Development of Personalized Classifier Based on Metastasis and the Immune Microenvironment to Predict the Prognosis of Osteosarcoma Patients

Overview

Journal Ann Transl Med

Publisher AME Publishing Company

Date 2023 Jan 20

PMID 36660665

Authors

Zhifeng Zhang

Jianyong Yuan

Yi Wang

Yanquan Zhang

Zhengmao Guan

Xu Su

Yizhou Wang

Affiliations

Soon will be listed here.

Abstract

Background: Osteosarcoma is a common malignant bone tumor with a poor prognosis. The progression and metastasis of osteosarcoma are significantly influenced by the tumor microenvironment (TME). This study aimed to develop a personalized classifier based on metastasis and immune cells in the TME to achieve better prognostic prediction in osteosarcoma.

Methods: Firstly, osteosarcoma metastasis-related differentially expressed genes (DEGs) and infiltrating immune cells in the TME were analyzed using a series of bioinformatics methods. The metastasis-related gene signature (MRS) and TME score of osteosarcoma patients were then developed. On this basis, a personalized MRS-TME classifier was constructed and validated in other clinical cohorts and different subgroups. In addition, the relationship between the MRS-related genes and the immune microenvironment was also clarified. Finally, the signaling pathways and immune response genes in osteosarcoma patients among different MRS-TME subgroups were analyzed to explore the underlying molecular mechanism.

Results: We first identified the metastasis-related DEGs in osteosarcoma, which were primarily involved in the muscle system process, calcium ion homeostasis, cell chemotaxis, and leukocyte migration. A personalized MRS-TME classifier was then constructed by integrating the MRS (10 genes) and TME (six immune cells) scores. The MRS-TME classifier demonstrated a potent capacity of predicting the survival prognosis in diverse osteosarcoma cohorts as well as in the clinical feature subgroups. The MRS score was negatively associated with the TME score, and patients in the MRS/TME subgroup exhibited a better prognosis compared to all other subgroups. Significant differences existed between the cellular signaling pathways and immune response profiles among the different MRS-TME subgroups, especially in relation to the metabolism-related biological processes and the inflammatory response.

Conclusions: The MRS-TME classifier might be a beneficial tool to aid in the prognostic evaluation and risk stratification of osteosarcoma patients.

Citing Articles

Exploration of metastasis-related signatures in osteosarcoma based on tumor microenvironment by integrated bioinformatic analysis.

Liao S, Gao X, Zhou K, Kang Y, Ji L, Zhong X Heliyon. 2025; 11(1):e41358.

PMID: 39844989 PMC: 11750479. DOI: 10.1016/j.heliyon.2024.e41358.

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