Co-expression network analysis identifies a gene signature as a predictive biomarker for energy metabolism in osteosarcoma.

ABSTRACT:

Background

Osteosarcoma (OS) is a common malignant bone tumor originating in the interstitial tissues and occurring mostly in adolescents and young adults. Energy metabolism is a prerequisite for cancer cell growth, proliferation, invasion, and metastasis. However, the gene signatures associated with energy metabolism and their underlying molecular mechanisms that drive them are unknown.

Methods

Energy metabolism-related genes were obtained from the TARGET database. We applied the "NFM" algorithm to classify putative signature gene into subtypes based on energy metabolism. Key genes related to progression were identified by weighted co-expression network analysis (WGCNA). Based on least absolute shrinkage and selection operator (LASSO) Cox proportional regression hazards mod

SUBMITTER: Zhu N 

PROVIDER: S-EPMC7310058 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature