August 13, 2025

Single-Cell Transcriptomics Identifies Novel Prognostic Signatures in HNSCC Immunotherapy Response.

Key Points

Single-cell transcriptomics revealed 19 pre-treatment and 13 post-treatment cell subpopulations in HNSCC.
A LASSO-Cox model using 51 survival-associated genes showed predictive performance with AUC values between 0.749 and 0.800.
Analysis focused on six major immune cell types, highlighting significant gene expression differences post-immunotherapy.
The model indicates high-risk groups based on immune cell infiltration and gene expression patterns, aiding in therapy optimization.

Abstract

Head and neck squamous cell carcinoma (HNSCC) poses a major therapeutic challenge. In this study, we aimed to analyze tumor immune microenvironment changes and develop a prognostic model based on immunotherapy response. We analyzed single-cell RNA sequencing data from three HNSCC patients receiving TLR8 agonist and anti-PD1 combination therapy, identified cell subpopulations before and after treatment with a focus on six major immune cell types, and developed a LASSO-Cox risk stratification model using combined single-cell and bulk RNA sequencing data. We identified 19 pre-treatment and 13 post-treatment cell subpopulations. Analysis of six major immune cell types revealed differential gene expression patterns. Based on treatment-induced differential genes, we developed a LASSO-Cox model with 51 survival-associated genes, which showed robust predictive performance (AUC: 0.749-0.800) across different timepoints for both HPV-positive and HPV-negative patients. High-risk groups had elevated MDSCs and CAFs, decreased immune cell infiltration (except Th2 CD4+ T cells and common lymphoid progenitors), and increased expression of ICB-related genes. In conclusion, our model effectively captures patients' immune status and provides insights for optimizing HNSCC immunotherapy strategies.

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