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: Yonglin Luo, Wenyang Wei, Yaxuan Huang, Jun Li, Weiling Qin, Quanxiang Hao, Jiemei Ye, Zhe Zhang, Yushan Liang, Xue Xiao, Yonglin Cai
Format: Article
Language:English
Published: Springer 2025-02-01
Series:Discover Oncology
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Online Access:https://doi.org/10.1007/s12672-025-01869-w
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author Yonglin Luo
Wenyang Wei
Yaxuan Huang
Jun Li
Weiling Qin
Quanxiang Hao
Jiemei Ye
Zhe Zhang
Yushan Liang
Xue Xiao
Yonglin Cai
author_facet Yonglin Luo
Wenyang Wei
Yaxuan Huang
Jun Li
Weiling Qin
Quanxiang Hao
Jiemei Ye
Zhe Zhang
Yushan Liang
Xue Xiao
Yonglin Cai
author_sort Yonglin Luo
collection DOAJ
description 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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spelling doaj-art-1b17f5eff0124b04ae06e2ec7bc8e5892025-02-09T12:43:22ZengSpringerDiscover Oncology2730-60112025-02-0116111910.1007/s12672-025-01869-wA new signature associated with anoikis predicts the outcome and immune infiltration in nasopharyngeal carcinomaYonglin Luo0Wenyang Wei1Yaxuan Huang2Jun Li3Weiling Qin4Quanxiang Hao5Jiemei Ye6Zhe Zhang7Yushan Liang8Xue Xiao9Yonglin Cai10Department of Clinical Laboratory, Wuzhou Red Cross HospitalSchool of Clinical Medicine, Guilin Medical UniversityDepartment of Otolaryngology-Head & Neck Surgery, First Affiliated Hospital of Guangxi Medical UniversityDepartment of Clinical Laboratory, Wuzhou Red Cross HospitalDepartment of Clinical Laboratory, Wuzhou Red Cross HospitalKey Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor (Guangxi Medical University), Ministry of EducationGuangxi Health Commission Key Laboratory of Molecular Epidemiology of Nasopharyngeal Carcinoma, Wuzhou Red Cross HospitalKey Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor (Guangxi Medical University), Ministry of EducationDepartment of Otolaryngology-Head & Neck Surgery, First Affiliated Hospital of Guangxi Medical UniversityKey Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor (Guangxi Medical University), Ministry of EducationGuangxi Health Commission Key Laboratory of Molecular Epidemiology of Nasopharyngeal Carcinoma, Wuzhou Red Cross HospitalAbstract 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.https://doi.org/10.1007/s12672-025-01869-wNasopharyngeal carcinomaAnoikisPrognosisImmune infiltration
spellingShingle Yonglin Luo
Wenyang Wei
Yaxuan Huang
Jun Li
Weiling Qin
Quanxiang Hao
Jiemei Ye
Zhe Zhang
Yushan Liang
Xue Xiao
Yonglin Cai
A new signature associated with anoikis predicts the outcome and immune infiltration in nasopharyngeal carcinoma
Discover Oncology
Nasopharyngeal carcinoma
Anoikis
Prognosis
Immune infiltration
title A new signature associated with anoikis predicts the outcome and immune infiltration in nasopharyngeal carcinoma
title_full A new signature associated with anoikis predicts the outcome and immune infiltration in nasopharyngeal carcinoma
title_fullStr A new signature associated with anoikis predicts the outcome and immune infiltration in nasopharyngeal carcinoma
title_full_unstemmed A new signature associated with anoikis predicts the outcome and immune infiltration in nasopharyngeal carcinoma
title_short A new signature associated with anoikis predicts the outcome and immune infiltration in nasopharyngeal carcinoma
title_sort new signature associated with anoikis predicts the outcome and immune infiltration in nasopharyngeal carcinoma
topic Nasopharyngeal carcinoma
Anoikis
Prognosis
Immune infiltration
url https://doi.org/10.1007/s12672-025-01869-w
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