Integrated Single-cell and Bulk RNA Sequencing Analysis Cross Talk between Ferroptosis-related Genes and Prognosis in Oral Cavity Squamous Cell Carcinoma.

IF 2.5 4区 医学 Q3 ONCOLOGY Recent patents on anti-cancer drug discovery Pub Date : 2024-01-01 DOI:10.2174/1574892818666230602112042
Tianjun Lan, Siqi Ren, Huijun Hu, Ruixin Wang, Qian Chen, Fan Wu, Qiuping Xu, Yanyan Li, Libin Shao, Liansheng Wang, Xin Liu, Haotian Cao, Jinsong Li
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Abstract

Background: Ferroptosis is a new type of programmed apoptosis and plays an important role in tumour inhibition and immunotherapy.

Objective: In this study, we aimed to explore the potential role of ferroptosis-related genes (FRGs) and the potential therapeutic targets in oral cavity squamous cell carcinoma (OCSCC).

Methods: The transcription data of OCSCC samples were obtained from the Cancer Genome Atlas (TCGA) database as a training dataset. The prognostic FRGs were extracted by univariate Cox regression analysis. Then, we constructed a prognostic model using the least absolute shrinkage and selection operator (LASSO) and Cox analysis to determine the independent prognosis FRGs. Based on this model, risk scores were calculated for the OCSCC samples. The model's capability was further evaluated by the receiver operating characteristic curve (ROC). Then, we used the GSE41613 dataset as an external validation cohort to confirm the model's predictive capability. Next, the immune infiltration and somatic mutation analysis were applied. Lastly, single-cell transcriptomic analysis was used to identify the key cells.

Results: A total of 12 prognostic FRGs were identified. Eventually, 6 FRGs were screened as independent predictors and a prognostic model was constructed in the training dataset, which significantly stratified OCSCC samples into high-risk and low-risk groups based on overall survival. The external validation of the model using the GSE41613 dataset demonstrated a satisfactory predictive capability for the prognosis of OCSCC. Further analysis revealed that patients in the highrisk group had distinct immune infiltration and somatic mutation patterns from low-risk patients. Mast cell infiltrations were identified as prognostic immune cells and played a role in OCSCC partly through ferroptosis.

Conclusion: We successfully constructed a novel 6 FRGs model and identified a prognostic immune cell, which can serve to predict clinical prognoses for OCSCC. Ferroptosis may be a new direction for immunotherapy of OCSCC.

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口腔鳞状细胞癌脱铁相关基因与预后的整合单细胞和体RNA测序分析
铁凋亡是一种新型的程序性细胞凋亡,在肿瘤抑制和免疫治疗中发挥着重要作用。在这项研究中,我们旨在探讨铁中毒相关基因(FRGs)在口腔鳞状细胞癌(OCSCC)中的潜在作用和潜在的治疗靶点。OCSCC样本的转录数据来自癌症基因组图谱(Cancer Genome Atlas, TCGA)数据库作为训练数据集。采用单因素Cox回归分析提取预后frg。然后,我们使用最小绝对收缩和选择算子(LASSO)和Cox分析构建预后模型,以确定独立的预后frg。基于该模型,计算OCSCC样本的风险评分。通过受试者工作特征曲线(ROC)进一步评价模型的性能。然后,我们使用GSE41613数据集作为外部验证队列来验证模型的预测能力。接下来进行免疫浸润和体细胞突变分析。最后,利用单细胞转录组学分析鉴定关键细胞。共鉴定出12个预后frg。最终,筛选6个frg作为独立预测因子,并在训练数据集中构建预后模型,根据总生存率将OCSCC样本显著分层为高风险和低风险组。使用GSE41613数据集对模型进行外部验证,结果表明该模型对OCSCC的预后具有令人满意的预测能力。进一步分析显示,高危组患者与低危组患者具有明显的免疫浸润和体细胞突变模式。肥大细胞浸润被确定为预后免疫细胞,部分通过铁下垂在OCSCC中发挥作用。我们成功构建了一种新的6 FRGs模型,并鉴定了一种预后免疫细胞,可用于预测OCSCC的临床预后。铁下垂可能是OCSCC免疫治疗的新方向。
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来源期刊
CiteScore
4.50
自引率
7.10%
发文量
55
审稿时长
3 months
期刊介绍: Aims & Scope Recent Patents on Anti-Cancer Drug Discovery publishes review and research articles that reflect or deal with studies in relation to a patent, application of reported patents in a study, discussion of comparison of results regarding application of a given patent, etc., and also guest edited thematic issues on recent patents in the field of anti-cancer drug discovery e.g. on novel bioactive compounds, analogs, targets & predictive biomarkers & drug efficacy biomarkers. The journal also publishes book reviews of eBooks and books on anti-cancer drug discovery. A selection of important and recent patents on anti-cancer drug discovery is also included in the journal. The journal is essential reading for all researchers involved in anti-cancer drug design and discovery. The journal also covers recent research (where patents have been registered) in fast emerging therapeutic areas/targets & therapeutic agents related to anti-cancer drug discovery.
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