A methylomics-associated nomogram predicts the overall survival risk of stage III to IV ovarian cancer

Accumulating studies demonstrated that DNA methylation may be potential prognostic hallmarks of various cancers. However, few studies have focused on the power of DNA methylation for prognostic prediction in patients with stage III to IV ovarian cancer (OC). Therefore, constructing a methylomics-related indicator to predict overall survival (OS) of stage III to IV OC was urgently required. A total of 520 OC patients with 485,577 DNA methylation sites from TCGA database were selected to develop a robust DNA methylation signature. The 520 patients were clustered into a training group (70%, n = 364 samples) and an internal validation group (30%, n = 156). The training group was used for digging a prognostic predictor based on univariate Cox proportional hazard analysis, least absolute shrinkage and selection operator (LASSO) as well as multivariate Cox regression analysis. The internal and external validation group (ICGC OV-AU project) were used for validating the predictive robustness of the predictor based on receiver operating characteristic (ROC) analysis and Kaplan-Meier survival analysis. We identified a 21-DNA methylation signature-based classifier for stage III-IV OC patients' OS. According to ROC analysis in the internal validation, external validation and entire TCGA set, we proved the high power of the 21-DNA methylation signature for predicting OS (area under the curve [AUC] at 1, 3, 5 years in internal validation set (0.782, 0.739, 0.777, respectively), external validation set (0.828, 0.760, 0.741, respectively), entire TCGA set (0.741, 0.748, 0.781, respectively). Besides, a nomogram was developed via methylation risk score as well as a few clinical variables, and the result showed a high ability of the predictive nomogram. In summary, we used integrated bioinformatics approaches to successfully identified a DNA methylation-associated nomogram, which can predict effectively the OS of patients with stage III to IV OC.

Automated summary

This study successfully established a DNA methylation-associated predictive model using bioinformatics approaches, which can effectively predict overall survival in patients with stage III to IV ovarian cancer. In addition, a diagnostic nomogram based on the methylation risk score and several clinical variables was developed, and the results showed a high predictive ability of the nomogram.