Exploration of a predictive model based on genes associated with fatty acid metabolism and clinical treatment for head and neck squamous cell carcinoma.

ABSTRACT:

Background

Head and neck squamous cell carcinoma (HNSCC) is one of the most prevalent malignant tumors of the head and neck and presents high risks of recurrence and poor prognosis postoperatively. The aim of this study was to establish a predictive model based on fatty acid metabolism (FAM) genes to forecast the prognosis of HNSCC patients and the subsequent treatment strategies.

Methods

We accessed the TCGA and GEO databases for HNSCC genes and clinical data. The FAM risk score model was created and validated using a combination of univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) regression analysis. Combining risk scores and clinical characteristics, a nomogram was established and assessed. Subsequently, the function, gene mutation, immu

SUBMITTER: Yuan Z 

PROVIDER: S-EPMC9701875 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature