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Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
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Risk score model with two immune infiltration-related long non-coding RNAs to predict prognosis in patients with
Ling-Rong Zeng1,2, Guang-Hui Zhu1,2, Hai-Bo Mei1,2
1Department 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.
Oncology Letters
|July 25, 2025
Summary
This study identifies two distinct immune types in osteosarcoma (OS) and develops a novel prognostic model using two immune infiltration-related long non-coding RNAs (IIRLs) to predict patient survival and guide treatment strategies.
Area of Science:
- Oncology
- Immunology
- Genetics
Background:
- Osteosarcoma (OS) is a prevalent bone cancer with complex immune interactions.
- Long non-coding RNAs (lncRNAs) play a role in cancer immunity, but their specific function in OS requires further elucidation.
- Understanding the tumor immune microenvironment is crucial for developing effective OS therapies.
Purpose of the Study:
- To classify osteosarcoma patients into distinct immunotypes based on their tumor immune microenvironment.
- To identify key lncRNAs associated with immune infiltration and patient prognosis in OS.
- To develop a novel risk score model for predicting osteosarcoma patient survival.
Main Methods:
- Single-sample gene set enrichment analysis (ssGSEA) and clustering algorithms (K-means, spectral, PCA-K-means) were used to define OS immunotypes.
- Differential expression analysis and univariate Cox regression (UCR) identified key lncRNAs.
- Iterative Lasso Cox regression established a prognostic risk score model based on two immune infiltration-related lncRNAs (IIRLs): LINC01094 and RP11-15K2.2.
Main Results:
- Two reproducible OS immunotypes were identified: an immune-infiltrating type and an immune-desert type.
- A risk score model based on LINC01094 and RP11-15K2.2 was developed as an independent prognostic factor for OS.
- The high-risk group exhibited increased immune cell infiltration, upregulated immune checkpoint inhibitors, and association with nucleotide oligomerization domain-like receptor signaling pathways.
Conclusions:
- The study successfully classified OS into distinct immunotypes and identified two IIRLs crucial for prognosis.
- The developed risk score model provides a novel tool for predicting OS patient outcomes.
- The findings suggest that IIRLs influence immune infiltration and related biological processes in osteosarcoma, offering potential therapeutic targets.
