Li Huimin, Jiao Yuheng, Zhang Yi, Liu Junzhi, Huang Shuixian
Department of Internal Medicine Residency Training Base, Gongli Hospital of Shanghai Pudong New Area, Shanghai, 200135, China.
Department of Heart Failure, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, 200120, China.
Cell Oncol (Dordr). 2024 Dec;47(6):2383-2405. doi: 10.1007/s13402-024-01025-6. Epub 2024 Dec 19.
The most common type of lung cancer is non-small cell lung cancer (NSCLC), accounting for 85% of all cases. Programmed cell death (PCD), an important regulatory mechanism for cell survival and homeostasis, has become increasingly prominent in cancer research in recent years. As such, exploring the role of PCD in NSCLC may help uncover new mechanisms for therapeutic targets.
We utilized the GEO database and TCGA NSCLC gene data to screen for co-expressed genes. To delve deeper, single-cell sequencing combined with spatial transcriptomics was employed to study the intrinsic mechanisms of programmed cell death in cells and their interaction with the tumor microenvironment. Furthermore, Mendelian randomization was applied to screen for causally related genes. Prognostic models were constructed using various machine learning algorithms, and multi-cohort multi-omics analyses were conducted to screen for genes. In vitro experiments were then carried out to reveal the biological functions of the genes and their relationship with apoptosis.
Cells with high programmed cell death activity primarily activate pathways related to apoptosis, cell migration, and hypoxia, while also exhibiting strong interactions with smooth muscle cells in the tumor microenvironment. Based on a set of programmed cell death genes, the prognostic model NSCLCPCD demonstrates strong predictive capabilities. Moreover, laboratory experiments confirm that SLC7A5 promotes the proliferation of NSCLC cells, and the knockout of SLC7A5 significantly increases tumor cell apoptosis.
Our data indicate that programmed cell death is predominantly associated with pathways related to apoptosis, tumor metastasis, and hypoxia. Additionally, it suggests that SLC7A5 is a significant risk indicator for the prognosis of non-small cell lung cancer (NSCLC) and may serve as an effective target for enhancing apoptosis in NSCLC tumor cells.
最常见的肺癌类型是非小细胞肺癌（NSCLC），占所有病例的85%。程序性细胞死亡（PCD）是细胞存活和体内平衡的重要调节机制，近年来在癌症研究中日益突出。因此，探索PCD在NSCLC中的作用可能有助于揭示治疗靶点的新机制。
我们利用GEO数据库和TCGA NSCLC基因数据筛选共表达基因。为了更深入地研究，采用单细胞测序结合空间转录组学来研究细胞中程序性细胞死亡的内在机制及其与肿瘤微环境的相互作用。此外，应用孟德尔随机化筛选因果相关基因。使用各种机器学习算法构建预后模型，并进行多队列多组学分析以筛选基因。然后进行体外实验以揭示基因的生物学功能及其与细胞凋亡的关系。
具有高程序性细胞死亡活性的细胞主要激活与细胞凋亡、细胞迁移和缺氧相关的通路，同时在肿瘤微环境中也与平滑肌细胞表现出强烈的相互作用。基于一组程序性细胞死亡基因，预后模型NSCLCPCD显示出强大的预测能力。此外，实验室实验证实SLC7A5促进NSCLC细胞的增殖，敲除SLC7A5可显著增加肿瘤细胞凋亡。
我们的数据表明，程序性细胞死亡主要与细胞凋亡、肿瘤转移和缺氧相关的通路有关。此外，这表明SLC7A5是非小细胞肺癌（NSCLC）预后的一个重要风险指标，并且可能作为增强NSCLC肿瘤细胞凋亡的有效靶点。
