Integrative immune subtyping of HNSCC reveals clinically relevant phenotypes and treatment-associated transitions
Indu KhatriiD, Terezinha Maria de SouzaiD, Saskia D. van AsteniD, Merzu Kebede BeleteiD, Felipe A. Vieira BragaiD, Merel Jongmans, Sriram SridhariD, Brandon W. HiggsiD, Iris C. R. M. KolderiD
Abstract
Head and neck squamous cell carcinoma (HNSCC) exhibits profound heterogeneity in clinical presentation, treatment response, and immune landscape. While prior classification systems have identified molecular and immune subtypes in this disease, their applicability to real-world clinical settings remains restricted to small, homogeneous cohorts and limited by lack of multimodal data integration and interpretation. We performed integrated multi-omics analysis including transcriptomic, genomic (copy number, single-nucleotide variants) on 1,149 tumors from 1,102 HNSCC patients across treatment settings. Using the Similarity Network Fusion (SNF) algorithm, we defined immune subtype clusters (ISCs) based on the full immune gene landscape. These clusters were characterized using mutational, transcriptional, and immune cell enrichment analyses, and mapped to hypoxia and traditional subtypes. Associations with clinical outcomes, including progression-free survival, were evaluated across first-line and post-metastatic treatment settings. Four distinct immune subtype clusters (ISC1-ISC4) were identified: ISC1: immune-cold and EMT-enriched; ISC2: immune activated; ISC3: mixed immune-regulatory and stromal-enriched phenotype; and ISC4: immunosuppressed. Distinct treatment response patterns were observed across subtypes in subjects treated with checkpoint inhibitors, chemotherapy, and combination regimens. 44 Patients with matched pre/post treatment tumors revealed treatment-associated transitions between immune subtypes: checkpoint inhibitor treatment enriched for immune activation, while chemotherapy treatment enriched for immunosuppressive signaling pathways. This study provides a clinically relevant immune subtyping framework for HNSCC based on real-world, multi-omics data. These subtypes reflect dynamic tumor-immune states and associated with treatment response and survival, supporting their use in guiding immune-based therapy in HNSCC.
02 /Specification & Classification
Click any tag to browse matching papers- Citations
- 1
- FWCI
- 2.98
- Field percentile
- top 15%
- Organism
- Assay
- Research Focus
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Tumor microenvironment governs the prognostic landscape of immunotherapy for head and neck squamous cell carcinoma: A computational model-guided analysis
Priyan Bhattacharya, Alban J. Linnenbach, … Rajanikanth Vadigepalli·PLoS Computational BiologyPeer-reviewed·Jun 3, 2025
- Tumor Niche Network-Defined Subtypes Predict Immunotherapy Response of Esophageal Squamous Cell Cancer
K.-P. Ko, S. Zhang, … J.-I. Park·bioRxiv·Feb 15, 2023
- High-dimensional and spatial analysis reveals immune landscape dependent progression in cutaneous squamous cell carcinoma
A. L. Ferguson, A. R. Sharman, … U. Palendira·Clinical Cancer ResearchPeer-reviewed·Aug 31, 2022
- Single-cell Spatial Metabolic and Immune Phenotyping of Head and Neck Cancer Tissues Identifies Tissue Signatures of Response and Resistance to Immunotherapy
N. Jhaveri, B. Ben Cheikh, … O. Braubach·bioRxiv·May 30, 2023
- Integrated Multi-Omics Analysis for Molecular Subtyping in NSCLC: A Cohort Study
Bin Yan, Zhangyu Wang, … Shixiang Wang·bioRxiv·Sep 5, 2025
- Integrated single-cell and spatial analysis identifies context-dependent myeloid-T cell interactions in head and neck cancer immune checkpoint blockade response
Athena E. Golfinos, Taja Ložar, … Huy Q. Dinh·bioRxiv·Mar 24, 2025