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Lookup NU author(s): Dr Daniel WilliamsonORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2023, The Author(s). 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.
Author(s): Burns J, Wilding CP, Krasny L, Zhu X, Chadha M, Tam YB, Ps H, Mahalingam AH, Lee ATJ, Arthur A, Guljar N, Perkins E, Pankova V, Jenks A, Djabatey V, Szecsei C, McCarthy F, Ragulan C, Milighetti M, Roumeliotis TI, Crosier S, Finetti M, Choudhary JS, Judson I, Fisher C, Schuster EF, Sadanandam A, Chen TW, Williamson D, Thway K, Jones RL, Cheang MCU, Huang PH
Publication type: Article
Publication status: Published
Journal: Nature Communications
Year: 2023
Volume: 14
Online publication date: 29/06/2023
Acceptance date: 15/06/2023
Date deposited: 19/02/2025
ISSN (electronic): 2041-1723
Publisher: Nature Research
URL: https://doi.org/10.1038/s41467-023-39486-2
DOI: 10.1038/s41467-023-39486-2
Data Access Statement: The raw proteomic data generated in this study have been deposited in the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD036226. The raw transcriptomic data are deposited at the European Genome-phenome Archive (EGA), which is hosted by the EBI and the CRG, under accession number EGAD00001010839. To protect patient privacy, as required by law, access to the raw transcriptomic data deposited in the EGA is controlled by the Data Access Committee (DAC) of the Institute of Cancer Research. All researchers can obtain access by submitting a project proposal to the DAC by contacting the corresponding author (P.H.H.). [See article for the remainder of the full data availability statement.]
PubMed id: 37386008
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