Mai Zizhao, Chen Huan, Huang Mingshu, Zhao Xinyuan, Cui Li
Stomatological Hospital, Southern Medical University, Guangzhou, China.
Division of Oral Biology and Medicine, School of Dentistry, University of California, Los Angeles, CA, United States.
Front Oncol. 2022 Jan 20;11:770241. doi: 10.3389/fonc.2021.770241. eCollection 2021.
Head and neck squamous cell carcinoma (HNSCC) is still a menace to public wellbeing globally. However, the underlying molecular events influencing the carcinogenesis and prognosis of HNSCC are poorly known.
Gene expression profiles of The Cancer Genome Atlas (TCGA) HNSCC dataset and GSE37991 were downloaded from the TCGA database and gene expression omnibus, respectively. The common differentially expressed metabolic enzymes (DEMEs) between HNSCC tissues and normal controls were screened out. Then a DEME-based molecular signature and a clinically practical nomogram model were constructed and validated.
A total of 23 commonly upregulated and 9 commonly downregulated DEMEs were identified in TCGA HNSCC and GSE37991. Gene ontology analyses of the common DEMEs revealed that alpha-amino acid metabolic process, glycosyl compound metabolic process, and cellular amino acid metabolic process were enriched. Based on the TCGA HNSCC cohort, we have built up a robust DEME-based prognostic signature including , , , , , and for predicting the clinical outcome of HNSCC. Furthermore, this prognosis signature was successfully validated in another independent cohort GSE65858. Moreover, a potent prognostic signature-based nomogram model was constructed to provide personalized therapeutic guidance for treating HNSCC. experiment revealed that the knockdown of TXNRD1 suppressed malignant activities of HNSCC cells.
Our study has successfully developed a robust DEME-based signature for predicting the prognosis of HNSCC. Moreover, the nomogram model might provide useful guidance for the precision treatment of HNSCC.
头颈部鳞状细胞癌(HNSCC)在全球范围内仍是对公众健康的一大威胁。然而,影响HNSCC发生发展及预后的潜在分子事件却鲜为人知。
分别从癌症基因组图谱(TCGA)数据库和基因表达综合数据库下载了TCGA HNSCC数据集和GSE37991的基因表达谱。筛选出HNSCC组织与正常对照之间共同差异表达的代谢酶(DEMEs)。然后构建并验证了基于DEMEs的分子特征和临床实用的列线图模型。
在TCGA HNSCC和GSE37991中总共鉴定出23种共同上调和9种共同下调的DEMEs。对共同DEMEs的基因本体分析表明,α-氨基酸代谢过程、糖基化合物代谢过程和细胞氨基酸代谢过程得到了富集。基于TCGA HNSCC队列,我们建立了一个强大的基于DEMEs的预后特征,包括 、 、 、 、 和 ,用于预测HNSCC的临床结局。此外,这一预后特征在另一个独立队列GSE65858中得到了成功验证。此外,构建了一个基于预后特征的有效列线图模型,为HNSCC的治疗提供个性化的治疗指导。实验表明,TXNRD1的敲低抑制了HNSCC细胞的恶性活性。
我们的研究成功开发了一种强大的基于DEMEs的特征,用于预测HNSCC的预后。此外,列线图模型可能为HNSCC的精准治疗提供有用的指导。