Work

Evaluation of the prognostic value of centrosome-related genes and assessment of the immune microenvironment in osteosarcoma

Year: 2025

Type: article

Abstract: BACKGROUND: Dysregulation of centrosome-related regulatory mechanisms has been implicated in chromosomal instability, aberrant cellular differentiation, and oncogenic transformation, which are factors influencing the development of osteosarcoma (OS). While centrosome-related genes (CRGs) have garnered substantial research attention, their prognostic significance in OS remains poorly characterized. This investigation sought to systematically evaluate CRGs as potential prognostic biomarkers, and their clinical relevance in OS progression. METHODS: The mRNA sequencing data and clinical information material were derived from the TARGET and GEO database. Molecular subtyping was performed through unsupervised clustering analysis using "ConsensusClusterPlus" package. Differential CRGs expression patterns across identified subtypes were interrogated via "limma" package. LASSO and Cox regression analysis enabled the construction of CRG-based prognostic scores and subsequent development of nomograms by "regplot". Experimental validation of CRGs expression profiles was conducted using qRT-PCR in OS cell lines versus normal osteoblasts. RESULTS: Unsupervised clustering revealed three CRG-defined molecular subtypes demonstrating significant heterogeneity in clinical outcomes. A reliable prognostic score comprising five CRGs was established that allowed patients to be categorized into different subgroups based on the score. Survival analyses showed a markedly shorter overall survival and the presence of a low immune cell infiltrate in high-risk patients. CRGs validation confirmed marked overexpression in malignant cells compared to normal controls. CONCLUSION: We developed and validated a novel CRG-based prognostic score demonstrating potential clinical utility for OS outcome prediction. This molecular score provides mechanistic insights into tumor-immune interactions and offers clinicians a quantitative framework for personalized therapeutic decision-making.

Source: Biochemical and Biophysical Research Communications

DOI: 10.1016/j.bbrc.2025.152739

Authors: Song Luo, Hui Yu, Yue Huang, Guoming Xia, Biao Long, Jianhui Liang

Institution: First Affiliated Hospital of Nanchang University

Language: English

Topic: Sarcoma Diagnosis and Treatment

Subfield: Pulmonary and Respiratory Medicine

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $3,110