Shanxi Province Key Laboratory of Oral Diseases Prevention and New Materials, Shanxi Medical University School and Hospital of Stomatology, Taiyuan, Shanxi, China.
Department of Physiology, School of Medicine.
Cancer Biomark. 2024;40(3-4):319-342. doi: 10.3233/CBM-230407.
Necroptosis is a caspase-independent regulated necrotic cell death modality that elicits strong adaptive immune responses, and has the potential to activate antitumor immunity. Long non-coding RNAs (lncRNAs) have critical effects on oral squamous cell carcinoma (OSCC), which are closely associated with the prognosis and immune regulation of OSCC patients.
This study aimed to identify a novel necroptosis-related lncRNAs signature to predict the prognosis and immune response of OSCC patients and provide patients with anti-tumor drug selection through bioinformatics analysis and in vitro experiments.
A series of analyses, including differential lncRNA screening, survival analysis, Cox regression analysis, ROC analysis, nomogram prediction, enrichment analysis, tumor-infiltrating immune cells, drug sensitivity analysis, and consensus cluster analysis, were performed to determine and validate the prognostic value of necroptosis-associated lncRNAs signature in OSCC. And real-time quantitative polymerase chain reaction (RT-qPCR) was used to determine the expression levels of these lncRNAs.
This signature including 5 lncRNAs (AC099850.3, StarD4-AS1, AC011978.1, LINC01503, CDKN2A-DT) in OSCC associated with necroptosis were established and verified by bioinformatics. Further, ROC, K-M, univariate/multivariate Cox regression, and nomogram analysis were used to evaluate the model's features for OSCC prognosis. Using multiple bioinformatics techniques, the levels of tumor-infiltrating immune cells, immune checkpoints and semi-inhibitory concentrations showed significant differences across risk subtypes. By consensus cluster analysis, there were significant differences between clusters in survival, immune checkpoint expression, clinicopathological correlation, and tumor immunity. RT-qPCR showed that AC099850.3, AC011978.1, LINC01503 were up-regulated, STARD4-AS1 and CDKN2A-DT were down-regulated in OSCC cell lines compared with human normal oral keratinoid cell line.
We established 5-NRLs markers, which is useful for assessing OSCC immune response and prognosis, recommending personalized antitumor drugs. The expression level of 5-NRLs in OSCC was identified in vitro, and the results preliminarily verified this model. And this study would generate new insights for future experimental research.
细胞坏死是一种不依赖于半胱天冬酶的调控性坏死细胞死亡方式,可引发强烈的适应性免疫反应,并有激活抗肿瘤免疫的潜力。长链非编码 RNA(lncRNA)对口腔鳞状细胞癌(OSCC)具有重要影响,与 OSCC 患者的预后和免疫调节密切相关。
本研究旨在通过生物信息学分析和体外实验,鉴定一种新的坏死相关 lncRNA 标志物,以预测 OSCC 患者的预后和免疫反应,并为患者提供抗肿瘤药物选择。
进行了一系列分析,包括差异 lncRNA 筛选、生存分析、Cox 回归分析、ROC 分析、列线图预测、富集分析、肿瘤浸润免疫细胞、药物敏感性分析和共识聚类分析,以确定和验证与 OSCC 中坏死相关的 lncRNA 标志物的预后价值。实时定量聚合酶链反应(RT-qPCR)用于测定这些 lncRNA 的表达水平。
本研究通过生物信息学方法建立并验证了与 OSCC 中坏死相关的包含 5 个 lncRNA(AC099850.3、StarD4-AS1、AC011978.1、LINC01503、CDKN2A-DT)的 lncRNA 标志物。进一步通过 ROC、K-M、单因素/多因素 Cox 回归和列线图分析评估了该模型在预测 OSCC 预后方面的特征。通过多种生物信息学技术,不同风险亚型之间的肿瘤浸润免疫细胞、免疫检查点和半抑制浓度水平存在显著差异。通过共识聚类分析,在生存、免疫检查点表达、临床病理相关性和肿瘤免疫方面,各聚类之间存在显著差异。RT-qPCR 显示与正常人口腔角质细胞系相比,OSCC 细胞系中 AC099850.3、AC011978.1、LINC01503 呈上调表达,STARD4-AS1 和 CDKN2A-DT 呈下调表达。
本研究建立了 5 个 NRLs 标志物,有助于评估 OSCC 免疫反应和预后,并为个体化抗肿瘤药物治疗提供建议。在体外鉴定了 5-NRLs 在 OSCC 中的表达水平,初步验证了该模型。本研究为进一步的实验研究提供了新的思路。