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pmid:40591047

Identification of key biomarkers and potential therapeutic drugs in nasopharyngeal carcinoma based on comprehensive bioinformatics analysis.

Cong Fu · Lin Sun · Lili Zhang · Tong Zhou · Yanzhi Bi

Discover oncology · 2025 doi:10.1007/s12672-025-03047-4

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

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title
Identification of key biomarkers and potential therapeutic drugs in nasopharyngeal carcinoma based on comprehensive bioinformatics analysis.
doi
10.1007/s12672-025-03047-4
pmid
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Cong Fu
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Lin Sun
[2]
Lili Zhang
[3]
Tong Zhou
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Yanzhi Bi
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Discover oncology
year
2025
abstract
Nasopharyngeal carcinoma (NPC) is the most prevalent type of head- and -neck cancer, and its diagnosis and treatment are currently facing significant challenges. This study aimed to identify biomarkers associated with NPC by performing bioinformatic analysis on the GSE12452, GSE53819, and GSE64634 datasets from the GEO database. First, differentially expressed genes (DEGs) between NPC and normal nasopharyngeal tissues were screened. Then, these DEGs were subjected to RobustRank Aggregation analysis. Through Receiver Operating Characteristic (ROC) analysis and three machine-learning models, biomarkers such as DNAH5, ZMYND10, LRRC6, ARMC4, DNAI2, and DNALI1 were identified. Enrichment analysis was performed to uncover the common pathways of these biomarkers. Using the Comparative Toxicogenomics Database (CTD), target drugs for NPC were predicted based on these biomarkers. Additionally, immune infiltration analysis was carried out to study the relationship between these biomarkers and immune cells. A regulatory network was also constructed. It was found that these biomarkers are mainly involved in cytokine-cytokine receptor interaction, and some are part of common cancer-related signaling pathways. In addition, quantitative real time polymerase chain reaction (qRT-PCR) results showed that the expression levels of all biomarkers were significantly elevated in normal cell samples. DNAH5 and ZMYND10 were significantly higher in normal surrounding tissues. These findings provided potential support for the early clinical diagnosis and treatment of nasopharyngeal carcinoma patients.
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Thus, RobustRankAggreg R package (v 1.2.1) [84] was employed to integrate the DEGs from the three datasets mentioned above.
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Complete file
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This study aimed to identify biomarkers associated with NPC by performing bioinformatic analysis on the GSE12452, GSE53819, and GSE64634 datasets from the GEO database. First, differentially expressed genes (DEGs) between NPC and normal nasopharyngeal tissues were screened. Then, these DEGs were subjected to RobustRank Aggregation analysis. Through Receiver Operating Characteristic (ROC) analysis and three machine-learning models, biomarkers such as DNAH5, ZMYND10, LRRC6, ARMC4, DNAI2, and DNALI1 were identified. Enrichment analysis was performed to uncover the common pathways of these biomarkers. Using the Comparative Toxicogenomics Database (CTD), target drugs for NPC were predicted based on these biomarkers. Additionally, immune infiltration analysis was carried out to study the relationship between these biomarkers and immune cells. A regulatory network was also constructed. 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