Identification and validation of novel biomarkers associated with immune infiltration for the diagnosis of osteosarcoma based on machine learning.

ABSTRACT: Objectives: Osteosarcoma is the most common primary malignant tumor in children and adolescents, and the 5-year survival of osteosarcoma patients gained no substantial improvement over the past decades. Effective biomarkers in diagnosing osteosarcoma are warranted to be developed. This study aims to explore novel biomarkers correlated with immune cell infiltration in the development and diagnosis of osteosarcoma. Methods: Three datasets (GSE19276, GSE36001, GSE126209) comprising osteosarcoma samples were extracted from Gene Expression Omnibus (GEO) database and merged to obtain the gene expression. Then, differentially expressed genes (DEGs) were identified by limma and potential biological functions and downstream pathways enrichment analysis of DEGs was performed. The machi

SUBMITTER: Ji Y 

PROVIDER: S-EPMC10507254 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature