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Pediatric and AYA Sarcomas

(P 251) SPATIAL MULTI-OMIC ANALYSIS OF RHABDOMYOSARCOMA IDENTIFIES THERAPEUTIC VULNERABILITIES

    Author(s)

  • Katharine Offer, MD

    Assistant Professor of Pediatrics
    Department of Pediatrics, Hackensack Meridian School of Medicine, Hackensack Meridian Health
    Hackensack, New Jersey, United States

    • Co-Author(s)

  • AP

    Adele Ponzoni, PhD

    Center for Discovery and Innovation, Hackensack Meridian Health
    Nutley, New Jersey, United States

  • EL

    Evangelos Liapis, PhD

    Center for Discovery and Innovation, Hackensack Meridian Health
    Nutley, New Jersey, United States

  • CC

    Claire Carter, PhD

    Center for Discovery and Innovation, Department of Pathology, Hackensack Meridian School of Medicine
    Nutley, New Jersey, United States

Objective: Rhabdomyosarcoma (RMS) has FOXO1 fusion positive (FP) and fusion negative (FN) subtypes showing distinct clinical behavior and treatment responses. The spatial biology and metabolic heterogeneity of RMS remain poorly understood. We aimed to characterize RMS using spatial multi-omics to identify phenotypes and lipid pathways that offer potential as therapeutic targets.

Methods: Patient samples, including metastatic FP RMS and TP53 mutated localized FN RMS, were analyzed using mass spectrometry imaging (MSI), H&E staining, and multiplex immunohistochemistry (mIHC). MALDI MSI was carried out using a Solarix XR 7T FTICR mass spectrometer according to our previously published protocols. SCiLS Lab multi-vendor software, ver. 2023c Pro was used for co-registration of imaging data with corresponding H&E and molecular biology data.

Results: Glycosphingolipids, cardiolipins, phosphatidylinositol, and ceramide-1-phosphates were identified within distinct tumor cells. Cellular accumulation of each lipid class was structure-dependent based on the fatty acid residue composition. All data were correlated to histopathology, mIHC and Ki67 proliferation index. MALDI MSI revealed heterogeneous lipid distributions within FP and FN RMS samples. We identified global lipid changes in proliferating tumor cells regardless of the molecular subtype. We also detected subtype specific alterations, with FP RMS displaying distinct biochemical clusters relative to FN RMS. Of interest, gangliosides contributed to subtype-specific spatial profiles, with localized high-intensity signals observed within tumor cell regions of FN RMS.

Conclusion: Spatial multi-omic analysis of RMS identified heterogeneous lipid landscapes in association with cellular phenotypes. The structure-specific accumulation of these lipids within distinct tumor cell populations provide novel insights into RMS biology and identify potential therapeutic routes for investigation.