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

ABSTRACT

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.