Comprehensive tumour-immune profiling reveals TREM2+ tumour-associated macrophages facilitating lymph node metastasis in head and neck squamous cell carcinoma

  • Clin Transl Med. 2026 Feb;16(2):e70604. doi: 10.1002/ctm2.70604.
Zhuokai Wu  1 Chixing Cheng  2  3  4 Zhaoxin Li  1 Minyi Ren  1 Hongxi Cao  1 Weijie Huang  1 Jun Wang  1 Lixian Wu  1 Tingyi Lee  1 Sien Zhang  1 Hanhao Zheng  3  4  5 Yixi Wang  1
Affiliations
  • 1. Hospital of Stomatology, Guanghua School of Stomatology, Guangdong Provincial Key Laboratory of Stomatology, Sun Yat-sen University, Guangzhou, China.
  • 2. Department of Urology, The Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai, China.
  • 3. Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
  • 4. State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Sun, Yat-sen University, Guangzhou, China.
  • 5. Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Abstract

Background: Lymph node (LN) metastasis is a well-established independent prognostic factor in head and neck squamous cell carcinoma (HNSCC). Formation of suppressive tumour immune microenvironment (TIME) is a major contributor to tumour immune evasion and metastasis. However, the TIME landscape underlying LN-metastatic HNSCC remains poorly elucidated.

Methods: A total of 688 866 single-cell transcriptomes across 212 HNSCC samples were integrated. Comprehensive bioinformatic analyses on single-cell RNA Sequencing and microarray datasets revealed a TREM2+ tumour-associated macrophage (TAM) cluster associated with LN metastasis. The functional role of TREM2+ TAMs was investigated through multiplex immunohistochemistry (mIHC) staining in clinical HNSCC cohort and in vitro co-culture experiments. Furthermore, machine learning algorithms were employed to construct a prognostic model for HNSCC.

Results: Integrative single-cell analysis revealed the immunosuppressive TIME of LN-metastatic HNSCC, characterised by high infiltration of exhausted CD8+ T cells (CD8+ Tex). We identified a specific TREM2+ TAM cluster that was strongly associated with CD8+ Tex infiltration and LN metastasis. In vitro experiment confirmed that TREM2+ TAMs promoted CD8+ T cell exhaustion. Mechanistically, TREM2+ TAMs exhibited a terminally differentiated phenotype driven by ETV5, and secreted SPP1 to interact with CD44 on CD8+ T cells, thus upregulating BHLHE40 to promote CD8+ Tex formation. Clinically, a prognostic model based on TREM2+ TAM signature genes was trained to independently predict HNSCC outcomes.

Conclusions: This study delineates the mechanism that TREM2+ TAMs promote LN metastasis in HNSCC by facilitating CD8+ T cells exhaustion via SPP1-CD44-BHLHE40 axis, proposing TREM2+ TAMs as potential therapeutic target for HNSCC.

Keywords
CD8+ Tex; HNSCC; LN metastasis; TIME; TREM2+ TAMs; scRNA‐seq.