Machine Learning-Driven Identification of Exosome-Related Genes in Head and Neck Squamous Cell Carcinoma for Prognostic Evaluation and Drug Response Prediction

Machine Learning-Driven Identification of Exosome-Related Genes in Head and Neck Squamous Cell Carcinoma for Prognostic Evaluation and Drug Response Prediction

<b>Background:</b> This study integrated four Gene Expression Omnibus (GEO) datasets to identify disease-specific feature genes in head and neck squamous cell carcinoma (HNSCC) through differential expression analysis with batch effect correction. <b>Methods</b>: The GeneCard...

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Bibliographic Details
Main Authors: Hua Cai, Liuqing Zhou, Yao Hu, Tao Zhou
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Biomedicines
Subjects:
exosome
head and neck squamous cell carcinoma
prognosis
immune infiltration
bioinformatics
Online Access:https://www.mdpi.com/2227-9059/13/4/780
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