Development of Potential Prognostic Biomarkers Based on DNA Methylation-Driven Genes for Patients with Endometrial Cancer

Yiling Lu; Weichun Tang; Xiaoyu Wang; Xinyi Kang; Jun You; Liping Chen

doi:10.2147/IJGM.S341771

Development of Potential Prognostic Biomarkers Based on DNA Methylation-Driven Genes for Patients with Endometrial Cancer

Int J Gen Med. 2021 Dec 31:14:10541-10555. doi: 10.2147/IJGM.S341771. eCollection 2021.

Authors

Yiling Lu^#¹, Weichun Tang^#^{2

3}, Xiaoyu Wang¹, Xinyi Kang¹, Jun You¹, Liping Chen¹

Affiliations

¹ Department of Obstetrics and Gynecology, Nantong First People's Hospital, Nantong, Jiangsu, 226001, People's Republic of China.
² NHC Key Laboratory of Antibody Technique, Nanjing Medical University, Nanjing, Jiangsu, 211166, People's Republic of China.
³ Department of Gynecology and Obstetrics, The Second Affiliated Hospital of Nantong University, Nantong, Jiangsu, 226001, People's Republic of China.

^# Contributed equally.

Abstract

Background: Endometrial cancer (EC) is a multifactorial disease, and its progression may be driven by abnormal genetic methylation. To clarify the underlying molecular mechanisms and sensitive biomarkers for EC, this study used an integrated bioinformatic analysis to explore the methylation-driven genes of EC.

Methods: The mRNA expression data, methylation data and corresponding clinical information of EC samples were downloaded from The Cancer Genome Atlas (TCGA) database. MethylMix algorithm was used to screen out methylation-driven genes in EC. Functional and pathway enrichment analysis and the protein-protein interaction (PPI) analysis were conducted to demonstrate the functions and interactions between these genes. Then, prognosis-related methylated genes were screened out by using univariate and multivariate Cox analyses, and a prognostic risk assessment model for EC was constructed. The methylation sites and expression profiles of candidate genes were further investigated.

Results: A total of 127 methylated genes were identified in EC. Four genes (RP11-968O1.5, DCAF12L1, MSX1 and ALS2CR11) were selected as candidate genes to construct a reliable prognostic risk model. The univariate and multivariate Cox proportional hazards regression analyses showed that the risk score based on four genes was an independent prognostic indicator for OS among EC patients. A nomogram was established and the calibration plot analysis indicated the good performance and clinical utility of the nomogram. In addition, the methylation and expression of MSX1 and DCAF12L1 were significantly associated with EC survival rate. The joint ROC analysis revealed that the AUC of DCAF12L1-MSX1 was 0.867, which suggested both have a good EC-diagnosing efficiency. We then coped DCAF12L1 and MSX1 with GESA analysis, finding both were mainly associated with the KRAS signaling pathway.

Conclusion: This bioinformatic study combs the methylated genes involved in EC development for the first time, finding that MSX1 and DCAF12L1 could serve as EC prognostic markers and drug targets.

Keywords: biomarkers; endometrial cancer; integrated bioinformatic analysis; methylation-driven genes; prognosis.

Grants and funding

Nantong Municipal Health Commission General Program B (Grant No:MB2021017). The Research project of Jiangsu Provincial Health Committee (Grant No:F202037). The Research project of Jiangsu Maternal and child Health Care Association (Grant No:FYX202029). The Research project of Nantong Health Committee (Grant No:QA2020003).