ArticleClinical epigenetics2025
Impact of DNA methylation on the recurrence risk of stage I non-small cell lung cancer with EGFR mutations.
Article in Clinical epigenetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- DNA Methylation in Lung Cancer: Predictive Biomarkers for Effective Immunotherapy.International journal of general medicine · 2025Review
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10 authors.
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Abstract
backgroundRecent studies have demonstrated that patients with stage IB-IIIA non-small cell lung cancer (NSCLC) harboring EGFR mutations (EGFRm) can significantly benefit from adjuvant therapy with EGFR-TKIs. Nevertheless, there remains controversial in clinical practice about the use of EGFR-TKI adjuvant therapy for patients with stage IB EGFRm NSCLC.
methodsThis retrospective cohort study was conducted at the Second Xiangya Hospital of Central South University. From January 2011 to December 2020, completely resected stage IA-IB NSCLC (8th TNM staging) patients with sensitive EGFR mutation were included. FFPE tumor and lymph node specimens were collected and subjected to the 8-gene methylation panel using modified MOB-qMSP approach. We employed stepwise regression to select variables and logistic regression to establish the predictive model. Cross-validation and decision curve analysis were performed.
resultsA total of 242 patients with IA2-IB EGFRm NSCLC were included in the study. Among these patients, 86 constituted the recurrence (Rec) group, while 156 formed the non-recurrence (Non-Rec) group. Through stepwise logistic regression, seven crucial feature variables were identified, including five-gene methylation variables (CDO1, TAC1, p16, CDH13, and APC) and two clinical variables (tumor invasion and differentiation). The ROC analysis revealed an AUC of 0.873 for the model with these seven variables. Internal cross-validation demonstrated a model accuracy exceeding 77%. The nomogram and decision curve analysis underscored the clinical utility of the model. We calculated the total score for each patient based on the nomogram and divided the patients into high-risk and low-risk groups. The cumulative risk curves for both groups evidenced that the recurrence risk in the high-risk group was significantly higher than in the low-risk group. We further divided the dataset into two cohorts-stage IA2-IA3 patients and stage IB patients. The model maintained a high AUC value (0.879) in stage IA2-A3 patients.
conclusionsOur study demonstrates that the methylation of five genes-CDO1, TAC1, p16, CDH13, and APC-in N2 lymph nodes represents a strong biomarker panel for predicting recurrence in stage IB EGFRm NSCLC after curative resection. This approach also shows exceptional predictive accuracy for postoperative recurrence in stage IA2-IA3 EGFRm NSCLC.
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