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ABSTRACT: Background
Osteosarcoma (OS) is a primary malignant bone tumor known for its aggressive nature and high potential for metastasis, primarily impacting adolescents and young adults. Few studies have focused on discovering gene signatures that effectively guide treatment strategies and predict outcomes in OS. The study aimed to create a prognostic model to predict OS patient survival.Methods
Candidate genes were identified by intersecting genes from survival analyses of two patient datasets. Unsupervised consensus clustering was employed with these candidate genes to investigate potential tumor types. Following this, a gene signature was developed and validated within one of the datasets. Finally, the immune microenvironment was assessed using the CIBERSORT and ESTIMATE algori
SUBMITTER: Wang X
PROVIDER: S-EPMC12776240 | biostudies-literature | 2025 Dec
REPOSITORIES: biostudies-literature