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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 / Copyright

    Affiliations: Department of Pediatric Orthopedics, The Affiliated Children's Hospital of Xiangya School of Medicine, Central South University (Hunan Children's Hospital), Changsha, Hunan 410007, P.R. China
    Copyright: © Zeng et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Article Number: 443
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    Published online on: July 15, 2025
       https://doi.org/10.3892/ol.2025.15189
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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.
View Figures

Figure 1

Consensus clustering of OS. (A)
Consensus clustering matrix for k=2. (B) Area under the curve of
the relative increase in cluster stability when k=2. (C) Consensus
clustering cumulative distribution function curve for k=2-9. OS,
osteosarcoma; CDF, cumulative distribution function.

Figure 2

Determination of two immune subtypes
in the OS. (A) Heatmap of single-sample gene set enrichment
analysis scores. (B) Expression levels of infiltrating immune cells
between Cluster 1 and 2. (C) Differences in tumor purity, ESTIMATE,
stromal and immune score. (D) Expression levels of immune
checkpoint genes, including LAG3, CD274, HAVCR2, NT5E, CTLA4, TIGIT
and PDCD1. ***P<0.001. OS, osteosarcoma; LAG3, lymphocyte
activation gene; HAVCR2, hepatitis A virus cellular receptor 2;
NT5E, 5′-nucleotidase ecto; CTLA4, cytotoxic T lymphocyte antigen
4; TIGIT, T cell immunoreceptor with Ig and ITIM domains; PDCD1,
programmed cell death protein 1; NK, natural killer; APC,
Antigen-Presenting Cell; TIL, tumor-infiltrating Lymphocyte; HLA,
human Leukocyte Antigen; DCs, Dendritic Cells; Tfh, T Follicular
helper.

Figure 3

Determination of DELs. (A) Heatmap
and (B) volcano plot of DELs between Cluster 1 and 2. (C)
Representation of DELs in a boxplot. DEL, differentially expressed
long non-coding RNA.

Figure 4

Development of IIRL prognostic
signature. (A) Univariate Cox regression was used to establish the
forest plot of six IIRLs associated with prognosis. (B)
Kaplan-Meier survival curves of patients with OS in the high- and
low-risk cohorts. (C) Risk score distribution, (D) OS status and
(E) heatmap of the prognostic lncRNAs signatures. (F) ROC curve for
overall survival of patients with OS. lnc, long non-coding; IIRL,
immune infiltration-related lncRNA; OS, osteosarcoma; AUC, area
under the curve; ROC, receiver operating characteristic.

Figure 5

UCR and MCR analyses of
clinicopathological factors associated with OS prognosis. (A) UCR
and (B) MCR analyses of risk score, sex, age and metastasis. UCR,
univariate Cox regression; MCR, multivariate Cox regression; OS,
osteosarcoma.

Figure 6

GO and KEGG enrichment analysis of
immune infiltration-related long non-coding RNAs co-expressed with
differentially expressed genes in OS. (A) GO and (B) KEGG
enrichment results. KEGG, Kyoto Encyclopedia of Genes and Genomes;
GO, Gene Ontology; OS, osteosarcoma; BP, biological Process CC
:Cellular Component MF :Molecular Function.

Figure 7

lncRNA-mRNA network of two lncRNAs
(red) and 69 mRNAs (pink). lnc, long non-coding.

Figure 8

Immune cell infiltration in patients
with OS. (A) Expression levels of infiltrating immune cells between
the high- and low-risk groups. (B) Tumor purity and ESTIMATE,
stromal and immune score. (C) Differences in the expression levels
of immune checkpoint genes, including LAG3, VSIR, CD274, HAVCR2,
NT5E, CTLA4, TIGIT and PDCD1. *P<0.05, **P<0.01,
***P<0.001 vs. high-risk group). OS, osteosarcoma; LAG3,
lymphocyte activation gene; HAVCR2, hepatitis A virus cellular
receptor 2; NT5E, 5′-nucleotidase ecto; CTLA4, cytotoxic
T-lymphocyte antigen 4; TIGIT, T cell immunoreceptor with Ig and
ITIM domains; PDCD1, programmed cell death protein 1.

Figure 9

High- vs. low-risk group gene set
enrichment analysis in Therapeutically Applicable Research to
Generate Effective Treatments database. (A) ‘Systemic lupus
erythematosus’, (B) ‘allograft rejection’, (C) ‘chemokine signaling
pathway’ and (D) ‘NOD-like receptor signaling pathway’. NOD,
nucleotide oligomerization domain; KEGG, Kyoto Encyclopedia of
Genes and Genomes.

Figure 10

Reverse transcription-quantitative
PCR to determine the relative expression levels of LINC01094 and
RP11-15K2.2 in hFOB1.19, MG-63, 143B and U2OS cells. **P<0.01
and ***P<0.001 vs. hFOB1.19.
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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
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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
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