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. 2025 Jul 30;14(7):4429-4446.
doi: 10.21037/tcr-2025-1263. Epub 2025 Jul 27.

Identification and validation of anoikis-related differentially expressed genes in nasopharyngeal carcinoma

Affiliations

Identification and validation of anoikis-related differentially expressed genes in nasopharyngeal carcinoma

Chaobin Huang et al. Transl Cancer Res. .

Abstract

Background: Anoikis resistance is a critical feature enabling cancer cells to survive during detachment from the extracellular matrix. This study aimed to identify and validate anoikis-related differentially expressed genes (ARDEGs) in nasopharyngeal carcinoma (NPC), providing new insights into the molecular mechanisms underlying NPC progression and potential therapeutic targets.

Methods: Four gene expression datasets from the Gene Expression Omnibus (GEO) database were integrated to form the GEO-Combined dataset. NPC and adjacent normal nasopharyngeal tissues comprising the Test_Data were subjected to RNA sequencing. The differentially expressed genes (DEGs) from the GEO-Combined and Test_Data datasets were screened. DEGs associated with anoikis were identified and termed as ARDEGs. The key genes were validated by quantitative real-time polymerase chain reaction (qRT-PCR).

Results: A total of 104 ARDEGs were identified in our study. Five key genes (i.e., PLAUR, PTGS2, SERPINE1, CHI3L1, and ITGAV) were identified using the random forest (RF) and least absolute shrinkage and selection operator (LASSO) algorithms. A nomogram based on these five key genes showed robust diagnostic performance, with the area under the curve (AUC) underscoring its utility as a prognostic tool. Further, the functional enrichment analysis indicated that the risk model was associated with the biological pathways involved in tumor migration and invasion. Based on the model constructed from the five key genes, our study found 152 pairs of messenger RNA (mRNA)-transcription factor (TF) interaction relationships, which may provide insights into the mechanisms of metastasis and recurrence of NPC.

Conclusions: The identification and validation of ARDEGs in NPC highlighted critical molecular players in anoikis resistance, offering potential targets for therapeutic interventions. Our study provides a comprehensive understanding of the role of ARDEGs in NPC, paving the way for further research into targeted therapies for NPC.

Keywords: Nasopharyngeal carcinoma (NPC); anoikis; bioinformatics analysis; prognosis; therapeutic targets.

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Conflict of interest statement

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1263/coif). The authors have no conflicts of interest to declare.

Figures

Figure 1
Figure 1
Overall analysis flow chart. ARDEG, anoikis-related differentially expressed gene; ARG, anoikis-related gene; DEG, differentially expressed gene; GEO, Gene Expression Omnibus; GO, Gene Ontology; GSEA, gene set enrichment analysis; GSVA, gene set variation analysis; KEGG, Kyoto Encyclopedia of Genes and Genomes; LASSO, least absolute shrinkage and selection operator; miRNA, microRNA; mRNA, messenger RNA; PPI, protein-protein interaction; RBP, RNA-binding protein; ROC, receiver operating characteristic; TF, transcription factor.
Figure 2
Figure 2
Identification of ARDEGs. (A) Volcano plot depicting the analysis of the DEGs between the different (NPC/control) groups in the Test_Data dataset. (B) Volcano plot illustrating the analysis of the DEGs between the different (NPC/control) groups in the GEO-Combined dataset. (C) Venn diagram showcasing the overlap between the DEGs and ARGs in the Test_Data and GEO-Combined datasets. (D) Heatmap visualizing the expression patterns of the ARDEGs between the different (NPC/control) groups in the Test_Data dataset. (E) Heatmap illustrating the expression patterns of the ARDEGs between the different (NPC/control) groups in the GEO-Combined dataset. ARDEG, anoikis-related differentially expressed gene; ARG, anoikis-related gene; DEG, differentially expressed gene; GEO, Gene Expression Omnibus; NPC, nasopharyngeal carcinoma.
Figure 3
Figure 3
GSEA. (A) Ridge plots illustrating the top four enriched biological features identified in the GSEA for the genes between the different (NPC/control) groups in the Test_Data dataset. Enriched genes in the Test_Data dataset were prominently associated with pathways such as the hedgehog signaling pathway (B), anchoring fibril formation (C), MET promotes cell motility pathway (D), and assembly of collagen fibrils and other multimeric structures (E). FDR, false discovery rate; GSEA, gene set enrichment analysis; KEGG, Kyoto Encyclopedia of Genes and Genomes; MET, mesenchymal-epithelial transition; NES, normalized enrichment score; NPC, nasopharyngeal carcinoma.
Figure 4
Figure 4
GSVA. Comprehensive numerical heatmap (A) and group comparison boxplots (B) showing the intricacies of the GSVA results in the NPC and control groups of the Test_Data dataset. The symbol “ns” is equivalent to P≥0.05, indicating no statistical significance. *, P<0.05; **, P<0.01. GSVA, gene set variation analysis; NPC, nasopharyngeal carcinoma.
Figure 5
Figure 5
Selection of the key genes and construction of the LASSO risk model. (A) Model training error plot for the RF algorithm. (B) Scatter plot of MeanDecreaseGini for the ARDEGs (displaying the top 30 in descending order). (C) Cross-validation error curve plot. (D) Diagnostic model plot for the LASSO regression model. (E) Variable trajectory plot for the LASSO regression model. (F) Forest plot of the key genes in the LASSO regression model. ARDEG, anoikis-related differentially expressed gene; coef, coefficient; LASSO, least absolute shrinkage and selection operator; RF, random forest.
Figure 6
Figure 6
Diagnostic performance of the LASSO risk model and expression validation of the key genes. ROC curves showing the diagnostic performance of the LASSO risk scores in the Test_Data dataset (A) and GEO-Combined dataset (B). Correlation heatmaps illustrating the relationships among key genes in the Test_Data (C) and GEO-Combined (D) datasets. Group comparison plots displaying the expression differences of the key genes between the different (NPC/control) groups in the Test_Data (E) and GEO-Combined (F) datasets. CHI3L1 (G), PTGS2 (H), SERPINE1 (I), PLAUR (J), and ITGAV (K) expression in NPC and adjacent normal tissues was evaluated by qRT-PCR. The symbol “ns” is equivalent to P≥0.05, indicating no statistical significance. *, P<0.05; **, P<0.01; ***, P<0.001. AUC, area under the curve; CI, confidence interval; FPR, false positive rate; GEO, Gene Expression Omnibus; LASSO, least absolute shrinkage and selection operator; NPC, nasopharyngeal carcinoma; qRT-PCR, quantitative real-time polymerase chain reaction; ROC, receiver operating characteristic; TPR, true positive rate.

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