通过全转录组测序和生物信息学分析鉴定口腔鳞状细胞癌中涉及的新型生物标志物。

Identification of novel biomarkers involved in oral squamous cell carcinoma by whole transcriptome sequencing and bioinformatics analysis.

作者信息

Du Hongliang, Wang Zhenze, Qi Mengyi, Pang Yunqing, Lin Qingling, He Dengqi, Wang Jing

机构信息

The First Clinical Medical College of Lanzhou University, Lanzhou, 730000, China.

Department of Oral and Maxillofacial Surgery, The First Hospital of Lanzhou University, Lanzhou, 730000, China.

出版信息

Cancer Cell Int. 2025 Jul 22;25(1):277. doi: 10.1186/s12935-025-03913-9.

DOI:10.1186/s12935-025-03913-9

PMID:40696350

Abstract

BACKGROUND

Oral squamous cell carcinoma (OSCC) is among the most common malignant tumors in the oral and maxillofacial regions, characterized by high drug resistance and poor treatment outcomes. This underscores the urgent need to identify novel biomarkers for OSCC.

METHODS

Differentially expressed messenger RNAs (mRNAs), microRNAs (miRNAs), and long non-coding RNAs (lncRNAs) (DE-mRNAs, DE-miRNAs, and DE-lncRNAs) between primary and control groups, as well as metastatic and primary groups, were identified using whole transcriptome sequencing data. Candidate OSCC genes were derived from DE-mRNAs. Potential biomarkers were then identified using five algorithms from CytoHubba. Biomarkers were validated via univariate Cox regression and Kaplan-Meier (K-M) survival analysis. Additional analyses included subcellular localization, mutation analysis, and Gene Set Enrichment Analysis (GSEA). Key drugs for OSCC treatment were also identified. Quantitative real time polymerase chain reaction (qRT-PCR) and immunohistochemistry were employed to verify the expression levels of key biomarkers.

RESULTS

A total of 304 candidate genes were identified, with 29 potential biomarkers selected by five algorithms. ANPEP, APOB, GLP1R, and SI exhibited significant survival differences in the K-M curves, establishing them as OSCC biomarkers. These biomarkers were predominantly localized in the cytoplasm, with SI and APOB showing the highest mutation susceptibility. Enrichment analysis revealed that the 'interferon-gamma response'biological function was co-enriched by ANPEP, APOB, and SI. Furthermore, BIBW2992 (afatinib) and PF.02341066 (crizotinib) were most strongly correlated with the biomarkers, suggesting their potential as key drugs for OSCC treatment. Additionally, the findings were validated by qRT-PCR and immunohistochemical analyses, and the results were consistent with the RNA-seq data.

CONCLUSION

ANPEP, APOB, GLP1R, and SI were identified as potential OSCC biomarkers, offering valuable insights for further research and therapeutic development.

摘要

背景

口腔鳞状细胞癌（OSCC）是口腔颌面部最常见的恶性肿瘤之一，具有高耐药性和较差的治疗效果。这凸显了迫切需要鉴定OSCC的新型生物标志物。

方法

利用全转录组测序数据，鉴定原发性组与对照组以及转移组与原发性组之间差异表达的信使核糖核酸（mRNA）、微小核糖核酸（miRNA）和长链非编码核糖核酸（lncRNA）（差异表达mRNA、差异表达miRNA和差异表达lncRNA）。候选OSCC基因源自差异表达mRNA。然后使用来自CytoHubba的五种算法鉴定潜在的生物标志物。通过单变量Cox回归和Kaplan-Meier（K-M）生存分析验证生物标志物。额外的分析包括亚细胞定位、突变分析和基因集富集分析（GSEA）。还确定了OSCC治疗的关键药物。采用定量实时聚合酶链反应（qRT-PCR）和免疫组织化学法验证关键生物标志物的表达水平。

结果

共鉴定出304个候选基因，通过五种算法选择出29个潜在生物标志物。ANPEP、APOB、GLP1R和SI在K-M曲线中表现出显著的生存差异，将它们确立为OSCC生物标志物。这些生物标志物主要定位于细胞质中，SI和APOB显示出最高的突变易感性。富集分析表明，“干扰素-γ反应”生物学功能由ANPEP、APOB和SI共同富集。此外，BIBW2992（阿法替尼）和PF.02341066（克唑替尼）与生物标志物的相关性最强，表明它们作为OSCC治疗关键药物的潜力。此外，研究结果通过qRT-PCR和免疫组织化学分析得到验证，结果与RNA测序数据一致。