Single-cell landscape of peripheral and tumor-infiltrating immune cells in HPV-negative HNSCC.
Rômulo Gonçalves Agostinho Galvani, Adolfo Alexis Rojas Hidalgo, Carlos Alberto Biagi-Junior, Bruno Fernandes Matuck, Jelte Martinus Maria Krol, Brittany Rupp, Nikhil Kumar, Khoa Huynh, Jinze Liu, Siddharth Sheth, Vinicius Maracaja-Coutinho, Kevin Matthew Byrd, Patricia Severino
Abstract
Open AccessHead and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer worldwide. HPV-negative HNSCC, arising in diverse upper airway mucosal niches, is particularly aggressive, with poor 5-y survival and a limited response to immune checkpoint inhibitors. A deeper understanding of the tumor-localized immune landscape is essential to uncover actionable immunotherapeutic targets. Here, we integrated two single-cell RNA sequencing (scRNA-seq) datasets from 29 samples totaling nearly 300,000 immune cells to dissect immune rewiring during tumor progression and lymph node metastasis in HPV-negative HNSCC. We identified distinct shifts in adaptive immune cell populations across 14 peripheral blood mononuclear cell (PBMC) and 21 tumor-infiltrating immune cell (TIC) states. Notably, TICs exhibited enriched interferon response and immunomodulatory gene signatures, in contrast to PBMCs, indicating tumor-specific immune imprinting. Ligand-receptor analysis revealed that immunosuppressive crosstalk between macrophages and cytotoxic cells was associated with advanced disease. To spatially validate these transcriptional states, we conducted multiplexed immunofluorescence profiling on nine locally invasive HPV-negative HNSCCs, all from the ventrolateral tongue mucosa. Spatial proteomics confirmed peritumoral enrichment of activated (CD107a+, ICOS+) NK and CD8+ T cells and intratumoral accumulation of exhausted (PD-1+, PD-L1+) phenotypes, mirroring pseudotime trajectories inferred from scRNA-seq. These findings highlight spatially localized cytotoxic cell exhaustion as a key immune evasion mechanism in HPV-negative HNSCC and underscore the value of integrating spatial and single-cell data to reveal therapeutic vulnerabilities.