Propionate metabolism‑related genes demonstrate the potential to serve as prognostic and immunotherapeutic markers in osteosarcoma

Liu,Wei; Xu,Ze; Li,Mingdong; Zhu,Nan; Zhang,Shuo; Zhang,Qilun; Zhan,Junfeng

doi:10.3892/ol.2025.15134

Propionate metabolism‑related genes demonstrate the potential to serve as prognostic and immunotherapeutic markers in osteosarcoma

Authors:
- Wei Liu
- Ze Xu
- Mingdong Li
- Nan Zhu
- Shuo Zhang
- Qilun Zhang
- Junfeng Zhan
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Affiliations: Department of Orthopedics, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230601, P.R. China, Department of Orthopedics and Traumatology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan 570311, P.R. China, Department of Central Laboratory, The Third People's Hospital of Bengbu, Bengbu, Anhui 233000, P.R. China
Published online on: June 10, 2025 https://doi.org/10.3892/ol.2025.15134
Article Number: 387
Copyright: © Liu et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Understanding the metabolic processes in osteosarcoma (OS) is key for the development of effective diagnostic and therapeutic modalities. Propionate metabolism has been found to have a crucial role in certain cancers, highlighting its potential relevance in OS. The aim of the present study was to identify novel prognostic indicators for OS based on gene expression profiles and clinical data. Differentially expressed genes (DEGs) in OS and propionate metabolism‑associated genes were identified by the analysis of public datasets. Subsequently, functional enrichment analysis was performed and a protein‑protein interaction network was constructed. Least absolute shrinkage and selection operato‑Cox regression analysis was then conducted to construct a risk model, which was used to establish high‑ and low‑risk patient groups, and the association of the risk model with immune cell infiltration and immunotherapy was assessed. Furthermore, a prognostic nomogram was constructed. In addition, cell assays were conducted to evaluate the influence of prognostic gene knockdown on OS cells. The bioinformatics analysis led to the identification of 18 DEGs associated with propionate metabolism in OS, and the risk score model revealed two prognostic genes, namely 4‑aminobutyrate aminotransferase (ABAT) and aldehyde dehydrogenase 7 family member A1 (ALDH7A1). Immune infiltration analysis highlighted a significant difference between high‑ and low‑risk groups, indicating a potential impact on the response to immune therapy. In addition, the propionate metabolism‑related gene signatures effectively distinguished OS patients with distinct clinical outcomes and tumor microenvironments, and single‑cell analysis revealed associations of ABAT and ALDH7A1 with immune cell infiltration. Furthermore, cell assays revealed that the knockdown of ABAT promoted OS cell growth, migration and invasion. In conclusion, the present study emphasized the relevance of propionate metabolism in OS and introduced a novel gene signature for clinical outcome prediction. Furthermore, the identified genes, ABAT and ALDH7A1, may hold promise as potential therapeutic targets.

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