarcomas with low infiltrating CD3 + T-lymphocyte levels nominates the complement cascade as a candidate immunotherapeutic target. Comparative analysis of proteomic and transcriptomic profiles highlights the proteomic-specific features for optimal risk stratification in angiosarcomas. Finally, we define functional signatures termed Sarcoma Proteomic Modules which transcend histological subtype classification and show that a vesicle transport protein signature is an independent prognostic factor for distant metastasis. Our study highlights the utility of proteomics for identifying molecular subgroups with implications for risk stratification and therapy selection and provides a rich resource for future sarcoma research.

Proteomic and Metabolomic Profiling in Soft Tissue Sarcomas.

OPINION STATEMENT: Advances in proteomic and metabolomic technologies have accelerated our understanding of multiple aspects of cancer biology across distinct tumour types. Here we review the current state-of-the-art in the use of proteomics and metabolomics in soft tissue sarcomas. We highlight the utility of these Omics-based methodologies to identify new drug targets, synthetic lethal interactions, candidate therapeutics and novel biomarkers to facilitate patient stratification. Due to the unbiased and global nature of these profiling methods to assess the levels of protein expression, post-translational modifications such as phosphorylation and glycosylation as well as key metabolites, many of these findings have broad applications not just in specific histotypes but across multiple STS subtypes. Specific examples of proteomic and metabolomic findings that have led to the development of early phase clinical trials of investigational agents will be discussed. While promising, the use of these technologies in the study of sarcoma is still limited, and there is a need for further research in this area. In particular, it would be important to integrate these approaches with other Omics strategies such as genomics and epigenomics as well as implement these tools alongside clinical trials in order to maximize the impact of these tools on our biological understanding and treatment of this group of rare diseases of unmet need.