Abstract
Background: DNA methylation affects the development, progression, and prognosis of various cancers. This study aimed to identify DNA methylated-differentially expressed genes (DEGs) and develop a methylation-driven gene model to evaluate the prognosis of ovarian cancer (OC).Methods: DNA methylation and mRNA expression profiles of OC patients were downloaded from The Cancer Genome Atlas, Genotype-Tissue Expression, and Gene Expression Omnibus databases. We used the R package MethylMix to identify DNA methylation-regulated DEGs and built a prognostic signature using LASSO Cox regression. A quantitative nomogram was then drawn based on the risk score and clinicopathological features.Results: We identified 56 methylation-related DEGs and constructed a prognostic risk signature with four genes according to the LASSO Cox regression algorithm. A higher risk score not only predicted poor prognosis, but also was an independent poor prognostic indicator, which was validated by receiver operating characteristic (ROC) curves and the validation cohort. A nomogram consisting of the risk score, age, FIGO stage, and tumor status was generated to predict 3- and 5-year overall survival (OS) in the training cohort. The joint survival analysis of DNA methylation and mRNA expression demonstrated that the two genes may serve as independent prognostic biomarkers for OS in OC.Conclusion: The established qualitative risk score model was found to be robust for evaluating individualized prognosis of OC and in guiding therapy.
Highlights
Ovarian cancer (OC), the most lethal gynecological cancer, is the seventh most common cancer and the fifth leading cause of cancer-related deaths in women, with a 5-year survival rate of 47.4% (Howlader et al, 2019)
After calculating the Pearson correlation coefficients between the methylation and expression levels, 57 genes with negative correlation coefficients were identified as methylation-related differentially expressed gene (DEG) (Figure 1B)
A signature consisting of four methylationrelated DEGs was built as a prognostic model for patients with OC
Summary
Ovarian cancer (OC), the most lethal gynecological cancer, is the seventh most common cancer and the fifth leading cause of cancer-related deaths in women, with a 5-year survival rate of 47.4% (Howlader et al, 2019). In the United States, over 22,000 new cases are diagnosed, and 14,000 patients die each year (Siegel et al, 2020). Exploring the pathogenesis of OC, formulating effective methods of early screening and diagnosis, and finding new prognostic biomarkers and treatment pathways for OC would help improve the therapeutic effect and survival rate of patients with OC. DNA methylation affects the development, progression, and prognosis of various cancers. This study aimed to identify DNA methylated-differentially expressed genes (DEGs) and develop a methylation-driven gene model to evaluate the prognosis of ovarian cancer (OC)
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