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<p>Head and neck squamous cell carcinoma (HNSCC) is a highly heterogeneous malignancy with poor prognosis, accompanied by metabolic reprogramming and tumor microenvironment (TME) disorders. Lactate metabolism is critical for tumor progression and immune escape, but its regulatory mechanism and clinical value in HNSCC remain unclear. We integrated single-cell and bulk RNA-sequencing data to identify lactate metabolism-related genes (LMGs). Using three machine learning algorithms, we selected six core LMGs and constructed a prognostic signature, which was validated in GSE41613 and GSE65858. Stem-like malignant cells showed the highest lactate metabolism activity among six epithelial subtypes. High-risk patients had shorter overall survival, with lower CD8 + T cell infiltration and higher M0 macrophages. Core genes were enriched in metabolic regulation and DNA replication. Compared with the high-risk group, low-risk patients exhibited higher sensitivity to chemotherapy and immunotherapy, and may benefit from BCL‑2/BCL‑XL inhibitors. Among the core genes, HPRT1 represents the most promising biomarker, whose expression is positively correlated with lactate production. This lactate‑related signature serves as a promising prognostic biomarker and therapeutic target, revealing metabolic-immune regulatory mechanisms in HNSCC.</p>

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Integrated bulk and single-cell transcriptomic analysis reveals the impact of lactate-related genes on prognosis and immune characteristics in HNSCC

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月12日

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  • Yuqing Wang,
  • Tao Shi,
  • Lisheng Yu,
  • Yixin Zhao

摘要

Head and neck squamous cell carcinoma (HNSCC) is a highly heterogeneous malignancy with poor prognosis, accompanied by metabolic reprogramming and tumor microenvironment (TME) disorders. Lactate metabolism is critical for tumor progression and immune escape, but its regulatory mechanism and clinical value in HNSCC remain unclear. We integrated single-cell and bulk RNA-sequencing data to identify lactate metabolism-related genes (LMGs). Using three machine learning algorithms, we selected six core LMGs and constructed a prognostic signature, which was validated in GSE41613 and GSE65858. Stem-like malignant cells showed the highest lactate metabolism activity among six epithelial subtypes. High-risk patients had shorter overall survival, with lower CD8 + T cell infiltration and higher M0 macrophages. Core genes were enriched in metabolic regulation and DNA replication. Compared with the high-risk group, low-risk patients exhibited higher sensitivity to chemotherapy and immunotherapy, and may benefit from BCL‑2/BCL‑XL inhibitors. Among the core genes, HPRT1 represents the most promising biomarker, whose expression is positively correlated with lactate production. This lactate‑related signature serves as a promising prognostic biomarker and therapeutic target, revealing metabolic-immune regulatory mechanisms in HNSCC.