Department of Oral and Maxillofacial Surgery, Affiliated Stomatology Hospital of Kunming Medical University, Kunming, China; Yunnan Key Laboratory of Stomatology, Kunming, China.
Yunnan Key Laboratory of Stomatology, Kunming, China; Department of Operative Dentistry, Preventive Dentistry and Endodontics, School of Stomatology, The Affiliated Stomatology Hospital, Kunming Medical University, Kunming, China.
Int Dent J. 2024 Oct;74(5):1053-1063. doi: 10.1016/j.identj.2024.04.005. Epub 2024 Apr 26.
Oral squamous cell carcinoma (OSCC) is the most common malignant tumour in the oral and maxillofacial region. Lactic acid accumulation in the tumour microenvironment (TME) has gained attention for its dual role as an energy source for cancer cells and an activator of signalling pathways crucial to tumour progression. This study aims to reveal the impact of lactate-related genes (LRGs) on the prognosis, TME, and immune characteristics of OSCC, with the ultimate goal of developing a novel prognostic model.
Unsupervised clustering analysis of LRGs in OSCC patients from The Cancer Genome Atlas database was conducted to evaluate and compare TME, immune features, and clinical characteristics across various lactate subtypes. A refined prognostic model was developed through the application of Cox and Least absolute shrinkage and selection operator (LASSO) regression techniques. External validation sets were then utilised to improve model accuracy, along with a detailed correlation analysis of drug sensitivity.
The Cancer Genome Atlas-OSCC patients were categorised into 4 distinct lactate subtypes based on LRGs. Notably, patients in subtype 1 and subtype 2 exhibited the least and most favourable prognoses, respectively. Subtype 1 patients showed elevated expression levels of immune checkpoint genes. Further analysis identified 1086 genes with significant expression differences between cancer and noncancer tissues, as well as between subtype 1 and subtype 2 patients. Selected genes for the prognostic model included ZNF662, CGNL1, VWCE, and ZFP42. The high-risk group defined by this model had a significantly poorer prognosis (P < .0001) and functioned as an independent prognostic factor (P < .001), accurately predicting 1-, 3-, and 5-year survival rates. Additionally, individuals in the high-risk category exhibited heightened sensitivity to chemotherapy drugs such as AZ6102 and Venetoclax.
The predictive model based on the genes ZNF662, CGNL1, VWCE, and ZFP42 can serve as a reliable biomarker, providing accurate prognostic predictions for OSCC patients and potential opportunities for pharmaceutical interventions.
口腔鳞状细胞癌（OSCC）是口腔颌面区域最常见的恶性肿瘤。肿瘤微环境（TME）中乳酸的积累因其作为癌细胞的能量来源和激活对肿瘤进展至关重要的信号通路的双重作用而受到关注。本研究旨在揭示乳酸相关基因（LRGs）对 OSCC 预后、TME 和免疫特征的影响，并最终开发一种新的预后模型。
对来自癌症基因组图谱（TCGA）数据库的 OSCC 患者的 LRGs 进行无监督聚类分析，以评估和比较不同乳酸亚型的 TME、免疫特征和临床特征。通过应用 Cox 和最小绝对收缩和选择算子（LASSO）回归技术开发了一个改良的预后模型。然后利用外部验证集来提高模型的准确性，并进行药物敏感性的详细相关性分析。
根据 LRGs，TCGA-OSCC 患者被分为 4 个不同的乳酸亚型。值得注意的是，亚型 1 和亚型 2 的患者分别具有最差和最佳的预后。亚型 1 患者的免疫检查点基因表达水平升高。进一步分析确定了 1086 个在癌症和非癌症组织之间以及在亚型 1 和亚型 2 患者之间表达差异显著的基因。用于预后模型的选定基因包括 ZNF662、CGNL1、VWCE 和 ZFP42。该模型定义的高风险组具有显著较差的预后（P<0.0001），并且是一个独立的预后因素（P<0.001），准确预测了 1、3 和 5 年的生存率。此外，高风险组的个体对 AZ6102 和 Venetoclax 等化疗药物表现出更高的敏感性。
基于 ZNF662、CGNL1、VWCE 和 ZFP42 基因的预测模型可以作为一种可靠的生物标志物，为 OSCC 患者提供准确的预后预测，并为药物干预提供潜在机会。
