ArticleAging2024
Molecular characterization of Golgi apparatus-related genes indicates prognosis and immune infiltration in osteosarcoma.
Article in Aging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 2 citations in OpenAlex.
- A novel prognostic model based on Golgi apparatus-related genes predicts patient survival in glioblastoma.Open medicine (Warsaw, Poland) · 2026Article
- Prognostic and immunological characterization of osteosarcoma patients evaluated by liquid-liquid phase separation related genes.Discover oncology · 2025Article
- Exploratory Analysis of Molecular Subtypes in Early-Stage Osteosarcoma: Identifying Resistance and Optimizing Therapy.Cancers · 2025Article
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe Golgi apparatus (GA) is crucial for protein synthesis and modification, and regulates various cellular processes. Dysregulation of GA can lead to pathological conditions like neoplastic growth. GA-related genes (GARGs) mutations are commonly found in cancer, contributing to tumor metastasis. However, the expression and prognostic significance of GARGs in osteosarcoma are yet to be understood.
methodsGene expression and clinical data of osteosarcoma patients were obtained from the TARGET and GEO databases. A consensus clustering analysis identified distinct molecular subtypes based on GARGs. Discrepancies in biological processes and immunological features among the subtypes were explored using GSVA, ssGSEA, and Metascape analysis. A GARGs signature was constructed using Cox regression. The prognostic value of the GARGs signature in osteosarcoma was evaluated using Kaplan-Meier curves and a nomogram.
resultsTwo GARG subtypes were identified, with Cluster A showing better prognosis, immunogenicity, and immune cell infiltration than Cluster B. A novel risk model of 3 GARGs was established using the TARGET dataset and validated with independent datasets. High-risk patients had poorer overall survival, and the GARGs signature independently predicted osteosarcoma prognosis. Combining risk scores and clinical characteristics in a nomogram improved prediction performance. Additionally, we discovered Stanniocalcin-2 (STC2) as a significant prognostic gene highly expressed in osteosarcoma and potential disease biomarker.
conclusionsOur study revealed that patients with osteosarcoma can be divided into two GARGs subgroups. Furthermore, we have developed a GARGs prognostic signature that can accurately forecast the prognosis of osteosarcoma patients.
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