Background: Nei Like DNA Glycosylase 2 (NEIL2) is strongly associated with the risk of Cervical cancer (CC), but the mechanism is not yet clear. Therefore, the aim of this study was to explore the potential mechanisms of NEIL2 as a novel prognostic biomarker for CC patients.
Methods: Firstly, the Cancer Genome Atlas (TCGA)-Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (CESC) dataset was acquired from the University of California Santa Cruz Xena database. Two CC-related datasets (GSE7410 and GSE63514) were acquired from the Gene Expression Omnibus database. CC samples in the TCGA-CESC cohort were divided into high and low-expression groups according to the optimal threshold of NEIL2 expression, and survival analysis was performed. NEIL2 expression and clinical characteristics were included in univariate Cox analysis and multifactorial Cox regression analysis to screen independent prognostic factors. An alignment diagram based on independent prognostic factors was constructed. In addition, the most relevant modules with NEIL2 expression were screened separately by weighted gene co-expression network analysis in TCGA-CESC and GSE7410, followed by intersection to obtain NEIL2-related hub genes. Next, the NEIL2 expression in a variety of common female cancers was visualized and. the survival differences were calculated in these cancers with high or low expression of NEIL2. Finally, we verified the differential expression of NEIL2 in CC and adjacent tissues by quantitative real-time polymerase chain reaction (qRT-PCR).
Results: The NEIL2 expression level was strongly correlated with CC. Survival situation for OS, PFI and DFS patients in high NEIL2 expression group were better than that in low expression group (P < 0.05). Moreover, the differential expression of NEIL2 was associated with age and disease type, with high NEIL2 expression being more common in patients with > 50 years and adenocarcinoma patients. High expression of NEIL2 and pathological factors N and T were the independent risk factors affecting the prognosis of CC patients, and the nomogram model has high prediction accuracy for CC, and the longer the time, the higher the accuracy. Eight NEIL2 related intersection genes (RTBDN, ENTPD2, TFF 2, PLA2G6, MUC 6, SLIT 1, ERN 2 and SERPINA6). Later analysis of NEIL2 gene in common female cancers (CC, UCC, BRCA) and associated with prognosis (P <0.05) indicates that differential expression of NEIL2 may be an independent risk factor for the prognosis of these common female cancers. Verification by qRT-PCR showed that NEIL2 expression was lower in CC than that in normal tissues (P = 0.0481), which was consistent with the results of the bioinformational analysis.
Conclusion: The expression level of NEIL2 has a strong correlation with CC and affects its prognosis, which is expected to become a new prognostic biomarker in CC, providing an important reference for the diagnosis, mechanism research and treatment of cervical cancer.
Keywords: Bioinformatics; Biomarkers; Cervical cancer; Differentially expressed genes; NEIL2.
© 2025. The Author(s).