A novel molecular classification system for head and neck squamous cell carcinoma: predicting treatment response and metastatic potential through multi-omics analysis.

ABSTRACT:

Background

Head and neck squamous cell carcinoma (HNSCC) demonstrates significant heterogeneity, necessitating improved molecular classification for precision treatment.

Methods

We integrated single-cell and bulk RNA sequencing data from 59,376 cells across ten datasets using Scissor and scSTAR packages. Molecular subtyping was performed through ssGSEA and WGCNA analysis, with immune infiltration evaluated using CIBERSORT. We developed a machine learning-based risk prediction model using 54 algorithms.

Results

We identified three molecular subtypes with distinct prognostic implications, showing significant survival differences across independent datasets (TCGA-HNSCC, P < 0.0001; GSE65858, P = 0.018). The C3 subtype showed enhanced immunotherapy response potential, whi

SUBMITTER: Liu X 

PROVIDER: S-EPMC11977092 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature