Frontiers in Oncology (May 2024)

Novel prognostic biomarkers in nasopharyngeal carcinoma unveiled by mega-data bioinformatics analysis

  • Yishuai Tan,
  • Yishuai Tan,
  • Jiao Zhou,
  • Kai Liu,
  • Ruowu Liu,
  • Jing Zhou,
  • Zhenru Wu,
  • Linke Li,
  • Jiaqi Zeng,
  • Xuxian Feng,
  • Biao Dong,
  • Jintao Du

DOI
https://doi.org/10.3389/fonc.2024.1354940
Journal volume & issue
Vol. 14

Abstract

Read online

Nasopharyngeal carcinoma (NPC) is commonly diagnosed at an advanced stage with a high incidence rate in Southeast Asia and Southeast China. However, the limited availability of NPC patient survival data in public databases has resulted in less rigorous studies examining the prediction of NPC survival through construction of Kaplan-Meier curves. These studies have primarily relied on small samples of NPC patients with progression-free survival (PFS) information or data from head and neck squamous cell carcinoma (HNSCC) studies almost without NPC patients. Thus, we coanalyzed RNA expression profiles in eleven datasets (46 normal (control) vs 160 tumor (NPC)) downloaded from the Gene Expression Omnibus (GEO) database and survival data provided by Jun Ma from Sun Yat-sen University. Then, differential analysis, gene ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and network analysis were performed using STRING database. After that, 2142 upregulated differentially expressed genes (DEGs) and 3857 downregulated DEGs were screened. Twenty-five of them were identified as hub genes, which were enriched in several pathways (cilium movement, extracellular matrix structural constituent, homologous recombination and cell cycle). Utilizing the comprehensive dataset we amassed from GEO database, we conducted a survival analysis of DEGs and subsequently constructed survival models. Seven DEGs (RASGRP2, MOCOS, TTC9, ARHGAP4, DPM3, CD37, and CD72) were identified and closely related to the survival prognosis of NPC. Finally, qRT-PCR, WB and IHC were performed to confirm the elevated expression of RASGRP2 and the decreased expression of TTC9, CD37, DPM3 and ARHGAP4, consistent with the DEG analysis. Conclusively, our findings provide insights into the novel prognostic biomarkers of NPC by mega-data bioinformatics analysis, which suggests that they may serve special targets in the treatment of NPC.

Keywords