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

Pankova, V.
Krasny, L.
Kerrison, W.
Tam, Y. B.
Chadha, M.
Burns, J.
Wilding, C. P.
Chen, L.
Chowdhury, A.
Perkins, E.
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Abstract
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.
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2024
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Pankova V, Krasny L, Kerrison W, Tam YB, Chadha M, Burns J, et al. Clinical implications and molecular features of extracellular matrix networks in soft tissue sarcomas. Clinical cancer research : an official journal of the American Association for Cancer Research. 2024 May 29. PubMed PMID: 38810090. Epub 2024/05/29. eng.
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