Construction of a novel mRNAsi-related risk model for predicting prognosis and immunotherapy response in osteosarcoma.

ABSTRACT:

Background

Targeting cancer stem cells (CSC) may represent a future therapeutic direction for osteosarcoma (OS), which mainly relies on the identification of CSC markers. This study aimed to classify OS based on messenger ribonucleic acid (mRNA) stemness indices (mRNAsi) and construct a mRNAsi-related risk model to predict the prognosis of OS.

Methods

The one-class logistic regression (OCLR) algorithm was applied to the RNA- sequencing (seq) data of human embryonic stem cells (hESC) and induced pluripotent stem cell (iPSC) lines to calculate mRNAsi. Weighted gene co-expression network analysis (WGCNA) was performed on data obtained from the TARGET database to screen the mRNAsi-related genes. Univariate Cox regression analysis was implemented to screen mRNAsi-related genes wi

SUBMITTER: Li Z 

PROVIDER: S-EPMC9929782 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature