Open Access

Risk score model with two immune infiltration‑related long non‑coding RNAs to predict prognosis in patients with osteosarcoma

  • Authors:
    • Ling-Rong Zeng
    • Guang-Hui Zhu
    • Hai-Bo Mei
    • Ge Yang
  • View Affiliations

  • Published online on: July 15, 2025     https://doi.org/10.3892/ol.2025.15189
  • Article Number: 443
  • Copyright: © Zeng et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Osteosarcoma (OS) is the most frequent type of cancer, as well as a common malignant tumor in orthopedics. Multiple long non‑coding RNAs (lncRNAs) are implicated in immune infiltration in numerous types of cancer. Using single‑sample gene set enrichment analysis to assign patients with OS, two immunotypes of OS were identified. Using K‑means, spectral and PCA‑K‑means clustering two immunotypes of OS were demonstrated to be reproducible and represent a biologically meaningful classification of patients with OS based on their tumor immune microenvironment. Cluster 1 was an immune‑infiltrating type, while Cluster 2 was an immune ‘desert’ type (low immune cell infiltration). Between Cluster 1 and 2, 29 common differentially expressed lncRNAs (DELs) were identified and univariate Cox regression (UCR) analysis was performed to identify DELs associated with overall survival. A risk score model was established by performing UCR and the iterative Lasso Cox regression analyses based on two immune infiltration‑related lncRNA (IIRLs; LINC01094 and RP11‑15K2.2). The risk model was a novel independent prognostic factor for patients with OS. A mutual influence between the expression of two IIRLs and mRNAs (LINC01094 and RP11‑15K2.2) was also identified. Gene Ontology demonstrated that these mRNAs were abundant in immune‑associated functions and pathways. Cytoscape was used to construct lncRNA‑mRNA networks. The discrepancy in tumor‑infiltrating immune cell abundance demonstrated that the high‑risk group was associated with infiltration of diverse immune cell types. Furthermore, the expression levels of immune checkpoint inhibitors were markedly upregulated in the high‑ compared with that in the low‑risk‑cohort. Gene set enrichment analysis revealed that the risk score was associated with nucleotide oligomerization domain‑like receptor signaling pathways. In summary, two IIRLs were developed in the present study to predict prognosis in patients with OS. The molecular mechanisms in the high‑risk group may influence immune infiltration‑linked biological processes.
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September-2025
Volume 30 Issue 3

Print ISSN: 1792-1074
Online ISSN:1792-1082

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Spandidos Publications style
Zeng L, Zhu G, Mei H and Yang G: Risk score model with two immune infiltration‑related long non‑coding RNAs to predict prognosis in patients with osteosarcoma. Oncol Lett 30: 443, 2025.
APA
Zeng, L., Zhu, G., Mei, H., & Yang, G. (2025). Risk score model with two immune infiltration‑related long non‑coding RNAs to predict prognosis in patients with osteosarcoma. Oncology Letters, 30, 443. https://doi.org/10.3892/ol.2025.15189
MLA
Zeng, L., Zhu, G., Mei, H., Yang, G."Risk score model with two immune infiltration‑related long non‑coding RNAs to predict prognosis in patients with osteosarcoma". Oncology Letters 30.3 (2025): 443.
Chicago
Zeng, L., Zhu, G., Mei, H., Yang, G."Risk score model with two immune infiltration‑related long non‑coding RNAs to predict prognosis in patients with osteosarcoma". Oncology Letters 30, no. 3 (2025): 443. https://doi.org/10.3892/ol.2025.15189