Xiao Jian, Li Wei, Tan Guolin, Gao Ru
Department of Otolaryngology-Head and Neck Surgery, The Third Xiangya Hospital of Central South University, Changsha, Hunan, China.
Front Genet. 2025 Apr 4;16:1540841. doi: 10.3389/fgene.2025.1540841. eCollection 2025.
Lactate, traditionally viewed as a byproduct of glycolysis, is increasingly recognized as a pivotal regulatory factor in cancer biology. This study addresses the limited understanding of lactate metabolism-related genes in head and neck squamous cell carcinoma (HNSC) by constructing a prognostic risk model centered on these genes to enhance prediction and treatment strategies for HNSC. Utilizing the Lactate Metabolism score (LMs) derived from The Cancer Genome Atlas (TCGA), we identified five key genes significantly associated with prognosis in HNSC patients. These genes were integrated into a prognostic risk model developed through Cox regression analysis, which demonstrated superior predictive performance, achieving area under the curve (AUC) values greater than 0.8 for five-year survival. The risk scores generated by our model were significantly correlated with critical features of the tumor microenvironment, including immune characteristics and markers of immune evasion. Higher risk scores correlated with a more tumor-promoting microenvironment and increased immune suppression, underscoring the model's relevance in understanding HNSC progression. Additionally, eight critical hub genes were identified, revealing significant differences in gene expression between risk score groups. Functional analyses demonstrated that the low-risk group exhibited a more favorable prognosis and enhanced immune characteristics. Our findings suggest that the lactate metabolism-based prognostic model may have implications for guiding the development of personalized treatment approaches, as it highlights the potential for targeted interventions that could modulate the tumor microenvironment and immune response.
乳酸,传统上被视为糖酵解的副产物,如今越来越被认为是癌症生物学中的一个关键调节因子。本研究旨在通过构建一个以这些基因为中心的预后风险模型,来解决对头颈部鳞状细胞癌(HNSC)中乳酸代谢相关基因认识有限的问题,以加强HNSC的预测和治疗策略。利用从癌症基因组图谱(TCGA)得出的乳酸代谢评分(LMs),我们确定了五个与HNSC患者预后显著相关的关键基因。这些基因被整合到通过Cox回归分析开发的预后风险模型中,该模型显示出卓越的预测性能,五年生存率的曲线下面积(AUC)值大于0.8。我们模型生成的风险评分与肿瘤微环境的关键特征显著相关,包括免疫特征和免疫逃逸标志物。较高的风险评分与更有利于肿瘤生长的微环境和更强的免疫抑制相关,突出了该模型在理解HNSC进展方面的相关性。此外,还确定了八个关键的枢纽基因,揭示了风险评分组之间基因表达的显著差异。功能分析表明,低风险组表现出更有利的预后和更强的免疫特征。我们的研究结果表明,基于乳酸代谢的预后模型可能对指导个性化治疗方法的开发具有意义,因为它突出了靶向干预的潜力,这种干预可以调节肿瘤微环境和免疫反应。