Li Jiahui, Qiao Zihe, Li Yuwei, Lu Xinyan, Shao Tingru, Lv Xiaozhi
Department of Oral and Maxillofacial Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, 510280, China.
Heliyon. 2024 Jun 17;10(12):e33193. doi: 10.1016/j.heliyon.2024.e33193. eCollection 2024 Jun 30.
Oral squamous cell carcinoma (OSCC) stands as the predominant form of oral cancer, marked by a poor prognosis. Ferroptosis, a type of programmed cell death, plays a critical role in the initiation and progression of various cancers. Long non-coding RNAs (lncRNAs) are prominent in modulating cancer development. Nevertheless, the prognostic significance of ferroptosis-related lncRNAs (FRLs) in OSCC remains inadequately explored. This study aims to develop a predictive signature based on FRLs to forecast the prognosis of OSCC patients.
We gathered expression profiles of FRLs along with clinical data from The Cancer Genome Atlas (TCGA) and FerrDb databases. A prognostic model based on 10 FRLs were constructed using Cox regression analyses with LASSO algorithms, and their predictive power was evaluated. Then, the model was used to investigate functional enrichment, immune landscape, m6A genes, somatic variations, and drug response in different risk cohorts of patients. Finally, the expression and function of STARD4-AS1 (steroidogenic acute regulator protein-related lipid transfer domain containing 4-antisense RNA 1), a potential prognostic marker for OSCC screening based on our bioinformatics analysis, were investigated in vitro.
We developed a signature comprising 10 FRLs to stratify patients into two risk cohorts according to their calculated risk scores. Patients classified as high-risk exhibited significantly poorer prognoses compared to those in the low-risk cohort. Furthermore, survival analysis, patient risk heat plot, and risk curve verified the accuracy of the signature. The role of this signature in OSCC was well investigated using immune microenvironment, mutational, and gene set enrichment analysis (GSEA). Moreover, seven drugs, including cisplatin and docetaxel, were identified as potential treatments for patients with high-risk cancers. In addition, the knockdown of STARD4-AS1 in OSCC cell lines markedly inhibited cell proliferation and migration and induced ferroptosis.
Using this signature may improve overall survival predictions in OSCC, throwing new light on immunotherapies and targeted therapies. Moreover, STARD4-AS1 might regulate the process of ferroptosis and could be used as a novel biomarker of OSCC.
口腔鳞状细胞癌（OSCC）是口腔癌的主要形式，预后较差。铁死亡是一种程序性细胞死亡，在各种癌症的发生和发展中起关键作用。长链非编码RNA（lncRNA）在调节癌症发展方面很突出。然而，铁死亡相关lncRNA（FRL）在OSCC中的预后意义仍未得到充分探索。本研究旨在开发一种基于FRL的预测特征，以预测OSCC患者的预后。
我们从癌症基因组图谱（TCGA）和FerrDb数据库收集了FRL的表达谱以及临床数据。使用Cox回归分析和LASSO算法构建了一个基于10个FRL的预后模型，并评估了其预测能力。然后，该模型用于研究不同风险患者队列中的功能富集、免疫景观、m6A基因、体细胞变异和药物反应。最后，在体外研究了STARD4-AS1（含类固醇生成急性调节蛋白相关脂质转移结构域4反义RNA1）的表达和功能，它是基于我们的生物信息学分析用于OSCC筛查的潜在预后标志物。
我们开发了一个由10个FRL组成的特征，根据计算出的风险评分将患者分为两个风险队列。与低风险队列中的患者相比，被归类为高风险的患者预后明显更差。此外，生存分析、患者风险热图和风险曲线验证了该特征的准确性。使用免疫微环境、突变和基因集富集分析（GSEA）对该特征在OSCC中的作用进行了充分研究。此外，包括顺铂和多西他赛在内的七种药物被确定为高风险癌症患者的潜在治疗药物。此外，在OSCC细胞系中敲低STARD4-AS1可显著抑制细胞增殖和迁移并诱导铁死亡。
使用该特征可能会改善OSCC的总体生存预测，为免疫疗法和靶向疗法提供新的思路。此外，STARD4-AS1可能调节铁死亡过程，并可作为OSCC的新型生物标志物。
