Zhang Shengyi, Li Xinhan, Xiahou Zhikai, Chen Ailing, Sun Renfang, Liu Chao, Yuan Jie
Department of Thoracic Surgery, Songjiang Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 201600, China.
The First Clinical Medical College of Shandong University of Traditional Chinese Medicine, Jinan, China.
Transl Oncol. 2025 Apr;54:102295. doi: 10.1016/j.tranon.2025.102295. Epub 2025 Feb 26.
In both industrialized and developing nations worldwide, lung adenocarcinoma is one of the deadliest malignant tumors and the primary cause of cancer-related deaths. Its cellular heterogeneity is unclear to the fullest extent, although in recent years, its prevalence in younger individuals has increased. Therefore, it is urgent to deepen the understanding of lung adenocarcinoma and explore new therapeutic methods.
CytoTRACE, Monocle, SCENIC, and enrichment analysis were used to analyze the single cell RNA data, we characterized the biological characteristics of mast cells (MCs) in lung adenocarcinoma patient samples. CellChat was used to analyze and validate the interaction between MCs and tumor cells in lung adenocarcinoma. Prognostic models were used to evaluate and predict the development trend and outcome of a patient's disease, such as the survival time of cancer patients. The python package SCENIC was used to evaluate the enrichment of transcription factors and the activity of regulators in lung adenocarcinoma cell subgroups. CCK-8 assay could validate the activity of a specific cell subgroup sequenced in single cell sequencing to confirm the role of this cell subgroup in tumor proliferation.
Our analysis identified seven major cell types, further grouping MCs within them and identifying four distinct subgroups, including MCs with high DUSP2 expression, which showed some tumor-related characteristics. In addition, we identified the key signaling receptor EGFR and validated it through in vitro knockdown experiments, demonstrating its role in promoting cancer. In addition, we established an independent prognostic indicator, the DUSP2+ MCs risk score, which showed an association between groups with high risk scores and poor outcomes.
These findings shed light on the complex interactions in the lung adenocarcinoma tumor microenvironment and suggest that targeting specific MCs subgroups, particularly through the EGFR signaling pathway, may provide new therapeutic strategies.
在全球范围内的工业化国家和发展中国家，肺腺癌都是最致命的恶性肿瘤之一，也是癌症相关死亡的主要原因。尽管近年来其在年轻个体中的患病率有所增加，但其细胞异质性仍未完全明确。因此，迫切需要加深对肺腺癌的理解并探索新的治疗方法。
使用CytoTRACE、Monocle、SCENIC和富集分析来分析单细胞RNA数据，我们对肺腺癌患者样本中肥大细胞（MCs）的生物学特征进行了表征。使用CellChat分析并验证肺腺癌中MCs与肿瘤细胞之间的相互作用。使用预后模型评估和预测患者疾病的发展趋势和结果，例如癌症患者的生存时间。使用Python包SCENIC评估肺腺癌细胞亚群中转录因子的富集情况和调节因子的活性。CCK-8测定可以验证单细胞测序中特定细胞亚群的活性，以确认该细胞亚群在肿瘤增殖中的作用。
我们的分析确定了七种主要细胞类型，进一步将其中的MCs进行分组并识别出四个不同的亚群，包括具有高DUSP2表达的MCs，其表现出一些与肿瘤相关的特征。此外，我们确定了关键信号受体EGFR，并通过体外敲低实验对其进行了验证，证明了其在促进癌症方面的作用。此外，我们建立了一个独立的预后指标，即DUSP2+MCs风险评分，该评分显示高风险评分组与不良结果之间存在关联。
这些发现揭示了肺腺癌肿瘤微环境中的复杂相互作用，并表明靶向特定的MCs亚群，特别是通过EGFR信号通路，可能提供新的治疗策略。
