Wen Hao, Zhang Panpan, Zhao Juan, Liu Yakui, Wan Lei, Li Haoran, Yi Jun, Li Xinqiang
Department of Thoracic and Cardiovascular Surgery, The Central Hospital of Jingmen, Jingmen, Hubei, China.
Wuhan Pulmonary Hospital, Respiratory and Critical Care 2, Wuhan, China.
Sci Rep. 2025 Jul 8;15(1):24440. doi: 10.1038/s41598-025-87361-5.
Non-small cell lung cancer (NSCLC) is a leading cause of cancer-related deaths worldwide. Despite advancements in treatment, prognosis for patients with advanced stages remains poor. Metabolic reprogramming in the tumor microenvironment, particularly abnormal glycolysis, plays a crucial role in immune evasion and treatment response. We collected nine single-cell datasets to create a single-cell atlas of CD8 + T cells from 89 NSCLC patients, revealing ten distinct states of these cells. We employed a multimodal data analysis approach, integrating bulk transcriptomics, single-cell transcriptomics, spatial transcriptomics, and proteomics. Using 117 machine learning models, we identified key genes associated with NSCLC metastasis. Notably, the StepCox[forward] + Lasso model was instrumental in pinpointing key genes that significantly impact disease prognosis. Our analysis revealed that LTB + LDHA + CD8 + T cells have a distinct metabolic and immune phenotype, characterized by enhanced glycolysis and elevated lactate production. This not only facilitates tumor cell migration and invasion but also impairs the cytotoxic function of CD8 + T cells. Furthermore, our machine learning models identified four key genes significantly associated with NSCLC metastasis: TBCD, PTPRC, LDHA, and ACTR2. Of these, high LDHA expression was strongly linked to poorer responses to immunotherapy and a higher risk of therapy resistance. LTB + LDHA + CD8 + T cells also reduced antitumor immune responses by inhibiting the secretion of effector molecules like GNLY. Additionally, elevated LDHA expression was associated with reduced CD8 + T cell infiltration, which further promotes tumor immune evasion. This study highlights the heterogeneity of CD8 + T cells in NSCLC, emphasizing the unique role of the LTB + CD8 + Tn subpopulation in metastasis. LDHA is identified as a critical key gene with a significant impact on immunotherapy outcomes, presenting a potential therapeutic target. These insights offer new biomarkers and targeted strategies for personalized immune therapy.
非小细胞肺癌（NSCLC）是全球癌症相关死亡的主要原因。尽管治疗取得了进展，但晚期患者的预后仍然很差。肿瘤微环境中的代谢重编程，尤其是异常糖酵解，在免疫逃逸和治疗反应中起着关键作用。我们收集了9个单细胞数据集，以创建来自89名NSCLC患者的CD8 + T细胞单细胞图谱，揭示了这些细胞的10种不同状态。我们采用了多模态数据分析方法，整合了批量转录组学、单细胞转录组学、空间转录组学和蛋白质组学。使用117个机器学习模型，我们确定了与NSCLC转移相关的关键基因。值得注意的是，StepCox[forward] + Lasso模型有助于确定对疾病预后有显著影响的关键基因。我们的分析表明，LTB + LDHA + CD8 + T细胞具有独特的代谢和免疫表型，其特征是糖酵解增强和乳酸产生增加。这不仅促进肿瘤细胞迁移和侵袭，还损害CD8 + T细胞的细胞毒性功能。此外，我们的机器学习模型确定了与NSCLC转移显著相关的四个关键基因：TBCD、PTPRC、LDHA和ACTR2。其中，高LDHA表达与免疫治疗反应较差和治疗耐药风险较高密切相关。LTB + LDHA + CD8 + T细胞还通过抑制GNLY等效应分子的分泌来降低抗肿瘤免疫反应。此外，LDHA表达升高与CD8 + T细胞浸润减少有关，这进一步促进肿瘤免疫逃逸。这项研究突出了NSCLC中CD8 + T细胞的异质性，强调了LTB + CD8 + Tn亚群在转移中的独特作用。LDHA被确定为对免疫治疗结果有重大影响的关键基因，是一个潜在的治疗靶点。这些见解为个性化免疫治疗提供了新的生物标志物和靶向策略。
