通过空间转录组学和机器学习探索非小细胞肺癌的肿瘤微环境相互作用和凋亡途径。

IF 4.9 2区 医学 Q2 CELL BIOLOGY Cellular Oncology Pub Date : 2024-12-01 Epub Date: 2024-12-19 DOI:10.1007/s13402-024-01025-6
Huimin Li, Yuheng Jiao, Yi Zhang, Junzhi Liu, Shuixian Huang
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引用次数: 0

摘要

背景:最常见的肺癌类型是非小细胞肺癌(NSCLC),占所有病例的85%。细胞程序性死亡(Programmed cell death, PCD)作为细胞存活和稳态的重要调控机制,近年来在肿瘤研究中得到越来越多的关注。因此,探索PCD在非小细胞肺癌中的作用可能有助于揭示治疗靶点的新机制。方法:利用GEO数据库和TCGA NSCLC基因数据筛选共表达基因。为了深入研究,我们采用单细胞测序结合空间转录组学来研究细胞程序性死亡的内在机制及其与肿瘤微环境的相互作用。此外,孟德尔随机化应用筛选因果相关基因。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,揭示基因的生物学功能及其与细胞凋亡的关系。结果:具有高程序性细胞死亡活性的细胞主要激活与凋亡、细胞迁移和缺氧相关的途径,同时也与肿瘤微环境中的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促进了NSCLC细胞的增殖,敲除SLC7A5可显著增加肿瘤细胞的凋亡。结论:我们的数据表明程序性细胞死亡主要与凋亡、肿瘤转移和缺氧相关的途径相关。提示SLC7A5是非小细胞肺癌(non-small cell lung cancer, NSCLC)预后的重要危险指标,可能是促进NSCLC肿瘤细胞凋亡的有效靶点。
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Exploring tumor microenvironment interactions and apoptosis pathways in NSCLC through spatial transcriptomics and machine learning.

Background: 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.

Methods: 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.

Results: 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.

Conclusions: 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.

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来源期刊
Cellular Oncology
Cellular Oncology ONCOLOGY-CELL BIOLOGY
CiteScore
10.30
自引率
1.50%
发文量
86
审稿时长
12 months
期刊介绍: The Official Journal of the International Society for Cellular Oncology Focuses on translational research Addresses the conversion of cell biology to clinical applications Cellular Oncology publishes scientific contributions from various biomedical and clinical disciplines involved in basic and translational cancer research on the cell and tissue level, technical and bioinformatics developments in this area, and clinical applications. This includes a variety of fields like genome technology, micro-arrays and other high-throughput techniques, genomic instability, SNP, DNA methylation, signaling pathways, DNA organization, (sub)microscopic imaging, proteomics, bioinformatics, functional effects of genomics, drug design and development, molecular diagnostics and targeted cancer therapies, genotype-phenotype interactions. A major goal is to translate the latest developments in these fields from the research laboratory into routine patient management. To this end Cellular Oncology forms a platform of scientific information exchange between molecular biologists and geneticists, technical developers, pathologists, (medical) oncologists and other clinicians involved in the management of cancer patients. In vitro studies are preferentially supported by validations in tumor tissue with clinicopathological associations.
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