Figure 4 from Clinical Implications and Molecular Features of Extracellular Matrix Networks in Soft Tissue Sarcomas

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posted on 2024-10-30, 14:40 authored by Valeriya Pankova, Lukas Krasny, William Kerrison, Yuen B. Tam, Madhumeeta Chadha, Jessica Burns, Christopher P. Wilding, Liang Chen, Avirup Chowdhury, Emma Perkins, Alexander T.J. Lee, Louise Howell, Nafia Guljar, Karen Sisley, Cyril Fisher, Priya Chudasama, Khin Thway, Robin L. Jones, Paul H. Huang

Identification, biological and clinical characterization of DDLPS subgroups. A, Heatmap showing the supervised clustering of 57 differentially expressed matrisome and adhesome proteins (DEPs) uniquely upregulated in each DDLPS subgroup. Black boxes indicate unique upregulated matrisome and adhesome DEPs in each of the subgroups. Bottom annotations indicate key tumor and patient characteristics. “*” Indicates that a clinical feature is significantly associated with DDLPS subgroups. B, Identities of upregulated matrisome and adhesome proteins in each DDLPS subgroup are shown on the right. Colored boxes on the right show functional pathways enriched in each DDLPS subgroup, as determined by overrepresentation analysis against the reactome pathway database. (C) Stacked bar charts showing the percentages of high and low CD3+, CD4+, and CD8+ TIL groups in each DDLPS subgroup. DDLPS cases were divided into high and low categories according to the median TILs score, separately for each stain. The χ2 test results are presented at the top of each plot. D, Significant (one-way ANOVA; FDR < 0.05) biological features obtained from ssGSEA of the MSigDB Hallmark gene sets. E, Kaplan–Meier plot of LRFS with stratification by DDLPS subgroups. Hazard ratio, 95% CI, and P-values were determined by univariate Cox regression with a two-sided Wald test.

Funding

Sarcoma UK (SUK)

Cancer Research UK (CRUK)

NIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer Research (BRC)

Royal Marsden Cancer Charity (The Royal Marsden Cancer Charity)

Institute of Cancer Research (ICR)

German Research Foundation

German Federal Ministry of Education

Sarcoma Foundation of America (SFA)

History

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DOI - Is supplement to Clinical Implications and Molecular Features of Extracellular Matrix Networks in Soft Tissue Sarcomas

ARTICLE ABSTRACT

The landscape of extracellular matrix (ECM) alterations in soft tissue sarcomas (STS) remains poorly characterized. We aimed to investigate the tumor ECM and adhesion signaling networks present in STS and their clinical implications. Proteomic and clinical data from 321 patients across 11 histological subtypes were analyzed to define ECM and integrin adhesion networks. Subgroup analysis was performed in leiomyosarcomas (LMS), dedifferentiated liposarcomas (DDLPS), and undifferentiated pleomorphic sarcomas (UPS). 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 coregulated ECM networks which are associated with tumor malignancy grade and histological subtype. Comparative analysis of LMS cell line and patient proteomic data identified the lymphocyte cytosolic protein 1 cytoskeletal protein as a prognostic factor in LMS. Characterization of ECM network events in DDLPS revealed three subtypes with distinct oncogenic signaling pathways and survival outcomes. Evaluation of the DDLPS subtype with the poorest prognosis nominates ECM remodeling proteins as candidate antistromal therapeutic targets. Finally, we define a proteoglycan signature that is an independent prognostic factor for overall survival in DDLPS and UPS. STS comprise heterogeneous ECM signaling networks and matrix-specific features that have utility for risk stratification and therapy selection, which could in future guide precision medicine in these rare cancers.