Li Yuqin, Wu Dejun, Xu Anjun, Xu Ming, Fu Baiqing, Xiong Wujun
Department of Gastroenterology, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, 2800 Gongwei Road, Pudong New District, Shanghai, 201399, China.
Department of General Surgery, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, 2800 Gongwei Road, Shanghai, 201399, China.
Heliyon. 2024 Jun 27;10(13):e33759. doi: 10.1016/j.heliyon.2024.e33759. eCollection 2024 Jul 15.
Natural killer (NK) cells play a significant role in anti-tumor immunity, and their involvement has been documented in various cancers. However, a deeper understanding of the mechanisms by which NK cells influence gastric cancer progression remains necessary.
We utilized the Cancer Genome Atlas (TCGA) database to acquire transcriptional profiles, clinical information, and mutation data for gastric cancer patients. R software and associated packages were employed for all analyses of this publicly available data.
We used multiple algorithms to evaluate the tumor microenvironment in gastric cancer samples. We performed differential expression analysis to pinpoint genes related to NK cells. Utilizing this data, we developed a prognostic model featuring three crucial NK cell-related genes: MAB21L2, ARPP21, and MUCL1. This model showed strong predictive performance in the training and validation groups. Consistently, patients identified as high-risk according to our model had worse overall survival rates. To further elucidate the biological differences between high-risk and low-risk patients, we performed enrichment analyses focusing on biological pathways and immune-related factors. Additionally, we observed a correlation between higher risk scores and non-responsiveness to treatment. Interestingly, high-risk patients were found to be potentially more sensitive to axitinib. We selected MUCL1 for further investigation due to its potential role in the model. While MUCL1 mRNA levels were elevated in both gastric cancer and paired normal tissues, protein expression analysis using the Human Protein Atlas database revealed a decrease in MUCL1 protein levels within tumor tissues.
Our findings contribute to a more comprehensive understanding of the role of NK cells in gastric cancer and highlight MUCL1 as a promising therapeutic target.
自然杀伤(NK)细胞在抗肿瘤免疫中发挥重要作用,其参与多种癌症已得到证实。然而,仍有必要更深入地了解NK细胞影响胃癌进展的机制。
我们利用癌症基因组图谱(TCGA)数据库获取胃癌患者的转录谱、临床信息和突变数据。使用R软件及相关软件包对这些公开数据进行所有分析。
我们使用多种算法评估胃癌样本中的肿瘤微环境。进行差异表达分析以确定与NK细胞相关的基因。利用这些数据,我们开发了一个预后模型,该模型包含三个关键的NK细胞相关基因:MAB21L2、ARPP21和MUCL1。该模型在训练组和验证组中均表现出强大的预测性能。同样,根据我们的模型被确定为高危的患者总体生存率较差。为了进一步阐明高危和低危患者之间的生物学差异,我们针对生物途径和免疫相关因素进行了富集分析。此外,我们观察到较高风险评分与治疗无反应之间存在相关性。有趣的是,发现高危患者可能对阿昔替尼更敏感。由于其在模型中的潜在作用,我们选择MUCL1进行进一步研究。虽然MUCL1 mRNA水平在胃癌组织和配对的正常组织中均升高,但使用人类蛋白质图谱数据库进行的蛋白质表达分析显示肿瘤组织内MUCL1蛋白水平降低。
我们的研究结果有助于更全面地了解NK细胞在胃癌中的作用,并突出MUCL1作为一个有前景的治疗靶点。