Machine-Learning-Based m5C Score for the Prognosis Diagnosis of Osteosarcoma.

ABSTRACT:

Background

Osteosarcoma is a common and highly metastatic malignant tumor, and m5C RNA methylation regulates various biological processes. The purpose of this study was to explore the prognostic role of m5C in osteosarcoma using machine learning.

Methods

Osteosarcoma gene data and the corresponding clinical information were downloaded from the GEO database. Machine learning methods were used to screen m5C-related genes and construct m5C scores. In addition, the clusterProfiler package was used to predict the m5C-related functional pathways. xCell and CIBERSORT were used to calculate the immune microenvironment cells. GSVA was applied to analyze different categories of m5C genes, and the correlation between the GSVA and m5C scores was evaluated.

Results

Twenty m5C gene

SUBMITTER: Zhang H 

PROVIDER: S-EPMC8523252 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature