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Keywords = non-cutaneous angiosarcomas

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13 pages, 1293 KB  
Article
Integration of an OS-Based Machine Learning Score (AS Score) and Immunoscore as Ancillary Tools for Predicting Immunotherapy Response in Sarcomas
by Isidro Machado, Raquel López-Reig, Eduardo Giner, Antonio Fernández-Serra, Celia Requena, Beatriz Llombart, Francisco Giner, Julia Cruz, Victor Traves, Javier Lavernia, Antonio Llombart-Bosch and José Antonio López Guerrero
Cancers 2025, 17(15), 2551; https://doi.org/10.3390/cancers17152551 - 1 Aug 2025
Cited by 1 | Viewed by 944
Abstract
Background: Angiosarcomas (ASs) represent a heterogeneous and highly aggressive subset of tumors that respond poorly to systemic treatments and are associated with short progression-free survival (PFS) and overall survival (OS). The aim of this study was to develop and validate an immune-related [...] Read more.
Background: Angiosarcomas (ASs) represent a heterogeneous and highly aggressive subset of tumors that respond poorly to systemic treatments and are associated with short progression-free survival (PFS) and overall survival (OS). The aim of this study was to develop and validate an immune-related prognostic model—termed the AS score—using data from two independent sarcoma cohorts. Methods: A prognostic model was developed using a previously characterized cohort of 25 angiosarcoma samples. Candidate genes were identified via the Maxstat algorithm (Maxstat v0.7-25 for R), combined with log-rank testing. The AS score was then computed by weighing normalized gene expression levels according to Cox regression coefficients. For external validation, transcriptomic data from TCGA Sarcoma cohort (n = 253) were analyzed. The Immunoscore—which reflects the tumor immune microenvironment—was inferred using the ESTIMATE package (v1.0.13) in R. All statistical analyses were performed in RStudio (v 4.0.3). Results: Four genes—IGF1R, MAP2K1, SERPINE1, and TCF12—were ultimately selected to construct the prognostic model. The resulting AS score enabled the classification of angiosarcoma cases into two prognostically distinct groups (p = 0.00012). Cases with high AS score values, which included both cutaneous and non-cutaneous forms, exhibited significantly poorer outcomes, whereas cases with low AS scores were predominantly cutaneous. A significant association was observed between the AS score and the Immunoscore (p = 0.025), with higher Immunoscore values found in high-AS score tumors. Validation using TCGA sarcoma cohort confirmed the prognostic value of both the AS score (p = 0.0066) and the Immunoscore (p = 0.0029), with a strong correlation between their continuous values (p = 2.9 × 10−8). Further survival analysis, integrating categorized scores into four groups, demonstrated robust prognostic significance (p = 0.00021). Notably, in tumors with a low Immunoscore, AS score stratification was not prognostic. In contrast, among cases with a high Immunoscore, the AS score effectively distinguished outcomes (p < 0.0001), identifying a subgroup with poor prognosis but potential sensitivity to immunotherapy. Conclusions: This combined classification using the AS score and Immunoscore has prognostic relevance in sarcoma, suggesting that angiosarcomas with an immunologically active microenvironment (high Immunoscore) and poor prognosis (high AS score) may be prime candidates for immunotherapy and this approach warrants prospective validation. Full article
(This article belongs to the Special Issue Genomics and Transcriptomics in Sarcoma)
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14 pages, 2685 KB  
Article
Genomic Landscape Comparison of Cardiac versus Extra-Cardiac Angiosarcomas
by Livia Gozzellino, Margherita Nannini, Milena Urbini, Carmine Pizzi, Ornella Leone, Barbara Corti, Chiara Baldovini, Francesco Angeli, Alberto Foà, Davide Pacini, Gianluca Folesani, Alice Costa, Teresa Palumbo, Maria Concetta Nigro, Gianandrea Pasquinelli, Annalisa Astolfi and Maria Abbondanza Pantaleo
Biomedicines 2023, 11(12), 3290; https://doi.org/10.3390/biomedicines11123290 - 12 Dec 2023
Cited by 2 | Viewed by 2536
Abstract
Angiosarcomas (ASs) are rare malignant vascular entities that can affect several regions in our body, including the heart. Cardiac ASs comprise 25–40% of cardiac sarcomas and can cause death within months of diagnosis. Thus, our aim was to identify potential differences and/or similarities [...] Read more.
Angiosarcomas (ASs) are rare malignant vascular entities that can affect several regions in our body, including the heart. Cardiac ASs comprise 25–40% of cardiac sarcomas and can cause death within months of diagnosis. Thus, our aim was to identify potential differences and/or similarities between cardiac and extra-cardiac ASs to enhance targeted therapies and, consequently, patients’ prognosis. Whole-transcriptome analysis of three cardiac and eleven extra-cardiac non-cutaneous samples was performed to investigate differential gene expression and mutational events between the two groups. The gene signature of cardiac and extra-cardiac non-cutaneous ASs was also compared to that of cutaneous angiosarcomas (n = 9). H/N/K-RAS and TP53 alterations were more recurrent in extra-cardiac ASs, while POTE-gene family overexpression was peculiar to cardiac ASs. Additionally, in vitro functional analyses showed that POTEH upregulation conferred a growth advantage to recipient cells, partly supporting the cardiac AS aggressive phenotype and patients’ scarce survival rate. These features should be considered when investigating alternative treatments. Full article
(This article belongs to the Section Cancer Biology and Oncology)
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