The Identification of Stemness-Related Genes in the Risk of Head and Neck Squamous Cell Carcinoma.

ABSTRACT:

Objectives

This study aimed to identify genes regulating cancer stemness of head and neck squamous cell carcinoma (HNSCC) and evaluate the ability of these genes to predict clinical outcomes.

Materials and methods

The stemness index (mRNAsi) was obtained using a one-class logistic regression machine learning algorithm based on sequencing data of HNSCC patients. Stemness-related genes were identified by weighted gene co-expression network analysis and least absolute shrinkage and selection operator analysis (LASSO). The coefficient of LASSO was applied to construct a diagnostic risk score model. The Cancer Genome Atlas database, the Gene Expression Omnibus database, Oncomine database and the Human Protein Atlas database were used to validate the expression of key genes. Inter

SUBMITTER: Feng G 

PROVIDER: S-EPMC8226229 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature