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Cancers
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Genomics and Transcriptomics in Sarcoma
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Genomics and Transcriptomics in Sarcoma

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Molecular Cancer Biology".

Deadline for manuscript submissions: closed (25 September 2025) | Viewed by 3880

Special Issue Editors

Prof. Dr. George Jour

E-Mail Website
Guest Editor
Department of Dermatology, NYU Grossman School of Medicine, New York, NY, USA
Interests: genomic; transcriptomic; sarcoma; translational research; clinical development
Dr. Jose G. Mantilla

E-Mail Website
Guest Editor
Department of Pathology, NYU Grossman School of Medicine, New York, NY, USA
Interests: oncology; bone; sarcoma; chordoma

Special Issue Information

Dear Colleagues,

This Special Issue will focus on novel methodologies in the genomic field for different types of sarcomas. Emphasis will be placed on DNA-based genomic and epigenetic methodologies and their application in diagnostic, prognostic, and therapeutic biomarker discovery and validation in sarcomas, both in tumor tissue and blood. Additionally, this issue will focus on research and reviews on transcriptomics and spatial transcriptomics in soft tissue. The purpose is to shed light on insights regarding the tumor microenvironment and its relationship to tumor biology and drug response. Special interest will be given to research focusing on AI models aiding the interpretation of complex datasets for diagnostics and treatment strategies in soft-tissue sarcomas.

Prof. Dr. George Jour
Dr. Jose G. Mantilla
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cancers is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • transcriptomics
  • single-cell RNA sequencing
  • machine learning
  • sarcoma

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Published Papers (4 papers)

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Research

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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 684
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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Review

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17 pages, 1073 KB  
Review
Recent Studies on Kaposi’s Sarcoma-Associated Herpesvirus Circular RNAs
by Cristian J. Pagtalunan, Isadora Zhang, Ariella Turley and Fenyong Liu
Cancers 2025, 17(23), 3743; https://doi.org/10.3390/cancers17233743 - 23 Nov 2025
Viewed by 356
Abstract
Kaposi’s sarcoma (KS), an AIDS-defining illness, is caused by Kaposi’s sarcoma-associated herpesvirus (KSHV). A member of the human herpesvirus family, designated as human herpesvirus 8 (HHV-8), KSHV is also linked to other oncogenic manifestations such as primary effusion lymphoma (PEL). The current dearth [...] Read more.
Kaposi’s sarcoma (KS), an AIDS-defining illness, is caused by Kaposi’s sarcoma-associated herpesvirus (KSHV). A member of the human herpesvirus family, designated as human herpesvirus 8 (HHV-8), KSHV is also linked to other oncogenic manifestations such as primary effusion lymphoma (PEL). The current dearth of available compounds against KSHV necessitates development of effective antiviral treatments. As with other herpesviruses, KSHV can result in both lytic and latent infections. KSHV pathogenesis and the development of KS have been associated with the expression of KSHV genes and transcripts during viral infections. The transcriptome of KSHV heavily intersects with regulatory pathways and mechanisms involved with a multitude of diseases in humans. Circular RNAs (circRNAs) have recently been discovered to be expressed by KSHV. Research endeavors on KSHV circRNAs have focused on the roles they play throughout latent and lytic infection. Understanding the specific functions and interactions of KSHV circRNAs with the viral and host transcriptomes, as well as how they are identified and analyzed, will be the primary focus of this review. Overall, recent advances in KSHV circRNA research have deepened our understanding of the KSHV transcriptome and pathogenesis and are paving the way for the development of circRNA-based antiviral therapies. Full article
(This article belongs to the Special Issue Genomics and Transcriptomics in Sarcoma)
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19 pages, 1020 KB  
Review
Genetic Heterogeneity of Undifferentiated Pleomorphic Sarcoma: Is There Potential for Targeted Therapy?
by Ekaterina A. Lesovaya, Timur I. Fetisov, Beniamin Yu. Bokhyan, Maria A. Senchenko, Dmitry V. Rogozhin, Varvara P. Maksimova, Anna N. Demko, Gennady A. Belitsky, Marianna G. Yakubovskaya and Kirill I. Kirsanov
Cancers 2025, 17(22), 3613; https://doi.org/10.3390/cancers17223613 - 10 Nov 2025
Viewed by 772
Abstract
Undifferentiated pleomorphic sarcoma (UPS) is the most morphologically and genetically heterogeneous form of soft tissue sarcoma. UPS tumors can exhibit a wide range of genetic abnormalities, including activating and inactivating mutations, gene amplifications, chromosomal translocations, and copy number variations. Owing to this extensive [...] Read more.
Undifferentiated pleomorphic sarcoma (UPS) is the most morphologically and genetically heterogeneous form of soft tissue sarcoma. UPS tumors can exhibit a wide range of genetic abnormalities, including activating and inactivating mutations, gene amplifications, chromosomal translocations, and copy number variations. Owing to this extensive genetic heterogeneity, no UPS-specific therapeutic targets have yet been validated, complicating diagnosis, prognosis, and the selection of targeted treatment strategies. Currently, immune checkpoint inhibitors (targeting PD-1, PD-L1, and CTLA-4) are the only validated targeted therapy for UPS, reflecting the frequent mutational events that activate immune response pathways. Because molecular genetic profiling alone provides limited prognostic value for chemoresistance in UPS, the development of experimental ex vivo and in vitro testing approaches may help to identify and exclude potentially ineffective targeted therapies. Full article
(This article belongs to the Special Issue Genomics and Transcriptomics in Sarcoma)
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15 pages, 236 KB  
Review
Novel Molecular Methods in Soft Tissue Sarcomas: From Diagnostics to Theragnostics
by Nicholas Frazzette and George Jour
Cancers 2025, 17(7), 1215; https://doi.org/10.3390/cancers17071215 - 3 Apr 2025
Cited by 2 | Viewed by 1625
Abstract
Soft tissue sarcomas (STSs) are a diverse group of malignant tumors derived from mesenchymal tissues [...] Full article
(This article belongs to the Special Issue Genomics and Transcriptomics in Sarcoma)
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