ORIGINAL RESEARCH article
Front. Oncol.
Sec. Cancer Immunity and Immunotherapy
Volume 15 - 2025 | doi: 10.3389/fonc.2025.1609501
Identification and Comprehensive Analysis of An Immune-Related Gene Prognostic Model for Indicating Tumor Immune Microenvironment Features in Soft Tissue Sarcoma
Provisionally accepted
- Liaoning University of Traditional Chinese Medicine, Shenyang, China
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Background: the STS is a rare type of tumor, and although its treatment has improved greatly in recent decades, the treatment of STS and the development of new drugs remains a major challenge. A new identification of prognostic biomarkers that reflect the biological heterogeneity of STS could therefore lead to better interventions for STS patients. In recent years, there has been a growing interest in the investigation of the impact of immune-related genes on cancer prognosis. Methods: based on RNAseq data obtained from TCGA-STS and GTEx patients, differential expression analysis, consensus clustering, enrichment analysis, tumor microenvironment assessment, risk model construction and other data analysis were performed. Last but not least, CALR, a central regulator inSTS, demonstrated oncogenic properties through overexpression/knockdown assays, supported by qRT-PCR and immunofluorescence data. Results: we constructed a prognostic model containing 8 IRGs for predicting STS prognosis by using the LASSO regression. Furthermore, the samples were categorized as either high-risk or low-risk based on the risk score computed by the model. Additionally, we compared the tumor microenvironment of STS samples using the ESTIMATE and CIBERSORT algorithms. Last, our experimental results proved that CALR was up-regulated in sarcoma cells compared to in normal cell. Conclusions: conclusively, IRGPM is a promising immune-related prognostic biomarker. As a prognostic indicator of immunotherapy, IRGPM might also help differentiate molecular and immune characteristics in STS.
Keywords: Soft Tissue Sarcoma, immune-related genes, Tumor Microenvironment, Immune Cell Infiltration, prognostic model Signatures
Received: 10 Apr 2025; Accepted: 07 Jul 2025.
Copyright: © 2025 Xu, Guan, Liu, Cai and Sun. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Xuefeng Guan, Liaoning University of Traditional Chinese Medicine, Shenyang, China
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