A new signature associated with anoikis predicts the outcome and immune infiltration in nasopharyngeal carcinoma
Abstract Background Previous studies have confirmed the phenomenon of anoikis resistance in nasopharyngeal carcinoma (NPC). Nevertheless, the prognostic significance of anoikis-related genes (ARGs) in NPC remains incompletely understood. This study aimed to create a predictive risk score using an AR...
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| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-02-01
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| Series: | Discover Oncology |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s12672-025-01869-w |
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| Summary: | Abstract Background Previous studies have confirmed the phenomenon of anoikis resistance in nasopharyngeal carcinoma (NPC). Nevertheless, the prognostic significance of anoikis-related genes (ARGs) in NPC remains incompletely understood. This study aimed to create a predictive risk score using an ARGs signature for NPC patients and to investigate how this score relates to clinicopathologic features and immune infiltration in the tumor microenvironment. Methods By using data from the Gene Expression Omnibus (GEO) database, we employed machine learning methods to discover prognostic ARGs and create a risk score. Key gene expression levels were validated through real-time PCR and immunohistochemical staining. Results Three differentially expressed ARGs (CDC25C, E2F1 and RBL2) with prognostic value were identified by the intersection of multiple machine learning algorithms. A risk score based on t 3-ARG feature was developed to stratify NPC patients into two distinct risk groups using the optimal model, Random Survival Forest. NPC patients with high-risk scores experienced notably shorter progression-free survival in comparison to those with low-risk scores. Multivariate Cox regression analysis indicated that the risk score served as an independent prognostic factor. The time-dependent ROC and decision curve analyses demonstrated the risk model's strong predictive accuracy and clinical utility. The low-risk score group exhibited features indicative of early clinical stage, immune activation, high immune checkpoint gene's expression, and low Epstein-Barr virus gene's expression. Functional analysis revealed enrichment of immune-related pathways in the low-risk group. Patients with high-risk scores were discovered to be unlikely to benefit from immune checkpoint inhibitor treatment. Moreover, the expression of RBL2, E2F1, and CDC25C were significantly correlated with the expression of caspase family genes. Finally, the lower mRNA and protein expression of RBL2 were validated in NPC cell lines and tissues. Conclusions Our ARGs-based signature model shows promising results in predicting the prognosis of NPC patients and might be associated with immune cell infiltration. |
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| ISSN: | 2730-6011 |