(P 07) A LIVING MULTI-OMICS BIOBANK OF PATIENT-DERIVED XENOGRAFT MODELS FOR SARCOMA

Objective: Sarcomas are rare and highly heterogeneous malignancies with poor prognosis and limited reliable preclinical models. Patient-derived xenograft (PDX) models provide an effective tool to study tumor biology and evaluate therapeutic strategies. We aimed to establish a large, clinically annotated sarcoma PDX biobank with integrated genomic and transcriptomic profiling to uncover key molecular characteristics.

Methods: Fresh tumor samples from sarcoma patients at Shanghai General Hospital were subcutaneously implanted into NOD scid gamma (NSG) mice to generate PDX models. Genomic and transcriptomic sequencing were performed on both PDXs and matched patient tumors. Histopathological and molecular concordance were evaluated, and actionable genomic alterations were annotated using the OncoKB knowledge base.

Results: Between 2014 and 2024, we successfully established 155 PDX models encompassing 11 sarcoma subtypes. Successful engraftment was associated with poorer prognosis, more aggressive clinical features, higher TP53 mutation rates, and elevated tumor mutational burden. PDXs preserved high morphological fidelity and demonstrated strong concordance with the corresponding patient tumors in gene expression, copy number alterations, and DNA methylation profiles. Compared with patient tumors, PDXs exhibited higher tumor purity but reduced stromal and immune cell components. Recurrent driver alterations, including TP53 mutations, MYC gain/amplification, and complex structural variants, were frequently observed, particularly in osteosarcoma. Canonical disease-specific fusion genes (e.g., SS18–SSX in synovial sarcoma, EWSR1–FLI1 in Ewing sarcoma) were consistently identified in both PDXs and matched patient samples, whereas noncanonical fusions showed lower concordance. Multi-passage sequencing confirmed genomic stability across serial passages, and 52% of models harbored potentially actionable alterations within the cohort. Additionally, clonal evolution analysis indicated that most PDXs followed a linear evolutionary trajectory compared with their original patient tumors.

Conclusion: To our knowledge, this represents the largest multi-omics–annotated sarcoma PDX biobank derived from a Chinese population, faithfully recapitulating patient tumors at both histological and molecular levels. This resource provides a robust platform for translational research in sarcoma.